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7
.github/workflows/coverage.yml
vendored
7
.github/workflows/coverage.yml
vendored
@@ -6,11 +6,16 @@ on:
|
||||
pull_request:
|
||||
branches: [main]
|
||||
|
||||
# Ensures that we cancel running jobs for the same PR / same workflow.
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
coverage:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install Rust
|
||||
run: rustup toolchain install nightly --profile minimal --component llvm-tools-preview
|
||||
- uses: Swatinem/rust-cache@v2
|
||||
|
||||
7
.github/workflows/long_running.yml
vendored
7
.github/workflows/long_running.yml
vendored
@@ -8,13 +8,18 @@ env:
|
||||
CARGO_TERM_COLOR: always
|
||||
NUM_FUNCTIONAL_TEST_ITERATIONS: 20000
|
||||
|
||||
# Ensures that we cancel running jobs for the same PR / same workflow.
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
test:
|
||||
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
- name: Install stable
|
||||
uses: actions-rs/toolchain@v1
|
||||
with:
|
||||
|
||||
11
.github/workflows/test.yml
vendored
11
.github/workflows/test.yml
vendored
@@ -9,13 +9,18 @@ on:
|
||||
env:
|
||||
CARGO_TERM_COLOR: always
|
||||
|
||||
# Ensures that we cancel running jobs for the same PR / same workflow.
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
jobs:
|
||||
check:
|
||||
|
||||
runs-on: ubuntu-latest
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Install nightly
|
||||
uses: actions-rs/toolchain@v1
|
||||
@@ -48,14 +53,14 @@ jobs:
|
||||
strategy:
|
||||
matrix:
|
||||
features: [
|
||||
{ label: "all", flags: "mmap,stopwords,brotli-compression,lz4-compression,snappy-compression,zstd-compression,failpoints" },
|
||||
{ label: "all", flags: "mmap,stopwords,lz4-compression,zstd-compression,failpoints" },
|
||||
{ label: "quickwit", flags: "mmap,quickwit,failpoints" }
|
||||
]
|
||||
|
||||
name: test-${{ matrix.features.label}}
|
||||
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Install stable
|
||||
uses: actions-rs/toolchain@v1
|
||||
|
||||
2
.gitignore
vendored
2
.gitignore
vendored
@@ -13,3 +13,5 @@ benchmark
|
||||
.idea
|
||||
trace.dat
|
||||
cargo-timing*
|
||||
control
|
||||
variable
|
||||
|
||||
@@ -254,7 +254,7 @@ The token positions of all of the terms are then stored in a separate file with
|
||||
The [TermInfo](src/postings/term_info.rs) gives an offset (expressed in position this time) in this file. As we iterate through the docset,
|
||||
we advance the position reader by the number of term frequencies of the current document.
|
||||
|
||||
## [fieldnorms/](src/fieldnorms): Here is my doc, how many tokens in this field?
|
||||
## [fieldnorm/](src/fieldnorm): Here is my doc, how many tokens in this field?
|
||||
|
||||
The [BM25](https://en.wikipedia.org/wiki/Okapi_BM25) formula also requires to know the number of tokens stored in a specific field for a given document. We store this information on one byte per document in the fieldnorm.
|
||||
The fieldnorm is therefore compressed. Values up to 40 are encoded unchanged.
|
||||
|
||||
116
CHANGELOG.md
116
CHANGELOG.md
@@ -1,3 +1,119 @@
|
||||
Tantivy 0.21
|
||||
================================
|
||||
#### Bugfixes
|
||||
- Fix track fast field memory consumption, which led to higher memory consumption than the budget allowed during indexing [#2148](https://github.com/quickwit-oss/tantivy/issues/2148)[#2147](https://github.com/quickwit-oss/tantivy/issues/2147)(@PSeitz)
|
||||
- Fix a regression from 0.20 where sort index by date wasn't working anymore [#2124](https://github.com/quickwit-oss/tantivy/issues/2124)(@PSeitz)
|
||||
- Fix getting the root facet on the `FacetCollector`. [#2086](https://github.com/quickwit-oss/tantivy/issues/2086)(@adamreichold)
|
||||
- Align numerical type priority order of columnar and query. [#2088](https://github.com/quickwit-oss/tantivy/issues/2088)(@fmassot)
|
||||
#### Breaking Changes
|
||||
- Remove support for Brotli and Snappy compression [#2123](https://github.com/quickwit-oss/tantivy/issues/2123)(@adamreichold)
|
||||
#### Features/Improvements
|
||||
- Implement lenient query parser [#2129](https://github.com/quickwit-oss/tantivy/pull/2129)(@trinity-1686a)
|
||||
- order_by_u64_field and order_by_fast_field allow sorting in ascending and descending order [#2111](https://github.com/quickwit-oss/tantivy/issues/2111)(@naveenann)
|
||||
- Allow dynamic filters in text analyzer builder [#2110](https://github.com/quickwit-oss/tantivy/issues/2110)(@fulmicoton @fmassot)
|
||||
- **Aggregation**
|
||||
- Add missing parameter for term aggregation [#2149](https://github.com/quickwit-oss/tantivy/issues/2149)[#2103](https://github.com/quickwit-oss/tantivy/issues/2103)(@PSeitz)
|
||||
- Add missing parameter for percentiles [#2157](https://github.com/quickwit-oss/tantivy/issues/2157)(@PSeitz)
|
||||
- Add missing parameter for stats,min,max,count,sum,avg [#2151](https://github.com/quickwit-oss/tantivy/issues/2151)(@PSeitz)
|
||||
- Improve aggregation deserialization error message [#2150](https://github.com/quickwit-oss/tantivy/issues/2150)(@PSeitz)
|
||||
- Add validation for type Bytes to term_agg [#2077](https://github.com/quickwit-oss/tantivy/issues/2077)(@PSeitz)
|
||||
- Alternative mixed field collection [#2135](https://github.com/quickwit-oss/tantivy/issues/2135)(@PSeitz)
|
||||
- Add missing query_terms impl for TermSetQuery. [#2120](https://github.com/quickwit-oss/tantivy/issues/2120)(@adamreichold)
|
||||
- Minor improvements to OwnedBytes [#2134](https://github.com/quickwit-oss/tantivy/issues/2134)(@adamreichold)
|
||||
- Remove allocations in split compound words [#2080](https://github.com/quickwit-oss/tantivy/issues/2080)(@PSeitz)
|
||||
- Ngram tokenizer now returns an error with invalid arguments [#2102](https://github.com/quickwit-oss/tantivy/issues/2102)(@fmassot)
|
||||
- Make TextAnalyzerBuilder public [#2097](https://github.com/quickwit-oss/tantivy/issues/2097)(@adamreichold)
|
||||
- Return an error when tokenizer is not found while indexing [#2093](https://github.com/quickwit-oss/tantivy/issues/2093)(@naveenann)
|
||||
- Delayed column opening during merge [#2132](https://github.com/quickwit-oss/tantivy/issues/2132)(@PSeitz)
|
||||
|
||||
Tantivy 0.20.2
|
||||
================================
|
||||
- Align numerical type priority order on the search side. [#2088](https://github.com/quickwit-oss/tantivy/issues/2088) (@fmassot)
|
||||
- Fix is_child_of function not considering the root facet. [#2086](https://github.com/quickwit-oss/tantivy/issues/2086) (@adamreichhold)
|
||||
|
||||
Tantivy 0.20.1
|
||||
================================
|
||||
- Fix building on windows with mmap [#2070](https://github.com/quickwit-oss/tantivy/issues/2070) (@ChillFish8)
|
||||
|
||||
Tantivy 0.20
|
||||
================================
|
||||
#### Bugfixes
|
||||
- Fix phrase queries with slop (slop supports now transpositions, algorithm that carries slop so far for num terms > 2) [#2031](https://github.com/quickwit-oss/tantivy/issues/2031)[#2020](https://github.com/quickwit-oss/tantivy/issues/2020)(@PSeitz)
|
||||
- Handle error for exists on MMapDirectory [#1988](https://github.com/quickwit-oss/tantivy/issues/1988) (@PSeitz)
|
||||
- Aggregation
|
||||
- Fix min doc_count empty merge bug [#2057](https://github.com/quickwit-oss/tantivy/issues/2057) (@PSeitz)
|
||||
- Fix: Sort order for term aggregations (sort order on key was inverted) [#1858](https://github.com/quickwit-oss/tantivy/issues/1858) (@PSeitz)
|
||||
|
||||
#### Features/Improvements
|
||||
- Add PhrasePrefixQuery [#1842](https://github.com/quickwit-oss/tantivy/issues/1842) (@trinity-1686a)
|
||||
- Add `coerce` option for text and numbers types (convert the value instead of returning an error during indexing) [#1904](https://github.com/quickwit-oss/tantivy/issues/1904) (@PSeitz)
|
||||
- Add regex tokenizer [#1759](https://github.com/quickwit-oss/tantivy/issues/1759)(@mkleen)
|
||||
- Move tokenizer API to seperate crate. Having a seperate crate with a stable API will allow us to use tokenizers with different tantivy versions. [#1767](https://github.com/quickwit-oss/tantivy/issues/1767) (@PSeitz)
|
||||
- **Columnar crate**: New fast field handling (@fulmicoton @PSeitz) [#1806](https://github.com/quickwit-oss/tantivy/issues/1806)[#1809](https://github.com/quickwit-oss/tantivy/issues/1809)
|
||||
- Support for fast fields with optional values. Previously tantivy supported only single-valued and multi-value fast fields. The encoding of optional fast fields is now very compact.
|
||||
- Fast field Support for JSON (schemaless fast fields). Support multiple types on the same column. [#1876](https://github.com/quickwit-oss/tantivy/issues/1876) (@fulmicoton)
|
||||
- Unified access for fast fields over different cardinalities.
|
||||
- Unified storage for typed and untyped fields.
|
||||
- Move fastfield codecs into columnar. [#1782](https://github.com/quickwit-oss/tantivy/issues/1782) (@fulmicoton)
|
||||
- Sparse dense index for optional values [#1716](https://github.com/quickwit-oss/tantivy/issues/1716) (@PSeitz)
|
||||
- Switch to nanosecond precision in DateTime fastfield [#2016](https://github.com/quickwit-oss/tantivy/issues/2016) (@PSeitz)
|
||||
- **Aggregation**
|
||||
- Add `date_histogram` aggregation (only `fixed_interval` for now) [#1900](https://github.com/quickwit-oss/tantivy/issues/1900) (@PSeitz)
|
||||
- Add `percentiles` aggregations [#1984](https://github.com/quickwit-oss/tantivy/issues/1984) (@PSeitz)
|
||||
- [**breaking**] Drop JSON support on intermediate agg result (we use postcard as format in `quickwit` to send intermediate results) [#1992](https://github.com/quickwit-oss/tantivy/issues/1992) (@PSeitz)
|
||||
- Set memory limit in bytes for aggregations after which they abort (Previously there was only the bucket limit) [#1942](https://github.com/quickwit-oss/tantivy/issues/1942)[#1957](https://github.com/quickwit-oss/tantivy/issues/1957)(@PSeitz)
|
||||
- Add support for u64,i64,f64 fields in term aggregation [#1883](https://github.com/quickwit-oss/tantivy/issues/1883) (@PSeitz)
|
||||
- Allow histogram bounds to be passed as Rfc3339 [#2076](https://github.com/quickwit-oss/tantivy/issues/2076) (@PSeitz)
|
||||
- Add count, min, max, and sum aggregations [#1794](https://github.com/quickwit-oss/tantivy/issues/1794) (@guilload)
|
||||
- Switch to Aggregation without serde_untagged => better deserialization errors. [#2003](https://github.com/quickwit-oss/tantivy/issues/2003) (@PSeitz)
|
||||
- Switch to ms in histogram for date type (ES compatibility) [#2045](https://github.com/quickwit-oss/tantivy/issues/2045) (@PSeitz)
|
||||
- Reduce term aggregation memory consumption [#2013](https://github.com/quickwit-oss/tantivy/issues/2013) (@PSeitz)
|
||||
- Reduce agg memory consumption: Replace generic aggregation collector (which has a high memory requirement per instance) in aggregation tree with optimized versions behind a trait.
|
||||
- Split term collection count and sub_agg (Faster term agg with less memory consumption for cases without sub-aggs) [#1921](https://github.com/quickwit-oss/tantivy/issues/1921) (@PSeitz)
|
||||
- Schemaless aggregations: In combination with stacker tantivy supports now schemaless aggregations via the JSON type.
|
||||
- Add aggregation support for JSON type [#1888](https://github.com/quickwit-oss/tantivy/issues/1888) (@PSeitz)
|
||||
- Mixed types support on JSON fields in aggs [#1971](https://github.com/quickwit-oss/tantivy/issues/1971) (@PSeitz)
|
||||
- Perf: Fetch blocks of vals in aggregation for all cardinality [#1950](https://github.com/quickwit-oss/tantivy/issues/1950) (@PSeitz)
|
||||
- Allow histogram bounds to be passed as Rfc3339 [#2076](https://github.com/quickwit-oss/tantivy/issues/2076) (@PSeitz)
|
||||
- `Searcher` with disabled scoring via `EnableScoring::Disabled` [#1780](https://github.com/quickwit-oss/tantivy/issues/1780) (@shikhar)
|
||||
- Enable tokenizer on json fields [#2053](https://github.com/quickwit-oss/tantivy/issues/2053) (@PSeitz)
|
||||
- Enforcing "NOT" and "-" queries consistency in UserInputAst [#1609](https://github.com/quickwit-oss/tantivy/issues/1609) (@bazhenov)
|
||||
- Faster indexing
|
||||
- Refactor tokenization pipeline to use GATs [#1924](https://github.com/quickwit-oss/tantivy/issues/1924) (@trinity-1686a)
|
||||
- Faster term hash map [#2058](https://github.com/quickwit-oss/tantivy/issues/2058)[#1940](https://github.com/quickwit-oss/tantivy/issues/1940) (@PSeitz)
|
||||
- tokenizer-api: reduce Tokenizer allocation overhead [#2062](https://github.com/quickwit-oss/tantivy/issues/2062) (@PSeitz)
|
||||
- Refactor vint [#2010](https://github.com/quickwit-oss/tantivy/issues/2010) (@PSeitz)
|
||||
- Faster search
|
||||
- Work in batches of docs on the SegmentCollector (Only for cases without score for now) [#1937](https://github.com/quickwit-oss/tantivy/issues/1937) (@PSeitz)
|
||||
- Faster fast field range queries using SIMD [#1954](https://github.com/quickwit-oss/tantivy/issues/1954) (@fulmicoton)
|
||||
- Improve fast field range query performance [#1864](https://github.com/quickwit-oss/tantivy/issues/1864) (@PSeitz)
|
||||
- Make BM25 scoring more flexible [#1855](https://github.com/quickwit-oss/tantivy/issues/1855) (@alexcole)
|
||||
- Switch fs2 to fs4 as it is now unmaintained and does not support illumos [#1944](https://github.com/quickwit-oss/tantivy/issues/1944) (@Toasterson)
|
||||
- Made BooleanWeight and BoostWeight public [#1991](https://github.com/quickwit-oss/tantivy/issues/1991) (@fulmicoton)
|
||||
- Make index compatible with virtual drives on Windows [#1843](https://github.com/quickwit-oss/tantivy/issues/1843) (@gyk)
|
||||
- Add stop words for Hungarian language [#2069](https://github.com/quickwit-oss/tantivy/issues/2069) (@tnxbutno)
|
||||
- Auto downgrade index record option, instead of vint error [#1857](https://github.com/quickwit-oss/tantivy/issues/1857) (@PSeitz)
|
||||
- Enable range query on fast field for u64 compatible types [#1762](https://github.com/quickwit-oss/tantivy/issues/1762) (@PSeitz) [#1876]
|
||||
- sstable
|
||||
- Isolating sstable and stacker in independant crates. [#1718](https://github.com/quickwit-oss/tantivy/issues/1718) (@fulmicoton)
|
||||
- New sstable format [#1943](https://github.com/quickwit-oss/tantivy/issues/1943)[#1953](https://github.com/quickwit-oss/tantivy/issues/1953) (@trinity-1686a)
|
||||
- Use DeltaReader directly to implement Dictionnary::ord_to_term [#1928](https://github.com/quickwit-oss/tantivy/issues/1928) (@trinity-1686a)
|
||||
- Use DeltaReader directly to implement Dictionnary::term_ord [#1925](https://github.com/quickwit-oss/tantivy/issues/1925) (@trinity-1686a)
|
||||
- Add seperate tokenizer manager for fast fields [#2019](https://github.com/quickwit-oss/tantivy/issues/2019) (@PSeitz)
|
||||
- Make construction of LevenshteinAutomatonBuilder for FuzzyTermQuery instances lazy. [#1756](https://github.com/quickwit-oss/tantivy/issues/1756) (@adamreichold)
|
||||
- Added support for madvise when opening an mmaped Index [#2036](https://github.com/quickwit-oss/tantivy/issues/2036) (@fulmicoton)
|
||||
- Rename `DatePrecision` to `DateTimePrecision` [#2051](https://github.com/quickwit-oss/tantivy/issues/2051) (@guilload)
|
||||
- Query Parser
|
||||
- Quotation mark can now be used for phrase queries. [#2050](https://github.com/quickwit-oss/tantivy/issues/2050) (@fulmicoton)
|
||||
- PhrasePrefixQuery is supported in the query parser via: `field:"phrase ter"*` [#2044](https://github.com/quickwit-oss/tantivy/issues/2044) (@adamreichold)
|
||||
- Docs
|
||||
- Update examples for literate docs [#1880](https://github.com/quickwit-oss/tantivy/issues/1880) (@PSeitz)
|
||||
- Add ip field example [#1775](https://github.com/quickwit-oss/tantivy/issues/1775) (@PSeitz)
|
||||
- Fix doc store cache documentation [#1821](https://github.com/quickwit-oss/tantivy/issues/1821) (@PSeitz)
|
||||
- Fix BooleanQuery document [#1999](https://github.com/quickwit-oss/tantivy/issues/1999) (@RT_Enzyme)
|
||||
- Update comments in the faceted search example [#1737](https://github.com/quickwit-oss/tantivy/issues/1737) (@DawChihLiou)
|
||||
|
||||
|
||||
Tantivy 0.19
|
||||
================================
|
||||
#### Bugfixes
|
||||
|
||||
62
Cargo.toml
62
Cargo.toml
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy"
|
||||
version = "0.19.0"
|
||||
version = "0.21.0"
|
||||
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
|
||||
license = "MIT"
|
||||
categories = ["database-implementations", "data-structures"]
|
||||
@@ -12,27 +12,27 @@ readme = "README.md"
|
||||
keywords = ["search", "information", "retrieval"]
|
||||
edition = "2021"
|
||||
rust-version = "1.62"
|
||||
exclude = ["benches/*.json", "benches/*.txt"]
|
||||
|
||||
[dependencies]
|
||||
oneshot = "0.1.5"
|
||||
base64 = "0.21.0"
|
||||
byteorder = "1.4.3"
|
||||
crc32fast = "1.3.2"
|
||||
tracing = "0.1"
|
||||
once_cell = "1.10.0"
|
||||
regex = { version = "1.5.5", default-features = false, features = ["std", "unicode"] }
|
||||
aho-corasick = "0.7"
|
||||
aho-corasick = "1.0"
|
||||
tantivy-fst = "0.4.0"
|
||||
memmap2 = { version = "0.5.3", optional = true }
|
||||
lz4_flex = { version = "0.10", default-features = false, features = ["checked-decode"], optional = true }
|
||||
brotli = { version = "3.3.4", optional = true }
|
||||
memmap2 = { version = "0.7.1", optional = true }
|
||||
lz4_flex = { version = "0.11", default-features = false, optional = true }
|
||||
zstd = { version = "0.12", optional = true, default-features = false }
|
||||
snap = { version = "1.0.5", optional = true }
|
||||
tempfile = { version = "3.3.0", optional = true }
|
||||
log = "0.4.16"
|
||||
serde = { version = "1.0.136", features = ["derive"] }
|
||||
serde_json = "1.0.79"
|
||||
num_cpus = "1.13.1"
|
||||
fs2 = { version = "0.4.3", optional = true }
|
||||
fs4 = { version = "0.6.3", optional = true }
|
||||
levenshtein_automata = "0.2.1"
|
||||
uuid = { version = "1.0.0", features = ["v4", "serde"] }
|
||||
crossbeam-channel = "0.5.4"
|
||||
@@ -43,25 +43,27 @@ census = "0.4.0"
|
||||
rustc-hash = "1.1.0"
|
||||
thiserror = "1.0.30"
|
||||
htmlescape = "0.3.1"
|
||||
fail = "0.5.0"
|
||||
murmurhash32 = "0.2.0"
|
||||
fail = { version = "0.5.0", optional = true }
|
||||
murmurhash32 = "0.3.0"
|
||||
time = { version = "0.3.10", features = ["serde-well-known"] }
|
||||
smallvec = "1.8.0"
|
||||
rayon = "1.5.2"
|
||||
lru = "0.9.0"
|
||||
lru = "0.11.0"
|
||||
fastdivide = "0.4.0"
|
||||
itertools = "0.10.3"
|
||||
itertools = "0.11.0"
|
||||
measure_time = "0.8.2"
|
||||
async-trait = "0.1.53"
|
||||
arc-swap = "1.5.0"
|
||||
|
||||
columnar = { version="0.1", path="./columnar", package ="tantivy-columnar" }
|
||||
sstable = { version="0.1", path="./sstable", package ="tantivy-sstable", optional = true }
|
||||
stacker = { version="0.1", path="./stacker", package ="tantivy-stacker" }
|
||||
query-grammar = { version= "0.19.0", path="./query-grammar", package = "tantivy-query-grammar" }
|
||||
tantivy-bitpacker = { version= "0.3", path="./bitpacker" }
|
||||
common = { version= "0.5", path = "./common/", package = "tantivy-common" }
|
||||
tokenizer-api = { version="0.1", path="./tokenizer-api", package="tantivy-tokenizer-api" }
|
||||
columnar = { version= "0.2", path="./columnar", package ="tantivy-columnar" }
|
||||
sstable = { version= "0.2", path="./sstable", package ="tantivy-sstable", optional = true }
|
||||
stacker = { version= "0.2", path="./stacker", package ="tantivy-stacker" }
|
||||
query-grammar = { version= "0.21.0", path="./query-grammar", package = "tantivy-query-grammar" }
|
||||
tantivy-bitpacker = { version= "0.5", path="./bitpacker" }
|
||||
common = { version= "0.6", path = "./common/", package = "tantivy-common" }
|
||||
tokenizer-api = { version= "0.2", path="./tokenizer-api", package="tantivy-tokenizer-api" }
|
||||
sketches-ddsketch = { version = "0.2.1", features = ["use_serde"] }
|
||||
futures-util = { version = "0.3.28", optional = true }
|
||||
|
||||
[target.'cfg(windows)'.dependencies]
|
||||
winapi = "0.3.9"
|
||||
@@ -72,12 +74,16 @@ maplit = "1.0.2"
|
||||
matches = "0.1.9"
|
||||
pretty_assertions = "1.2.1"
|
||||
proptest = "1.0.0"
|
||||
criterion = "0.4"
|
||||
test-log = "0.2.10"
|
||||
env_logger = "0.10.0"
|
||||
pprof = { version = "0.11.0", features = ["flamegraph", "criterion"] }
|
||||
futures = "0.3.21"
|
||||
paste = "1.0.11"
|
||||
more-asserts = "0.3.1"
|
||||
rand_distr = "0.4.3"
|
||||
|
||||
[target.'cfg(not(windows))'.dev-dependencies]
|
||||
criterion = "0.5"
|
||||
pprof = { git = "https://github.com/PSeitz/pprof-rs/", rev = "53af24b", features = ["flamegraph", "criterion"] } # temp fork that works with criterion 0.5
|
||||
|
||||
[dev-dependencies.fail]
|
||||
version = "0.5.0"
|
||||
@@ -88,24 +94,27 @@ opt-level = 3
|
||||
debug = false
|
||||
debug-assertions = false
|
||||
|
||||
[profile.bench]
|
||||
opt-level = 3
|
||||
debug = true
|
||||
debug-assertions = false
|
||||
|
||||
[profile.test]
|
||||
debug-assertions = true
|
||||
overflow-checks = true
|
||||
|
||||
[features]
|
||||
default = ["mmap", "stopwords", "lz4-compression"]
|
||||
mmap = ["fs2", "tempfile", "memmap2"]
|
||||
mmap = ["fs4", "tempfile", "memmap2"]
|
||||
stopwords = []
|
||||
|
||||
brotli-compression = ["brotli"]
|
||||
lz4-compression = ["lz4_flex"]
|
||||
snappy-compression = ["snap"]
|
||||
zstd-compression = ["zstd"]
|
||||
|
||||
failpoints = ["fail/failpoints"]
|
||||
failpoints = ["fail", "fail/failpoints"]
|
||||
unstable = [] # useful for benches.
|
||||
|
||||
quickwit = ["sstable"]
|
||||
quickwit = ["sstable", "futures-util"]
|
||||
|
||||
[workspace]
|
||||
members = ["query-grammar", "bitpacker", "common", "ownedbytes", "stacker", "sstable", "tokenizer-api", "columnar"]
|
||||
@@ -120,7 +129,7 @@ members = ["query-grammar", "bitpacker", "common", "ownedbytes", "stacker", "sst
|
||||
[[test]]
|
||||
name = "failpoints"
|
||||
path = "tests/failpoints/mod.rs"
|
||||
required-features = ["fail/failpoints"]
|
||||
required-features = ["failpoints"]
|
||||
|
||||
[[bench]]
|
||||
name = "analyzer"
|
||||
@@ -129,4 +138,3 @@ harness = false
|
||||
[[bench]]
|
||||
name = "index-bench"
|
||||
harness = false
|
||||
|
||||
|
||||
2
Makefile
2
Makefile
@@ -1,5 +1,5 @@
|
||||
test:
|
||||
echo "Run test only... No examples."
|
||||
@echo "Run test only... No examples."
|
||||
cargo test --tests --lib
|
||||
|
||||
fmt:
|
||||
|
||||
@@ -26,6 +26,8 @@ Your mileage WILL vary depending on the nature of queries and their load.
|
||||
|
||||
<img src="doc/assets/images/searchbenchmark.png">
|
||||
|
||||
Details about the benchmark can be found at this [repository](https://github.com/quickwit-oss/search-benchmark-game).
|
||||
|
||||
# Features
|
||||
|
||||
- Full-text search
|
||||
@@ -42,7 +44,7 @@ Your mileage WILL vary depending on the nature of queries and their load.
|
||||
- Single valued and multivalued u64, i64, and f64 fast fields (equivalent of doc values in Lucene)
|
||||
- `&[u8]` fast fields
|
||||
- Text, i64, u64, f64, dates, ip, bool, and hierarchical facet fields
|
||||
- Compressed document store (LZ4, Zstd, None, Brotli, Snap)
|
||||
- Compressed document store (LZ4, Zstd, None)
|
||||
- Range queries
|
||||
- Faceted search
|
||||
- Configurable indexing (optional term frequency and position indexing)
|
||||
|
||||
21
RELEASE.md
Normal file
21
RELEASE.md
Normal file
@@ -0,0 +1,21 @@
|
||||
# Release a new Tantivy Version
|
||||
|
||||
## Steps
|
||||
|
||||
1. Identify new packages in workspace since last release
|
||||
2. Identify changed packages in workspace since last release
|
||||
3. Bump version in `Cargo.toml` and their dependents for all changed packages
|
||||
4. Update version of root `Cargo.toml`
|
||||
5. Publish version starting with leaf nodes
|
||||
6. Set git tag with new version
|
||||
|
||||
|
||||
In conjucation with `cargo-release` Steps 1-4 (I'm not sure if the change detection works):
|
||||
Set new packages to version 0.0.0
|
||||
|
||||
Replace prev-tag-name
|
||||
```bash
|
||||
cargo release --workspace --no-publish -v --prev-tag-name 0.19 --push-remote origin minor --no-tag --execute
|
||||
```
|
||||
|
||||
no-tag or it will create tags for all the subpackages
|
||||
23
appveyor.yml
23
appveyor.yml
@@ -1,23 +0,0 @@
|
||||
# Appveyor configuration template for Rust using rustup for Rust installation
|
||||
# https://github.com/starkat99/appveyor-rust
|
||||
|
||||
os: Visual Studio 2015
|
||||
environment:
|
||||
matrix:
|
||||
- channel: stable
|
||||
target: x86_64-pc-windows-msvc
|
||||
|
||||
install:
|
||||
- appveyor DownloadFile https://win.rustup.rs/ -FileName rustup-init.exe
|
||||
- rustup-init -yv --default-toolchain %channel% --default-host %target%
|
||||
- set PATH=%PATH%;%USERPROFILE%\.cargo\bin
|
||||
- if defined msys_bits set PATH=%PATH%;C:\msys64\mingw%msys_bits%\bin
|
||||
- rustc -vV
|
||||
- cargo -vV
|
||||
|
||||
build: false
|
||||
|
||||
test_script:
|
||||
- REM SET RUST_LOG=tantivy,test & cargo test --all --verbose --no-default-features --features lz4-compression --features mmap
|
||||
- REM SET RUST_LOG=tantivy,test & cargo test test_store --verbose --no-default-features --features lz4-compression --features snappy-compression --features brotli-compression --features mmap
|
||||
- REM SET RUST_BACKTRACE=1 & cargo build --examples
|
||||
@@ -1,11 +1,13 @@
|
||||
use criterion::{criterion_group, criterion_main, Criterion};
|
||||
use tantivy::tokenizer::TokenizerManager;
|
||||
use tantivy::tokenizer::{
|
||||
LowerCaser, RemoveLongFilter, SimpleTokenizer, TextAnalyzer, TokenizerManager,
|
||||
};
|
||||
|
||||
const ALICE_TXT: &str = include_str!("alice.txt");
|
||||
|
||||
pub fn criterion_benchmark(c: &mut Criterion) {
|
||||
let tokenizer_manager = TokenizerManager::default();
|
||||
let tokenizer = tokenizer_manager.get("default").unwrap();
|
||||
let mut tokenizer = tokenizer_manager.get("default").unwrap();
|
||||
c.bench_function("default-tokenize-alice", |b| {
|
||||
b.iter(|| {
|
||||
let mut word_count = 0;
|
||||
@@ -16,7 +18,26 @@ pub fn criterion_benchmark(c: &mut Criterion) {
|
||||
assert_eq!(word_count, 30_731);
|
||||
})
|
||||
});
|
||||
let mut dynamic_analyzer = TextAnalyzer::builder(SimpleTokenizer::default())
|
||||
.dynamic()
|
||||
.filter_dynamic(RemoveLongFilter::limit(40))
|
||||
.filter_dynamic(LowerCaser)
|
||||
.build();
|
||||
c.bench_function("dynamic-tokenize-alice", |b| {
|
||||
b.iter(|| {
|
||||
let mut word_count = 0;
|
||||
let mut token_stream = dynamic_analyzer.token_stream(ALICE_TXT);
|
||||
while token_stream.advance() {
|
||||
word_count += 1;
|
||||
}
|
||||
assert_eq!(word_count, 30_731);
|
||||
})
|
||||
});
|
||||
}
|
||||
|
||||
criterion_group!(benches, criterion_benchmark);
|
||||
criterion_group! {
|
||||
name = benches;
|
||||
config = Criterion::default().sample_size(200);
|
||||
targets = criterion_benchmark
|
||||
}
|
||||
criterion_main!(benches);
|
||||
|
||||
1000
benches/gh.json
Normal file
1000
benches/gh.json
Normal file
File diff suppressed because one or more lines are too long
@@ -1,10 +1,15 @@
|
||||
use criterion::{criterion_group, criterion_main, Criterion};
|
||||
use criterion::{criterion_group, criterion_main, Criterion, Throughput};
|
||||
use pprof::criterion::{Output, PProfProfiler};
|
||||
use tantivy::schema::{INDEXED, STORED, STRING, TEXT};
|
||||
use tantivy::schema::{FAST, INDEXED, STORED, STRING, TEXT};
|
||||
use tantivy::Index;
|
||||
|
||||
const HDFS_LOGS: &str = include_str!("hdfs.json");
|
||||
const NUM_REPEATS: usize = 2;
|
||||
const GH_LOGS: &str = include_str!("gh.json");
|
||||
const WIKI: &str = include_str!("wiki.json");
|
||||
|
||||
fn get_lines(input: &str) -> Vec<&str> {
|
||||
input.trim().split('\n').collect()
|
||||
}
|
||||
|
||||
pub fn hdfs_index_benchmark(c: &mut Criterion) {
|
||||
let schema = {
|
||||
@@ -28,85 +33,147 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
|
||||
};
|
||||
|
||||
let mut group = c.benchmark_group("index-hdfs");
|
||||
group.throughput(Throughput::Bytes(HDFS_LOGS.len() as u64));
|
||||
group.sample_size(20);
|
||||
group.bench_function("index-hdfs-no-commit", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for _ in 0..NUM_REPEATS {
|
||||
for doc_json in HDFS_LOGS.trim().split('\n') {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-with-commit", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for _ in 0..NUM_REPEATS {
|
||||
for doc_json in HDFS_LOGS.trim().split('\n') {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-no-commit-with-docstore", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema_with_store.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for _ in 0..NUM_REPEATS {
|
||||
for doc_json in HDFS_LOGS.trim().split('\n') {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-with-commit-with-docstore", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(schema_with_store.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for _ in 0..NUM_REPEATS {
|
||||
for doc_json in HDFS_LOGS.trim().split('\n') {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
for doc_json in &lines {
|
||||
let doc = schema.parse_document(doc_json).unwrap();
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-no-commit-json-without-docstore", |b| {
|
||||
let lines = get_lines(HDFS_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for _ in 0..NUM_REPEATS {
|
||||
for doc_json in HDFS_LOGS.trim().split('\n') {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
for doc_json in &lines {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
});
|
||||
group.bench_function("index-hdfs-with-commit-json-without-docstore", |b| {
|
||||
}
|
||||
|
||||
pub fn gh_index_benchmark(c: &mut Criterion) {
|
||||
let dynamic_schema = {
|
||||
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
|
||||
schema_builder.add_json_field("json", TEXT | FAST);
|
||||
schema_builder.build()
|
||||
};
|
||||
|
||||
let mut group = c.benchmark_group("index-gh");
|
||||
group.throughput(Throughput::Bytes(GH_LOGS.len() as u64));
|
||||
|
||||
group.bench_function("index-gh-no-commit", |b| {
|
||||
let lines = get_lines(GH_LOGS);
|
||||
b.iter(|| {
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
})
|
||||
});
|
||||
group.bench_function("index-gh-with-commit", |b| {
|
||||
let lines = get_lines(GH_LOGS);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for _ in 0..NUM_REPEATS {
|
||||
for doc_json in HDFS_LOGS.trim().split('\n') {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
for doc_json in &lines {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
});
|
||||
}
|
||||
|
||||
pub fn wiki_index_benchmark(c: &mut Criterion) {
|
||||
let dynamic_schema = {
|
||||
let mut schema_builder = tantivy::schema::SchemaBuilder::new();
|
||||
schema_builder.add_json_field("json", TEXT | FAST);
|
||||
schema_builder.build()
|
||||
};
|
||||
|
||||
let mut group = c.benchmark_group("index-wiki");
|
||||
group.throughput(Throughput::Bytes(WIKI.len() as u64));
|
||||
|
||||
group.bench_function("index-wiki-no-commit", |b| {
|
||||
let lines = get_lines(WIKI);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
})
|
||||
});
|
||||
group.bench_function("index-wiki-with-commit", |b| {
|
||||
let lines = get_lines(WIKI);
|
||||
b.iter(|| {
|
||||
let json_field = dynamic_schema.get_field("json").unwrap();
|
||||
let index = Index::create_in_ram(dynamic_schema.clone());
|
||||
let mut index_writer = index.writer_with_num_threads(1, 100_000_000).unwrap();
|
||||
for doc_json in &lines {
|
||||
let json_val: serde_json::Map<String, serde_json::Value> =
|
||||
serde_json::from_str(doc_json).unwrap();
|
||||
let doc = tantivy::doc!(json_field=>json_val);
|
||||
index_writer.add_document(doc).unwrap();
|
||||
}
|
||||
index_writer.commit().unwrap();
|
||||
})
|
||||
@@ -115,7 +182,17 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
|
||||
|
||||
criterion_group! {
|
||||
name = benches;
|
||||
config = Criterion::default().with_profiler(PProfProfiler::new(100, Output::Flamegraph(None)));
|
||||
config = Criterion::default();
|
||||
targets = hdfs_index_benchmark
|
||||
}
|
||||
criterion_main!(benches);
|
||||
criterion_group! {
|
||||
name = gh_benches;
|
||||
config = Criterion::default().with_profiler(PProfProfiler::new(100, Output::Flamegraph(None)));
|
||||
targets = gh_index_benchmark
|
||||
}
|
||||
criterion_group! {
|
||||
name = wiki_benches;
|
||||
config = Criterion::default().with_profiler(PProfProfiler::new(100, Output::Flamegraph(None)));
|
||||
targets = wiki_index_benchmark
|
||||
}
|
||||
criterion_main!(benches, gh_benches, wiki_benches);
|
||||
|
||||
1000
benches/wiki.json
Normal file
1000
benches/wiki.json
Normal file
File diff suppressed because one or more lines are too long
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy-bitpacker"
|
||||
version = "0.3.0"
|
||||
version = "0.5.0"
|
||||
edition = "2021"
|
||||
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
|
||||
license = "MIT"
|
||||
@@ -15,6 +15,7 @@ homepage = "https://github.com/quickwit-oss/tantivy"
|
||||
# See more keys and their definitions at https://doc.rust-lang.org/cargo/reference/manifest.html
|
||||
|
||||
[dependencies]
|
||||
bitpacking = {version="0.8", default-features=false, features = ["bitpacker1x"]}
|
||||
|
||||
[dev-dependencies]
|
||||
rand = "0.8"
|
||||
|
||||
@@ -1,10 +1,14 @@
|
||||
use std::convert::TryInto;
|
||||
use std::io;
|
||||
use std::ops::{Range, RangeInclusive};
|
||||
|
||||
use bitpacking::{BitPacker as ExternalBitPackerTrait, BitPacker1x};
|
||||
|
||||
pub struct BitPacker {
|
||||
mini_buffer: u64,
|
||||
mini_buffer_written: usize,
|
||||
}
|
||||
|
||||
impl Default for BitPacker {
|
||||
fn default() -> Self {
|
||||
BitPacker::new()
|
||||
@@ -118,6 +122,125 @@ impl BitUnpacker {
|
||||
let val_shifted = val_unshifted_unmasked >> bit_shift;
|
||||
val_shifted & self.mask
|
||||
}
|
||||
|
||||
// Decodes the range of bitpacked `u32` values with idx
|
||||
// in [start_idx, start_idx + output.len()).
|
||||
//
|
||||
// #Panics
|
||||
//
|
||||
// This methods panics if `num_bits` is > 32.
|
||||
fn get_batch_u32s(&self, start_idx: u32, data: &[u8], output: &mut [u32]) {
|
||||
assert!(
|
||||
self.bit_width() <= 32,
|
||||
"Bitwidth must be <= 32 to use this method."
|
||||
);
|
||||
|
||||
let end_idx = start_idx + output.len() as u32;
|
||||
|
||||
let end_bit_read = end_idx * self.num_bits;
|
||||
let end_byte_read = (end_bit_read + 7) / 8;
|
||||
assert!(
|
||||
end_byte_read as usize <= data.len(),
|
||||
"Requested index is out of bounds."
|
||||
);
|
||||
|
||||
// Simple slow implementation of get_batch_u32s, to deal with our ramps.
|
||||
let get_batch_ramp = |start_idx: u32, output: &mut [u32]| {
|
||||
for (out, idx) in output.iter_mut().zip(start_idx..) {
|
||||
*out = self.get(idx, data) as u32;
|
||||
}
|
||||
};
|
||||
|
||||
// We use an unrolled routine to decode 32 values at once.
|
||||
// We therefore decompose our range of values to decode into three ranges:
|
||||
// - Entrance ramp: [start_idx, fast_track_start) (up to 31 values)
|
||||
// - Highway: [fast_track_start, fast_track_end) (a length multiple of 32s)
|
||||
// - Exit ramp: [fast_track_end, start_idx + output.len()) (up to 31 values)
|
||||
|
||||
// We want the start of the fast track to start align with bytes.
|
||||
// A sufficient condition is to start with an idx that is a multiple of 8,
|
||||
// so highway start is the closest multiple of 8 that is >= start_idx.
|
||||
let entrance_ramp_len = 8 - (start_idx % 8) % 8;
|
||||
|
||||
let highway_start: u32 = start_idx + entrance_ramp_len;
|
||||
|
||||
if highway_start + BitPacker1x::BLOCK_LEN as u32 > end_idx {
|
||||
// We don't have enough values to have even a single block of highway.
|
||||
// Let's just supply the values the simple way.
|
||||
get_batch_ramp(start_idx, output);
|
||||
return;
|
||||
}
|
||||
|
||||
let num_blocks: u32 = (end_idx - highway_start) / BitPacker1x::BLOCK_LEN as u32;
|
||||
|
||||
// Entrance ramp
|
||||
get_batch_ramp(start_idx, &mut output[..entrance_ramp_len as usize]);
|
||||
|
||||
// Highway
|
||||
let mut offset = (highway_start * self.num_bits) as usize / 8;
|
||||
let mut output_cursor = (highway_start - start_idx) as usize;
|
||||
for _ in 0..num_blocks {
|
||||
offset += BitPacker1x.decompress(
|
||||
&data[offset..],
|
||||
&mut output[output_cursor..],
|
||||
self.num_bits as u8,
|
||||
);
|
||||
output_cursor += 32;
|
||||
}
|
||||
|
||||
// Exit ramp
|
||||
let highway_end = highway_start + num_blocks * BitPacker1x::BLOCK_LEN as u32;
|
||||
get_batch_ramp(highway_end, &mut output[output_cursor..]);
|
||||
}
|
||||
|
||||
pub fn get_ids_for_value_range(
|
||||
&self,
|
||||
range: RangeInclusive<u64>,
|
||||
id_range: Range<u32>,
|
||||
data: &[u8],
|
||||
positions: &mut Vec<u32>,
|
||||
) {
|
||||
if self.bit_width() > 32 {
|
||||
self.get_ids_for_value_range_slow(range, id_range, data, positions)
|
||||
} else {
|
||||
if *range.start() > u32::MAX as u64 {
|
||||
positions.clear();
|
||||
return;
|
||||
}
|
||||
let range_u32 = (*range.start() as u32)..=(*range.end()).min(u32::MAX as u64) as u32;
|
||||
self.get_ids_for_value_range_fast(range_u32, id_range, data, positions)
|
||||
}
|
||||
}
|
||||
|
||||
fn get_ids_for_value_range_slow(
|
||||
&self,
|
||||
range: RangeInclusive<u64>,
|
||||
id_range: Range<u32>,
|
||||
data: &[u8],
|
||||
positions: &mut Vec<u32>,
|
||||
) {
|
||||
positions.clear();
|
||||
for i in id_range {
|
||||
// If we cared we could make this branchless, but the slow implementation should rarely
|
||||
// kick in.
|
||||
let val = self.get(i, data);
|
||||
if range.contains(&val) {
|
||||
positions.push(i);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn get_ids_for_value_range_fast(
|
||||
&self,
|
||||
value_range: RangeInclusive<u32>,
|
||||
id_range: Range<u32>,
|
||||
data: &[u8],
|
||||
positions: &mut Vec<u32>,
|
||||
) {
|
||||
positions.resize(id_range.len(), 0u32);
|
||||
self.get_batch_u32s(id_range.start, data, positions);
|
||||
crate::filter_vec::filter_vec_in_place(value_range, id_range.start, positions)
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
@@ -200,4 +323,58 @@ mod test {
|
||||
test_bitpacker_aux(num_bits, &vals);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
#[should_panic]
|
||||
fn test_get_batch_panics_over_32_bits() {
|
||||
let bitunpacker = BitUnpacker::new(33);
|
||||
let mut output: [u32; 1] = [0u32];
|
||||
bitunpacker.get_batch_u32s(0, &[0, 0, 0, 0, 0, 0, 0, 0], &mut output[..]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_get_batch_limit() {
|
||||
let bitunpacker = BitUnpacker::new(1);
|
||||
let mut output: [u32; 3] = [0u32, 0u32, 0u32];
|
||||
bitunpacker.get_batch_u32s(8 * 4 - 3, &[0u8, 0u8, 0u8, 0u8], &mut output[..]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
#[should_panic]
|
||||
fn test_get_batch_panics_when_off_scope() {
|
||||
let bitunpacker = BitUnpacker::new(1);
|
||||
let mut output: [u32; 3] = [0u32, 0u32, 0u32];
|
||||
// We are missing exactly one bit.
|
||||
bitunpacker.get_batch_u32s(8 * 4 - 2, &[0u8, 0u8, 0u8, 0u8], &mut output[..]);
|
||||
}
|
||||
|
||||
proptest::proptest! {
|
||||
#[test]
|
||||
fn test_get_batch_u32s_proptest(num_bits in 0u8..=32u8) {
|
||||
let mask =
|
||||
if num_bits == 32u8 {
|
||||
u32::MAX
|
||||
} else {
|
||||
(1u32 << num_bits) - 1
|
||||
};
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
let mut bitpacker = BitPacker::new();
|
||||
for val in 0..100 {
|
||||
bitpacker.write(val & mask as u64, num_bits, &mut buffer).unwrap();
|
||||
}
|
||||
bitpacker.flush(&mut buffer).unwrap();
|
||||
let bitunpacker = BitUnpacker::new(num_bits);
|
||||
let mut output: Vec<u32> = Vec::new();
|
||||
for len in [0, 1, 2, 32, 33, 34, 64] {
|
||||
for start_idx in 0u32..32u32 {
|
||||
output.resize(len as usize, 0);
|
||||
bitunpacker.get_batch_u32s(start_idx, &buffer, &mut output);
|
||||
for i in 0..len {
|
||||
let expected = (start_idx + i as u32) & mask;
|
||||
assert_eq!(output[i], expected);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -64,10 +64,8 @@ fn mem_usage<T>(items: &Vec<T>) -> usize {
|
||||
|
||||
impl BlockedBitpacker {
|
||||
pub fn new() -> Self {
|
||||
let mut compressed_blocks = vec![];
|
||||
compressed_blocks.resize(8, 0);
|
||||
Self {
|
||||
compressed_blocks,
|
||||
compressed_blocks: vec![0; 8],
|
||||
buffer: vec![],
|
||||
offset_and_bits: vec![],
|
||||
}
|
||||
|
||||
365
bitpacker/src/filter_vec/avx2.rs
Normal file
365
bitpacker/src/filter_vec/avx2.rs
Normal file
@@ -0,0 +1,365 @@
|
||||
//! SIMD filtering of a vector as described in the following blog post.
|
||||
//! <https://quickwit.io/blog/filtering%20a%20vector%20with%20simd%20instructions%20avx-2%20and%20avx-512>
|
||||
use std::arch::x86_64::{
|
||||
__m256i as DataType, _mm256_add_epi32 as op_add, _mm256_cmpgt_epi32 as op_greater,
|
||||
_mm256_lddqu_si256 as load_unaligned, _mm256_or_si256 as op_or, _mm256_set1_epi32 as set1,
|
||||
_mm256_storeu_si256 as store_unaligned, _mm256_xor_si256 as op_xor, *,
|
||||
};
|
||||
use std::ops::RangeInclusive;
|
||||
|
||||
const NUM_LANES: usize = 8;
|
||||
|
||||
const HIGHEST_BIT: u32 = 1 << 31;
|
||||
|
||||
#[inline]
|
||||
fn u32_to_i32(val: u32) -> i32 {
|
||||
(val ^ HIGHEST_BIT) as i32
|
||||
}
|
||||
|
||||
#[inline]
|
||||
unsafe fn u32_to_i32_avx2(vals_u32x8s: DataType) -> DataType {
|
||||
const HIGHEST_BIT_MASK: DataType = from_u32x8([HIGHEST_BIT; NUM_LANES]);
|
||||
op_xor(vals_u32x8s, HIGHEST_BIT_MASK)
|
||||
}
|
||||
|
||||
pub fn filter_vec_in_place(range: RangeInclusive<u32>, offset: u32, output: &mut Vec<u32>) {
|
||||
// We use a monotonic mapping from u32 to i32 to make the comparison possible in AVX2.
|
||||
let range_i32: RangeInclusive<i32> = u32_to_i32(*range.start())..=u32_to_i32(*range.end());
|
||||
let num_words = output.len() / NUM_LANES;
|
||||
let mut output_len = unsafe {
|
||||
filter_vec_avx2_aux(
|
||||
output.as_ptr() as *const __m256i,
|
||||
range_i32,
|
||||
output.as_mut_ptr(),
|
||||
offset,
|
||||
num_words,
|
||||
)
|
||||
};
|
||||
let reminder_start = num_words * NUM_LANES;
|
||||
for i in reminder_start..output.len() {
|
||||
let val = output[i];
|
||||
output[output_len] = offset + i as u32;
|
||||
output_len += if range.contains(&val) { 1 } else { 0 };
|
||||
}
|
||||
output.truncate(output_len);
|
||||
}
|
||||
|
||||
#[target_feature(enable = "avx2")]
|
||||
unsafe fn filter_vec_avx2_aux(
|
||||
mut input: *const __m256i,
|
||||
range: RangeInclusive<i32>,
|
||||
output: *mut u32,
|
||||
offset: u32,
|
||||
num_words: usize,
|
||||
) -> usize {
|
||||
let mut output_tail = output;
|
||||
let range_simd = set1(*range.start())..=set1(*range.end());
|
||||
let mut ids = from_u32x8([
|
||||
offset,
|
||||
offset + 1,
|
||||
offset + 2,
|
||||
offset + 3,
|
||||
offset + 4,
|
||||
offset + 5,
|
||||
offset + 6,
|
||||
offset + 7,
|
||||
]);
|
||||
const SHIFT: __m256i = from_u32x8([NUM_LANES as u32; NUM_LANES]);
|
||||
for _ in 0..num_words {
|
||||
let word = load_unaligned(input);
|
||||
let word = u32_to_i32_avx2(word);
|
||||
let keeper_bitset = compute_filter_bitset(word, range_simd.clone());
|
||||
let added_len = keeper_bitset.count_ones();
|
||||
let filtered_doc_ids = compact(ids, keeper_bitset);
|
||||
store_unaligned(output_tail as *mut __m256i, filtered_doc_ids);
|
||||
output_tail = output_tail.offset(added_len as isize);
|
||||
ids = op_add(ids, SHIFT);
|
||||
input = input.offset(1);
|
||||
}
|
||||
output_tail.offset_from(output) as usize
|
||||
}
|
||||
|
||||
#[inline]
|
||||
#[target_feature(enable = "avx2")]
|
||||
unsafe fn compact(data: DataType, mask: u8) -> DataType {
|
||||
let vperm_mask = MASK_TO_PERMUTATION[mask as usize];
|
||||
_mm256_permutevar8x32_epi32(data, vperm_mask)
|
||||
}
|
||||
|
||||
#[inline]
|
||||
#[target_feature(enable = "avx2")]
|
||||
unsafe fn compute_filter_bitset(val: __m256i, range: std::ops::RangeInclusive<__m256i>) -> u8 {
|
||||
let too_low = op_greater(*range.start(), val);
|
||||
let too_high = op_greater(val, *range.end());
|
||||
let inside = op_or(too_low, too_high);
|
||||
255 - std::arch::x86_64::_mm256_movemask_ps(std::mem::transmute::<DataType, __m256>(inside))
|
||||
as u8
|
||||
}
|
||||
|
||||
union U8x32 {
|
||||
vector: DataType,
|
||||
vals: [u32; NUM_LANES],
|
||||
}
|
||||
|
||||
const fn from_u32x8(vals: [u32; NUM_LANES]) -> DataType {
|
||||
unsafe { U8x32 { vals }.vector }
|
||||
}
|
||||
|
||||
const MASK_TO_PERMUTATION: [DataType; 256] = [
|
||||
from_u32x8([0, 0, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 0, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 0, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 0, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([3, 0, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 0, 0, 0, 0]),
|
||||
from_u32x8([4, 0, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 4, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 4, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 4, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 4, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 4, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 4, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 4, 0, 0, 0, 0]),
|
||||
from_u32x8([3, 4, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 4, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 4, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 4, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 4, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 4, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 4, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 4, 0, 0, 0]),
|
||||
from_u32x8([5, 0, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 5, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 5, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 5, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 5, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 5, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 5, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 5, 0, 0, 0, 0]),
|
||||
from_u32x8([3, 5, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 5, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 5, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 5, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 5, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 5, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 5, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 5, 0, 0, 0]),
|
||||
from_u32x8([4, 5, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 4, 5, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 4, 5, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 4, 5, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 4, 5, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 4, 5, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 4, 5, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 4, 5, 0, 0, 0]),
|
||||
from_u32x8([3, 4, 5, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 4, 5, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 4, 5, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 4, 5, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 4, 5, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 4, 5, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 4, 5, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 4, 5, 0, 0]),
|
||||
from_u32x8([6, 0, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 6, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 6, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 6, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([3, 6, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 6, 0, 0, 0]),
|
||||
from_u32x8([4, 6, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 4, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 4, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 4, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 4, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 4, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 4, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 4, 6, 0, 0, 0]),
|
||||
from_u32x8([3, 4, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 4, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 4, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 4, 6, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 4, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 4, 6, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 4, 6, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 4, 6, 0, 0]),
|
||||
from_u32x8([5, 6, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 5, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 5, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 5, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 5, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 5, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 5, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 5, 6, 0, 0, 0]),
|
||||
from_u32x8([3, 5, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 5, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 5, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 5, 6, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 5, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 5, 6, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 5, 6, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 5, 6, 0, 0]),
|
||||
from_u32x8([4, 5, 6, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 4, 5, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 4, 5, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 4, 5, 6, 0, 0, 0]),
|
||||
from_u32x8([2, 4, 5, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 4, 5, 6, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 4, 5, 6, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 4, 5, 6, 0, 0]),
|
||||
from_u32x8([3, 4, 5, 6, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 4, 5, 6, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 4, 5, 6, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 4, 5, 6, 0, 0]),
|
||||
from_u32x8([2, 3, 4, 5, 6, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 4, 5, 6, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 4, 5, 6, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 4, 5, 6, 0]),
|
||||
from_u32x8([7, 0, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 7, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 7, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 7, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([3, 7, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 7, 0, 0, 0]),
|
||||
from_u32x8([4, 7, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 4, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 4, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 4, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 4, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 4, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 4, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 4, 7, 0, 0, 0]),
|
||||
from_u32x8([3, 4, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 4, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 4, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 4, 7, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 4, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 4, 7, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 4, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 4, 7, 0, 0]),
|
||||
from_u32x8([5, 7, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 5, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 5, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 5, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 5, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 5, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 5, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 5, 7, 0, 0, 0]),
|
||||
from_u32x8([3, 5, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 5, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 5, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 5, 7, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 5, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 5, 7, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 5, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 5, 7, 0, 0]),
|
||||
from_u32x8([4, 5, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 4, 5, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 4, 5, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 4, 5, 7, 0, 0, 0]),
|
||||
from_u32x8([2, 4, 5, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 4, 5, 7, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 4, 5, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 4, 5, 7, 0, 0]),
|
||||
from_u32x8([3, 4, 5, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 4, 5, 7, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 4, 5, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 4, 5, 7, 0, 0]),
|
||||
from_u32x8([2, 3, 4, 5, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 4, 5, 7, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 4, 5, 7, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 4, 5, 7, 0]),
|
||||
from_u32x8([6, 7, 0, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 6, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 6, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([2, 6, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([3, 6, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([2, 3, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 6, 7, 0, 0]),
|
||||
from_u32x8([4, 6, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 4, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 4, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 4, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([2, 4, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 4, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 4, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 4, 6, 7, 0, 0]),
|
||||
from_u32x8([3, 4, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 4, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 4, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 4, 6, 7, 0, 0]),
|
||||
from_u32x8([2, 3, 4, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 4, 6, 7, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 4, 6, 7, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 4, 6, 7, 0]),
|
||||
from_u32x8([5, 6, 7, 0, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 5, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([1, 5, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 5, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([2, 5, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 5, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([1, 2, 5, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 5, 6, 7, 0, 0]),
|
||||
from_u32x8([3, 5, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 5, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([1, 3, 5, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 5, 6, 7, 0, 0]),
|
||||
from_u32x8([2, 3, 5, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 5, 6, 7, 0, 0]),
|
||||
from_u32x8([1, 2, 3, 5, 6, 7, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 5, 6, 7, 0]),
|
||||
from_u32x8([4, 5, 6, 7, 0, 0, 0, 0]),
|
||||
from_u32x8([0, 4, 5, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([1, 4, 5, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 1, 4, 5, 6, 7, 0, 0]),
|
||||
from_u32x8([2, 4, 5, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 2, 4, 5, 6, 7, 0, 0]),
|
||||
from_u32x8([1, 2, 4, 5, 6, 7, 0, 0]),
|
||||
from_u32x8([0, 1, 2, 4, 5, 6, 7, 0]),
|
||||
from_u32x8([3, 4, 5, 6, 7, 0, 0, 0]),
|
||||
from_u32x8([0, 3, 4, 5, 6, 7, 0, 0]),
|
||||
from_u32x8([1, 3, 4, 5, 6, 7, 0, 0]),
|
||||
from_u32x8([0, 1, 3, 4, 5, 6, 7, 0]),
|
||||
from_u32x8([2, 3, 4, 5, 6, 7, 0, 0]),
|
||||
from_u32x8([0, 2, 3, 4, 5, 6, 7, 0]),
|
||||
from_u32x8([1, 2, 3, 4, 5, 6, 7, 0]),
|
||||
from_u32x8([0, 1, 2, 3, 4, 5, 6, 7]),
|
||||
];
|
||||
165
bitpacker/src/filter_vec/mod.rs
Normal file
165
bitpacker/src/filter_vec/mod.rs
Normal file
@@ -0,0 +1,165 @@
|
||||
use std::ops::RangeInclusive;
|
||||
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
mod avx2;
|
||||
|
||||
mod scalar;
|
||||
|
||||
#[derive(Clone, Copy, Eq, PartialEq, Debug)]
|
||||
#[repr(u8)]
|
||||
enum FilterImplPerInstructionSet {
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
AVX2 = 0u8,
|
||||
Scalar = 1u8,
|
||||
}
|
||||
|
||||
impl FilterImplPerInstructionSet {
|
||||
#[inline]
|
||||
pub fn is_available(&self) -> bool {
|
||||
match *self {
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
FilterImplPerInstructionSet::AVX2 => is_x86_feature_detected!("avx2"),
|
||||
FilterImplPerInstructionSet::Scalar => true,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// List of available implementation in preferred order.
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
const IMPLS: [FilterImplPerInstructionSet; 2] = [
|
||||
FilterImplPerInstructionSet::AVX2,
|
||||
FilterImplPerInstructionSet::Scalar,
|
||||
];
|
||||
|
||||
#[cfg(not(target_arch = "x86_64"))]
|
||||
const IMPLS: [FilterImplPerInstructionSet; 1] = [FilterImplPerInstructionSet::Scalar];
|
||||
|
||||
impl FilterImplPerInstructionSet {
|
||||
#[allow(unused_variables)]
|
||||
#[inline]
|
||||
fn from(code: u8) -> FilterImplPerInstructionSet {
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
if code == FilterImplPerInstructionSet::AVX2 as u8 {
|
||||
return FilterImplPerInstructionSet::AVX2;
|
||||
}
|
||||
FilterImplPerInstructionSet::Scalar
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn filter_vec_in_place(self, range: RangeInclusive<u32>, offset: u32, output: &mut Vec<u32>) {
|
||||
match self {
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
FilterImplPerInstructionSet::AVX2 => avx2::filter_vec_in_place(range, offset, output),
|
||||
FilterImplPerInstructionSet::Scalar => {
|
||||
scalar::filter_vec_in_place(range, offset, output)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn get_best_available_instruction_set() -> FilterImplPerInstructionSet {
|
||||
use std::sync::atomic::{AtomicU8, Ordering};
|
||||
static INSTRUCTION_SET_BYTE: AtomicU8 = AtomicU8::new(u8::MAX);
|
||||
let instruction_set_byte: u8 = INSTRUCTION_SET_BYTE.load(Ordering::Relaxed);
|
||||
if instruction_set_byte == u8::MAX {
|
||||
// Let's initialize the instruction set and cache it.
|
||||
let instruction_set = IMPLS
|
||||
.into_iter()
|
||||
.find(FilterImplPerInstructionSet::is_available)
|
||||
.unwrap();
|
||||
INSTRUCTION_SET_BYTE.store(instruction_set as u8, Ordering::Relaxed);
|
||||
return instruction_set;
|
||||
}
|
||||
FilterImplPerInstructionSet::from(instruction_set_byte)
|
||||
}
|
||||
|
||||
pub fn filter_vec_in_place(range: RangeInclusive<u32>, offset: u32, output: &mut Vec<u32>) {
|
||||
get_best_available_instruction_set().filter_vec_in_place(range, offset, output)
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn test_get_best_available_instruction_set() {
|
||||
// This does not test much unfortunately.
|
||||
// We just make sure the function returns without crashing and returns the same result.
|
||||
let instruction_set = get_best_available_instruction_set();
|
||||
assert_eq!(get_best_available_instruction_set(), instruction_set);
|
||||
}
|
||||
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
#[test]
|
||||
fn test_instruction_set_to_code_from_code() {
|
||||
for instruction_set in [
|
||||
FilterImplPerInstructionSet::AVX2,
|
||||
FilterImplPerInstructionSet::Scalar,
|
||||
] {
|
||||
let code = instruction_set as u8;
|
||||
assert_eq!(instruction_set, FilterImplPerInstructionSet::from(code));
|
||||
}
|
||||
}
|
||||
|
||||
fn test_filter_impl_empty_aux(filter_impl: FilterImplPerInstructionSet) {
|
||||
let mut output = vec![];
|
||||
filter_impl.filter_vec_in_place(0..=u32::MAX, 0, &mut output);
|
||||
assert_eq!(&output, &[]);
|
||||
}
|
||||
|
||||
fn test_filter_impl_simple_aux(filter_impl: FilterImplPerInstructionSet) {
|
||||
let mut output = vec![3, 2, 1, 5, 11, 2, 5, 10, 2];
|
||||
filter_impl.filter_vec_in_place(3..=10, 0, &mut output);
|
||||
assert_eq!(&output, &[0, 3, 6, 7]);
|
||||
}
|
||||
|
||||
fn test_filter_impl_simple_aux_shifted(filter_impl: FilterImplPerInstructionSet) {
|
||||
let mut output = vec![3, 2, 1, 5, 11, 2, 5, 10, 2];
|
||||
filter_impl.filter_vec_in_place(3..=10, 10, &mut output);
|
||||
assert_eq!(&output, &[10, 13, 16, 17]);
|
||||
}
|
||||
|
||||
fn test_filter_impl_simple_outside_i32_range(filter_impl: FilterImplPerInstructionSet) {
|
||||
let mut output = vec![u32::MAX, i32::MAX as u32 + 1, 0, 1, 3, 1, 1, 1, 1];
|
||||
filter_impl.filter_vec_in_place(1..=i32::MAX as u32 + 1u32, 0, &mut output);
|
||||
assert_eq!(&output, &[1, 3, 4, 5, 6, 7, 8]);
|
||||
}
|
||||
|
||||
fn test_filter_impl_test_suite(filter_impl: FilterImplPerInstructionSet) {
|
||||
test_filter_impl_empty_aux(filter_impl);
|
||||
test_filter_impl_simple_aux(filter_impl);
|
||||
test_filter_impl_simple_aux_shifted(filter_impl);
|
||||
test_filter_impl_simple_outside_i32_range(filter_impl);
|
||||
}
|
||||
|
||||
#[test]
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
fn test_filter_implementation_avx2() {
|
||||
if FilterImplPerInstructionSet::AVX2.is_available() {
|
||||
test_filter_impl_test_suite(FilterImplPerInstructionSet::AVX2);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_filter_implementation_scalar() {
|
||||
test_filter_impl_test_suite(FilterImplPerInstructionSet::Scalar);
|
||||
}
|
||||
|
||||
#[cfg(target_arch = "x86_64")]
|
||||
proptest::proptest! {
|
||||
#[test]
|
||||
fn test_filter_compare_scalar_and_avx2_impl_proptest(
|
||||
start in proptest::prelude::any::<u32>(),
|
||||
end in proptest::prelude::any::<u32>(),
|
||||
offset in 0u32..2u32,
|
||||
mut vals in proptest::collection::vec(0..u32::MAX, 0..30)) {
|
||||
if FilterImplPerInstructionSet::AVX2.is_available() {
|
||||
let mut vals_clone = vals.clone();
|
||||
FilterImplPerInstructionSet::AVX2.filter_vec_in_place(start..=end, offset, &mut vals);
|
||||
FilterImplPerInstructionSet::Scalar.filter_vec_in_place(start..=end, offset, &mut vals_clone);
|
||||
assert_eq!(&vals, &vals_clone);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
13
bitpacker/src/filter_vec/scalar.rs
Normal file
13
bitpacker/src/filter_vec/scalar.rs
Normal file
@@ -0,0 +1,13 @@
|
||||
use std::ops::RangeInclusive;
|
||||
|
||||
pub fn filter_vec_in_place(range: RangeInclusive<u32>, offset: u32, output: &mut Vec<u32>) {
|
||||
// We restrict the accepted boundary, because unsigned integers & SIMD don't
|
||||
// play well.
|
||||
let mut output_cursor = 0;
|
||||
for i in 0..output.len() {
|
||||
let val = output[i];
|
||||
output[output_cursor] = offset + i as u32;
|
||||
output_cursor += if range.contains(&val) { 1 } else { 0 };
|
||||
}
|
||||
output.truncate(output_cursor);
|
||||
}
|
||||
@@ -1,5 +1,6 @@
|
||||
mod bitpacker;
|
||||
mod blocked_bitpacker;
|
||||
mod filter_vec;
|
||||
|
||||
use std::cmp::Ordering;
|
||||
|
||||
|
||||
90
cliff.toml
Normal file
90
cliff.toml
Normal file
@@ -0,0 +1,90 @@
|
||||
# configuration file for git-cliff{ pattern = "foo", replace = "bar"}
|
||||
# see https://github.com/orhun/git-cliff#configuration-file
|
||||
|
||||
[changelog]
|
||||
# changelog header
|
||||
header = """
|
||||
"""
|
||||
# template for the changelog body
|
||||
# https://tera.netlify.app/docs/#introduction
|
||||
body = """
|
||||
{% if version %}\
|
||||
{{ version | trim_start_matches(pat="v") }} ({{ timestamp | date(format="%Y-%m-%d") }})
|
||||
==================
|
||||
{% else %}\
|
||||
## [unreleased]
|
||||
{% endif %}\
|
||||
{% for commit in commits %}
|
||||
- {% if commit.breaking %}[**breaking**] {% endif %}{{ commit.message | split(pat="\n") | first | trim | upper_first }}(@{{ commit.author.name }})\
|
||||
{% endfor %}
|
||||
"""
|
||||
# remove the leading and trailing whitespace from the template
|
||||
trim = true
|
||||
# changelog footer
|
||||
footer = """
|
||||
"""
|
||||
|
||||
postprocessors = [
|
||||
{ pattern = 'Paul Masurel', replace = "fulmicoton"}, # replace with github user
|
||||
{ pattern = 'PSeitz', replace = "PSeitz"}, # replace with github user
|
||||
{ pattern = 'Adam Reichold', replace = "adamreichold"}, # replace with github user
|
||||
{ pattern = 'trinity-1686a', replace = "trinity-1686a"}, # replace with github user
|
||||
{ pattern = 'Michael Kleen', replace = "mkleen"}, # replace with github user
|
||||
{ pattern = 'Adrien Guillo', replace = "guilload"}, # replace with github user
|
||||
{ pattern = 'François Massot', replace = "fmassot"}, # replace with github user
|
||||
{ pattern = 'Naveen Aiathurai', replace = "naveenann"}, # replace with github user
|
||||
{ pattern = '', replace = ""}, # replace with github user
|
||||
]
|
||||
|
||||
[git]
|
||||
# parse the commits based on https://www.conventionalcommits.org
|
||||
# This is required or commit.message contains the whole commit message and not just the title
|
||||
conventional_commits = true
|
||||
# filter out the commits that are not conventional
|
||||
filter_unconventional = false
|
||||
# process each line of a commit as an individual commit
|
||||
split_commits = false
|
||||
# regex for preprocessing the commit messages
|
||||
commit_preprocessors = [
|
||||
{ pattern = '\((\w+\s)?#([0-9]+)\)', replace = "[#${2}](https://github.com/quickwit-oss/tantivy/issues/${2})"}, # replace issue numbers
|
||||
]
|
||||
#link_parsers = [
|
||||
#{ pattern = "#(\\d+)", href = "https://github.com/quickwit-oss/tantivy/pulls/$1"},
|
||||
#]
|
||||
# regex for parsing and grouping commits
|
||||
commit_parsers = [
|
||||
{ message = "^feat", group = "Features"},
|
||||
{ message = "^fix", group = "Bug Fixes"},
|
||||
{ message = "^doc", group = "Documentation"},
|
||||
{ message = "^perf", group = "Performance"},
|
||||
{ message = "^refactor", group = "Refactor"},
|
||||
{ message = "^style", group = "Styling"},
|
||||
{ message = "^test", group = "Testing"},
|
||||
{ message = "^chore\\(release\\): prepare for", skip = true},
|
||||
{ message = "(?i)clippy", skip = true},
|
||||
{ message = "(?i)dependabot", skip = true},
|
||||
{ message = "(?i)fmt", skip = true},
|
||||
{ message = "(?i)bump", skip = true},
|
||||
{ message = "(?i)readme", skip = true},
|
||||
{ message = "(?i)comment", skip = true},
|
||||
{ message = "(?i)spelling", skip = true},
|
||||
{ message = "^chore", group = "Miscellaneous Tasks"},
|
||||
{ body = ".*security", group = "Security"},
|
||||
{ message = ".*", group = "Other", default_scope = "other"},
|
||||
]
|
||||
# protect breaking changes from being skipped due to matching a skipping commit_parser
|
||||
protect_breaking_commits = false
|
||||
# filter out the commits that are not matched by commit parsers
|
||||
filter_commits = false
|
||||
# glob pattern for matching git tags
|
||||
tag_pattern = "v[0-9]*"
|
||||
# regex for skipping tags
|
||||
skip_tags = "v0.1.0-beta.1"
|
||||
# regex for ignoring tags
|
||||
ignore_tags = ""
|
||||
# sort the tags topologically
|
||||
topo_order = false
|
||||
# sort the commits inside sections by oldest/newest order
|
||||
sort_commits = "newest"
|
||||
# limit the number of commits included in the changelog.
|
||||
# limit_commits = 42
|
||||
@@ -1,28 +1,28 @@
|
||||
[package]
|
||||
name = "tantivy-columnar"
|
||||
version = "0.1.0"
|
||||
version = "0.2.0"
|
||||
edition = "2021"
|
||||
license = "MIT"
|
||||
homepage = "https://github.com/quickwit-oss/tantivy"
|
||||
repository = "https://github.com/quickwit-oss/tantivy"
|
||||
description = "column oriented storage for tantivy"
|
||||
categories = ["database-implementations", "data-structures", "compression"]
|
||||
|
||||
[dependencies]
|
||||
itertools = "0.10.5"
|
||||
log = "0.4.17"
|
||||
itertools = "0.11.0"
|
||||
fnv = "1.0.7"
|
||||
fastdivide = "0.4.0"
|
||||
rand = { version = "0.8.5", optional = true }
|
||||
measure_time = { version = "0.8.2", optional = true }
|
||||
prettytable-rs = { version = "0.10.0", optional = true }
|
||||
|
||||
stacker = { path = "../stacker", package="tantivy-stacker"}
|
||||
sstable = { path = "../sstable", package = "tantivy-sstable" }
|
||||
common = { path = "../common", package = "tantivy-common" }
|
||||
tantivy-bitpacker = { version= "0.3", path = "../bitpacker/" }
|
||||
stacker = { version= "0.2", path = "../stacker", package="tantivy-stacker"}
|
||||
sstable = { version= "0.2", path = "../sstable", package = "tantivy-sstable" }
|
||||
common = { version= "0.6", path = "../common", package = "tantivy-common" }
|
||||
tantivy-bitpacker = { version= "0.5", path = "../bitpacker/" }
|
||||
serde = "1.0.152"
|
||||
|
||||
[dev-dependencies]
|
||||
proptest = "1"
|
||||
more-asserts = "0.3.1"
|
||||
rand = "0.8.5"
|
||||
rand = "0.8"
|
||||
|
||||
[features]
|
||||
unstable = []
|
||||
|
||||
132
columnar/src/block_accessor.rs
Normal file
132
columnar/src/block_accessor.rs
Normal file
@@ -0,0 +1,132 @@
|
||||
use std::cmp::Ordering;
|
||||
|
||||
use crate::{Column, DocId, RowId};
|
||||
|
||||
#[derive(Debug, Default, Clone)]
|
||||
pub struct ColumnBlockAccessor<T> {
|
||||
val_cache: Vec<T>,
|
||||
docid_cache: Vec<DocId>,
|
||||
missing_docids_cache: Vec<DocId>,
|
||||
row_id_cache: Vec<RowId>,
|
||||
}
|
||||
|
||||
impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
|
||||
ColumnBlockAccessor<T>
|
||||
{
|
||||
#[inline]
|
||||
pub fn fetch_block(&mut self, docs: &[u32], accessor: &Column<T>) {
|
||||
self.docid_cache.clear();
|
||||
self.row_id_cache.clear();
|
||||
accessor.row_ids_for_docs(docs, &mut self.docid_cache, &mut self.row_id_cache);
|
||||
self.val_cache.resize(self.row_id_cache.len(), T::default());
|
||||
accessor
|
||||
.values
|
||||
.get_vals(&self.row_id_cache, &mut self.val_cache);
|
||||
}
|
||||
#[inline]
|
||||
pub fn fetch_block_with_missing(&mut self, docs: &[u32], accessor: &Column<T>, missing: T) {
|
||||
self.fetch_block(docs, accessor);
|
||||
// We can compare docid_cache with docs to find missing docs
|
||||
if docs.len() != self.docid_cache.len() || accessor.index.is_multivalue() {
|
||||
self.missing_docids_cache.clear();
|
||||
find_missing_docs(docs, &self.docid_cache, |doc| {
|
||||
self.missing_docids_cache.push(doc);
|
||||
self.val_cache.push(missing);
|
||||
});
|
||||
self.docid_cache
|
||||
.extend_from_slice(&self.missing_docids_cache);
|
||||
}
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn iter_vals(&self) -> impl Iterator<Item = T> + '_ {
|
||||
self.val_cache.iter().cloned()
|
||||
}
|
||||
|
||||
#[inline]
|
||||
pub fn iter_docid_vals(&self) -> impl Iterator<Item = (DocId, T)> + '_ {
|
||||
self.docid_cache
|
||||
.iter()
|
||||
.cloned()
|
||||
.zip(self.val_cache.iter().cloned())
|
||||
}
|
||||
}
|
||||
|
||||
/// Given two sorted lists of docids `docs` and `hits`, hits is a subset of `docs`.
|
||||
/// Return all docs that are not in `hits`.
|
||||
fn find_missing_docs<F>(docs: &[u32], hits: &[u32], mut callback: F)
|
||||
where F: FnMut(u32) {
|
||||
let mut docs_iter = docs.iter();
|
||||
let mut hits_iter = hits.iter();
|
||||
|
||||
let mut doc = docs_iter.next();
|
||||
let mut hit = hits_iter.next();
|
||||
|
||||
while let (Some(¤t_doc), Some(¤t_hit)) = (doc, hit) {
|
||||
match current_doc.cmp(¤t_hit) {
|
||||
Ordering::Less => {
|
||||
callback(current_doc);
|
||||
doc = docs_iter.next();
|
||||
}
|
||||
Ordering::Equal => {
|
||||
doc = docs_iter.next();
|
||||
hit = hits_iter.next();
|
||||
}
|
||||
Ordering::Greater => {
|
||||
hit = hits_iter.next();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
while let Some(¤t_doc) = doc {
|
||||
callback(current_doc);
|
||||
doc = docs_iter.next();
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn test_find_missing_docs() {
|
||||
let docs: Vec<u32> = vec![1, 2, 3, 4, 5, 6, 7, 8, 9, 10];
|
||||
let hits: Vec<u32> = vec![2, 4, 6, 8, 10];
|
||||
|
||||
let mut missing_docs: Vec<u32> = Vec::new();
|
||||
|
||||
find_missing_docs(&docs, &hits, |missing_doc| {
|
||||
missing_docs.push(missing_doc);
|
||||
});
|
||||
|
||||
assert_eq!(missing_docs, vec![1, 3, 5, 7, 9]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_find_missing_docs_empty() {
|
||||
let docs: Vec<u32> = Vec::new();
|
||||
let hits: Vec<u32> = vec![2, 4, 6, 8, 10];
|
||||
|
||||
let mut missing_docs: Vec<u32> = Vec::new();
|
||||
|
||||
find_missing_docs(&docs, &hits, |missing_doc| {
|
||||
missing_docs.push(missing_doc);
|
||||
});
|
||||
|
||||
assert_eq!(missing_docs, vec![]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_find_missing_docs_all_missing() {
|
||||
let docs: Vec<u32> = vec![1, 2, 3, 4, 5];
|
||||
let hits: Vec<u32> = Vec::new();
|
||||
|
||||
let mut missing_docs: Vec<u32> = Vec::new();
|
||||
|
||||
find_missing_docs(&docs, &hits, |missing_doc| {
|
||||
missing_docs.push(missing_doc);
|
||||
});
|
||||
|
||||
assert_eq!(missing_docs, vec![1, 2, 3, 4, 5]);
|
||||
}
|
||||
}
|
||||
@@ -1,6 +1,6 @@
|
||||
use std::io;
|
||||
use std::ops::Deref;
|
||||
use std::sync::Arc;
|
||||
use std::{fmt, io};
|
||||
|
||||
use sstable::{Dictionary, VoidSSTable};
|
||||
|
||||
@@ -21,7 +21,22 @@ pub struct BytesColumn {
|
||||
pub(crate) term_ord_column: Column<u64>,
|
||||
}
|
||||
|
||||
impl fmt::Debug for BytesColumn {
|
||||
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
|
||||
f.debug_struct("BytesColumn")
|
||||
.field("term_ord_column", &self.term_ord_column)
|
||||
.finish()
|
||||
}
|
||||
}
|
||||
|
||||
impl BytesColumn {
|
||||
pub fn empty(num_docs: u32) -> BytesColumn {
|
||||
BytesColumn {
|
||||
dictionary: Arc::new(Dictionary::empty()),
|
||||
term_ord_column: Column::build_empty_column(num_docs),
|
||||
}
|
||||
}
|
||||
|
||||
/// Fills the given `output` buffer with the term associated to the ordinal `ord`.
|
||||
///
|
||||
/// Returns `false` if the term does not exist (e.g. `term_ord` is greater or equal to the
|
||||
@@ -56,6 +71,12 @@ impl BytesColumn {
|
||||
#[derive(Clone)]
|
||||
pub struct StrColumn(BytesColumn);
|
||||
|
||||
impl fmt::Debug for StrColumn {
|
||||
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
||||
write!(f, "{:?}", self.term_ord_column)
|
||||
}
|
||||
}
|
||||
|
||||
impl From<StrColumn> for BytesColumn {
|
||||
fn from(str_column: StrColumn) -> BytesColumn {
|
||||
str_column.0
|
||||
@@ -63,7 +84,7 @@ impl From<StrColumn> for BytesColumn {
|
||||
}
|
||||
|
||||
impl StrColumn {
|
||||
pub(crate) fn wrap(bytes_column: BytesColumn) -> StrColumn {
|
||||
pub fn wrap(bytes_column: BytesColumn) -> StrColumn {
|
||||
StrColumn(bytes_column)
|
||||
}
|
||||
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
mod dictionary_encoded;
|
||||
mod serialize;
|
||||
|
||||
use std::fmt::Debug;
|
||||
use std::fmt::{self, Debug};
|
||||
use std::io::Write;
|
||||
use std::ops::{Deref, Range, RangeInclusive};
|
||||
use std::sync::Arc;
|
||||
@@ -16,14 +16,33 @@ pub use serialize::{
|
||||
use crate::column_index::ColumnIndex;
|
||||
use crate::column_values::monotonic_mapping::StrictlyMonotonicMappingToInternal;
|
||||
use crate::column_values::{monotonic_map_column, ColumnValues};
|
||||
use crate::{Cardinality, MonotonicallyMappableToU64, RowId};
|
||||
use crate::{Cardinality, DocId, EmptyColumnValues, MonotonicallyMappableToU64, RowId};
|
||||
|
||||
#[derive(Clone)]
|
||||
pub struct Column<T = u64> {
|
||||
pub idx: ColumnIndex,
|
||||
pub index: ColumnIndex,
|
||||
pub values: Arc<dyn ColumnValues<T>>,
|
||||
}
|
||||
|
||||
impl<T: Debug + PartialOrd + Send + Sync + Copy + 'static> Debug for Column<T> {
|
||||
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
||||
let num_docs = self.num_docs();
|
||||
let entries = (0..num_docs)
|
||||
.map(|i| (i, self.values_for_doc(i).collect::<Vec<_>>()))
|
||||
.filter(|(_, vals)| !vals.is_empty());
|
||||
f.debug_map().entries(entries).finish()
|
||||
}
|
||||
}
|
||||
|
||||
impl<T: PartialOrd + Default> Column<T> {
|
||||
pub fn build_empty_column(num_docs: u32) -> Column<T> {
|
||||
Column {
|
||||
index: ColumnIndex::Empty { num_docs },
|
||||
values: Arc::new(EmptyColumnValues),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl<T: MonotonicallyMappableToU64> Column<T> {
|
||||
pub fn to_u64_monotonic(self) -> Column<u64> {
|
||||
let values = Arc::new(monotonic_map_column(
|
||||
@@ -31,7 +50,7 @@ impl<T: MonotonicallyMappableToU64> Column<T> {
|
||||
StrictlyMonotonicMappingToInternal::<T>::new(),
|
||||
));
|
||||
Column {
|
||||
idx: self.idx,
|
||||
index: self.index,
|
||||
values,
|
||||
}
|
||||
}
|
||||
@@ -40,11 +59,11 @@ impl<T: MonotonicallyMappableToU64> Column<T> {
|
||||
impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
|
||||
#[inline]
|
||||
pub fn get_cardinality(&self) -> Cardinality {
|
||||
self.idx.get_cardinality()
|
||||
self.index.get_cardinality()
|
||||
}
|
||||
|
||||
pub fn num_docs(&self) -> RowId {
|
||||
match &self.idx {
|
||||
match &self.index {
|
||||
ColumnIndex::Empty { num_docs } => *num_docs,
|
||||
ColumnIndex::Full => self.values.num_vals(),
|
||||
ColumnIndex::Optional(optional_index) => optional_index.num_docs(),
|
||||
@@ -68,8 +87,25 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
|
||||
self.values_for_doc(row_id).next()
|
||||
}
|
||||
|
||||
pub fn values_for_doc(&self, row_id: RowId) -> impl Iterator<Item = T> + '_ {
|
||||
self.value_row_ids(row_id)
|
||||
/// Translates a block of docis to row_ids.
|
||||
///
|
||||
/// returns the row_ids and the matching docids on the same index
|
||||
/// e.g.
|
||||
/// DocId In: [0, 5, 6]
|
||||
/// DocId Out: [0, 0, 6, 6]
|
||||
/// RowId Out: [0, 1, 2, 3]
|
||||
#[inline]
|
||||
pub fn row_ids_for_docs(
|
||||
&self,
|
||||
doc_ids: &[DocId],
|
||||
doc_ids_out: &mut Vec<DocId>,
|
||||
row_ids: &mut Vec<RowId>,
|
||||
) {
|
||||
self.index.docids_to_rowids(doc_ids, doc_ids_out, row_ids)
|
||||
}
|
||||
|
||||
pub fn values_for_doc(&self, doc_id: DocId) -> impl Iterator<Item = T> + '_ {
|
||||
self.value_row_ids(doc_id)
|
||||
.map(|value_row_id: RowId| self.values.get_val(value_row_id))
|
||||
}
|
||||
|
||||
@@ -82,17 +118,19 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
|
||||
doc_ids: &mut Vec<u32>,
|
||||
) {
|
||||
// convert passed docid range to row id range
|
||||
let rowid_range = self.idx.docid_range_to_rowids(selected_docid_range.clone());
|
||||
let rowid_range = self
|
||||
.index
|
||||
.docid_range_to_rowids(selected_docid_range.clone());
|
||||
|
||||
// Load rows
|
||||
self.values
|
||||
.get_row_ids_for_value_range(value_range, rowid_range, doc_ids);
|
||||
// Convert rows to docids
|
||||
self.idx
|
||||
self.index
|
||||
.select_batch_in_place(selected_docid_range.start, doc_ids);
|
||||
}
|
||||
|
||||
/// Fils the output vector with the (possibly multiple values that are associated_with
|
||||
/// Fills the output vector with the (possibly multiple values that are associated_with
|
||||
/// `row_id`.
|
||||
///
|
||||
/// This method clears the `output` vector.
|
||||
@@ -113,7 +151,7 @@ impl<T> Deref for Column<T> {
|
||||
type Target = ColumnIndex;
|
||||
|
||||
fn deref(&self) -> &Self::Target {
|
||||
&self.idx
|
||||
&self.index
|
||||
}
|
||||
}
|
||||
|
||||
@@ -151,7 +189,7 @@ impl<T: PartialOrd + Debug + Send + Sync + Copy + 'static> ColumnValues<T>
|
||||
}
|
||||
|
||||
fn num_vals(&self) -> u32 {
|
||||
match &self.column.idx {
|
||||
match &self.column.index {
|
||||
ColumnIndex::Empty { .. } => 0u32,
|
||||
ColumnIndex::Full => self.column.values.num_vals(),
|
||||
ColumnIndex::Optional(optional_idx) => optional_idx.num_docs(),
|
||||
|
||||
@@ -52,7 +52,7 @@ pub fn open_column_u64<T: MonotonicallyMappableToU64>(bytes: OwnedBytes) -> io::
|
||||
let column_index = crate::column_index::open_column_index(column_index_data)?;
|
||||
let column_values = load_u64_based_column_values(column_values_data)?;
|
||||
Ok(Column {
|
||||
idx: column_index,
|
||||
index: column_index,
|
||||
values: column_values,
|
||||
})
|
||||
}
|
||||
@@ -71,7 +71,7 @@ pub fn open_column_u128<T: MonotonicallyMappableToU128>(
|
||||
let column_index = crate::column_index::open_column_index(column_index_data)?;
|
||||
let column_values = crate::column_values::open_u128_mapped(column_values_data)?;
|
||||
Ok(Column {
|
||||
idx: column_index,
|
||||
index: column_index,
|
||||
values: column_values,
|
||||
})
|
||||
}
|
||||
|
||||
@@ -1,29 +1,82 @@
|
||||
mod shuffled;
|
||||
mod stacked;
|
||||
|
||||
use common::ReadOnlyBitSet;
|
||||
use shuffled::merge_column_index_shuffled;
|
||||
use stacked::merge_column_index_stacked;
|
||||
|
||||
use crate::column_index::SerializableColumnIndex;
|
||||
use crate::{Cardinality, ColumnIndex, MergeRowOrder};
|
||||
|
||||
// For simplification, we never have cardinality go down due to deletes.
|
||||
fn detect_cardinality(columns: &[Option<ColumnIndex>]) -> Cardinality {
|
||||
columns
|
||||
.iter()
|
||||
.flatten()
|
||||
.map(ColumnIndex::get_cardinality)
|
||||
.max()
|
||||
.unwrap_or(Cardinality::Full)
|
||||
fn detect_cardinality_single_column_index(
|
||||
column_index: &ColumnIndex,
|
||||
alive_bitset_opt: &Option<ReadOnlyBitSet>,
|
||||
) -> Cardinality {
|
||||
let Some(alive_bitset) = alive_bitset_opt else {
|
||||
return column_index.get_cardinality();
|
||||
};
|
||||
let cardinality_before_deletes = column_index.get_cardinality();
|
||||
if cardinality_before_deletes == Cardinality::Full {
|
||||
// The columnar cardinality can only become more restrictive in the presence of deletes
|
||||
// (where cardinality sorted from the more restrictive to the least restrictive are Full,
|
||||
// Optional, Multivalued)
|
||||
//
|
||||
// If we are already "Full", we are guaranteed to stay "Full" after deletes.
|
||||
return Cardinality::Full;
|
||||
}
|
||||
let mut cardinality_so_far = Cardinality::Full;
|
||||
for doc_id in alive_bitset.iter() {
|
||||
let num_values = column_index.value_row_ids(doc_id).len();
|
||||
let row_cardinality = match num_values {
|
||||
0 => Cardinality::Optional,
|
||||
1 => Cardinality::Full,
|
||||
_ => Cardinality::Multivalued,
|
||||
};
|
||||
cardinality_so_far = cardinality_so_far.max(row_cardinality);
|
||||
if cardinality_so_far >= cardinality_before_deletes {
|
||||
// There won't be any improvement in the cardinality.
|
||||
// We can early exit.
|
||||
return cardinality_before_deletes;
|
||||
}
|
||||
}
|
||||
cardinality_so_far
|
||||
}
|
||||
|
||||
fn detect_cardinality(
|
||||
column_indexes: &[ColumnIndex],
|
||||
merge_row_order: &MergeRowOrder,
|
||||
) -> Cardinality {
|
||||
match merge_row_order {
|
||||
MergeRowOrder::Stack(_) => column_indexes
|
||||
.iter()
|
||||
.map(ColumnIndex::get_cardinality)
|
||||
.max()
|
||||
.unwrap_or(Cardinality::Full),
|
||||
MergeRowOrder::Shuffled(shuffle_merge_order) => {
|
||||
let mut merged_cardinality = Cardinality::Full;
|
||||
for (column_index, alive_bitset_opt) in column_indexes
|
||||
.iter()
|
||||
.zip(shuffle_merge_order.alive_bitsets.iter())
|
||||
{
|
||||
let cardinality: Cardinality =
|
||||
detect_cardinality_single_column_index(column_index, alive_bitset_opt);
|
||||
if cardinality == Cardinality::Multivalued {
|
||||
return cardinality;
|
||||
}
|
||||
merged_cardinality = merged_cardinality.max(cardinality);
|
||||
}
|
||||
merged_cardinality
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub fn merge_column_index<'a>(
|
||||
columns: &'a [Option<ColumnIndex>],
|
||||
columns: &'a [ColumnIndex],
|
||||
merge_row_order: &'a MergeRowOrder,
|
||||
) -> SerializableColumnIndex<'a> {
|
||||
// For simplification, we do not try to detect whether the cardinality could be
|
||||
// downgraded thanks to deletes.
|
||||
let cardinality_after_merge = detect_cardinality(columns);
|
||||
let cardinality_after_merge = detect_cardinality(columns, merge_row_order);
|
||||
match merge_row_order {
|
||||
MergeRowOrder::Stack(stack_merge_order) => {
|
||||
merge_column_index_stacked(columns, cardinality_after_merge, stack_merge_order)
|
||||
@@ -45,42 +98,61 @@ mod tests {
|
||||
use crate::column_index::merge::detect_cardinality;
|
||||
use crate::column_index::multivalued_index::MultiValueIndex;
|
||||
use crate::column_index::{merge_column_index, OptionalIndex, SerializableColumnIndex};
|
||||
use crate::{Cardinality, ColumnIndex, MergeRowOrder, RowAddr, RowId, ShuffleMergeOrder};
|
||||
use crate::{
|
||||
Cardinality, ColumnIndex, MergeRowOrder, RowAddr, RowId, ShuffleMergeOrder, StackMergeOrder,
|
||||
};
|
||||
|
||||
#[test]
|
||||
fn test_detect_cardinality() {
|
||||
assert_eq!(detect_cardinality(&[]), Cardinality::Full);
|
||||
assert_eq!(
|
||||
detect_cardinality(&[], &StackMergeOrder::stack_for_test(&[]).into()),
|
||||
Cardinality::Full
|
||||
);
|
||||
let optional_index: ColumnIndex = OptionalIndex::for_test(1, &[]).into();
|
||||
let multivalued_index: ColumnIndex = MultiValueIndex::for_test(&[0, 1]).into();
|
||||
assert_eq!(
|
||||
detect_cardinality(&[Some(optional_index.clone()), None]),
|
||||
detect_cardinality(
|
||||
&[optional_index.clone(), ColumnIndex::Empty { num_docs: 0 }],
|
||||
&StackMergeOrder::stack_for_test(&[1, 0]).into()
|
||||
),
|
||||
Cardinality::Optional
|
||||
);
|
||||
assert_eq!(
|
||||
detect_cardinality(&[Some(optional_index.clone()), Some(ColumnIndex::Full)]),
|
||||
detect_cardinality(
|
||||
&[optional_index.clone(), ColumnIndex::Full],
|
||||
&StackMergeOrder::stack_for_test(&[1, 1]).into()
|
||||
),
|
||||
Cardinality::Optional
|
||||
);
|
||||
assert_eq!(
|
||||
detect_cardinality(&[Some(multivalued_index.clone()), None]),
|
||||
detect_cardinality(
|
||||
&[
|
||||
multivalued_index.clone(),
|
||||
ColumnIndex::Empty { num_docs: 0 }
|
||||
],
|
||||
&StackMergeOrder::stack_for_test(&[1, 0]).into()
|
||||
),
|
||||
Cardinality::Multivalued
|
||||
);
|
||||
assert_eq!(
|
||||
detect_cardinality(&[
|
||||
Some(multivalued_index.clone()),
|
||||
Some(optional_index.clone())
|
||||
]),
|
||||
detect_cardinality(
|
||||
&[multivalued_index.clone(), optional_index.clone()],
|
||||
&StackMergeOrder::stack_for_test(&[1, 1]).into()
|
||||
),
|
||||
Cardinality::Multivalued
|
||||
);
|
||||
assert_eq!(
|
||||
detect_cardinality(&[Some(optional_index), Some(multivalued_index)]),
|
||||
detect_cardinality(
|
||||
&[optional_index, multivalued_index],
|
||||
&StackMergeOrder::stack_for_test(&[1, 1]).into()
|
||||
),
|
||||
Cardinality::Multivalued
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_merge_index_multivalued_sorted() {
|
||||
let column_indexes: Vec<Option<ColumnIndex>> =
|
||||
vec![Some(MultiValueIndex::for_test(&[0, 2, 5]).into())];
|
||||
let column_indexes: Vec<ColumnIndex> = vec![MultiValueIndex::for_test(&[0, 2, 5]).into()];
|
||||
let merge_row_order: MergeRowOrder = ShuffleMergeOrder::for_test(
|
||||
&[2],
|
||||
vec![
|
||||
@@ -96,18 +168,19 @@ mod tests {
|
||||
)
|
||||
.into();
|
||||
let merged_column_index = merge_column_index(&column_indexes[..], &merge_row_order);
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index
|
||||
else { panic!("Excpected a multivalued index") };
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index else {
|
||||
panic!("Excpected a multivalued index")
|
||||
};
|
||||
let start_indexes: Vec<RowId> = start_index_iterable.boxed_iter().collect();
|
||||
assert_eq!(&start_indexes, &[0, 3, 5]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_merge_index_multivalued_sorted_several_segment() {
|
||||
let column_indexes: Vec<Option<ColumnIndex>> = vec![
|
||||
Some(MultiValueIndex::for_test(&[0, 2, 5]).into()),
|
||||
None,
|
||||
Some(MultiValueIndex::for_test(&[0, 1, 4]).into()),
|
||||
let column_indexes: Vec<ColumnIndex> = vec![
|
||||
MultiValueIndex::for_test(&[0, 2, 5]).into(),
|
||||
ColumnIndex::Empty { num_docs: 0 },
|
||||
MultiValueIndex::for_test(&[0, 1, 4]).into(),
|
||||
];
|
||||
let merge_row_order: MergeRowOrder = ShuffleMergeOrder::for_test(
|
||||
&[2, 0, 2],
|
||||
@@ -128,8 +201,9 @@ mod tests {
|
||||
)
|
||||
.into();
|
||||
let merged_column_index = merge_column_index(&column_indexes[..], &merge_row_order);
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index
|
||||
else { panic!("Excpected a multivalued index") };
|
||||
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index else {
|
||||
panic!("Excpected a multivalued index")
|
||||
};
|
||||
let start_indexes: Vec<RowId> = start_index_iterable.boxed_iter().collect();
|
||||
assert_eq!(&start_indexes, &[0, 3, 5, 6]);
|
||||
}
|
||||
|
||||
@@ -5,7 +5,7 @@ use crate::iterable::Iterable;
|
||||
use crate::{Cardinality, ColumnIndex, RowId, ShuffleMergeOrder};
|
||||
|
||||
pub fn merge_column_index_shuffled<'a>(
|
||||
column_indexes: &'a [Option<ColumnIndex>],
|
||||
column_indexes: &'a [ColumnIndex],
|
||||
cardinality_after_merge: Cardinality,
|
||||
shuffle_merge_order: &'a ShuffleMergeOrder,
|
||||
) -> SerializableColumnIndex<'a> {
|
||||
@@ -33,41 +33,41 @@ pub fn merge_column_index_shuffled<'a>(
|
||||
///
|
||||
/// In other words the column_indexes passed as argument may NOT be multivalued.
|
||||
fn merge_column_index_shuffled_optional<'a>(
|
||||
column_indexes: &'a [Option<ColumnIndex>],
|
||||
column_indexes: &'a [ColumnIndex],
|
||||
merge_order: &'a ShuffleMergeOrder,
|
||||
) -> Box<dyn Iterable<RowId> + 'a> {
|
||||
Box::new(ShuffledOptionalIndex {
|
||||
Box::new(ShuffledIndex {
|
||||
column_indexes,
|
||||
merge_order,
|
||||
})
|
||||
}
|
||||
|
||||
struct ShuffledOptionalIndex<'a> {
|
||||
column_indexes: &'a [Option<ColumnIndex>],
|
||||
struct ShuffledIndex<'a> {
|
||||
column_indexes: &'a [ColumnIndex],
|
||||
merge_order: &'a ShuffleMergeOrder,
|
||||
}
|
||||
|
||||
impl<'a> Iterable<u32> for ShuffledOptionalIndex<'a> {
|
||||
impl<'a> Iterable<u32> for ShuffledIndex<'a> {
|
||||
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
|
||||
Box::new(self.merge_order
|
||||
.iter_new_to_old_row_addrs()
|
||||
.enumerate()
|
||||
.filter_map(|(new_row_id, old_row_addr)| {
|
||||
let Some(column_index) = &self.column_indexes[old_row_addr.segment_ord as usize] else {
|
||||
return None;
|
||||
};
|
||||
let row_id = new_row_id as u32;
|
||||
if column_index.has_value(old_row_addr.row_id) {
|
||||
Some(row_id)
|
||||
} else {
|
||||
None
|
||||
}
|
||||
}))
|
||||
Box::new(
|
||||
self.merge_order
|
||||
.iter_new_to_old_row_addrs()
|
||||
.enumerate()
|
||||
.filter_map(|(new_row_id, old_row_addr)| {
|
||||
let column_index = &self.column_indexes[old_row_addr.segment_ord as usize];
|
||||
let row_id = new_row_id as u32;
|
||||
if column_index.has_value(old_row_addr.row_id) {
|
||||
Some(row_id)
|
||||
} else {
|
||||
None
|
||||
}
|
||||
}),
|
||||
)
|
||||
}
|
||||
}
|
||||
|
||||
fn merge_column_index_shuffled_multivalued<'a>(
|
||||
column_indexes: &'a [Option<ColumnIndex>],
|
||||
column_indexes: &'a [ColumnIndex],
|
||||
merge_order: &'a ShuffleMergeOrder,
|
||||
) -> Box<dyn Iterable<RowId> + 'a> {
|
||||
Box::new(ShuffledMultivaluedIndex {
|
||||
@@ -77,19 +77,16 @@ fn merge_column_index_shuffled_multivalued<'a>(
|
||||
}
|
||||
|
||||
struct ShuffledMultivaluedIndex<'a> {
|
||||
column_indexes: &'a [Option<ColumnIndex>],
|
||||
column_indexes: &'a [ColumnIndex],
|
||||
merge_order: &'a ShuffleMergeOrder,
|
||||
}
|
||||
|
||||
fn iter_num_values<'a>(
|
||||
column_indexes: &'a [Option<ColumnIndex>],
|
||||
column_indexes: &'a [ColumnIndex],
|
||||
merge_order: &'a ShuffleMergeOrder,
|
||||
) -> impl Iterator<Item = u32> + 'a {
|
||||
merge_order.iter_new_to_old_row_addrs().map(|row_addr| {
|
||||
let Some(column_index) = &column_indexes[row_addr.segment_ord as usize] else {
|
||||
// No values in the entire column. It surely means there are 0 values associated to this row.
|
||||
return 0u32;
|
||||
};
|
||||
let column_index = &column_indexes[row_addr.segment_ord as usize];
|
||||
match column_index {
|
||||
ColumnIndex::Empty { .. } => 0u32,
|
||||
ColumnIndex::Full => 1,
|
||||
@@ -143,7 +140,7 @@ mod tests {
|
||||
#[test]
|
||||
fn test_merge_column_index_optional_shuffle() {
|
||||
let optional_index: ColumnIndex = OptionalIndex::for_test(2, &[0]).into();
|
||||
let column_indexes = vec![Some(optional_index), Some(ColumnIndex::Full)];
|
||||
let column_indexes = vec![optional_index, ColumnIndex::Full];
|
||||
let row_addrs = vec![
|
||||
RowAddr {
|
||||
segment_ord: 0u32,
|
||||
@@ -160,7 +157,13 @@ mod tests {
|
||||
Cardinality::Optional,
|
||||
&shuffle_merge_order,
|
||||
);
|
||||
let SerializableColumnIndex::Optional { non_null_row_ids, num_rows } = serializable_index else { panic!() };
|
||||
let SerializableColumnIndex::Optional {
|
||||
non_null_row_ids,
|
||||
num_rows,
|
||||
} = serializable_index
|
||||
else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(num_rows, 2);
|
||||
let non_null_rows: Vec<RowId> = non_null_row_ids.boxed_iter().collect();
|
||||
assert_eq!(&non_null_rows, &[1]);
|
||||
|
||||
@@ -9,7 +9,7 @@ use crate::{Cardinality, ColumnIndex, RowId, StackMergeOrder};
|
||||
///
|
||||
/// There are no sort nor deletes involved.
|
||||
pub fn merge_column_index_stacked<'a>(
|
||||
columns: &'a [Option<ColumnIndex>],
|
||||
columns: &'a [ColumnIndex],
|
||||
cardinality_after_merge: Cardinality,
|
||||
stack_merge_order: &'a StackMergeOrder,
|
||||
) -> SerializableColumnIndex<'a> {
|
||||
@@ -33,7 +33,7 @@ pub fn merge_column_index_stacked<'a>(
|
||||
}
|
||||
|
||||
struct StackedOptionalIndex<'a> {
|
||||
columns: &'a [Option<ColumnIndex>],
|
||||
columns: &'a [ColumnIndex],
|
||||
stack_merge_order: &'a StackMergeOrder,
|
||||
}
|
||||
|
||||
@@ -46,16 +46,16 @@ impl<'a> Iterable<RowId> for StackedOptionalIndex<'a> {
|
||||
.flat_map(|(columnar_id, column_index_opt)| {
|
||||
let columnar_row_range = self.stack_merge_order.columnar_range(columnar_id);
|
||||
let rows_it: Box<dyn Iterator<Item = RowId>> = match column_index_opt {
|
||||
Some(ColumnIndex::Full) => Box::new(columnar_row_range),
|
||||
Some(ColumnIndex::Optional(optional_index)) => Box::new(
|
||||
ColumnIndex::Full => Box::new(columnar_row_range),
|
||||
ColumnIndex::Optional(optional_index) => Box::new(
|
||||
optional_index
|
||||
.iter_rows()
|
||||
.map(move |row_id: RowId| columnar_row_range.start + row_id),
|
||||
),
|
||||
Some(ColumnIndex::Multivalued(_)) => {
|
||||
ColumnIndex::Multivalued(_) => {
|
||||
panic!("No multivalued index is allowed when stacking column index");
|
||||
}
|
||||
None | Some(ColumnIndex::Empty { .. }) => Box::new(std::iter::empty()),
|
||||
ColumnIndex::Empty { .. } => Box::new(std::iter::empty()),
|
||||
};
|
||||
rows_it
|
||||
}),
|
||||
@@ -65,20 +65,18 @@ impl<'a> Iterable<RowId> for StackedOptionalIndex<'a> {
|
||||
|
||||
#[derive(Clone, Copy)]
|
||||
struct StackedMultivaluedIndex<'a> {
|
||||
columns: &'a [Option<ColumnIndex>],
|
||||
columns: &'a [ColumnIndex],
|
||||
stack_merge_order: &'a StackMergeOrder,
|
||||
}
|
||||
|
||||
fn convert_column_opt_to_multivalued_index<'a>(
|
||||
column_index_opt: Option<&'a ColumnIndex>,
|
||||
column_index_opt: &'a ColumnIndex,
|
||||
num_rows: RowId,
|
||||
) -> Box<dyn Iterator<Item = RowId> + 'a> {
|
||||
match column_index_opt {
|
||||
None | Some(ColumnIndex::Empty { .. }) => {
|
||||
Box::new(iter::repeat(0u32).take(num_rows as usize + 1))
|
||||
}
|
||||
Some(ColumnIndex::Full) => Box::new(0..num_rows + 1),
|
||||
Some(ColumnIndex::Optional(optional_index)) => {
|
||||
ColumnIndex::Empty { .. } => Box::new(iter::repeat(0u32).take(num_rows as usize + 1)),
|
||||
ColumnIndex::Full => Box::new(0..num_rows + 1),
|
||||
ColumnIndex::Optional(optional_index) => {
|
||||
Box::new(
|
||||
(0..num_rows)
|
||||
// TODO optimize
|
||||
@@ -86,9 +84,7 @@ fn convert_column_opt_to_multivalued_index<'a>(
|
||||
.chain(std::iter::once(optional_index.num_non_nulls())),
|
||||
)
|
||||
}
|
||||
Some(ColumnIndex::Multivalued(multivalued_index)) => {
|
||||
multivalued_index.start_index_column.iter()
|
||||
}
|
||||
ColumnIndex::Multivalued(multivalued_index) => multivalued_index.start_index_column.iter(),
|
||||
}
|
||||
}
|
||||
|
||||
@@ -97,7 +93,6 @@ impl<'a> Iterable<RowId> for StackedMultivaluedIndex<'a> {
|
||||
let multivalued_indexes =
|
||||
self.columns
|
||||
.iter()
|
||||
.map(Option::as_ref)
|
||||
.enumerate()
|
||||
.map(|(columnar_id, column_opt)| {
|
||||
let num_rows =
|
||||
|
||||
@@ -12,7 +12,7 @@ pub use serialize::{open_column_index, serialize_column_index, SerializableColum
|
||||
use crate::column_index::multivalued_index::MultiValueIndex;
|
||||
use crate::{Cardinality, DocId, RowId};
|
||||
|
||||
#[derive(Clone)]
|
||||
#[derive(Clone, Debug)]
|
||||
pub enum ColumnIndex {
|
||||
Empty {
|
||||
num_docs: u32,
|
||||
@@ -37,11 +37,19 @@ impl From<MultiValueIndex> for ColumnIndex {
|
||||
}
|
||||
|
||||
impl ColumnIndex {
|
||||
#[inline]
|
||||
pub fn is_multivalue(&self) -> bool {
|
||||
matches!(self, ColumnIndex::Multivalued(_))
|
||||
}
|
||||
// Returns the cardinality of the column index.
|
||||
//
|
||||
// By convention, if the column contains no docs, we consider that it is
|
||||
// full.
|
||||
#[inline]
|
||||
pub fn get_cardinality(&self) -> Cardinality {
|
||||
match self {
|
||||
ColumnIndex::Empty { num_docs: 0 } | ColumnIndex::Full => Cardinality::Full,
|
||||
ColumnIndex::Empty { .. } => Cardinality::Optional,
|
||||
ColumnIndex::Full => Cardinality::Full,
|
||||
ColumnIndex::Optional(_) => Cardinality::Optional,
|
||||
ColumnIndex::Multivalued(_) => Cardinality::Multivalued,
|
||||
}
|
||||
@@ -74,6 +82,45 @@ impl ColumnIndex {
|
||||
}
|
||||
}
|
||||
|
||||
/// Translates a block of docis to row_ids.
|
||||
///
|
||||
/// returns the row_ids and the matching docids on the same index
|
||||
/// e.g.
|
||||
/// DocId In: [0, 5, 6]
|
||||
/// DocId Out: [0, 0, 6, 6]
|
||||
/// RowId Out: [0, 1, 2, 3]
|
||||
#[inline]
|
||||
pub fn docids_to_rowids(
|
||||
&self,
|
||||
doc_ids: &[DocId],
|
||||
doc_ids_out: &mut Vec<DocId>,
|
||||
row_ids: &mut Vec<RowId>,
|
||||
) {
|
||||
match self {
|
||||
ColumnIndex::Empty { .. } => {}
|
||||
ColumnIndex::Full => {
|
||||
doc_ids_out.extend_from_slice(doc_ids);
|
||||
row_ids.extend_from_slice(doc_ids);
|
||||
}
|
||||
ColumnIndex::Optional(optional_index) => {
|
||||
for doc_id in doc_ids {
|
||||
if let Some(row_id) = optional_index.rank_if_exists(*doc_id) {
|
||||
doc_ids_out.push(*doc_id);
|
||||
row_ids.push(row_id);
|
||||
}
|
||||
}
|
||||
}
|
||||
ColumnIndex::Multivalued(multivalued_index) => {
|
||||
for doc_id in doc_ids {
|
||||
for row_id in multivalued_index.range(*doc_id) {
|
||||
doc_ids_out.push(*doc_id);
|
||||
row_ids.push(row_id);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub fn docid_range_to_rowids(&self, doc_id: Range<DocId>) -> Range<RowId> {
|
||||
match self {
|
||||
ColumnIndex::Empty { .. } => 0..0,
|
||||
@@ -113,3 +160,21 @@ impl ColumnIndex {
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use crate::{Cardinality, ColumnIndex};
|
||||
|
||||
#[test]
|
||||
fn test_column_index_get_cardinality() {
|
||||
assert_eq!(
|
||||
ColumnIndex::Empty { num_docs: 0 }.get_cardinality(),
|
||||
Cardinality::Full
|
||||
);
|
||||
assert_eq!(ColumnIndex::Full.get_cardinality(), Cardinality::Full);
|
||||
assert_eq!(
|
||||
ColumnIndex::Empty { num_docs: 1 }.get_cardinality(),
|
||||
Cardinality::Optional
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -35,6 +35,14 @@ pub struct MultiValueIndex {
|
||||
pub start_index_column: Arc<dyn crate::ColumnValues<RowId>>,
|
||||
}
|
||||
|
||||
impl std::fmt::Debug for MultiValueIndex {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
|
||||
f.debug_struct("MultiValuedIndex")
|
||||
.field("num_rows", &self.start_index_column.num_vals())
|
||||
.finish_non_exhaustive()
|
||||
}
|
||||
}
|
||||
|
||||
impl From<Arc<dyn ColumnValues<RowId>>> for MultiValueIndex {
|
||||
fn from(start_index_column: Arc<dyn ColumnValues<RowId>>) -> Self {
|
||||
MultiValueIndex { start_index_column }
|
||||
@@ -106,11 +114,8 @@ impl MultiValueIndex {
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use std::ops::Range;
|
||||
use std::sync::Arc;
|
||||
|
||||
use super::MultiValueIndex;
|
||||
use crate::column_values::IterColumn;
|
||||
use crate::{ColumnValues, RowId};
|
||||
|
||||
fn index_to_pos_helper(
|
||||
index: &MultiValueIndex,
|
||||
@@ -124,9 +129,7 @@ mod tests {
|
||||
|
||||
#[test]
|
||||
fn test_positions_to_docid() {
|
||||
let offsets: Vec<RowId> = vec![0, 10, 12, 15, 22, 23]; // docid values are [0..10, 10..12, 12..15, etc.]
|
||||
let column: Arc<dyn ColumnValues<RowId>> = Arc::new(IterColumn::from(offsets.into_iter()));
|
||||
let index = MultiValueIndex::from(column);
|
||||
let index = MultiValueIndex::for_test(&[0, 10, 12, 15, 22, 23]);
|
||||
assert_eq!(index.num_docs(), 5);
|
||||
let positions = &[10u32, 11, 15, 20, 21, 22];
|
||||
assert_eq!(index_to_pos_helper(&index, 0..5, positions), vec![1, 3, 4]);
|
||||
|
||||
@@ -88,6 +88,15 @@ pub struct OptionalIndex {
|
||||
block_metas: Arc<[BlockMeta]>,
|
||||
}
|
||||
|
||||
impl std::fmt::Debug for OptionalIndex {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
f.debug_struct("OptionalIndex")
|
||||
.field("num_rows", &self.num_rows)
|
||||
.field("num_non_null_rows", &self.num_non_null_rows)
|
||||
.finish_non_exhaustive()
|
||||
}
|
||||
}
|
||||
|
||||
/// Splits a value address into lower and upper 16bits.
|
||||
/// The lower 16 bits are the value in the block
|
||||
/// The upper 16 bits are the block index
|
||||
|
||||
@@ -5,7 +5,7 @@ use crate::iterable::Iterable;
|
||||
use crate::{ColumnIndex, ColumnValues, MergeRowOrder};
|
||||
|
||||
pub(crate) struct MergedColumnValues<'a, T> {
|
||||
pub(crate) column_indexes: &'a [Option<ColumnIndex>],
|
||||
pub(crate) column_indexes: &'a [ColumnIndex],
|
||||
pub(crate) column_values: &'a [Option<Arc<dyn ColumnValues<T>>>],
|
||||
pub(crate) merge_row_order: &'a MergeRowOrder,
|
||||
}
|
||||
@@ -23,8 +23,7 @@ impl<'a, T: Copy + PartialOrd + Debug> Iterable<T> for MergedColumnValues<'a, T>
|
||||
shuffle_merge_order
|
||||
.iter_new_to_old_row_addrs()
|
||||
.flat_map(|row_addr| {
|
||||
let column_index =
|
||||
self.column_indexes[row_addr.segment_ord as usize].as_ref()?;
|
||||
let column_index = &self.column_indexes[row_addr.segment_ord as usize];
|
||||
let column_values =
|
||||
self.column_values[row_addr.segment_ord as usize].as_ref()?;
|
||||
let value_range = column_index.value_row_ids(row_addr.row_id);
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
|
||||
//! # `fastfield_codecs`
|
||||
//!
|
||||
//! - Columnar storage of data for tantivy [`Column`].
|
||||
//! - Columnar storage of data for tantivy [`crate::Column`].
|
||||
//! - Encode data in different codecs.
|
||||
//! - Monotonically map values to u64/u128
|
||||
|
||||
@@ -58,10 +58,21 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
/// # Panics
|
||||
///
|
||||
/// May panic if `idx` is greater than the column length.
|
||||
fn get_vals(&self, idx: &[u32], output: &mut [T]) {
|
||||
assert!(idx.len() == output.len());
|
||||
for (out, idx) in output.iter_mut().zip(idx.iter()) {
|
||||
*out = self.get_val(*idx as u32);
|
||||
fn get_vals(&self, indexes: &[u32], output: &mut [T]) {
|
||||
assert!(indexes.len() == output.len());
|
||||
let out_and_idx_chunks = output.chunks_exact_mut(4).zip(indexes.chunks_exact(4));
|
||||
for (out_x4, idx_x4) in out_and_idx_chunks {
|
||||
out_x4[0] = self.get_val(idx_x4[0]);
|
||||
out_x4[1] = self.get_val(idx_x4[1]);
|
||||
out_x4[2] = self.get_val(idx_x4[2]);
|
||||
out_x4[3] = self.get_val(idx_x4[3]);
|
||||
}
|
||||
|
||||
let step_size = 4;
|
||||
let cutoff = indexes.len() - indexes.len() % step_size;
|
||||
|
||||
for idx in cutoff..indexes.len() {
|
||||
output[idx] = self.get_val(indexes[idx]);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -83,7 +94,6 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
/// Get the row ids of values which are in the provided value range.
|
||||
///
|
||||
/// Note that position == docid for single value fast fields
|
||||
#[inline(always)]
|
||||
fn get_row_ids_for_value_range(
|
||||
&self,
|
||||
value_range: RangeInclusive<T>,
|
||||
@@ -99,20 +109,26 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
}
|
||||
}
|
||||
|
||||
/// Returns the minimum value for this fast field.
|
||||
/// Returns a lower bound for this column of values.
|
||||
///
|
||||
/// This min_value may not be exact.
|
||||
/// For instance, the min value does not take in account of possible
|
||||
/// deleted document. All values are however guaranteed to be higher than
|
||||
/// `.min_value()`.
|
||||
/// All values are guaranteed to be higher than `.min_value()`
|
||||
/// but this value is not necessary the best boundary value.
|
||||
///
|
||||
/// We have
|
||||
/// ∀i < self.num_vals(), self.get_val(i) >= self.min_value()
|
||||
/// But we don't have necessarily
|
||||
/// ∃i < self.num_vals(), self.get_val(i) == self.min_value()
|
||||
fn min_value(&self) -> T;
|
||||
|
||||
/// Returns the maximum value for this fast field.
|
||||
/// Returns an upper bound for this column of values.
|
||||
///
|
||||
/// This max_value may not be exact.
|
||||
/// For instance, the max value does not take in account of possible
|
||||
/// deleted document. All values are however guaranteed to be higher than
|
||||
/// `.max_value()`.
|
||||
/// All values are guaranteed to be lower than `.max_value()`
|
||||
/// but this value is not necessary the best boundary value.
|
||||
///
|
||||
/// We have
|
||||
/// ∀i < self.num_vals(), self.get_val(i) <= self.max_value()
|
||||
/// But we don't have necessarily
|
||||
/// ∃i < self.num_vals(), self.get_val(i) == self.max_value()
|
||||
fn max_value(&self) -> T;
|
||||
|
||||
/// The number of values in the column.
|
||||
@@ -124,6 +140,27 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
|
||||
}
|
||||
}
|
||||
|
||||
/// Empty column of values.
|
||||
pub struct EmptyColumnValues;
|
||||
|
||||
impl<T: PartialOrd + Default> ColumnValues<T> for EmptyColumnValues {
|
||||
fn get_val(&self, _idx: u32) -> T {
|
||||
panic!("Internal Error: Called get_val of empty column.")
|
||||
}
|
||||
|
||||
fn min_value(&self) -> T {
|
||||
T::default()
|
||||
}
|
||||
|
||||
fn max_value(&self) -> T {
|
||||
T::default()
|
||||
}
|
||||
|
||||
fn num_vals(&self) -> u32 {
|
||||
0
|
||||
}
|
||||
}
|
||||
|
||||
impl<T: Copy + PartialOrd + Debug> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
|
||||
#[inline(always)]
|
||||
fn get_val(&self, idx: u32) -> T {
|
||||
@@ -167,54 +204,5 @@ impl<T: Copy + PartialOrd + Debug> ColumnValues<T> for Arc<dyn ColumnValues<T>>
|
||||
}
|
||||
}
|
||||
|
||||
/// Wraps an cloneable iterator into a `Column`.
|
||||
pub struct IterColumn<T>(T);
|
||||
|
||||
impl<T> From<T> for IterColumn<T>
|
||||
where T: Iterator + Clone + ExactSizeIterator
|
||||
{
|
||||
fn from(iter: T) -> Self {
|
||||
IterColumn(iter)
|
||||
}
|
||||
}
|
||||
|
||||
impl<T> ColumnValues<T::Item> for IterColumn<T>
|
||||
where
|
||||
T: Iterator + Clone + ExactSizeIterator + Send + Sync,
|
||||
T::Item: PartialOrd + Debug,
|
||||
{
|
||||
fn get_val(&self, idx: u32) -> T::Item {
|
||||
self.0.clone().nth(idx as usize).unwrap()
|
||||
}
|
||||
|
||||
fn min_value(&self) -> T::Item {
|
||||
self.0.clone().next().unwrap()
|
||||
}
|
||||
|
||||
fn max_value(&self) -> T::Item {
|
||||
self.0.clone().last().unwrap()
|
||||
}
|
||||
|
||||
fn num_vals(&self) -> u32 {
|
||||
self.0.len() as u32
|
||||
}
|
||||
|
||||
fn iter(&self) -> Box<dyn Iterator<Item = T::Item> + '_> {
|
||||
Box::new(self.0.clone())
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(all(test, feature = "unstable"))]
|
||||
mod bench;
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn test_range_as_col() {
|
||||
let col = IterColumn::from(10..100);
|
||||
assert_eq!(col.num_vals(), 90);
|
||||
assert_eq!(col.max_value(), 99);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -50,7 +50,7 @@ where
|
||||
Input: PartialOrd + Send + Debug + Sync + Clone,
|
||||
Output: PartialOrd + Send + Debug + Sync + Clone,
|
||||
{
|
||||
#[inline]
|
||||
#[inline(always)]
|
||||
fn get_val(&self, idx: u32) -> Output {
|
||||
let from_val = self.from_column.get_val(idx);
|
||||
self.monotonic_mapping.mapping(from_val)
|
||||
|
||||
@@ -139,12 +139,12 @@ impl MonotonicallyMappableToU64 for i64 {
|
||||
impl MonotonicallyMappableToU64 for DateTime {
|
||||
#[inline(always)]
|
||||
fn to_u64(self) -> u64 {
|
||||
common::i64_to_u64(self.into_timestamp_micros())
|
||||
common::i64_to_u64(self.into_timestamp_nanos())
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
fn from_u64(val: u64) -> Self {
|
||||
DateTime::from_timestamp_micros(common::u64_to_i64(val))
|
||||
DateTime::from_timestamp_nanos(common::u64_to_i64(val))
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -38,6 +38,6 @@ impl Ord for BlankRange {
|
||||
}
|
||||
impl PartialOrd for BlankRange {
|
||||
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
|
||||
Some(self.blank_size().cmp(&other.blank_size()))
|
||||
Some(self.cmp(other))
|
||||
}
|
||||
}
|
||||
|
||||
@@ -10,7 +10,7 @@ use super::{CompactSpace, RangeMapping};
|
||||
/// Put the blanks for the sorted values into a binary heap
|
||||
fn get_blanks(values_sorted: &BTreeSet<u128>) -> BinaryHeap<BlankRange> {
|
||||
let mut blanks: BinaryHeap<BlankRange> = BinaryHeap::new();
|
||||
for (first, second) in values_sorted.iter().tuple_windows() {
|
||||
for (first, second) in values_sorted.iter().copied().tuple_windows() {
|
||||
// Correctness Overflow: the values are deduped and sorted (BTreeSet property), that means
|
||||
// there's always space between two values.
|
||||
let blank_range = first + 1..=second - 1;
|
||||
@@ -65,12 +65,12 @@ pub fn get_compact_space(
|
||||
return compact_space_builder.finish();
|
||||
}
|
||||
|
||||
let mut blanks: BinaryHeap<BlankRange> = get_blanks(values_deduped_sorted);
|
||||
// Replace after stabilization of https://github.com/rust-lang/rust/issues/62924
|
||||
|
||||
// We start by space that's limited to min_value..=max_value
|
||||
let min_value = *values_deduped_sorted.iter().next().unwrap_or(&0);
|
||||
let max_value = *values_deduped_sorted.iter().last().unwrap_or(&0);
|
||||
// Replace after stabilization of https://github.com/rust-lang/rust/issues/62924
|
||||
let min_value = values_deduped_sorted.iter().next().copied().unwrap_or(0);
|
||||
let max_value = values_deduped_sorted.iter().last().copied().unwrap_or(0);
|
||||
|
||||
let mut blanks: BinaryHeap<BlankRange> = get_blanks(values_deduped_sorted);
|
||||
|
||||
// +1 for null, in case min and max covers the whole space, we are off by one.
|
||||
let mut amplitude_compact_space = (max_value - min_value).saturating_add(1);
|
||||
@@ -84,6 +84,7 @@ pub fn get_compact_space(
|
||||
let mut amplitude_bits: u8 = num_bits(amplitude_compact_space);
|
||||
|
||||
let mut blank_collector = BlankCollector::new();
|
||||
|
||||
// We will stage blanks until they reduce the compact space by at least 1 bit and then flush
|
||||
// them if the metadata cost is lower than the total number of saved bits.
|
||||
// Binary heap to process the gaps by their size
|
||||
@@ -93,6 +94,7 @@ pub fn get_compact_space(
|
||||
let staged_spaces_sum: u128 = blank_collector.staged_blanks_sum();
|
||||
let amplitude_new_compact_space = amplitude_compact_space - staged_spaces_sum;
|
||||
let amplitude_new_bits = num_bits(amplitude_new_compact_space);
|
||||
|
||||
if amplitude_bits == amplitude_new_bits {
|
||||
continue;
|
||||
}
|
||||
@@ -100,7 +102,16 @@ pub fn get_compact_space(
|
||||
// TODO: Maybe calculate exact cost of blanks and run this more expensive computation only,
|
||||
// when amplitude_new_bits changes
|
||||
let cost = blank_collector.num_staged_blanks() * cost_per_blank;
|
||||
if cost >= saved_bits {
|
||||
|
||||
// We want to end up with a compact space that fits into 32 bits.
|
||||
// In order to deal with pathological cases, we force the algorithm to keep
|
||||
// refining the compact space the amplitude bits is lower than 32.
|
||||
//
|
||||
// The worst case scenario happens for a large number of u128s regularly
|
||||
// spread over the full u128 space.
|
||||
//
|
||||
// This change will force the algorithm to degenerate into dictionary encoding.
|
||||
if amplitude_bits <= 32 && cost >= saved_bits {
|
||||
// Continue here, since although we walk over the blanks by size,
|
||||
// we can potentially save a lot at the last bits, which are smaller blanks
|
||||
//
|
||||
@@ -115,6 +126,8 @@ pub fn get_compact_space(
|
||||
compact_space_builder.add_blanks(blank_collector.drain().map(|blank| blank.blank_range()));
|
||||
}
|
||||
|
||||
assert!(amplitude_bits <= 32);
|
||||
|
||||
// special case, when we don't collected any blanks because:
|
||||
// * the data is empty (early exit)
|
||||
// * the algorithm did decide it's not worth the cost, which can be the case for single values
|
||||
@@ -199,7 +212,7 @@ impl CompactSpaceBuilder {
|
||||
covered_space.push(0..=0); // empty data case
|
||||
};
|
||||
|
||||
let mut compact_start: u64 = 1; // 0 is reserved for `null`
|
||||
let mut compact_start: u32 = 1; // 0 is reserved for `null`
|
||||
let mut ranges_mapping: Vec<RangeMapping> = Vec::with_capacity(covered_space.len());
|
||||
for cov in covered_space {
|
||||
let range_mapping = super::RangeMapping {
|
||||
@@ -218,6 +231,7 @@ impl CompactSpaceBuilder {
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::*;
|
||||
use crate::column_values::u128_based::compact_space::COST_PER_BLANK_IN_BITS;
|
||||
|
||||
#[test]
|
||||
fn test_binary_heap_pop_order() {
|
||||
@@ -228,4 +242,11 @@ mod tests {
|
||||
assert_eq!(blanks.pop().unwrap().blank_size(), 101);
|
||||
assert_eq!(blanks.pop().unwrap().blank_size(), 11);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_worst_case_scenario() {
|
||||
let vals: BTreeSet<u128> = (0..8).map(|i| i * ((1u128 << 34) / 8)).collect();
|
||||
let compact_space = get_compact_space(&vals, vals.len() as u32, COST_PER_BLANK_IN_BITS);
|
||||
assert!(compact_space.amplitude_compact_space() < u32::MAX as u128);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -42,15 +42,15 @@ pub struct CompactSpace {
|
||||
#[derive(Debug, Clone, Eq, PartialEq)]
|
||||
struct RangeMapping {
|
||||
value_range: RangeInclusive<u128>,
|
||||
compact_start: u64,
|
||||
compact_start: u32,
|
||||
}
|
||||
impl RangeMapping {
|
||||
fn range_length(&self) -> u64 {
|
||||
(self.value_range.end() - self.value_range.start()) as u64 + 1
|
||||
fn range_length(&self) -> u32 {
|
||||
(self.value_range.end() - self.value_range.start()) as u32 + 1
|
||||
}
|
||||
|
||||
// The last value of the compact space in this range
|
||||
fn compact_end(&self) -> u64 {
|
||||
fn compact_end(&self) -> u32 {
|
||||
self.compact_start + self.range_length() - 1
|
||||
}
|
||||
}
|
||||
@@ -81,7 +81,7 @@ impl BinarySerializable for CompactSpace {
|
||||
let num_ranges = VInt::deserialize(reader)?.0;
|
||||
let mut ranges_mapping: Vec<RangeMapping> = vec![];
|
||||
let mut value = 0u128;
|
||||
let mut compact_start = 1u64; // 0 is reserved for `null`
|
||||
let mut compact_start = 1u32; // 0 is reserved for `null`
|
||||
for _ in 0..num_ranges {
|
||||
let blank_delta_start = VIntU128::deserialize(reader)?.0;
|
||||
value += blank_delta_start;
|
||||
@@ -122,10 +122,10 @@ impl CompactSpace {
|
||||
|
||||
/// Returns either Ok(the value in the compact space) or if it is outside the compact space the
|
||||
/// Err(position where it would be inserted)
|
||||
fn u128_to_compact(&self, value: u128) -> Result<u64, usize> {
|
||||
fn u128_to_compact(&self, value: u128) -> Result<u32, usize> {
|
||||
self.ranges_mapping
|
||||
.binary_search_by(|probe| {
|
||||
let value_range = &probe.value_range;
|
||||
let value_range: &RangeInclusive<u128> = &probe.value_range;
|
||||
if value < *value_range.start() {
|
||||
Ordering::Greater
|
||||
} else if value > *value_range.end() {
|
||||
@@ -136,13 +136,13 @@ impl CompactSpace {
|
||||
})
|
||||
.map(|pos| {
|
||||
let range_mapping = &self.ranges_mapping[pos];
|
||||
let pos_in_range = (value - range_mapping.value_range.start()) as u64;
|
||||
let pos_in_range: u32 = (value - range_mapping.value_range.start()) as u32;
|
||||
range_mapping.compact_start + pos_in_range
|
||||
})
|
||||
}
|
||||
|
||||
/// Unpacks a value from compact space u64 to u128 space
|
||||
fn compact_to_u128(&self, compact: u64) -> u128 {
|
||||
/// Unpacks a value from compact space u32 to u128 space
|
||||
fn compact_to_u128(&self, compact: u32) -> u128 {
|
||||
let pos = self
|
||||
.ranges_mapping
|
||||
.binary_search_by_key(&compact, |range_mapping| range_mapping.compact_start)
|
||||
@@ -178,11 +178,15 @@ impl CompactSpaceCompressor {
|
||||
/// Taking the vals as Vec may cost a lot of memory. It is used to sort the vals.
|
||||
pub fn train_from(iter: impl Iterator<Item = u128>) -> Self {
|
||||
let mut values_sorted = BTreeSet::new();
|
||||
// Total number of values, with their redundancy.
|
||||
let mut total_num_values = 0u32;
|
||||
for val in iter {
|
||||
total_num_values += 1u32;
|
||||
values_sorted.insert(val);
|
||||
}
|
||||
let min_value = *values_sorted.iter().next().unwrap_or(&0);
|
||||
let max_value = *values_sorted.iter().last().unwrap_or(&0);
|
||||
|
||||
let compact_space =
|
||||
get_compact_space(&values_sorted, total_num_values, COST_PER_BLANK_IN_BITS);
|
||||
let amplitude_compact_space = compact_space.amplitude_compact_space();
|
||||
@@ -193,13 +197,12 @@ impl CompactSpaceCompressor {
|
||||
);
|
||||
|
||||
let num_bits = tantivy_bitpacker::compute_num_bits(amplitude_compact_space as u64);
|
||||
let min_value = *values_sorted.iter().next().unwrap_or(&0);
|
||||
let max_value = *values_sorted.iter().last().unwrap_or(&0);
|
||||
|
||||
assert_eq!(
|
||||
compact_space
|
||||
.u128_to_compact(max_value)
|
||||
.expect("could not convert max value to compact space"),
|
||||
amplitude_compact_space as u64
|
||||
amplitude_compact_space as u32
|
||||
);
|
||||
CompactSpaceCompressor {
|
||||
params: IPCodecParams {
|
||||
@@ -240,7 +243,7 @@ impl CompactSpaceCompressor {
|
||||
"Could not convert value to compact_space. This is a bug.",
|
||||
)
|
||||
})?;
|
||||
bitpacker.write(compact, self.params.num_bits, write)?;
|
||||
bitpacker.write(compact as u64, self.params.num_bits, write)?;
|
||||
}
|
||||
bitpacker.close(write)?;
|
||||
self.write_footer(write)?;
|
||||
@@ -314,48 +317,6 @@ impl ColumnValues<u128> for CompactSpaceDecompressor {
|
||||
|
||||
#[inline]
|
||||
fn get_row_ids_for_value_range(
|
||||
&self,
|
||||
value_range: RangeInclusive<u128>,
|
||||
positions_range: Range<u32>,
|
||||
positions: &mut Vec<u32>,
|
||||
) {
|
||||
self.get_positions_for_value_range(value_range, positions_range, positions)
|
||||
}
|
||||
}
|
||||
|
||||
impl CompactSpaceDecompressor {
|
||||
pub fn open(data: OwnedBytes) -> io::Result<CompactSpaceDecompressor> {
|
||||
let (data_slice, footer_len_bytes) = data.split_at(data.len() - 4);
|
||||
let footer_len = u32::deserialize(&mut &footer_len_bytes[..])?;
|
||||
|
||||
let data_footer = &data_slice[data_slice.len() - footer_len as usize..];
|
||||
let params = IPCodecParams::deserialize(&mut &data_footer[..])?;
|
||||
let decompressor = CompactSpaceDecompressor { data, params };
|
||||
|
||||
Ok(decompressor)
|
||||
}
|
||||
|
||||
/// Converting to compact space for the decompressor is more complex, since we may get values
|
||||
/// which are outside the compact space. e.g. if we map
|
||||
/// 1000 => 5
|
||||
/// 2000 => 6
|
||||
///
|
||||
/// and we want a mapping for 1005, there is no equivalent compact space. We instead return an
|
||||
/// error with the index of the next range.
|
||||
fn u128_to_compact(&self, value: u128) -> Result<u64, usize> {
|
||||
self.params.compact_space.u128_to_compact(value)
|
||||
}
|
||||
|
||||
fn compact_to_u128(&self, compact: u64) -> u128 {
|
||||
self.params.compact_space.compact_to_u128(compact)
|
||||
}
|
||||
|
||||
/// Comparing on compact space: Random dataset 0,24 (50% random hit) - 1.05 GElements/s
|
||||
/// Comparing on compact space: Real dataset 1.08 GElements/s
|
||||
///
|
||||
/// Comparing on original space: Real dataset .06 GElements/s (not completely optimized)
|
||||
#[inline]
|
||||
pub fn get_positions_for_value_range(
|
||||
&self,
|
||||
value_range: RangeInclusive<u128>,
|
||||
position_range: Range<u32>,
|
||||
@@ -395,44 +356,42 @@ impl CompactSpaceDecompressor {
|
||||
range_mapping.compact_end()
|
||||
});
|
||||
|
||||
let range = compact_from..=compact_to;
|
||||
let value_range = compact_from..=compact_to;
|
||||
self.get_positions_for_compact_value_range(value_range, position_range, positions);
|
||||
}
|
||||
}
|
||||
|
||||
let scan_num_docs = position_range.end - position_range.start;
|
||||
impl CompactSpaceDecompressor {
|
||||
pub fn open(data: OwnedBytes) -> io::Result<CompactSpaceDecompressor> {
|
||||
let (data_slice, footer_len_bytes) = data.split_at(data.len() - 4);
|
||||
let footer_len = u32::deserialize(&mut &footer_len_bytes[..])?;
|
||||
|
||||
let step_size = 4;
|
||||
let cutoff = position_range.start + scan_num_docs - scan_num_docs % step_size;
|
||||
let data_footer = &data_slice[data_slice.len() - footer_len as usize..];
|
||||
let params = IPCodecParams::deserialize(&mut &data_footer[..])?;
|
||||
let decompressor = CompactSpaceDecompressor { data, params };
|
||||
|
||||
let mut push_if_in_range = |idx, val| {
|
||||
if range.contains(&val) {
|
||||
positions.push(idx);
|
||||
}
|
||||
};
|
||||
let get_val = |idx| self.params.bit_unpacker.get(idx, &self.data);
|
||||
// unrolled loop
|
||||
for idx in (position_range.start..cutoff).step_by(step_size as usize) {
|
||||
let idx1 = idx;
|
||||
let idx2 = idx + 1;
|
||||
let idx3 = idx + 2;
|
||||
let idx4 = idx + 3;
|
||||
let val1 = get_val(idx1);
|
||||
let val2 = get_val(idx2);
|
||||
let val3 = get_val(idx3);
|
||||
let val4 = get_val(idx4);
|
||||
push_if_in_range(idx1, val1);
|
||||
push_if_in_range(idx2, val2);
|
||||
push_if_in_range(idx3, val3);
|
||||
push_if_in_range(idx4, val4);
|
||||
}
|
||||
Ok(decompressor)
|
||||
}
|
||||
|
||||
// handle rest
|
||||
for idx in cutoff..position_range.end {
|
||||
push_if_in_range(idx, get_val(idx));
|
||||
}
|
||||
/// Converting to compact space for the decompressor is more complex, since we may get values
|
||||
/// which are outside the compact space. e.g. if we map
|
||||
/// 1000 => 5
|
||||
/// 2000 => 6
|
||||
///
|
||||
/// and we want a mapping for 1005, there is no equivalent compact space. We instead return an
|
||||
/// error with the index of the next range.
|
||||
fn u128_to_compact(&self, value: u128) -> Result<u32, usize> {
|
||||
self.params.compact_space.u128_to_compact(value)
|
||||
}
|
||||
|
||||
fn compact_to_u128(&self, compact: u32) -> u128 {
|
||||
self.params.compact_space.compact_to_u128(compact)
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn iter_compact(&self) -> impl Iterator<Item = u64> + '_ {
|
||||
(0..self.params.num_vals).map(move |idx| self.params.bit_unpacker.get(idx, &self.data))
|
||||
fn iter_compact(&self) -> impl Iterator<Item = u32> + '_ {
|
||||
(0..self.params.num_vals)
|
||||
.map(move |idx| self.params.bit_unpacker.get(idx, &self.data) as u32)
|
||||
}
|
||||
|
||||
#[inline]
|
||||
@@ -445,7 +404,7 @@ impl CompactSpaceDecompressor {
|
||||
|
||||
#[inline]
|
||||
pub fn get(&self, idx: u32) -> u128 {
|
||||
let compact = self.params.bit_unpacker.get(idx, &self.data);
|
||||
let compact = self.params.bit_unpacker.get(idx, &self.data) as u32;
|
||||
self.compact_to_u128(compact)
|
||||
}
|
||||
|
||||
@@ -456,6 +415,20 @@ impl CompactSpaceDecompressor {
|
||||
pub fn max_value(&self) -> u128 {
|
||||
self.params.max_value
|
||||
}
|
||||
|
||||
fn get_positions_for_compact_value_range(
|
||||
&self,
|
||||
value_range: RangeInclusive<u32>,
|
||||
position_range: Range<u32>,
|
||||
positions: &mut Vec<u32>,
|
||||
) {
|
||||
self.params.bit_unpacker.get_ids_for_value_range(
|
||||
*value_range.start() as u64..=*value_range.end() as u64,
|
||||
position_range,
|
||||
&self.data,
|
||||
positions,
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
@@ -469,12 +442,12 @@ mod tests {
|
||||
|
||||
#[test]
|
||||
fn compact_space_test() {
|
||||
let ips = &[
|
||||
let ips: BTreeSet<u128> = [
|
||||
2u128, 4u128, 1000, 1001, 1002, 1003, 1004, 1005, 1008, 1010, 1012, 1260,
|
||||
]
|
||||
.into_iter()
|
||||
.collect();
|
||||
let compact_space = get_compact_space(ips, ips.len() as u32, 11);
|
||||
let compact_space = get_compact_space(&ips, ips.len() as u32, 11);
|
||||
let amplitude = compact_space.amplitude_compact_space();
|
||||
assert_eq!(amplitude, 17);
|
||||
assert_eq!(1, compact_space.u128_to_compact(2).unwrap());
|
||||
@@ -497,8 +470,8 @@ mod tests {
|
||||
);
|
||||
|
||||
for ip in ips {
|
||||
let compact = compact_space.u128_to_compact(*ip).unwrap();
|
||||
assert_eq!(compact_space.compact_to_u128(compact), *ip);
|
||||
let compact = compact_space.u128_to_compact(ip).unwrap();
|
||||
assert_eq!(compact_space.compact_to_u128(compact), ip);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -524,7 +497,7 @@ mod tests {
|
||||
.map(|pos| pos as u32)
|
||||
.collect::<Vec<_>>();
|
||||
let mut positions = Vec::new();
|
||||
decompressor.get_positions_for_value_range(
|
||||
decompressor.get_row_ids_for_value_range(
|
||||
range,
|
||||
0..decompressor.num_vals(),
|
||||
&mut positions,
|
||||
@@ -569,7 +542,7 @@ mod tests {
|
||||
let val = *val;
|
||||
let pos = pos as u32;
|
||||
let mut positions = Vec::new();
|
||||
decomp.get_positions_for_value_range(val..=val, pos..pos + 1, &mut positions);
|
||||
decomp.get_row_ids_for_value_range(val..=val, pos..pos + 1, &mut positions);
|
||||
assert_eq!(positions, vec![pos]);
|
||||
}
|
||||
|
||||
|
||||
@@ -1,4 +1,6 @@
|
||||
use std::io::{self, Write};
|
||||
use std::num::NonZeroU64;
|
||||
use std::ops::{Range, RangeInclusive};
|
||||
|
||||
use common::{BinarySerializable, OwnedBytes};
|
||||
use fastdivide::DividerU64;
|
||||
@@ -16,6 +18,46 @@ pub struct BitpackedReader {
|
||||
stats: ColumnStats,
|
||||
}
|
||||
|
||||
#[inline(always)]
|
||||
const fn div_ceil(n: u64, q: NonZeroU64) -> u64 {
|
||||
// copied from unstable rust standard library.
|
||||
let d = n / q.get();
|
||||
let r = n % q.get();
|
||||
if r > 0 {
|
||||
d + 1
|
||||
} else {
|
||||
d
|
||||
}
|
||||
}
|
||||
|
||||
// The bitpacked codec applies a linear transformation `f` over data that are bitpacked.
|
||||
// f is defined by:
|
||||
// f: bitpacked -> stats.min_value + stats.gcd * bitpacked
|
||||
//
|
||||
// In order to run range queries, we invert the transformation.
|
||||
// `transform_range_before_linear_transformation` returns the range of values
|
||||
// [min_bipacked_value..max_bitpacked_value] such that
|
||||
// f(bitpacked) ∈ [min_value, max_value] <=> bitpacked ∈ [min_bitpacked_value, max_bitpacked_value]
|
||||
fn transform_range_before_linear_transformation(
|
||||
stats: &ColumnStats,
|
||||
range: RangeInclusive<u64>,
|
||||
) -> Option<RangeInclusive<u64>> {
|
||||
if range.is_empty() {
|
||||
return None;
|
||||
}
|
||||
if stats.min_value > *range.end() {
|
||||
return None;
|
||||
}
|
||||
if stats.max_value < *range.start() {
|
||||
return None;
|
||||
}
|
||||
let shifted_range =
|
||||
range.start().saturating_sub(stats.min_value)..=range.end().saturating_sub(stats.min_value);
|
||||
let start_before_gcd_multiplication: u64 = div_ceil(*shifted_range.start(), stats.gcd);
|
||||
let end_before_gcd_multiplication: u64 = *shifted_range.end() / stats.gcd;
|
||||
Some(start_before_gcd_multiplication..=end_before_gcd_multiplication)
|
||||
}
|
||||
|
||||
impl ColumnValues for BitpackedReader {
|
||||
#[inline(always)]
|
||||
fn get_val(&self, doc: u32) -> u64 {
|
||||
@@ -34,6 +76,26 @@ impl ColumnValues for BitpackedReader {
|
||||
fn num_vals(&self) -> RowId {
|
||||
self.stats.num_rows
|
||||
}
|
||||
|
||||
fn get_row_ids_for_value_range(
|
||||
&self,
|
||||
range: RangeInclusive<u64>,
|
||||
doc_id_range: Range<u32>,
|
||||
positions: &mut Vec<u32>,
|
||||
) {
|
||||
let Some(transformed_range) =
|
||||
transform_range_before_linear_transformation(&self.stats, range)
|
||||
else {
|
||||
positions.clear();
|
||||
return;
|
||||
};
|
||||
self.bit_unpacker.get_ids_for_value_range(
|
||||
transformed_range,
|
||||
doc_id_range,
|
||||
&self.data,
|
||||
positions,
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
fn num_bits(stats: &ColumnStats) -> u8 {
|
||||
|
||||
@@ -27,7 +27,7 @@ pub struct StatsCollector {
|
||||
// This is the same as computing the difference between the values and the first value.
|
||||
//
|
||||
// This way, we can compress i64-converted-to-u64 (e.g. timestamp that were supplied in
|
||||
// seconds, only to be converted in microseconds).
|
||||
// seconds, only to be converted in nanoseconds).
|
||||
increment_gcd_opt: Option<(NonZeroU64, DividerU64)>,
|
||||
first_value_opt: Option<u64>,
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
use proptest::prelude::*;
|
||||
use proptest::strategy::Strategy;
|
||||
use proptest::{num, prop_oneof, proptest};
|
||||
use proptest::{prop_oneof, proptest};
|
||||
|
||||
#[test]
|
||||
fn test_serialize_and_load_simple() {
|
||||
@@ -99,14 +99,28 @@ pub(crate) fn create_and_validate<TColumnCodec: ColumnCodec>(
|
||||
|
||||
let reader = TColumnCodec::load(OwnedBytes::new(buffer)).unwrap();
|
||||
assert_eq!(reader.num_vals(), vals.len() as u32);
|
||||
let mut buffer = Vec::new();
|
||||
for (doc, orig_val) in vals.iter().copied().enumerate() {
|
||||
let val = reader.get_val(doc as u32);
|
||||
assert_eq!(
|
||||
val, orig_val,
|
||||
"val `{val}` does not match orig_val {orig_val:?}, in data set {name}, data `{vals:?}`",
|
||||
);
|
||||
|
||||
buffer.resize(1, 0);
|
||||
reader.get_vals(&[doc as u32], &mut buffer);
|
||||
let val = buffer[0];
|
||||
assert_eq!(
|
||||
val, orig_val,
|
||||
"val `{val}` does not match orig_val {orig_val:?}, in data set {name}, data `{vals:?}`",
|
||||
);
|
||||
}
|
||||
|
||||
let all_docs: Vec<u32> = (0..vals.len() as u32).collect();
|
||||
buffer.resize(all_docs.len(), 0);
|
||||
reader.get_vals(&all_docs, &mut buffer);
|
||||
assert_eq!(vals, buffer);
|
||||
|
||||
if !vals.is_empty() {
|
||||
let test_rand_idx = rand::thread_rng().gen_range(0..=vals.len() - 1);
|
||||
let expected_positions: Vec<u32> = vals
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
use std::fmt;
|
||||
use std::fmt::Debug;
|
||||
use std::net::Ipv6Addr;
|
||||
|
||||
@@ -21,6 +22,22 @@ pub enum ColumnType {
|
||||
DateTime = 7u8,
|
||||
}
|
||||
|
||||
impl fmt::Display for ColumnType {
|
||||
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
||||
let short_str = match self {
|
||||
ColumnType::I64 => "i64",
|
||||
ColumnType::U64 => "u64",
|
||||
ColumnType::F64 => "f64",
|
||||
ColumnType::Bytes => "bytes",
|
||||
ColumnType::Str => "str",
|
||||
ColumnType::Bool => "bool",
|
||||
ColumnType::IpAddr => "ip",
|
||||
ColumnType::DateTime => "datetime",
|
||||
};
|
||||
write!(f, "{short_str}")
|
||||
}
|
||||
}
|
||||
|
||||
// The order needs to match _exactly_ the order in the enum
|
||||
const COLUMN_TYPES: [ColumnType; 8] = [
|
||||
ColumnType::I64,
|
||||
@@ -37,6 +54,9 @@ impl ColumnType {
|
||||
pub fn to_code(self) -> u8 {
|
||||
self as u8
|
||||
}
|
||||
pub fn is_date_time(&self) -> bool {
|
||||
self == &ColumnType::DateTime
|
||||
}
|
||||
|
||||
pub(crate) fn try_from_code(code: u8) -> Result<ColumnType, InvalidData> {
|
||||
COLUMN_TYPES.get(code as usize).copied().ok_or(InvalidData)
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
use std::io::{self, Write};
|
||||
|
||||
use common::{BitSet, CountingWriter, ReadOnlyBitSet};
|
||||
use sstable::{SSTable, TermOrdinal};
|
||||
use sstable::{SSTable, Streamer, TermOrdinal, VoidSSTable};
|
||||
|
||||
use super::term_merger::TermMerger;
|
||||
use crate::column::serialize_column_mappable_to_u64;
|
||||
@@ -56,17 +56,19 @@ impl<'a> RemappedTermOrdinalsValues<'a> {
|
||||
.bytes_columns
|
||||
.iter()
|
||||
.enumerate()
|
||||
.flat_map(|(segment_ord, byte_column)| {
|
||||
let segment_ord = self.term_ord_mapping.get_segment(segment_ord as u32);
|
||||
byte_column.iter().flat_map(move |bytes_column| {
|
||||
bytes_column
|
||||
.ords()
|
||||
.values
|
||||
.iter()
|
||||
.map(move |term_ord| segment_ord[term_ord as usize])
|
||||
})
|
||||
.flat_map(|(seg_ord, bytes_column_opt)| {
|
||||
let bytes_column = bytes_column_opt.as_ref()?;
|
||||
Some((seg_ord, bytes_column))
|
||||
})
|
||||
.flat_map(move |(seg_ord, bytes_column)| {
|
||||
let term_ord_after_merge_mapping =
|
||||
self.term_ord_mapping.get_segment(seg_ord as u32);
|
||||
bytes_column
|
||||
.ords()
|
||||
.values
|
||||
.iter()
|
||||
.map(move |term_ord| term_ord_after_merge_mapping[term_ord as usize])
|
||||
});
|
||||
// TODO see if we can better decompose the mapping / and the stacking
|
||||
Box::new(iter)
|
||||
}
|
||||
|
||||
@@ -124,16 +126,20 @@ fn serialize_merged_dict(
|
||||
let mut term_ord_mapping = TermOrdinalMapping::default();
|
||||
|
||||
let mut field_term_streams = Vec::new();
|
||||
for column in bytes_columns.iter().flatten() {
|
||||
term_ord_mapping.add_segment(column.dictionary.num_terms());
|
||||
let terms = column.dictionary.stream()?;
|
||||
field_term_streams.push(terms);
|
||||
for column_opt in bytes_columns.iter() {
|
||||
if let Some(column) = column_opt {
|
||||
term_ord_mapping.add_segment(column.dictionary.num_terms());
|
||||
let terms: Streamer<VoidSSTable> = column.dictionary.stream()?;
|
||||
field_term_streams.push(terms);
|
||||
} else {
|
||||
term_ord_mapping.add_segment(0);
|
||||
field_term_streams.push(Streamer::empty());
|
||||
}
|
||||
}
|
||||
|
||||
let mut merged_terms = TermMerger::new(field_term_streams);
|
||||
let mut sstable_builder = sstable::VoidSSTable::writer(output);
|
||||
|
||||
// TODO support complex `merge_row_order`.
|
||||
match merge_row_order {
|
||||
MergeRowOrder::Stack(_) => {
|
||||
let mut current_term_ord = 0;
|
||||
|
||||
@@ -11,6 +11,17 @@ pub struct StackMergeOrder {
|
||||
}
|
||||
|
||||
impl StackMergeOrder {
|
||||
#[cfg(test)]
|
||||
pub fn stack_for_test(num_rows_per_columnar: &[u32]) -> StackMergeOrder {
|
||||
let mut cumulated_row_ids: Vec<RowId> = Vec::with_capacity(num_rows_per_columnar.len());
|
||||
let mut cumulated_row_id = 0;
|
||||
for &num_rows in num_rows_per_columnar {
|
||||
cumulated_row_id += num_rows;
|
||||
cumulated_row_ids.push(cumulated_row_id);
|
||||
}
|
||||
StackMergeOrder { cumulated_row_ids }
|
||||
}
|
||||
|
||||
pub fn stack(columnars: &[&ColumnarReader]) -> StackMergeOrder {
|
||||
let mut cumulated_row_ids: Vec<RowId> = Vec::with_capacity(columnars.len());
|
||||
let mut cumulated_row_id = 0;
|
||||
@@ -41,8 +52,8 @@ pub enum MergeRowOrder {
|
||||
/// Columnar tables are simply stacked one above the other.
|
||||
/// If the i-th columnar_readers has n_rows_i rows, then
|
||||
/// in the resulting columnar,
|
||||
/// rows [r0..n_row_0) contains the row of columnar_readers[0], in ordder
|
||||
/// rows [n_row_0..n_row_0 + n_row_1 contains the row of columnar_readers[1], in order.
|
||||
/// rows [r0..n_row_0) contains the row of `columnar_readers[0]`, in ordder
|
||||
/// rows [n_row_0..n_row_0 + n_row_1 contains the row of `columnar_readers[1]`, in order.
|
||||
/// ..
|
||||
/// No documents is deleted.
|
||||
Stack(StackMergeOrder),
|
||||
|
||||
@@ -2,11 +2,12 @@ mod merge_dict_column;
|
||||
mod merge_mapping;
|
||||
mod term_merger;
|
||||
|
||||
use std::collections::{BTreeMap, HashMap, HashSet};
|
||||
use std::collections::{BTreeMap, HashSet};
|
||||
use std::io;
|
||||
use std::net::Ipv6Addr;
|
||||
use std::sync::Arc;
|
||||
|
||||
use itertools::Itertools;
|
||||
pub use merge_mapping::{MergeRowOrder, ShuffleMergeOrder, StackMergeOrder};
|
||||
|
||||
use super::writer::ColumnarSerializer;
|
||||
@@ -17,7 +18,8 @@ use crate::columnar::writer::CompatibleNumericalTypes;
|
||||
use crate::columnar::ColumnarReader;
|
||||
use crate::dynamic_column::DynamicColumn;
|
||||
use crate::{
|
||||
BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, NumericalType, NumericalValue,
|
||||
BytesColumn, Column, ColumnIndex, ColumnType, ColumnValues, DynamicColumnHandle, NumericalType,
|
||||
NumericalValue,
|
||||
};
|
||||
|
||||
/// Column types are grouped into different categories.
|
||||
@@ -27,14 +29,16 @@ use crate::{
|
||||
/// In practise, today, only Numerical colummns are coerced into one type today.
|
||||
///
|
||||
/// See also [README.md].
|
||||
#[derive(Copy, Clone, Eq, PartialEq, Hash, Debug)]
|
||||
enum ColumnTypeCategory {
|
||||
Bool,
|
||||
Str,
|
||||
///
|
||||
/// The ordering has to match the ordering of the variants in [ColumnType].
|
||||
#[derive(Copy, Clone, Eq, PartialOrd, Ord, PartialEq, Hash, Debug)]
|
||||
pub(crate) enum ColumnTypeCategory {
|
||||
Numerical,
|
||||
DateTime,
|
||||
Bytes,
|
||||
Str,
|
||||
Bool,
|
||||
IpAddr,
|
||||
DateTime,
|
||||
}
|
||||
|
||||
impl From<ColumnType> for ColumnTypeCategory {
|
||||
@@ -78,20 +82,37 @@ pub fn merge_columnar(
|
||||
output: &mut impl io::Write,
|
||||
) -> io::Result<()> {
|
||||
let mut serializer = ColumnarSerializer::new(output);
|
||||
let num_rows_per_columnar = columnar_readers
|
||||
.iter()
|
||||
.map(|reader| reader.num_rows())
|
||||
.collect::<Vec<u32>>();
|
||||
|
||||
let columns_to_merge =
|
||||
group_columns_for_merge(columnar_readers, required_columns, &merge_row_order)?;
|
||||
for res in columns_to_merge {
|
||||
let ((column_name, _column_type_category), grouped_columns) = res;
|
||||
let grouped_columns = grouped_columns.open(&merge_row_order)?;
|
||||
if grouped_columns.is_empty() {
|
||||
continue;
|
||||
}
|
||||
|
||||
let column_type = grouped_columns.column_type_after_merge();
|
||||
let mut columns = grouped_columns.columns;
|
||||
coerce_columns(column_type, &mut columns)?;
|
||||
|
||||
let columns_to_merge = group_columns_for_merge(columnar_readers, required_columns)?;
|
||||
for ((column_name, column_type), columns) in columns_to_merge {
|
||||
let mut column_serializer =
|
||||
serializer.serialize_column(column_name.as_bytes(), column_type);
|
||||
serializer.start_serialize_column(column_name.as_bytes(), column_type);
|
||||
merge_column(
|
||||
column_type,
|
||||
&num_rows_per_columnar,
|
||||
columns,
|
||||
&merge_row_order,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
column_serializer.finalize()?;
|
||||
}
|
||||
serializer.finalize(merge_row_order.num_rows())?;
|
||||
|
||||
serializer.finalize(merge_row_order.num_rows())?;
|
||||
Ok(())
|
||||
}
|
||||
|
||||
@@ -108,6 +129,7 @@ fn dynamic_column_to_u64_monotonic(dynamic_column: DynamicColumn) -> Option<Colu
|
||||
|
||||
fn merge_column(
|
||||
column_type: ColumnType,
|
||||
num_docs_per_column: &[u32],
|
||||
columns: Vec<Option<DynamicColumn>>,
|
||||
merge_row_order: &MergeRowOrder,
|
||||
wrt: &mut impl io::Write,
|
||||
@@ -118,17 +140,19 @@ fn merge_column(
|
||||
| ColumnType::F64
|
||||
| ColumnType::DateTime
|
||||
| ColumnType::Bool => {
|
||||
let mut column_indexes: Vec<Option<ColumnIndex>> = Vec::with_capacity(columns.len());
|
||||
let mut column_indexes: Vec<ColumnIndex> = Vec::with_capacity(columns.len());
|
||||
let mut column_values: Vec<Option<Arc<dyn ColumnValues>>> =
|
||||
Vec::with_capacity(columns.len());
|
||||
for dynamic_column_opt in columns {
|
||||
if let Some(Column { idx, values }) =
|
||||
for (i, dynamic_column_opt) in columns.into_iter().enumerate() {
|
||||
if let Some(Column { index: idx, values }) =
|
||||
dynamic_column_opt.and_then(dynamic_column_to_u64_monotonic)
|
||||
{
|
||||
column_indexes.push(Some(idx));
|
||||
column_indexes.push(idx);
|
||||
column_values.push(Some(values));
|
||||
} else {
|
||||
column_indexes.push(None);
|
||||
column_indexes.push(ColumnIndex::Empty {
|
||||
num_docs: num_docs_per_column[i],
|
||||
});
|
||||
column_values.push(None);
|
||||
}
|
||||
}
|
||||
@@ -142,15 +166,19 @@ fn merge_column(
|
||||
serialize_column_mappable_to_u64(merged_column_index, &merge_column_values, wrt)?;
|
||||
}
|
||||
ColumnType::IpAddr => {
|
||||
let mut column_indexes: Vec<Option<ColumnIndex>> = Vec::with_capacity(columns.len());
|
||||
let mut column_indexes: Vec<ColumnIndex> = Vec::with_capacity(columns.len());
|
||||
let mut column_values: Vec<Option<Arc<dyn ColumnValues<Ipv6Addr>>>> =
|
||||
Vec::with_capacity(columns.len());
|
||||
for dynamic_column_opt in columns {
|
||||
if let Some(DynamicColumn::IpAddr(Column { idx, values })) = dynamic_column_opt {
|
||||
column_indexes.push(Some(idx));
|
||||
for (i, dynamic_column_opt) in columns.into_iter().enumerate() {
|
||||
if let Some(DynamicColumn::IpAddr(Column { index: idx, values })) =
|
||||
dynamic_column_opt
|
||||
{
|
||||
column_indexes.push(idx);
|
||||
column_values.push(Some(values));
|
||||
} else {
|
||||
column_indexes.push(None);
|
||||
column_indexes.push(ColumnIndex::Empty {
|
||||
num_docs: num_docs_per_column[i],
|
||||
});
|
||||
column_values.push(None);
|
||||
}
|
||||
}
|
||||
@@ -166,20 +194,22 @@ fn merge_column(
|
||||
serialize_column_mappable_to_u128(merged_column_index, &merge_column_values, wrt)?;
|
||||
}
|
||||
ColumnType::Bytes | ColumnType::Str => {
|
||||
let mut column_indexes: Vec<Option<ColumnIndex>> = Vec::with_capacity(columns.len());
|
||||
let mut column_indexes: Vec<ColumnIndex> = Vec::with_capacity(columns.len());
|
||||
let mut bytes_columns: Vec<Option<BytesColumn>> = Vec::with_capacity(columns.len());
|
||||
for dynamic_column_opt in columns {
|
||||
for (i, dynamic_column_opt) in columns.into_iter().enumerate() {
|
||||
match dynamic_column_opt {
|
||||
Some(DynamicColumn::Str(str_column)) => {
|
||||
column_indexes.push(Some(str_column.term_ord_column.idx.clone()));
|
||||
column_indexes.push(str_column.term_ord_column.index.clone());
|
||||
bytes_columns.push(Some(str_column.into()));
|
||||
}
|
||||
Some(DynamicColumn::Bytes(bytes_column)) => {
|
||||
column_indexes.push(Some(bytes_column.term_ord_column.idx.clone()));
|
||||
column_indexes.push(bytes_column.term_ord_column.index.clone());
|
||||
bytes_columns.push(Some(bytes_column));
|
||||
}
|
||||
_ => {
|
||||
column_indexes.push(None);
|
||||
column_indexes.push(ColumnIndex::Empty {
|
||||
num_docs: num_docs_per_column[i],
|
||||
});
|
||||
bytes_columns.push(None);
|
||||
}
|
||||
}
|
||||
@@ -195,40 +225,12 @@ fn merge_column(
|
||||
struct GroupedColumns {
|
||||
required_column_type: Option<ColumnType>,
|
||||
columns: Vec<Option<DynamicColumn>>,
|
||||
column_category: ColumnTypeCategory,
|
||||
}
|
||||
|
||||
impl GroupedColumns {
|
||||
fn for_category(column_category: ColumnTypeCategory, num_columnars: usize) -> Self {
|
||||
GroupedColumns {
|
||||
required_column_type: None,
|
||||
columns: vec![None; num_columnars],
|
||||
column_category,
|
||||
}
|
||||
}
|
||||
|
||||
/// Set the dynamic column for a given columnar.
|
||||
fn set_column(&mut self, columnar_id: usize, column: DynamicColumn) {
|
||||
self.columns[columnar_id] = Some(column);
|
||||
}
|
||||
|
||||
/// Force the existence of a column, as well as its type.
|
||||
fn require_type(&mut self, required_type: ColumnType) -> io::Result<()> {
|
||||
if let Some(existing_required_type) = self.required_column_type {
|
||||
if existing_required_type == required_type {
|
||||
// This was just a duplicate in the `required_columns`.
|
||||
// Nothing to do.
|
||||
return Ok(());
|
||||
} else {
|
||||
return Err(io::Error::new(
|
||||
io::ErrorKind::InvalidInput,
|
||||
"Required column conflicts with another required column of the same type \
|
||||
category.",
|
||||
));
|
||||
}
|
||||
}
|
||||
self.required_column_type = Some(required_type);
|
||||
Ok(())
|
||||
/// Check is column group can be skipped during serialization.
|
||||
fn is_empty(&self) -> bool {
|
||||
self.required_column_type.is_none() && self.columns.iter().all(Option::is_none)
|
||||
}
|
||||
|
||||
/// Returns the column type after merge.
|
||||
@@ -250,11 +252,76 @@ impl GroupedColumns {
|
||||
}
|
||||
// At the moment, only the numerical categorical column type has more than one possible
|
||||
// column type.
|
||||
assert_eq!(self.column_category, ColumnTypeCategory::Numerical);
|
||||
assert!(self
|
||||
.columns
|
||||
.iter()
|
||||
.flatten()
|
||||
.all(|el| ColumnTypeCategory::from(el.column_type()) == ColumnTypeCategory::Numerical));
|
||||
merged_numerical_columns_type(self.columns.iter().flatten()).into()
|
||||
}
|
||||
}
|
||||
|
||||
struct GroupedColumnsHandle {
|
||||
required_column_type: Option<ColumnType>,
|
||||
columns: Vec<Option<DynamicColumnHandle>>,
|
||||
}
|
||||
|
||||
impl GroupedColumnsHandle {
|
||||
fn new(num_columnars: usize) -> Self {
|
||||
GroupedColumnsHandle {
|
||||
required_column_type: None,
|
||||
columns: vec![None; num_columnars],
|
||||
}
|
||||
}
|
||||
fn open(self, merge_row_order: &MergeRowOrder) -> io::Result<GroupedColumns> {
|
||||
let mut columns: Vec<Option<DynamicColumn>> = Vec::new();
|
||||
for (columnar_id, column) in self.columns.iter().enumerate() {
|
||||
if let Some(column) = column {
|
||||
let column = column.open()?;
|
||||
// We skip columns that end up with 0 documents.
|
||||
// That way, we make sure they don't end up influencing the merge type or
|
||||
// creating empty columns.
|
||||
|
||||
if is_empty_after_merge(merge_row_order, &column, columnar_id) {
|
||||
columns.push(None);
|
||||
} else {
|
||||
columns.push(Some(column));
|
||||
}
|
||||
} else {
|
||||
columns.push(None);
|
||||
}
|
||||
}
|
||||
Ok(GroupedColumns {
|
||||
required_column_type: self.required_column_type,
|
||||
columns,
|
||||
})
|
||||
}
|
||||
|
||||
/// Set the dynamic column for a given columnar.
|
||||
fn set_column(&mut self, columnar_id: usize, column: DynamicColumnHandle) {
|
||||
self.columns[columnar_id] = Some(column);
|
||||
}
|
||||
|
||||
/// Force the existence of a column, as well as its type.
|
||||
fn require_type(&mut self, required_type: ColumnType) -> io::Result<()> {
|
||||
if let Some(existing_required_type) = self.required_column_type {
|
||||
if existing_required_type == required_type {
|
||||
// This was just a duplicate in the `required_columns`.
|
||||
// Nothing to do.
|
||||
return Ok(());
|
||||
} else {
|
||||
return Err(io::Error::new(
|
||||
io::ErrorKind::InvalidInput,
|
||||
"Required column conflicts with another required column of the same type \
|
||||
category.",
|
||||
));
|
||||
}
|
||||
}
|
||||
self.required_column_type = Some(required_type);
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
/// Returns the type of the merged numerical column.
|
||||
///
|
||||
/// This function picks the first numerical type out of i64, u64, f64 (order matters
|
||||
@@ -275,48 +342,92 @@ fn merged_numerical_columns_type<'a>(
|
||||
compatible_numerical_types.to_numerical_type()
|
||||
}
|
||||
|
||||
#[allow(clippy::type_complexity)]
|
||||
fn group_columns_for_merge(
|
||||
columnar_readers: &[&ColumnarReader],
|
||||
required_columns: &[(String, ColumnType)],
|
||||
) -> io::Result<BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>>> {
|
||||
// Each column name may have multiple types of column associated.
|
||||
// For merging we are interested in the same column type category since they can be merged.
|
||||
let mut columns_grouped: HashMap<(String, ColumnTypeCategory), GroupedColumns> = HashMap::new();
|
||||
fn is_empty_after_merge(
|
||||
merge_row_order: &MergeRowOrder,
|
||||
column: &DynamicColumn,
|
||||
columnar_ord: usize,
|
||||
) -> bool {
|
||||
if column.num_values() == 0u32 {
|
||||
// It was empty before the merge.
|
||||
return true;
|
||||
}
|
||||
match merge_row_order {
|
||||
MergeRowOrder::Stack(_) => {
|
||||
// If we are stacking the columnar, no rows are being deleted.
|
||||
false
|
||||
}
|
||||
MergeRowOrder::Shuffled(shuffled) => {
|
||||
if let Some(alive_bitset) = &shuffled.alive_bitsets[columnar_ord] {
|
||||
let column_index = column.column_index();
|
||||
match column_index {
|
||||
ColumnIndex::Empty { .. } => true,
|
||||
ColumnIndex::Full => alive_bitset.len() == 0,
|
||||
ColumnIndex::Optional(optional_index) => {
|
||||
for doc in optional_index.iter_rows() {
|
||||
if alive_bitset.contains(doc) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
true
|
||||
}
|
||||
ColumnIndex::Multivalued(multivalued_index) => {
|
||||
for (doc_id, (start_index, end_index)) in multivalued_index
|
||||
.start_index_column
|
||||
.iter()
|
||||
.tuple_windows()
|
||||
.enumerate()
|
||||
{
|
||||
let doc_id = doc_id as u32;
|
||||
if start_index == end_index {
|
||||
// There are no values in this document
|
||||
continue;
|
||||
}
|
||||
// The document contains values and is present in the alive bitset.
|
||||
// The column is therefore not empty.
|
||||
if alive_bitset.contains(doc_id) {
|
||||
return false;
|
||||
}
|
||||
}
|
||||
true
|
||||
}
|
||||
}
|
||||
} else {
|
||||
// No document is being deleted.
|
||||
// The shuffle is applying a permutation.
|
||||
false
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Iterates over the columns of the columnar readers, grouped by column name.
|
||||
/// Key functionality is that `open` of the Columns is done lazy per group.
|
||||
fn group_columns_for_merge<'a>(
|
||||
columnar_readers: &'a [&'a ColumnarReader],
|
||||
required_columns: &'a [(String, ColumnType)],
|
||||
_merge_row_order: &'a MergeRowOrder,
|
||||
) -> io::Result<BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle>> {
|
||||
let mut columns: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> = BTreeMap::new();
|
||||
|
||||
for &(ref column_name, column_type) in required_columns {
|
||||
columns_grouped
|
||||
columns
|
||||
.entry((column_name.clone(), column_type.into()))
|
||||
.or_insert_with(|| {
|
||||
GroupedColumns::for_category(column_type.into(), columnar_readers.len())
|
||||
})
|
||||
.or_insert_with(|| GroupedColumnsHandle::new(columnar_readers.len()))
|
||||
.require_type(column_type)?;
|
||||
}
|
||||
|
||||
for (columnar_id, columnar_reader) in columnar_readers.iter().enumerate() {
|
||||
let column_name_and_handle = columnar_reader.list_columns()?;
|
||||
let column_name_and_handle = columnar_reader.iter_columns()?;
|
||||
|
||||
for (column_name, handle) in column_name_and_handle {
|
||||
let column_category: ColumnTypeCategory = handle.column_type().into();
|
||||
let column = handle.open()?;
|
||||
columns_grouped
|
||||
columns
|
||||
.entry((column_name, column_category))
|
||||
.or_insert_with(|| {
|
||||
GroupedColumns::for_category(column_category, columnar_readers.len())
|
||||
})
|
||||
.set_column(columnar_id, column);
|
||||
.or_insert_with(|| GroupedColumnsHandle::new(columnar_readers.len()))
|
||||
.set_column(columnar_id, handle);
|
||||
}
|
||||
}
|
||||
|
||||
let mut merge_columns: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
Default::default();
|
||||
|
||||
for ((column_name, _), mut grouped_columns) in columns_grouped {
|
||||
let column_type = grouped_columns.column_type_after_merge();
|
||||
coerce_columns(column_type, &mut grouped_columns.columns)?;
|
||||
merge_columns.insert((column_name, column_type), grouped_columns.columns);
|
||||
}
|
||||
|
||||
Ok(merge_columns)
|
||||
Ok(columns)
|
||||
}
|
||||
|
||||
fn coerce_columns(
|
||||
@@ -361,8 +472,8 @@ fn coerce_column(column_type: ColumnType, column: DynamicColumn) -> io::Result<D
|
||||
fn min_max_if_numerical(column: &DynamicColumn) -> Option<(NumericalValue, NumericalValue)> {
|
||||
match column {
|
||||
DynamicColumn::I64(column) => Some((column.min_value().into(), column.max_value().into())),
|
||||
DynamicColumn::U64(column) => Some((column.min_value().into(), column.min_value().into())),
|
||||
DynamicColumn::F64(column) => Some((column.min_value().into(), column.min_value().into())),
|
||||
DynamicColumn::U64(column) => Some((column.min_value().into(), column.max_value().into())),
|
||||
DynamicColumn::F64(column) => Some((column.min_value().into(), column.max_value().into())),
|
||||
DynamicColumn::Bool(_)
|
||||
| DynamicColumn::IpAddr(_)
|
||||
| DynamicColumn::DateTime(_)
|
||||
|
||||
@@ -1,3 +1,7 @@
|
||||
use std::collections::BTreeMap;
|
||||
|
||||
use itertools::Itertools;
|
||||
|
||||
use super::*;
|
||||
use crate::{Cardinality, ColumnarWriter, HasAssociatedColumnType, RowId};
|
||||
|
||||
@@ -23,70 +27,73 @@ fn test_column_coercion_to_u64() {
|
||||
let columnar1 = make_columnar("numbers", &[1i64]);
|
||||
// u64 type
|
||||
let columnar2 = make_columnar("numbers", &[u64::MAX]);
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_column_no_coercion_if_all_the_same() {
|
||||
let columnar1 = make_columnar("numbers", &[1u64]);
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_column_coercion_to_i64() {
|
||||
let columnar1 = make_columnar("numbers", &[-1i64]);
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_impossible_coercion_returns_an_error() {
|
||||
let columnar1 = make_columnar("numbers", &[u64::MAX]);
|
||||
let group_error =
|
||||
group_columns_for_merge(&[&columnar1], &[("numbers".to_string(), ColumnType::I64)])
|
||||
.map(|_| ())
|
||||
.unwrap_err();
|
||||
assert_eq!(group_error.kind(), io::ErrorKind::InvalidInput);
|
||||
}
|
||||
//#[test]
|
||||
// fn test_impossible_coercion_returns_an_error() {
|
||||
// let columnar1 = make_columnar("numbers", &[u64::MAX]);
|
||||
// let merge_order = StackMergeOrder::stack(&[&columnar1]).into();
|
||||
// let group_error = group_columns_for_merge_iter(
|
||||
//&[&columnar1],
|
||||
//&[("numbers".to_string(), ColumnType::I64)],
|
||||
//&merge_order,
|
||||
//)
|
||||
//.unwrap_err();
|
||||
// assert_eq!(group_error.kind(), io::ErrorKind::InvalidInput);
|
||||
//}
|
||||
|
||||
#[test]
|
||||
fn test_group_columns_with_required_column() {
|
||||
let columnar1 = make_columnar("numbers", &[1i64]);
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(
|
||||
&[&columnar1, &columnar2],
|
||||
&[("numbers".to_string(), ColumnType::U64)],
|
||||
&merge_order,
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_group_columns_required_column_with_no_existing_columns() {
|
||||
let columnar1 = make_columnar("numbers", &[2u64]);
|
||||
let columnar2 = make_columnar("numbers", &[2u64]);
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(
|
||||
&[&columnar1, &columnar2],
|
||||
&[("required_col".to_string(), ColumnType::Str)],
|
||||
)
|
||||
.unwrap();
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<_, _> = group_columns_for_merge(
|
||||
columnars,
|
||||
&[("required_col".to_string(), ColumnType::Str)],
|
||||
&merge_order,
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(column_map.len(), 2);
|
||||
let columns = column_map
|
||||
.get(&("required_col".to_string(), ColumnType::Str))
|
||||
.unwrap();
|
||||
let columns = &column_map
|
||||
.get(&("required_col".to_string(), ColumnTypeCategory::Str))
|
||||
.unwrap()
|
||||
.columns;
|
||||
assert_eq!(columns.len(), 2);
|
||||
assert!(columns[0].is_none());
|
||||
assert!(columns[1].is_none());
|
||||
@@ -96,35 +103,42 @@ fn test_group_columns_required_column_with_no_existing_columns() {
|
||||
fn test_group_columns_required_column_is_above_all_columns_have_the_same_type_rule() {
|
||||
let columnar1 = make_columnar("numbers", &[2i64]);
|
||||
let columnar2 = make_columnar("numbers", &[2i64]);
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(
|
||||
&[&columnar1, &columnar2],
|
||||
columnars,
|
||||
&[("numbers".to_string(), ColumnType::U64)],
|
||||
&merge_order,
|
||||
)
|
||||
.unwrap();
|
||||
assert_eq!(column_map.len(), 1);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::U64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_missing_column() {
|
||||
let columnar1 = make_columnar("numbers", &[-1i64]);
|
||||
let columnar2 = make_columnar("numbers2", &[2u64]);
|
||||
let column_map: BTreeMap<(String, ColumnType), Vec<Option<DynamicColumn>>> =
|
||||
group_columns_for_merge(&[&columnar1, &columnar2], &[]).unwrap();
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let merge_order = StackMergeOrder::stack(columnars).into();
|
||||
let column_map: BTreeMap<(String, ColumnTypeCategory), GroupedColumnsHandle> =
|
||||
group_columns_for_merge(columnars, &[], &merge_order).unwrap();
|
||||
assert_eq!(column_map.len(), 2);
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnType::I64)));
|
||||
assert!(column_map.contains_key(&("numbers".to_string(), ColumnTypeCategory::Numerical)));
|
||||
{
|
||||
let columns = column_map
|
||||
.get(&("numbers".to_string(), ColumnType::I64))
|
||||
.unwrap();
|
||||
let columns = &column_map
|
||||
.get(&("numbers".to_string(), ColumnTypeCategory::Numerical))
|
||||
.unwrap()
|
||||
.columns;
|
||||
assert!(columns[0].is_some());
|
||||
assert!(columns[1].is_none());
|
||||
}
|
||||
{
|
||||
let columns = column_map
|
||||
.get(&("numbers2".to_string(), ColumnType::U64))
|
||||
.unwrap();
|
||||
let columns = &column_map
|
||||
.get(&("numbers2".to_string(), ColumnTypeCategory::Numerical))
|
||||
.unwrap()
|
||||
.columns;
|
||||
assert!(columns[0].is_none());
|
||||
assert!(columns[1].is_some());
|
||||
}
|
||||
@@ -153,20 +167,24 @@ fn make_numerical_columnar_multiple_columns(
|
||||
ColumnarReader::open(buffer).unwrap()
|
||||
}
|
||||
|
||||
fn make_byte_columnar_multiple_columns(columns: &[(&str, &[&[&[u8]]])]) -> ColumnarReader {
|
||||
#[track_caller]
|
||||
fn make_byte_columnar_multiple_columns(
|
||||
columns: &[(&str, &[&[&[u8]]])],
|
||||
num_rows: u32,
|
||||
) -> ColumnarReader {
|
||||
let mut dataframe_writer = ColumnarWriter::default();
|
||||
for (column_name, column_values) in columns {
|
||||
assert_eq!(
|
||||
column_values.len(),
|
||||
num_rows as usize,
|
||||
"All columns must have `{num_rows}` rows"
|
||||
);
|
||||
for (row_id, vals) in column_values.iter().enumerate() {
|
||||
for val in vals.iter() {
|
||||
dataframe_writer.record_bytes(row_id as u32, column_name, val);
|
||||
}
|
||||
}
|
||||
}
|
||||
let num_rows = columns
|
||||
.iter()
|
||||
.map(|(_, val_rows)| val_rows.len() as RowId)
|
||||
.max()
|
||||
.unwrap_or(0u32);
|
||||
let mut buffer: Vec<u8> = Vec::new();
|
||||
dataframe_writer
|
||||
.serialize(num_rows, None, &mut buffer)
|
||||
@@ -218,7 +236,9 @@ fn test_merge_columnar_numbers() {
|
||||
assert_eq!(columnar_reader.num_columns(), 1);
|
||||
let cols = columnar_reader.read_columns("numbers").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::F64(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::F64(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.get_cardinality(), Cardinality::Optional);
|
||||
assert_eq!(vals.first(0u32), Some(-1f64));
|
||||
assert_eq!(vals.first(1u32), None);
|
||||
@@ -244,7 +264,11 @@ fn test_merge_columnar_texts() {
|
||||
assert_eq!(columnar_reader.num_columns(), 1);
|
||||
let cols = columnar_reader.read_columns("texts").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::Str(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::Str(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.ords().get_cardinality(), Cardinality::Optional);
|
||||
|
||||
let get_str_for_ord = |ord| {
|
||||
let mut out = String::new();
|
||||
vals.ord_to_str(ord, &mut out).unwrap();
|
||||
@@ -272,8 +296,8 @@ fn test_merge_columnar_texts() {
|
||||
|
||||
#[test]
|
||||
fn test_merge_columnar_byte() {
|
||||
let columnar1 = make_byte_columnar_multiple_columns(&[("bytes", &[&[b"bbbb"], &[b"baaa"]])]);
|
||||
let columnar2 = make_byte_columnar_multiple_columns(&[("bytes", &[&[], &[b"a"]])]);
|
||||
let columnar1 = make_byte_columnar_multiple_columns(&[("bytes", &[&[b"bbbb"], &[b"baaa"]])], 2);
|
||||
let columnar2 = make_byte_columnar_multiple_columns(&[("bytes", &[&[], &[b"a"]])], 2);
|
||||
let mut buffer = Vec::new();
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let stack_merge_order = StackMergeOrder::stack(columnars);
|
||||
@@ -289,7 +313,9 @@ fn test_merge_columnar_byte() {
|
||||
assert_eq!(columnar_reader.num_columns(), 1);
|
||||
let cols = columnar_reader.read_columns("bytes").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else { panic!() };
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
let get_bytes_for_ord = |ord| {
|
||||
let mut out = Vec::new();
|
||||
vals.ord_to_bytes(ord, &mut out).unwrap();
|
||||
@@ -316,3 +342,155 @@ fn test_merge_columnar_byte() {
|
||||
assert_eq!(get_bytes_for_row(2), b"");
|
||||
assert_eq!(get_bytes_for_row(3), b"a");
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_merge_columnar_byte_with_missing() {
|
||||
let columnar1 = make_byte_columnar_multiple_columns(&[], 3);
|
||||
let columnar2 = make_byte_columnar_multiple_columns(&[("col", &[&[b"b"], &[]])], 2);
|
||||
let columnar3 = make_byte_columnar_multiple_columns(
|
||||
&[
|
||||
("col", &[&[], &[b"b"], &[b"a", b"b"]]),
|
||||
("col2", &[&[b"hello"], &[], &[b"a", b"b"]]),
|
||||
],
|
||||
3,
|
||||
);
|
||||
let mut buffer = Vec::new();
|
||||
let columnars = &[&columnar1, &columnar2, &columnar3];
|
||||
let stack_merge_order = StackMergeOrder::stack(columnars);
|
||||
crate::columnar::merge_columnar(
|
||||
columnars,
|
||||
&[],
|
||||
MergeRowOrder::Stack(stack_merge_order),
|
||||
&mut buffer,
|
||||
)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_rows(), 3 + 2 + 3);
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let cols = columnar_reader.read_columns("col").unwrap();
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::Bytes(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
let get_bytes_for_ord = |ord| {
|
||||
let mut out = Vec::new();
|
||||
vals.ord_to_bytes(ord, &mut out).unwrap();
|
||||
out
|
||||
};
|
||||
assert_eq!(vals.dictionary.num_terms(), 2);
|
||||
assert_eq!(get_bytes_for_ord(0), b"a");
|
||||
assert_eq!(get_bytes_for_ord(1), b"b");
|
||||
let get_bytes_for_row = |row_id| {
|
||||
let terms: Vec<Vec<u8>> = vals
|
||||
.term_ords(row_id)
|
||||
.map(|term_ord| {
|
||||
let mut out = Vec::new();
|
||||
vals.ord_to_bytes(term_ord, &mut out).unwrap();
|
||||
out
|
||||
})
|
||||
.collect();
|
||||
terms
|
||||
};
|
||||
assert!(get_bytes_for_row(0).is_empty());
|
||||
assert!(get_bytes_for_row(1).is_empty());
|
||||
assert!(get_bytes_for_row(2).is_empty());
|
||||
assert_eq!(get_bytes_for_row(3), vec![b"b".to_vec()]);
|
||||
assert!(get_bytes_for_row(4).is_empty());
|
||||
assert!(get_bytes_for_row(5).is_empty());
|
||||
assert_eq!(get_bytes_for_row(6), vec![b"b".to_vec()]);
|
||||
assert_eq!(get_bytes_for_row(7), vec![b"a".to_vec(), b"b".to_vec()]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_merge_columnar_different_types() {
|
||||
let columnar1 = make_text_columnar_multiple_columns(&[("mixed", &[&["a"]])]);
|
||||
let columnar2 = make_text_columnar_multiple_columns(&[("mixed", &[&[], &["b"]])]);
|
||||
let columnar3 = make_columnar("mixed", &[1i64]);
|
||||
let mut buffer = Vec::new();
|
||||
let columnars = &[&columnar1, &columnar2, &columnar3];
|
||||
let stack_merge_order = StackMergeOrder::stack(columnars);
|
||||
crate::columnar::merge_columnar(
|
||||
columnars,
|
||||
&[],
|
||||
MergeRowOrder::Stack(stack_merge_order),
|
||||
&mut buffer,
|
||||
)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_rows(), 4);
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let cols = columnar_reader.read_columns("mixed").unwrap();
|
||||
|
||||
// numeric column
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
let DynamicColumn::I64(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.get_cardinality(), Cardinality::Optional);
|
||||
assert_eq!(vals.values_for_doc(0).collect_vec(), vec![]);
|
||||
assert_eq!(vals.values_for_doc(1).collect_vec(), vec![]);
|
||||
assert_eq!(vals.values_for_doc(2).collect_vec(), vec![]);
|
||||
assert_eq!(vals.values_for_doc(3).collect_vec(), vec![1]);
|
||||
assert_eq!(vals.values_for_doc(4).collect_vec(), vec![]);
|
||||
|
||||
// text column
|
||||
let dynamic_column = cols[1].open().unwrap();
|
||||
let DynamicColumn::Str(vals) = dynamic_column else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(vals.ords().get_cardinality(), Cardinality::Optional);
|
||||
let get_str_for_ord = |ord| {
|
||||
let mut out = String::new();
|
||||
vals.ord_to_str(ord, &mut out).unwrap();
|
||||
out
|
||||
};
|
||||
|
||||
assert_eq!(vals.dictionary.num_terms(), 2);
|
||||
assert_eq!(get_str_for_ord(0), "a");
|
||||
assert_eq!(get_str_for_ord(1), "b");
|
||||
|
||||
let get_str_for_row = |row_id| {
|
||||
let term_ords: Vec<String> = vals
|
||||
.term_ords(row_id)
|
||||
.map(|el| {
|
||||
let mut out = String::new();
|
||||
vals.ord_to_str(el, &mut out).unwrap();
|
||||
out
|
||||
})
|
||||
.collect();
|
||||
term_ords
|
||||
};
|
||||
|
||||
assert_eq!(get_str_for_row(0), vec!["a".to_string()]);
|
||||
assert_eq!(get_str_for_row(1), Vec::<String>::new());
|
||||
assert_eq!(get_str_for_row(2), vec!["b".to_string()]);
|
||||
assert_eq!(get_str_for_row(3), Vec::<String>::new());
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_merge_columnar_different_empty_cardinality() {
|
||||
let columnar1 = make_text_columnar_multiple_columns(&[("mixed", &[&["a"]])]);
|
||||
let columnar2 = make_columnar("mixed", &[1i64]);
|
||||
let mut buffer = Vec::new();
|
||||
let columnars = &[&columnar1, &columnar2];
|
||||
let stack_merge_order = StackMergeOrder::stack(columnars);
|
||||
crate::columnar::merge_columnar(
|
||||
columnars,
|
||||
&[],
|
||||
MergeRowOrder::Stack(stack_merge_order),
|
||||
&mut buffer,
|
||||
)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
assert_eq!(columnar_reader.num_rows(), 2);
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let cols = columnar_reader.read_columns("mixed").unwrap();
|
||||
|
||||
// numeric column
|
||||
let dynamic_column = cols[0].open().unwrap();
|
||||
assert_eq!(dynamic_column.get_cardinality(), Cardinality::Optional);
|
||||
|
||||
// text column
|
||||
let dynamic_column = cols[1].open().unwrap();
|
||||
assert_eq!(dynamic_column.get_cardinality(), Cardinality::Optional);
|
||||
}
|
||||
|
||||
@@ -5,6 +5,8 @@ mod reader;
|
||||
mod writer;
|
||||
|
||||
pub use column_type::{ColumnType, HasAssociatedColumnType};
|
||||
#[cfg(test)]
|
||||
pub(crate) use merge::ColumnTypeCategory;
|
||||
pub use merge::{merge_columnar, MergeRowOrder, ShuffleMergeOrder, StackMergeOrder};
|
||||
pub use reader::ColumnarReader;
|
||||
pub use writer::ColumnarWriter;
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
use std::{io, mem};
|
||||
use std::{fmt, io, mem};
|
||||
|
||||
use common::file_slice::FileSlice;
|
||||
use common::BinarySerializable;
|
||||
@@ -21,6 +21,32 @@ pub struct ColumnarReader {
|
||||
num_rows: RowId,
|
||||
}
|
||||
|
||||
impl fmt::Debug for ColumnarReader {
|
||||
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
|
||||
let num_rows = self.num_rows();
|
||||
let columns = self.list_columns().unwrap();
|
||||
let num_cols = columns.len();
|
||||
let mut debug_struct = f.debug_struct("Columnar");
|
||||
debug_struct
|
||||
.field("num_rows", &num_rows)
|
||||
.field("num_cols", &num_cols);
|
||||
for (col_name, dynamic_column_handle) in columns.into_iter().take(5) {
|
||||
let col = dynamic_column_handle.open().unwrap();
|
||||
if col.num_values() > 10 {
|
||||
debug_struct.field(&col_name, &"..");
|
||||
} else {
|
||||
debug_struct.field(&col_name, &col);
|
||||
}
|
||||
}
|
||||
if num_cols > 5 {
|
||||
debug_struct.finish_non_exhaustive()?;
|
||||
} else {
|
||||
debug_struct.finish()?;
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
/// Functions by both the async/sync code listing columns.
|
||||
/// It takes a stream from the column sstable and return the list of
|
||||
/// `DynamicColumn` available in it.
|
||||
@@ -76,30 +102,41 @@ impl ColumnarReader {
|
||||
pub fn num_rows(&self) -> RowId {
|
||||
self.num_rows
|
||||
}
|
||||
// Iterate over the columns in a sorted way
|
||||
pub fn iter_columns(
|
||||
&self,
|
||||
) -> io::Result<impl Iterator<Item = (String, DynamicColumnHandle)> + '_> {
|
||||
let mut stream = self.column_dictionary.stream()?;
|
||||
Ok(std::iter::from_fn(move || {
|
||||
if stream.advance() {
|
||||
let key_bytes: &[u8] = stream.key();
|
||||
let column_code: u8 = key_bytes.last().cloned().unwrap();
|
||||
// TODO Error Handling. The API gets quite ugly when returning the error here, so
|
||||
// instead we could just check the first N columns upfront.
|
||||
let column_type: ColumnType = ColumnType::try_from_code(column_code)
|
||||
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))
|
||||
.unwrap();
|
||||
let range = stream.value().clone();
|
||||
let column_name =
|
||||
// The last two bytes are respectively the 0u8 separator and the column_type.
|
||||
String::from_utf8_lossy(&key_bytes[..key_bytes.len() - 2]).to_string();
|
||||
let file_slice = self
|
||||
.column_data
|
||||
.slice(range.start as usize..range.end as usize);
|
||||
let column_handle = DynamicColumnHandle {
|
||||
file_slice,
|
||||
column_type,
|
||||
};
|
||||
Some((column_name, column_handle))
|
||||
} else {
|
||||
None
|
||||
}
|
||||
}))
|
||||
}
|
||||
|
||||
// TODO Add unit tests
|
||||
pub fn list_columns(&self) -> io::Result<Vec<(String, DynamicColumnHandle)>> {
|
||||
let mut stream = self.column_dictionary.stream()?;
|
||||
let mut results = Vec::new();
|
||||
while stream.advance() {
|
||||
let key_bytes: &[u8] = stream.key();
|
||||
let column_code: u8 = key_bytes.last().cloned().unwrap();
|
||||
let column_type: ColumnType = ColumnType::try_from_code(column_code)
|
||||
.map_err(|_| io_invalid_data(format!("Unknown column code `{column_code}`")))?;
|
||||
let range = stream.value().clone();
|
||||
let column_name =
|
||||
// The last two bytes are respectively the 0u8 separator and the column_type.
|
||||
String::from_utf8_lossy(&key_bytes[..key_bytes.len() - 2]).to_string();
|
||||
let file_slice = self
|
||||
.column_data
|
||||
.slice(range.start as usize..range.end as usize);
|
||||
let column_handle = DynamicColumnHandle {
|
||||
file_slice,
|
||||
column_type,
|
||||
};
|
||||
results.push((column_name, column_handle));
|
||||
}
|
||||
Ok(results)
|
||||
Ok(self.iter_columns()?.collect())
|
||||
}
|
||||
|
||||
fn stream_for_column_range(&self, column_name: &str) -> sstable::StreamerBuilder<RangeSSTable> {
|
||||
|
||||
@@ -79,7 +79,6 @@ fn mutate_or_create_column<V, TMutator>(
|
||||
|
||||
impl ColumnarWriter {
|
||||
pub fn mem_usage(&self) -> usize {
|
||||
// TODO add dictionary builders.
|
||||
self.arena.mem_usage()
|
||||
+ self.numerical_field_hash_map.mem_usage()
|
||||
+ self.bool_field_hash_map.mem_usage()
|
||||
@@ -87,6 +86,11 @@ impl ColumnarWriter {
|
||||
+ self.str_field_hash_map.mem_usage()
|
||||
+ self.ip_addr_field_hash_map.mem_usage()
|
||||
+ self.datetime_field_hash_map.mem_usage()
|
||||
+ self
|
||||
.dictionaries
|
||||
.iter()
|
||||
.map(|dict| dict.mem_usage())
|
||||
.sum::<usize>()
|
||||
}
|
||||
|
||||
/// Returns the list of doc ids from 0..num_docs sorted by the `sort_field`
|
||||
@@ -98,22 +102,37 @@ impl ColumnarWriter {
|
||||
///
|
||||
/// The sort applied is stable.
|
||||
pub fn sort_order(&self, sort_field: &str, num_docs: RowId, reversed: bool) -> Vec<u32> {
|
||||
let Some(numerical_col_writer) =
|
||||
self.numerical_field_hash_map.get::<NumericalColumnWriter>(sort_field.as_bytes()) else {
|
||||
return Vec::new();
|
||||
let Some(numerical_col_writer) = self
|
||||
.numerical_field_hash_map
|
||||
.get::<NumericalColumnWriter>(sort_field.as_bytes())
|
||||
.or_else(|| {
|
||||
self.datetime_field_hash_map
|
||||
.get::<NumericalColumnWriter>(sort_field.as_bytes())
|
||||
})
|
||||
else {
|
||||
return Vec::new();
|
||||
};
|
||||
let mut symbols_buffer = Vec::new();
|
||||
let mut values = Vec::new();
|
||||
let mut last_doc_opt: Option<RowId> = None;
|
||||
let mut start_doc_check_fill = 0;
|
||||
let mut current_doc_opt: Option<RowId> = None;
|
||||
// Assumption: NewDoc will never call the same doc twice and is strictly increasing between
|
||||
// calls
|
||||
for op in numerical_col_writer.operation_iterator(&self.arena, None, &mut symbols_buffer) {
|
||||
match op {
|
||||
ColumnOperation::NewDoc(doc) => {
|
||||
last_doc_opt = Some(doc);
|
||||
current_doc_opt = Some(doc);
|
||||
}
|
||||
ColumnOperation::Value(numerical_value) => {
|
||||
if let Some(last_doc) = last_doc_opt {
|
||||
if let Some(current_doc) = current_doc_opt {
|
||||
// Fill up with 0.0 since last doc
|
||||
values.extend((start_doc_check_fill..current_doc).map(|doc| (0.0, doc)));
|
||||
start_doc_check_fill = current_doc + 1;
|
||||
// handle multi values
|
||||
current_doc_opt = None;
|
||||
|
||||
let score: f32 = f64::coerce(numerical_value) as f32;
|
||||
values.push((score, last_doc));
|
||||
values.push((score, current_doc));
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -123,9 +142,9 @@ impl ColumnarWriter {
|
||||
}
|
||||
values.sort_by(|(left_score, _), (right_score, _)| {
|
||||
if reversed {
|
||||
right_score.partial_cmp(left_score).unwrap()
|
||||
right_score.total_cmp(left_score)
|
||||
} else {
|
||||
left_score.partial_cmp(right_score).unwrap()
|
||||
left_score.total_cmp(right_score)
|
||||
}
|
||||
});
|
||||
values.into_iter().map(|(_score, doc)| doc).collect()
|
||||
@@ -257,7 +276,7 @@ impl ColumnarWriter {
|
||||
let mut column: ColumnWriter = column_opt.unwrap_or_default();
|
||||
column.record(
|
||||
doc,
|
||||
NumericalValue::I64(datetime.into_timestamp_micros()),
|
||||
NumericalValue::I64(datetime.into_timestamp_nanos()),
|
||||
arena,
|
||||
);
|
||||
column
|
||||
@@ -361,7 +380,7 @@ impl ColumnarWriter {
|
||||
let column_writer: ColumnWriter = self.bool_field_hash_map.read(addr);
|
||||
let cardinality = column_writer.get_cardinality(num_docs);
|
||||
let mut column_serializer =
|
||||
serializer.serialize_column(column_name, column_type);
|
||||
serializer.start_serialize_column(column_name, column_type);
|
||||
serialize_bool_column(
|
||||
cardinality,
|
||||
num_docs,
|
||||
@@ -373,12 +392,13 @@ impl ColumnarWriter {
|
||||
buffers,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
column_serializer.finalize()?;
|
||||
}
|
||||
ColumnType::IpAddr => {
|
||||
let column_writer: ColumnWriter = self.ip_addr_field_hash_map.read(addr);
|
||||
let cardinality = column_writer.get_cardinality(num_docs);
|
||||
let mut column_serializer =
|
||||
serializer.serialize_column(column_name, ColumnType::IpAddr);
|
||||
serializer.start_serialize_column(column_name, ColumnType::IpAddr);
|
||||
serialize_ip_addr_column(
|
||||
cardinality,
|
||||
num_docs,
|
||||
@@ -390,6 +410,7 @@ impl ColumnarWriter {
|
||||
buffers,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
column_serializer.finalize()?;
|
||||
}
|
||||
ColumnType::Bytes | ColumnType::Str => {
|
||||
let str_or_bytes_column_writer: StrOrBytesColumnWriter =
|
||||
@@ -404,7 +425,7 @@ impl ColumnarWriter {
|
||||
.column_writer
|
||||
.get_cardinality(num_docs);
|
||||
let mut column_serializer =
|
||||
serializer.serialize_column(column_name, column_type);
|
||||
serializer.start_serialize_column(column_name, column_type);
|
||||
serialize_bytes_or_str_column(
|
||||
cardinality,
|
||||
num_docs,
|
||||
@@ -418,13 +439,14 @@ impl ColumnarWriter {
|
||||
buffers,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
column_serializer.finalize()?;
|
||||
}
|
||||
ColumnType::F64 | ColumnType::I64 | ColumnType::U64 => {
|
||||
let numerical_column_writer: NumericalColumnWriter =
|
||||
self.numerical_field_hash_map.read(addr);
|
||||
let cardinality = numerical_column_writer.cardinality(num_docs);
|
||||
let mut column_serializer =
|
||||
serializer.serialize_column(column_name, column_type);
|
||||
serializer.start_serialize_column(column_name, column_type);
|
||||
let numerical_type = column_type.numerical_type().unwrap();
|
||||
serialize_numerical_column(
|
||||
cardinality,
|
||||
@@ -438,12 +460,13 @@ impl ColumnarWriter {
|
||||
buffers,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
column_serializer.finalize()?;
|
||||
}
|
||||
ColumnType::DateTime => {
|
||||
let column_writer: ColumnWriter = self.datetime_field_hash_map.read(addr);
|
||||
let cardinality = column_writer.get_cardinality(num_docs);
|
||||
let mut column_serializer =
|
||||
serializer.serialize_column(column_name, ColumnType::DateTime);
|
||||
serializer.start_serialize_column(column_name, ColumnType::DateTime);
|
||||
serialize_numerical_column(
|
||||
cardinality,
|
||||
num_docs,
|
||||
@@ -456,6 +479,7 @@ impl ColumnarWriter {
|
||||
buffers,
|
||||
&mut column_serializer,
|
||||
)?;
|
||||
column_serializer.finalize()?;
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
@@ -34,11 +34,12 @@ impl<W: io::Write> ColumnarSerializer<W> {
|
||||
}
|
||||
}
|
||||
|
||||
pub fn serialize_column<'a>(
|
||||
/// Creates a ColumnSerializer.
|
||||
pub fn start_serialize_column<'a>(
|
||||
&'a mut self,
|
||||
column_name: &[u8],
|
||||
column_type: ColumnType,
|
||||
) -> impl io::Write + 'a {
|
||||
) -> ColumnSerializer<'a, W> {
|
||||
let start_offset = self.wrt.written_bytes();
|
||||
prepare_key(column_name, column_type, &mut self.prepare_key_buffer);
|
||||
ColumnSerializer {
|
||||
@@ -60,20 +61,21 @@ impl<W: io::Write> ColumnarSerializer<W> {
|
||||
}
|
||||
}
|
||||
|
||||
struct ColumnSerializer<'a, W: io::Write> {
|
||||
pub struct ColumnSerializer<'a, W: io::Write> {
|
||||
columnar_serializer: &'a mut ColumnarSerializer<W>,
|
||||
start_offset: u64,
|
||||
}
|
||||
|
||||
impl<'a, W: io::Write> Drop for ColumnSerializer<'a, W> {
|
||||
fn drop(&mut self) {
|
||||
impl<'a, W: io::Write> ColumnSerializer<'a, W> {
|
||||
pub fn finalize(self) -> io::Result<()> {
|
||||
let end_offset: u64 = self.columnar_serializer.wrt.written_bytes();
|
||||
let byte_range = self.start_offset..end_offset;
|
||||
self.columnar_serializer.sstable_range.insert_cannot_fail(
|
||||
self.columnar_serializer.sstable_range.insert(
|
||||
&self.columnar_serializer.prepare_key_buffer[..],
|
||||
&byte_range,
|
||||
);
|
||||
)?;
|
||||
self.columnar_serializer.prepare_key_buffer.clear();
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -32,6 +32,7 @@ pub struct OrderedId(pub u32);
|
||||
#[derive(Default)]
|
||||
pub(crate) struct DictionaryBuilder {
|
||||
dict: FnvHashMap<Vec<u8>, UnorderedId>,
|
||||
memory_consumption: usize,
|
||||
}
|
||||
|
||||
impl DictionaryBuilder {
|
||||
@@ -43,6 +44,8 @@ impl DictionaryBuilder {
|
||||
}
|
||||
let new_id = UnorderedId(self.dict.len() as u32);
|
||||
self.dict.insert(term.to_vec(), new_id);
|
||||
self.memory_consumption += term.len();
|
||||
self.memory_consumption += 40; // Term Metadata + HashMap overhead
|
||||
new_id
|
||||
}
|
||||
|
||||
@@ -63,6 +66,10 @@ impl DictionaryBuilder {
|
||||
sstable_builder.finish()?;
|
||||
Ok(TermIdMapping { unordered_to_ord })
|
||||
}
|
||||
|
||||
pub(crate) fn mem_usage(&self) -> usize {
|
||||
self.memory_consumption
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
|
||||
@@ -1,14 +1,14 @@
|
||||
use std::io;
|
||||
use std::net::Ipv6Addr;
|
||||
use std::sync::Arc;
|
||||
use std::{fmt, io};
|
||||
|
||||
use common::file_slice::FileSlice;
|
||||
use common::{DateTime, HasLen, OwnedBytes};
|
||||
use common::{ByteCount, DateTime, HasLen, OwnedBytes};
|
||||
|
||||
use crate::column::{BytesColumn, Column, StrColumn};
|
||||
use crate::column_values::{monotonic_map_column, StrictlyMonotonicFn};
|
||||
use crate::columnar::ColumnType;
|
||||
use crate::{Cardinality, NumericalType};
|
||||
use crate::{Cardinality, ColumnIndex, NumericalType};
|
||||
|
||||
#[derive(Clone)]
|
||||
pub enum DynamicColumn {
|
||||
@@ -22,19 +22,54 @@ pub enum DynamicColumn {
|
||||
Str(StrColumn),
|
||||
}
|
||||
|
||||
impl DynamicColumn {
|
||||
pub fn get_cardinality(&self) -> Cardinality {
|
||||
impl fmt::Debug for DynamicColumn {
|
||||
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
||||
write!(f, "[{} {} |", self.get_cardinality(), self.column_type())?;
|
||||
match self {
|
||||
DynamicColumn::Bool(c) => c.get_cardinality(),
|
||||
DynamicColumn::I64(c) => c.get_cardinality(),
|
||||
DynamicColumn::U64(c) => c.get_cardinality(),
|
||||
DynamicColumn::F64(c) => c.get_cardinality(),
|
||||
DynamicColumn::IpAddr(c) => c.get_cardinality(),
|
||||
DynamicColumn::DateTime(c) => c.get_cardinality(),
|
||||
DynamicColumn::Bytes(c) => c.ords().get_cardinality(),
|
||||
DynamicColumn::Str(c) => c.ords().get_cardinality(),
|
||||
DynamicColumn::Bool(col) => write!(f, " {col:?}")?,
|
||||
DynamicColumn::I64(col) => write!(f, " {col:?}")?,
|
||||
DynamicColumn::U64(col) => write!(f, " {col:?}")?,
|
||||
DynamicColumn::F64(col) => write!(f, "{col:?}")?,
|
||||
DynamicColumn::IpAddr(col) => write!(f, "{col:?}")?,
|
||||
DynamicColumn::DateTime(col) => write!(f, "{col:?}")?,
|
||||
DynamicColumn::Bytes(col) => write!(f, "{col:?}")?,
|
||||
DynamicColumn::Str(col) => write!(f, "{col:?}")?,
|
||||
}
|
||||
write!(f, "]")
|
||||
}
|
||||
}
|
||||
|
||||
impl DynamicColumn {
|
||||
pub fn column_index(&self) -> &ColumnIndex {
|
||||
match self {
|
||||
DynamicColumn::Bool(c) => &c.index,
|
||||
DynamicColumn::I64(c) => &c.index,
|
||||
DynamicColumn::U64(c) => &c.index,
|
||||
DynamicColumn::F64(c) => &c.index,
|
||||
DynamicColumn::IpAddr(c) => &c.index,
|
||||
DynamicColumn::DateTime(c) => &c.index,
|
||||
DynamicColumn::Bytes(c) => &c.ords().index,
|
||||
DynamicColumn::Str(c) => &c.ords().index,
|
||||
}
|
||||
}
|
||||
|
||||
pub fn get_cardinality(&self) -> Cardinality {
|
||||
self.column_index().get_cardinality()
|
||||
}
|
||||
|
||||
pub fn num_values(&self) -> u32 {
|
||||
match self {
|
||||
DynamicColumn::Bool(c) => c.values.num_vals(),
|
||||
DynamicColumn::I64(c) => c.values.num_vals(),
|
||||
DynamicColumn::U64(c) => c.values.num_vals(),
|
||||
DynamicColumn::F64(c) => c.values.num_vals(),
|
||||
DynamicColumn::IpAddr(c) => c.values.num_vals(),
|
||||
DynamicColumn::DateTime(c) => c.values.num_vals(),
|
||||
DynamicColumn::Bytes(c) => c.ords().values.num_vals(),
|
||||
DynamicColumn::Str(c) => c.ords().values.num_vals(),
|
||||
}
|
||||
}
|
||||
|
||||
pub fn column_type(&self) -> ColumnType {
|
||||
match self {
|
||||
DynamicColumn::Bool(_) => ColumnType::Bool,
|
||||
@@ -73,11 +108,11 @@ impl DynamicColumn {
|
||||
fn coerce_to_f64(self) -> Option<DynamicColumn> {
|
||||
match self {
|
||||
DynamicColumn::I64(column) => Some(DynamicColumn::F64(Column {
|
||||
idx: column.idx,
|
||||
index: column.index,
|
||||
values: Arc::new(monotonic_map_column(column.values, MapI64ToF64)),
|
||||
})),
|
||||
DynamicColumn::U64(column) => Some(DynamicColumn::F64(Column {
|
||||
idx: column.idx,
|
||||
index: column.index,
|
||||
values: Arc::new(monotonic_map_column(column.values, MapU64ToF64)),
|
||||
})),
|
||||
DynamicColumn::F64(_) => Some(self),
|
||||
@@ -91,7 +126,7 @@ impl DynamicColumn {
|
||||
return None;
|
||||
}
|
||||
Some(DynamicColumn::I64(Column {
|
||||
idx: column.idx,
|
||||
index: column.index,
|
||||
values: Arc::new(monotonic_map_column(column.values, MapU64ToI64)),
|
||||
}))
|
||||
}
|
||||
@@ -106,7 +141,7 @@ impl DynamicColumn {
|
||||
return None;
|
||||
}
|
||||
Some(DynamicColumn::U64(Column {
|
||||
idx: column.idx,
|
||||
index: column.index,
|
||||
values: Arc::new(monotonic_map_column(column.values, MapI64ToU64)),
|
||||
}))
|
||||
}
|
||||
@@ -193,7 +228,7 @@ static_dynamic_conversions!(StrColumn, Str);
|
||||
static_dynamic_conversions!(BytesColumn, Bytes);
|
||||
static_dynamic_conversions!(Column<Ipv6Addr>, IpAddr);
|
||||
|
||||
#[derive(Clone)]
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct DynamicColumnHandle {
|
||||
pub(crate) file_slice: FileSlice,
|
||||
pub(crate) column_type: ColumnType,
|
||||
@@ -212,7 +247,7 @@ impl DynamicColumnHandle {
|
||||
}
|
||||
|
||||
/// Returns the `u64` fast field reader reader associated with `fields` of types
|
||||
/// Str, u64, i64, f64, or datetime.
|
||||
/// Str, u64, i64, f64, bool, or datetime.
|
||||
///
|
||||
/// If not, the fastfield reader will returns the u64-value associated with the original
|
||||
/// FastValue.
|
||||
@@ -223,9 +258,12 @@ impl DynamicColumnHandle {
|
||||
let column: BytesColumn = crate::column::open_column_bytes(column_bytes)?;
|
||||
Ok(Some(column.term_ord_column))
|
||||
}
|
||||
ColumnType::Bool => Ok(None),
|
||||
ColumnType::IpAddr => Ok(None),
|
||||
ColumnType::I64 | ColumnType::U64 | ColumnType::F64 | ColumnType::DateTime => {
|
||||
ColumnType::Bool
|
||||
| ColumnType::I64
|
||||
| ColumnType::U64
|
||||
| ColumnType::F64
|
||||
| ColumnType::DateTime => {
|
||||
let column = crate::column::open_column_u64::<u64>(column_bytes)?;
|
||||
Ok(Some(column))
|
||||
}
|
||||
@@ -248,8 +286,8 @@ impl DynamicColumnHandle {
|
||||
Ok(dynamic_column)
|
||||
}
|
||||
|
||||
pub fn num_bytes(&self) -> usize {
|
||||
self.file_slice.len()
|
||||
pub fn num_bytes(&self) -> ByteCount {
|
||||
self.file_slice.len().into()
|
||||
}
|
||||
|
||||
pub fn column_type(&self) -> ColumnType {
|
||||
|
||||
@@ -7,8 +7,10 @@ extern crate more_asserts;
|
||||
#[cfg(all(test, feature = "unstable"))]
|
||||
extern crate test;
|
||||
|
||||
use std::fmt::Display;
|
||||
use std::io;
|
||||
|
||||
mod block_accessor;
|
||||
mod column;
|
||||
mod column_index;
|
||||
pub mod column_values;
|
||||
@@ -19,9 +21,12 @@ mod iterable;
|
||||
pub(crate) mod utils;
|
||||
mod value;
|
||||
|
||||
pub use block_accessor::ColumnBlockAccessor;
|
||||
pub use column::{BytesColumn, Column, StrColumn};
|
||||
pub use column_index::ColumnIndex;
|
||||
pub use column_values::{ColumnValues, MonotonicallyMappableToU128, MonotonicallyMappableToU64};
|
||||
pub use column_values::{
|
||||
ColumnValues, EmptyColumnValues, MonotonicallyMappableToU128, MonotonicallyMappableToU64,
|
||||
};
|
||||
pub use columnar::{
|
||||
merge_columnar, ColumnType, ColumnarReader, ColumnarWriter, HasAssociatedColumnType,
|
||||
MergeRowOrder, ShuffleMergeOrder, StackMergeOrder,
|
||||
@@ -34,7 +39,7 @@ pub use self::dynamic_column::{DynamicColumn, DynamicColumnHandle};
|
||||
pub type RowId = u32;
|
||||
pub type DocId = u32;
|
||||
|
||||
#[derive(Clone, Copy)]
|
||||
#[derive(Clone, Copy, Debug)]
|
||||
pub struct RowAddr {
|
||||
pub segment_ord: u32,
|
||||
pub row_id: RowId,
|
||||
@@ -71,6 +76,17 @@ pub enum Cardinality {
|
||||
Multivalued = 2,
|
||||
}
|
||||
|
||||
impl Display for Cardinality {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
|
||||
let short_str = match self {
|
||||
Cardinality::Full => "full",
|
||||
Cardinality::Optional => "opt",
|
||||
Cardinality::Multivalued => "mult",
|
||||
};
|
||||
write!(f, "{short_str}")
|
||||
}
|
||||
}
|
||||
|
||||
impl Cardinality {
|
||||
pub fn is_optional(&self) -> bool {
|
||||
matches!(self, Cardinality::Optional)
|
||||
@@ -81,7 +97,6 @@ impl Cardinality {
|
||||
pub(crate) fn to_code(self) -> u8 {
|
||||
self as u8
|
||||
}
|
||||
|
||||
pub(crate) fn try_from_code(code: u8) -> Result<Cardinality, InvalidData> {
|
||||
match code {
|
||||
0 => Ok(Cardinality::Full),
|
||||
|
||||
@@ -1,10 +1,19 @@
|
||||
use std::collections::HashMap;
|
||||
use std::fmt::Debug;
|
||||
use std::net::Ipv6Addr;
|
||||
|
||||
use common::DateTime;
|
||||
use proptest::prelude::*;
|
||||
use proptest::sample::subsequence;
|
||||
|
||||
use crate::column_values::MonotonicallyMappableToU128;
|
||||
use crate::columnar::ColumnType;
|
||||
use crate::columnar::{ColumnType, ColumnTypeCategory};
|
||||
use crate::dynamic_column::{DynamicColumn, DynamicColumnHandle};
|
||||
use crate::value::NumericalValue;
|
||||
use crate::{Cardinality, ColumnarReader, ColumnarWriter};
|
||||
use crate::value::{Coerce, NumericalValue};
|
||||
use crate::{
|
||||
BytesColumn, Cardinality, Column, ColumnarReader, ColumnarWriter, RowAddr, RowId,
|
||||
ShuffleMergeOrder, StackMergeOrder,
|
||||
};
|
||||
|
||||
#[test]
|
||||
fn test_dataframe_writer_str() {
|
||||
@@ -17,7 +26,7 @@ fn test_dataframe_writer_str() {
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
assert_eq!(cols[0].num_bytes(), 158);
|
||||
assert_eq!(cols[0].num_bytes(), 87);
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -31,7 +40,7 @@ fn test_dataframe_writer_bytes() {
|
||||
assert_eq!(columnar.num_columns(), 1);
|
||||
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
assert_eq!(cols[0].num_bytes(), 158);
|
||||
assert_eq!(cols[0].num_bytes(), 87);
|
||||
}
|
||||
|
||||
#[test]
|
||||
@@ -48,7 +57,9 @@ fn test_dataframe_writer_bool() {
|
||||
assert_eq!(cols[0].num_bytes(), 22);
|
||||
assert_eq!(cols[0].column_type(), ColumnType::Bool);
|
||||
let dyn_bool_col = cols[0].open().unwrap();
|
||||
let DynamicColumn::Bool(bool_col) = dyn_bool_col else { panic!(); };
|
||||
let DynamicColumn::Bool(bool_col) = dyn_bool_col else {
|
||||
panic!();
|
||||
};
|
||||
let vals: Vec<Option<bool>> = (0..5).map(|row_id| bool_col.first(row_id)).collect();
|
||||
assert_eq!(&vals, &[None, Some(false), None, Some(true), None,]);
|
||||
}
|
||||
@@ -70,7 +81,9 @@ fn test_dataframe_writer_u64_multivalued() {
|
||||
assert_eq!(cols.len(), 1);
|
||||
assert_eq!(cols[0].num_bytes(), 29);
|
||||
let dyn_i64_col = cols[0].open().unwrap();
|
||||
let DynamicColumn::I64(divisor_col) = dyn_i64_col else { panic!(); };
|
||||
let DynamicColumn::I64(divisor_col) = dyn_i64_col else {
|
||||
panic!();
|
||||
};
|
||||
assert_eq!(
|
||||
divisor_col.get_cardinality(),
|
||||
crate::Cardinality::Multivalued
|
||||
@@ -92,7 +105,9 @@ fn test_dataframe_writer_ip_addr() {
|
||||
assert_eq!(cols[0].num_bytes(), 42);
|
||||
assert_eq!(cols[0].column_type(), ColumnType::IpAddr);
|
||||
let dyn_bool_col = cols[0].open().unwrap();
|
||||
let DynamicColumn::IpAddr(ip_col) = dyn_bool_col else { panic!(); };
|
||||
let DynamicColumn::IpAddr(ip_col) = dyn_bool_col else {
|
||||
panic!();
|
||||
};
|
||||
let vals: Vec<Option<Ipv6Addr>> = (0..5).map(|row_id| ip_col.first(row_id)).collect();
|
||||
assert_eq!(
|
||||
&vals,
|
||||
@@ -125,8 +140,10 @@ fn test_dataframe_writer_numerical() {
|
||||
// - null footer 6 bytes
|
||||
assert_eq!(cols[0].num_bytes(), 33);
|
||||
let column = cols[0].open().unwrap();
|
||||
let DynamicColumn::I64(column_i64) = column else { panic!(); };
|
||||
assert_eq!(column_i64.idx.get_cardinality(), Cardinality::Optional);
|
||||
let DynamicColumn::I64(column_i64) = column else {
|
||||
panic!();
|
||||
};
|
||||
assert_eq!(column_i64.index.get_cardinality(), Cardinality::Optional);
|
||||
assert_eq!(column_i64.first(0), None);
|
||||
assert_eq!(column_i64.first(1), Some(12i64));
|
||||
assert_eq!(column_i64.first(2), Some(13i64));
|
||||
@@ -136,6 +153,46 @@ fn test_dataframe_writer_numerical() {
|
||||
assert_eq!(column_i64.first(6), None); //< we can change the spec for that one.
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_dataframe_sort_by_full() {
|
||||
let mut dataframe_writer = ColumnarWriter::default();
|
||||
dataframe_writer.record_numerical(0u32, "value", NumericalValue::U64(1));
|
||||
dataframe_writer.record_numerical(1u32, "value", NumericalValue::U64(2));
|
||||
let data = dataframe_writer.sort_order("value", 2, false);
|
||||
assert_eq!(data, vec![0, 1]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_dataframe_sort_by_opt() {
|
||||
let mut dataframe_writer = ColumnarWriter::default();
|
||||
dataframe_writer.record_numerical(1u32, "value", NumericalValue::U64(3));
|
||||
dataframe_writer.record_numerical(3u32, "value", NumericalValue::U64(2));
|
||||
let data = dataframe_writer.sort_order("value", 5, false);
|
||||
// 0, 2, 4 is 0.0
|
||||
assert_eq!(data, vec![0, 2, 4, 3, 1]);
|
||||
let data = dataframe_writer.sort_order("value", 5, true);
|
||||
assert_eq!(
|
||||
data,
|
||||
vec![4, 2, 0, 3, 1].into_iter().rev().collect::<Vec<_>>()
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_dataframe_sort_by_multi() {
|
||||
let mut dataframe_writer = ColumnarWriter::default();
|
||||
// valid for sort
|
||||
dataframe_writer.record_numerical(1u32, "value", NumericalValue::U64(2));
|
||||
// those are ignored for sort
|
||||
dataframe_writer.record_numerical(1u32, "value", NumericalValue::U64(4));
|
||||
dataframe_writer.record_numerical(1u32, "value", NumericalValue::U64(4));
|
||||
// valid for sort
|
||||
dataframe_writer.record_numerical(3u32, "value", NumericalValue::U64(3));
|
||||
// ignored, would change sort order
|
||||
dataframe_writer.record_numerical(3u32, "value", NumericalValue::U64(1));
|
||||
let data = dataframe_writer.sort_order("value", 4, false);
|
||||
assert_eq!(data, vec![0, 2, 1, 3]);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_dictionary_encoded_str() {
|
||||
let mut buffer = Vec::new();
|
||||
@@ -149,7 +206,9 @@ fn test_dictionary_encoded_str() {
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let col_handles = columnar_reader.read_columns("my.column").unwrap();
|
||||
assert_eq!(col_handles.len(), 1);
|
||||
let DynamicColumn::Str(str_col) = col_handles[0].open().unwrap() else { panic!(); };
|
||||
let DynamicColumn::Str(str_col) = col_handles[0].open().unwrap() else {
|
||||
panic!();
|
||||
};
|
||||
let index: Vec<Option<u64>> = (0..5).map(|row_id| str_col.ords().first(row_id)).collect();
|
||||
assert_eq!(index, &[None, Some(0), None, Some(2), Some(1)]);
|
||||
assert_eq!(str_col.num_rows(), 5);
|
||||
@@ -181,7 +240,9 @@ fn test_dictionary_encoded_bytes() {
|
||||
assert_eq!(columnar_reader.num_columns(), 2);
|
||||
let col_handles = columnar_reader.read_columns("my.column").unwrap();
|
||||
assert_eq!(col_handles.len(), 1);
|
||||
let DynamicColumn::Bytes(bytes_col) = col_handles[0].open().unwrap() else { panic!(); };
|
||||
let DynamicColumn::Bytes(bytes_col) = col_handles[0].open().unwrap() else {
|
||||
panic!();
|
||||
};
|
||||
let index: Vec<Option<u64>> = (0..5)
|
||||
.map(|row_id| bytes_col.ords().first(row_id))
|
||||
.collect();
|
||||
@@ -210,3 +271,675 @@ fn test_dictionary_encoded_bytes() {
|
||||
.unwrap();
|
||||
assert_eq!(term_buffer, b"b");
|
||||
}
|
||||
|
||||
fn num_strategy() -> impl Strategy<Value = NumericalValue> {
|
||||
prop_oneof![
|
||||
3 => Just(NumericalValue::U64(0u64)),
|
||||
3 => Just(NumericalValue::U64(u64::MAX)),
|
||||
3 => Just(NumericalValue::I64(0i64)),
|
||||
3 => Just(NumericalValue::I64(i64::MIN)),
|
||||
3 => Just(NumericalValue::I64(i64::MAX)),
|
||||
3 => Just(NumericalValue::F64(1.2f64)),
|
||||
1 => any::<f64>().prop_map(NumericalValue::from),
|
||||
1 => any::<u64>().prop_map(NumericalValue::from),
|
||||
1 => any::<i64>().prop_map(NumericalValue::from),
|
||||
]
|
||||
}
|
||||
|
||||
#[derive(Debug, Clone, Copy)]
|
||||
enum ColumnValue {
|
||||
Str(&'static str),
|
||||
Bytes(&'static [u8]),
|
||||
Numerical(NumericalValue),
|
||||
IpAddr(Ipv6Addr),
|
||||
Bool(bool),
|
||||
DateTime(DateTime),
|
||||
}
|
||||
|
||||
impl<T: Into<NumericalValue>> From<T> for ColumnValue {
|
||||
fn from(val: T) -> ColumnValue {
|
||||
ColumnValue::Numerical(val.into())
|
||||
}
|
||||
}
|
||||
|
||||
impl ColumnValue {
|
||||
pub(crate) fn column_type_category(&self) -> ColumnTypeCategory {
|
||||
match self {
|
||||
ColumnValue::Str(_) => ColumnTypeCategory::Str,
|
||||
ColumnValue::Bytes(_) => ColumnTypeCategory::Bytes,
|
||||
ColumnValue::Numerical(_) => ColumnTypeCategory::Numerical,
|
||||
ColumnValue::IpAddr(_) => ColumnTypeCategory::IpAddr,
|
||||
ColumnValue::Bool(_) => ColumnTypeCategory::Bool,
|
||||
ColumnValue::DateTime(_) => ColumnTypeCategory::DateTime,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn column_name_strategy() -> impl Strategy<Value = &'static str> {
|
||||
prop_oneof![Just("c1"), Just("c2")]
|
||||
}
|
||||
|
||||
fn string_strategy() -> impl Strategy<Value = &'static str> {
|
||||
prop_oneof![Just("a"), Just("b")]
|
||||
}
|
||||
|
||||
fn bytes_strategy() -> impl Strategy<Value = &'static [u8]> {
|
||||
prop_oneof![Just(&[0u8][..]), Just(&[1u8][..])]
|
||||
}
|
||||
|
||||
// A random column value
|
||||
fn column_value_strategy() -> impl Strategy<Value = ColumnValue> {
|
||||
prop_oneof![
|
||||
10 => string_strategy().prop_map(|s| ColumnValue::Str(s)),
|
||||
1 => bytes_strategy().prop_map(|b| ColumnValue::Bytes(b)),
|
||||
40 => num_strategy().prop_map(|n| ColumnValue::Numerical(n)),
|
||||
1 => (1u16..3u16).prop_map(|ip_addr_byte| ColumnValue::IpAddr(Ipv6Addr::new(
|
||||
127,
|
||||
0,
|
||||
0,
|
||||
0,
|
||||
0,
|
||||
0,
|
||||
0,
|
||||
ip_addr_byte
|
||||
))),
|
||||
1 => any::<bool>().prop_map(|b| ColumnValue::Bool(b)),
|
||||
1 => (0_679_723_993i64..1_679_723_995i64)
|
||||
.prop_map(|val| { ColumnValue::DateTime(DateTime::from_timestamp_secs(val)) })
|
||||
]
|
||||
}
|
||||
|
||||
// A document contains up to 4 values.
|
||||
fn doc_strategy() -> impl Strategy<Value = Vec<(&'static str, ColumnValue)>> {
|
||||
proptest::collection::vec((column_name_strategy(), column_value_strategy()), 0..=4)
|
||||
}
|
||||
|
||||
fn num_docs_strategy() -> impl Strategy<Value = usize> {
|
||||
prop_oneof!(
|
||||
// We focus heavily on the 0..2 case as we assume it is sufficient to cover all edge cases.
|
||||
0usize..=3usize,
|
||||
// We leave 50% of the effort exploring more defensively.
|
||||
3usize..=12usize
|
||||
)
|
||||
}
|
||||
|
||||
// A columnar contains up to 2 docs.
|
||||
fn columnar_docs_strategy() -> impl Strategy<Value = Vec<Vec<(&'static str, ColumnValue)>>> {
|
||||
num_docs_strategy()
|
||||
.prop_flat_map(|num_docs| proptest::collection::vec(doc_strategy(), num_docs))
|
||||
}
|
||||
|
||||
fn columnar_docs_and_mapping_strategy(
|
||||
) -> impl Strategy<Value = (Vec<Vec<(&'static str, ColumnValue)>>, Vec<RowId>)> {
|
||||
columnar_docs_strategy().prop_flat_map(|docs| {
|
||||
permutation_strategy(docs.len()).prop_map(move |permutation| (docs.clone(), permutation))
|
||||
})
|
||||
}
|
||||
|
||||
fn permutation_strategy(n: usize) -> impl Strategy<Value = Vec<RowId>> {
|
||||
Just((0u32..n as RowId).collect()).prop_shuffle()
|
||||
}
|
||||
|
||||
fn permutation_and_subset_strategy(n: usize) -> impl Strategy<Value = Vec<usize>> {
|
||||
let vals: Vec<usize> = (0..n).collect();
|
||||
subsequence(vals, 0..=n).prop_shuffle()
|
||||
}
|
||||
|
||||
fn build_columnar_with_mapping(
|
||||
docs: &[Vec<(&'static str, ColumnValue)>],
|
||||
old_to_new_row_ids_opt: Option<&[RowId]>,
|
||||
) -> ColumnarReader {
|
||||
let num_docs = docs.len() as u32;
|
||||
let mut buffer = Vec::new();
|
||||
let mut columnar_writer = ColumnarWriter::default();
|
||||
for (doc_id, vals) in docs.iter().enumerate() {
|
||||
for (column_name, col_val) in vals {
|
||||
match *col_val {
|
||||
ColumnValue::Str(str_val) => {
|
||||
columnar_writer.record_str(doc_id as u32, column_name, str_val);
|
||||
}
|
||||
ColumnValue::Bytes(bytes) => {
|
||||
columnar_writer.record_bytes(doc_id as u32, column_name, bytes)
|
||||
}
|
||||
ColumnValue::Numerical(num) => {
|
||||
columnar_writer.record_numerical(doc_id as u32, column_name, num);
|
||||
}
|
||||
ColumnValue::IpAddr(ip_addr) => {
|
||||
columnar_writer.record_ip_addr(doc_id as u32, column_name, ip_addr);
|
||||
}
|
||||
ColumnValue::Bool(bool_val) => {
|
||||
columnar_writer.record_bool(doc_id as u32, column_name, bool_val);
|
||||
}
|
||||
ColumnValue::DateTime(date_time) => {
|
||||
columnar_writer.record_datetime(doc_id as u32, column_name, date_time);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
columnar_writer
|
||||
.serialize(num_docs, old_to_new_row_ids_opt, &mut buffer)
|
||||
.unwrap();
|
||||
let columnar_reader = ColumnarReader::open(buffer).unwrap();
|
||||
columnar_reader
|
||||
}
|
||||
|
||||
fn build_columnar(docs: &[Vec<(&'static str, ColumnValue)>]) -> ColumnarReader {
|
||||
build_columnar_with_mapping(docs, None)
|
||||
}
|
||||
|
||||
fn assert_columnar_eq_strict(left: &ColumnarReader, right: &ColumnarReader) {
|
||||
assert_columnar_eq(left, right, false);
|
||||
}
|
||||
|
||||
fn assert_columnar_eq(
|
||||
left: &ColumnarReader,
|
||||
right: &ColumnarReader,
|
||||
lenient_on_numerical_value: bool,
|
||||
) {
|
||||
assert_eq!(left.num_rows(), right.num_rows());
|
||||
let left_columns = left.list_columns().unwrap();
|
||||
let right_columns = right.list_columns().unwrap();
|
||||
assert_eq!(left_columns.len(), right_columns.len());
|
||||
for i in 0..left_columns.len() {
|
||||
assert_eq!(left_columns[i].0, right_columns[i].0);
|
||||
let left_column = left_columns[i].1.open().unwrap();
|
||||
let right_column = right_columns[i].1.open().unwrap();
|
||||
assert_dyn_column_eq(&left_column, &right_column, lenient_on_numerical_value);
|
||||
}
|
||||
}
|
||||
|
||||
fn assert_column_eq<T: Copy + PartialOrd + Debug + Send + Sync + 'static>(
|
||||
left: &Column<T>,
|
||||
right: &Column<T>,
|
||||
) {
|
||||
assert_eq!(left.get_cardinality(), right.get_cardinality());
|
||||
assert_eq!(left.num_docs(), right.num_docs());
|
||||
let num_docs = left.num_docs();
|
||||
for doc in 0..num_docs {
|
||||
assert_eq!(
|
||||
left.index.value_row_ids(doc),
|
||||
right.index.value_row_ids(doc)
|
||||
);
|
||||
}
|
||||
assert_eq!(left.values.num_vals(), right.values.num_vals());
|
||||
let num_vals = left.values.num_vals();
|
||||
for i in 0..num_vals {
|
||||
assert_eq!(left.values.get_val(i), right.values.get_val(i));
|
||||
}
|
||||
}
|
||||
|
||||
fn assert_bytes_column_eq(left: &BytesColumn, right: &BytesColumn) {
|
||||
assert_eq!(
|
||||
left.term_ord_column.get_cardinality(),
|
||||
right.term_ord_column.get_cardinality()
|
||||
);
|
||||
assert_eq!(left.num_rows(), right.num_rows());
|
||||
assert_column_eq(&left.term_ord_column, &right.term_ord_column);
|
||||
assert_eq!(left.dictionary.num_terms(), right.dictionary.num_terms());
|
||||
let num_terms = left.dictionary.num_terms();
|
||||
let mut left_terms = left.dictionary.stream().unwrap();
|
||||
let mut right_terms = right.dictionary.stream().unwrap();
|
||||
for _ in 0..num_terms {
|
||||
assert!(left_terms.advance());
|
||||
assert!(right_terms.advance());
|
||||
assert_eq!(left_terms.key(), right_terms.key());
|
||||
}
|
||||
assert!(!left_terms.advance());
|
||||
assert!(!right_terms.advance());
|
||||
}
|
||||
|
||||
fn assert_dyn_column_eq(
|
||||
left_dyn_column: &DynamicColumn,
|
||||
right_dyn_column: &DynamicColumn,
|
||||
lenient_on_numerical_value: bool,
|
||||
) {
|
||||
assert_eq!(
|
||||
&left_dyn_column.get_cardinality(),
|
||||
&right_dyn_column.get_cardinality()
|
||||
);
|
||||
match &(left_dyn_column, right_dyn_column) {
|
||||
(DynamicColumn::Bool(left_col), DynamicColumn::Bool(right_col)) => {
|
||||
assert_column_eq(left_col, right_col);
|
||||
}
|
||||
(DynamicColumn::I64(left_col), DynamicColumn::I64(right_col)) => {
|
||||
assert_column_eq(left_col, right_col);
|
||||
}
|
||||
(DynamicColumn::U64(left_col), DynamicColumn::U64(right_col)) => {
|
||||
assert_column_eq(left_col, right_col);
|
||||
}
|
||||
(DynamicColumn::F64(left_col), DynamicColumn::F64(right_col)) => {
|
||||
assert_column_eq(left_col, right_col);
|
||||
}
|
||||
(DynamicColumn::DateTime(left_col), DynamicColumn::DateTime(right_col)) => {
|
||||
assert_column_eq(left_col, right_col);
|
||||
}
|
||||
(DynamicColumn::IpAddr(left_col), DynamicColumn::IpAddr(right_col)) => {
|
||||
assert_column_eq(left_col, right_col);
|
||||
}
|
||||
(DynamicColumn::Bytes(left_col), DynamicColumn::Bytes(right_col)) => {
|
||||
assert_bytes_column_eq(left_col, right_col);
|
||||
}
|
||||
(DynamicColumn::Str(left_col), DynamicColumn::Str(right_col)) => {
|
||||
assert_bytes_column_eq(left_col, right_col);
|
||||
}
|
||||
(left, right) => {
|
||||
if lenient_on_numerical_value {
|
||||
assert_eq!(
|
||||
ColumnTypeCategory::from(left.column_type()),
|
||||
ColumnTypeCategory::from(right.column_type())
|
||||
);
|
||||
} else {
|
||||
panic!(
|
||||
"Column type are not the same: {:?} vs {:?}",
|
||||
left.column_type(),
|
||||
right.column_type()
|
||||
);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
trait AssertEqualToColumnValue {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue);
|
||||
}
|
||||
|
||||
impl AssertEqualToColumnValue for bool {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::Bool(val) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, val);
|
||||
}
|
||||
}
|
||||
|
||||
impl AssertEqualToColumnValue for Ipv6Addr {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::IpAddr(val) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, val);
|
||||
}
|
||||
}
|
||||
|
||||
impl<T: Coerce + PartialEq + Debug + Into<NumericalValue>> AssertEqualToColumnValue for T {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::Numerical(num) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, &T::coerce(*num));
|
||||
}
|
||||
}
|
||||
|
||||
impl AssertEqualToColumnValue for DateTime {
|
||||
fn assert_equal_to_column_value(&self, column_value: &ColumnValue) {
|
||||
let ColumnValue::DateTime(dt) = column_value else {
|
||||
panic!()
|
||||
};
|
||||
assert_eq!(self, dt);
|
||||
}
|
||||
}
|
||||
|
||||
fn assert_column_values<
|
||||
T: AssertEqualToColumnValue + PartialEq + Copy + PartialOrd + Debug + Send + Sync + 'static,
|
||||
>(
|
||||
col: &Column<T>,
|
||||
expected: &HashMap<u32, Vec<&ColumnValue>>,
|
||||
) {
|
||||
let mut num_non_empty_rows = 0;
|
||||
for doc in 0..col.num_docs() {
|
||||
let doc_vals: Vec<T> = col.values_for_doc(doc).collect();
|
||||
if doc_vals.is_empty() {
|
||||
continue;
|
||||
}
|
||||
num_non_empty_rows += 1;
|
||||
let expected_vals = expected.get(&doc).unwrap();
|
||||
assert_eq!(doc_vals.len(), expected_vals.len());
|
||||
for (val, &expected) in doc_vals.iter().zip(expected_vals.iter()) {
|
||||
val.assert_equal_to_column_value(expected)
|
||||
}
|
||||
}
|
||||
assert_eq!(num_non_empty_rows, expected.len());
|
||||
}
|
||||
|
||||
fn assert_bytes_column_values(
|
||||
col: &BytesColumn,
|
||||
expected: &HashMap<u32, Vec<&ColumnValue>>,
|
||||
is_str: bool,
|
||||
) {
|
||||
let mut num_non_empty_rows = 0;
|
||||
let mut buffer = Vec::new();
|
||||
for doc in 0..col.term_ord_column.num_docs() {
|
||||
let doc_vals: Vec<u64> = col.term_ords(doc).collect();
|
||||
if doc_vals.is_empty() {
|
||||
continue;
|
||||
}
|
||||
let expected_vals = expected.get(&doc).unwrap();
|
||||
assert_eq!(doc_vals.len(), expected_vals.len());
|
||||
for (&expected_col_val, &ord) in expected_vals.iter().zip(&doc_vals) {
|
||||
col.ord_to_bytes(ord, &mut buffer).unwrap();
|
||||
match expected_col_val {
|
||||
ColumnValue::Str(str_val) => {
|
||||
assert!(is_str);
|
||||
assert_eq!(str_val.as_bytes(), &buffer);
|
||||
}
|
||||
ColumnValue::Bytes(bytes_val) => {
|
||||
assert!(!is_str);
|
||||
assert_eq!(bytes_val, &buffer);
|
||||
}
|
||||
_ => {
|
||||
panic!();
|
||||
}
|
||||
}
|
||||
}
|
||||
num_non_empty_rows += 1;
|
||||
}
|
||||
assert_eq!(num_non_empty_rows, expected.len());
|
||||
}
|
||||
|
||||
// This proptest attempts to create a tiny columnar based of up to 3 rows, and checks that the
|
||||
// resulting columnar matches the row data.
|
||||
proptest! {
|
||||
#![proptest_config(ProptestConfig::with_cases(500))]
|
||||
#[test]
|
||||
fn test_single_columnar_builder_proptest(docs in columnar_docs_strategy()) {
|
||||
let columnar = build_columnar(&docs[..]);
|
||||
assert_eq!(columnar.num_rows() as usize, docs.len());
|
||||
let mut expected_columns: HashMap<(&str, ColumnTypeCategory), HashMap<u32, Vec<&ColumnValue>> > = Default::default();
|
||||
for (doc_id, doc_vals) in docs.iter().enumerate() {
|
||||
for (col_name, col_val) in doc_vals {
|
||||
expected_columns
|
||||
.entry((col_name, col_val.column_type_category()))
|
||||
.or_default()
|
||||
.entry(doc_id as u32)
|
||||
.or_default()
|
||||
.push(col_val);
|
||||
}
|
||||
}
|
||||
let column_list = columnar.list_columns().unwrap();
|
||||
assert_eq!(expected_columns.len(), column_list.len());
|
||||
for (column_name, column) in column_list {
|
||||
let dynamic_column = column.open().unwrap();
|
||||
let col_category: ColumnTypeCategory = dynamic_column.column_type().into();
|
||||
let expected_col_values: &HashMap<u32, Vec<&ColumnValue>> = expected_columns.get(&(column_name.as_str(), col_category)).unwrap();
|
||||
match &dynamic_column {
|
||||
DynamicColumn::Bool(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::I64(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::U64(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::F64(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::IpAddr(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::DateTime(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::Bytes(col) =>
|
||||
assert_bytes_column_values(col, expected_col_values, false),
|
||||
DynamicColumn::Str(col) =>
|
||||
assert_bytes_column_values(col, expected_col_values, true),
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Same as `test_single_columnar_builder_proptest` but with a shuffling mapping.
|
||||
proptest! {
|
||||
#![proptest_config(ProptestConfig::with_cases(500))]
|
||||
#[test]
|
||||
fn test_single_columnar_builder_with_shuffle_proptest((docs, mapping) in columnar_docs_and_mapping_strategy()) {
|
||||
let columnar = build_columnar_with_mapping(&docs[..], Some(&mapping));
|
||||
assert_eq!(columnar.num_rows() as usize, docs.len());
|
||||
let mut expected_columns: HashMap<(&str, ColumnTypeCategory), HashMap<u32, Vec<&ColumnValue>> > = Default::default();
|
||||
for (doc_id, doc_vals) in docs.iter().enumerate() {
|
||||
for (col_name, col_val) in doc_vals {
|
||||
expected_columns
|
||||
.entry((col_name, col_val.column_type_category()))
|
||||
.or_default()
|
||||
.entry(mapping[doc_id])
|
||||
.or_default()
|
||||
.push(col_val);
|
||||
}
|
||||
}
|
||||
let column_list = columnar.list_columns().unwrap();
|
||||
assert_eq!(expected_columns.len(), column_list.len());
|
||||
for (column_name, column) in column_list {
|
||||
let dynamic_column = column.open().unwrap();
|
||||
let col_category: ColumnTypeCategory = dynamic_column.column_type().into();
|
||||
let expected_col_values: &HashMap<u32, Vec<&ColumnValue>> = expected_columns.get(&(column_name.as_str(), col_category)).unwrap();
|
||||
for _doc_id in 0..columnar.num_rows() {
|
||||
match &dynamic_column {
|
||||
DynamicColumn::Bool(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::I64(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::U64(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::F64(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::IpAddr(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::DateTime(col) =>
|
||||
assert_column_values(col, expected_col_values),
|
||||
DynamicColumn::Bytes(col) =>
|
||||
assert_bytes_column_values(col, expected_col_values, false),
|
||||
DynamicColumn::Str(col) =>
|
||||
assert_bytes_column_values(col, expected_col_values, true),
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// This tests create 2 or 3 random small columnar and attempts to merge them.
|
||||
// It compares the resulting merged dataframe with what would have been obtained by building the
|
||||
// dataframe from the concatenated rows to begin with.
|
||||
proptest! {
|
||||
#![proptest_config(ProptestConfig::with_cases(1000))]
|
||||
#[test]
|
||||
fn test_columnar_merge_proptest(columnar_docs in proptest::collection::vec(columnar_docs_strategy(), 2..=3)) {
|
||||
let columnar_readers: Vec<ColumnarReader> = columnar_docs.iter()
|
||||
.map(|docs| build_columnar(&docs[..]))
|
||||
.collect::<Vec<_>>();
|
||||
let columnar_readers_arr: Vec<&ColumnarReader> = columnar_readers.iter().collect();
|
||||
let mut output: Vec<u8> = Vec::new();
|
||||
let stack_merge_order = StackMergeOrder::stack(&columnar_readers_arr[..]).into();
|
||||
crate::merge_columnar(&columnar_readers_arr[..], &[], stack_merge_order, &mut output).unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> = columnar_docs.iter().cloned().flatten().collect();
|
||||
let expected_merged_columnar = build_columnar(&concat_rows[..]);
|
||||
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_columnar_merging_empty_columnar() {
|
||||
let columnar_docs: Vec<Vec<Vec<(&str, ColumnValue)>>> =
|
||||
vec![vec![], vec![vec![("c1", ColumnValue::Str("a"))]]];
|
||||
let columnar_readers: Vec<ColumnarReader> = columnar_docs
|
||||
.iter()
|
||||
.map(|docs| build_columnar(&docs[..]))
|
||||
.collect::<Vec<_>>();
|
||||
let columnar_readers_arr: Vec<&ColumnarReader> = columnar_readers.iter().collect();
|
||||
let mut output: Vec<u8> = Vec::new();
|
||||
let stack_merge_order = StackMergeOrder::stack(&columnar_readers_arr[..]);
|
||||
crate::merge_columnar(
|
||||
&columnar_readers_arr[..],
|
||||
&[],
|
||||
crate::MergeRowOrder::Stack(stack_merge_order),
|
||||
&mut output,
|
||||
)
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> =
|
||||
columnar_docs.iter().cloned().flatten().collect();
|
||||
let expected_merged_columnar = build_columnar(&concat_rows[..]);
|
||||
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_columnar_merging_number_columns() {
|
||||
let columnar_docs: Vec<Vec<Vec<(&str, ColumnValue)>>> = vec![
|
||||
// columnar 1
|
||||
vec![
|
||||
// doc 1.1
|
||||
vec![("c2", ColumnValue::Numerical(0i64.into()))],
|
||||
],
|
||||
// columnar2
|
||||
vec![
|
||||
// doc 2.1
|
||||
vec![("c2", ColumnValue::Numerical(0u64.into()))],
|
||||
// doc 2.2
|
||||
vec![("c2", ColumnValue::Numerical(u64::MAX.into()))],
|
||||
],
|
||||
];
|
||||
let columnar_readers: Vec<ColumnarReader> = columnar_docs
|
||||
.iter()
|
||||
.map(|docs| build_columnar(&docs[..]))
|
||||
.collect::<Vec<_>>();
|
||||
let columnar_readers_arr: Vec<&ColumnarReader> = columnar_readers.iter().collect();
|
||||
let mut output: Vec<u8> = Vec::new();
|
||||
let stack_merge_order = StackMergeOrder::stack(&columnar_readers_arr[..]);
|
||||
crate::merge_columnar(
|
||||
&columnar_readers_arr[..],
|
||||
&[],
|
||||
crate::MergeRowOrder::Stack(stack_merge_order),
|
||||
&mut output,
|
||||
)
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
let concat_rows: Vec<Vec<(&'static str, ColumnValue)>> =
|
||||
columnar_docs.iter().cloned().flatten().collect();
|
||||
let expected_merged_columnar = build_columnar(&concat_rows[..]);
|
||||
assert_columnar_eq_strict(&merged_columnar, &expected_merged_columnar);
|
||||
}
|
||||
|
||||
// TODO add non trivial remap and merge
|
||||
// TODO test required_columns
|
||||
// TODO document edge case: required_columns incompatible with values.
|
||||
|
||||
fn columnar_docs_and_remap(
|
||||
) -> impl Strategy<Value = (Vec<Vec<Vec<(&'static str, ColumnValue)>>>, Vec<RowAddr>)> {
|
||||
proptest::collection::vec(columnar_docs_strategy(), 2..=3).prop_flat_map(
|
||||
|columnars_docs: Vec<Vec<Vec<(&str, ColumnValue)>>>| {
|
||||
let row_addrs: Vec<RowAddr> = columnars_docs
|
||||
.iter()
|
||||
.enumerate()
|
||||
.flat_map(|(segment_ord, columnar_docs)| {
|
||||
(0u32..columnar_docs.len() as u32).map(move |row_id| RowAddr {
|
||||
segment_ord: segment_ord as u32,
|
||||
row_id,
|
||||
})
|
||||
})
|
||||
.collect();
|
||||
permutation_and_subset_strategy(row_addrs.len()).prop_map(move |shuffled_subset| {
|
||||
let shuffled_row_addr_subset: Vec<RowAddr> =
|
||||
shuffled_subset.iter().map(|ord| row_addrs[*ord]).collect();
|
||||
(columnars_docs.clone(), shuffled_row_addr_subset)
|
||||
})
|
||||
},
|
||||
)
|
||||
}
|
||||
|
||||
proptest! {
|
||||
#![proptest_config(ProptestConfig::with_cases(1000))]
|
||||
#[test]
|
||||
fn test_columnar_merge_and_remap_proptest((columnar_docs, shuffle_merge_order) in columnar_docs_and_remap()) {
|
||||
let shuffled_rows: Vec<Vec<(&'static str, ColumnValue)>> = shuffle_merge_order.iter()
|
||||
.map(|row_addr| columnar_docs[row_addr.segment_ord as usize][row_addr.row_id as usize].clone())
|
||||
.collect();
|
||||
let expected_merged_columnar = build_columnar(&shuffled_rows[..]);
|
||||
let columnar_readers: Vec<ColumnarReader> = columnar_docs.iter()
|
||||
.map(|docs| build_columnar(&docs[..]))
|
||||
.collect::<Vec<_>>();
|
||||
let columnar_readers_arr: Vec<&ColumnarReader> = columnar_readers.iter().collect();
|
||||
let mut output: Vec<u8> = Vec::new();
|
||||
let segment_num_rows: Vec<RowId> = columnar_docs.iter().map(|docs| docs.len() as RowId).collect();
|
||||
let shuffle_merge_order = ShuffleMergeOrder::for_test(&segment_num_rows, shuffle_merge_order);
|
||||
crate::merge_columnar(&columnar_readers_arr[..], &[], shuffle_merge_order.into(), &mut output).unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
assert_columnar_eq(&merged_columnar, &expected_merged_columnar, true);
|
||||
}
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_columnar_merge_empty() {
|
||||
let columnar_reader_1 = build_columnar(&[]);
|
||||
let rows: &[Vec<_>] = &[vec![("c1", ColumnValue::Str("a"))]][..];
|
||||
let columnar_reader_2 = build_columnar(rows);
|
||||
let mut output: Vec<u8> = Vec::new();
|
||||
let segment_num_rows: Vec<RowId> = vec![0, 0];
|
||||
let shuffle_merge_order = ShuffleMergeOrder::for_test(&segment_num_rows, vec![]);
|
||||
crate::merge_columnar(
|
||||
&[&columnar_reader_1, &columnar_reader_2],
|
||||
&[],
|
||||
shuffle_merge_order.into(),
|
||||
&mut output,
|
||||
)
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
assert_eq!(merged_columnar.num_rows(), 0);
|
||||
assert_eq!(merged_columnar.num_columns(), 0);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_columnar_merge_single_str_column() {
|
||||
let columnar_reader_1 = build_columnar(&[]);
|
||||
let rows: &[Vec<_>] = &[vec![("c1", ColumnValue::Str("a"))]][..];
|
||||
let columnar_reader_2 = build_columnar(rows);
|
||||
let mut output: Vec<u8> = Vec::new();
|
||||
let segment_num_rows: Vec<RowId> = vec![0, 1];
|
||||
let shuffle_merge_order = ShuffleMergeOrder::for_test(
|
||||
&segment_num_rows,
|
||||
vec![RowAddr {
|
||||
segment_ord: 1u32,
|
||||
row_id: 0u32,
|
||||
}],
|
||||
);
|
||||
crate::merge_columnar(
|
||||
&[&columnar_reader_1, &columnar_reader_2],
|
||||
&[],
|
||||
shuffle_merge_order.into(),
|
||||
&mut output,
|
||||
)
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
assert_eq!(merged_columnar.num_rows(), 1);
|
||||
assert_eq!(merged_columnar.num_columns(), 1);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_delete_decrease_cardinality() {
|
||||
let columnar_reader_1 = build_columnar(&[]);
|
||||
let rows: &[Vec<_>] = &[
|
||||
vec![
|
||||
("c", ColumnValue::from(0i64)),
|
||||
("c", ColumnValue::from(0i64)),
|
||||
],
|
||||
vec![("c", ColumnValue::from(0i64))],
|
||||
][..];
|
||||
// c is multivalued here
|
||||
let columnar_reader_2 = build_columnar(rows);
|
||||
let mut output: Vec<u8> = Vec::new();
|
||||
let shuffle_merge_order = ShuffleMergeOrder::for_test(
|
||||
&[0, 2],
|
||||
vec![RowAddr {
|
||||
segment_ord: 1u32,
|
||||
row_id: 1u32,
|
||||
}],
|
||||
);
|
||||
crate::merge_columnar(
|
||||
&[&columnar_reader_1, &columnar_reader_2],
|
||||
&[],
|
||||
shuffle_merge_order.into(),
|
||||
&mut output,
|
||||
)
|
||||
.unwrap();
|
||||
let merged_columnar = ColumnarReader::open(output).unwrap();
|
||||
assert_eq!(merged_columnar.num_rows(), 1);
|
||||
assert_eq!(merged_columnar.num_columns(), 1);
|
||||
let cols = merged_columnar.read_columns("c").unwrap();
|
||||
assert_eq!(cols.len(), 1);
|
||||
assert_eq!(cols[0].column_type(), ColumnType::I64);
|
||||
assert_eq!(cols[0].open().unwrap().get_cardinality(), Cardinality::Full);
|
||||
}
|
||||
|
||||
@@ -109,7 +109,7 @@ impl Coerce for f64 {
|
||||
impl Coerce for DateTime {
|
||||
fn coerce(value: NumericalValue) -> Self {
|
||||
let timestamp_micros = i64::coerce(value);
|
||||
DateTime::from_timestamp_micros(timestamp_micros)
|
||||
DateTime::from_timestamp_nanos(timestamp_micros)
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy-common"
|
||||
version = "0.5.0"
|
||||
version = "0.6.0"
|
||||
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
|
||||
license = "MIT"
|
||||
edition = "2021"
|
||||
@@ -14,7 +14,7 @@ repository = "https://github.com/quickwit-oss/tantivy"
|
||||
|
||||
[dependencies]
|
||||
byteorder = "1.4.3"
|
||||
ownedbytes = { version= "0.5", path="../ownedbytes" }
|
||||
ownedbytes = { version= "0.6", path="../ownedbytes" }
|
||||
async-trait = "0.1"
|
||||
time = { version = "0.3.10", features = ["serde-well-known"] }
|
||||
serde = { version = "1.0.136", features = ["derive"] }
|
||||
|
||||
39
common/benches/bench.rs
Normal file
39
common/benches/bench.rs
Normal file
@@ -0,0 +1,39 @@
|
||||
#![feature(test)]
|
||||
|
||||
extern crate test;
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use rand::seq::IteratorRandom;
|
||||
use rand::thread_rng;
|
||||
use tantivy_common::serialize_vint_u32;
|
||||
use test::Bencher;
|
||||
|
||||
#[bench]
|
||||
fn bench_vint(b: &mut Bencher) {
|
||||
let vals: Vec<u32> = (0..20_000).collect();
|
||||
b.iter(|| {
|
||||
let mut out = 0u64;
|
||||
for val in vals.iter().cloned() {
|
||||
let mut buf = [0u8; 8];
|
||||
serialize_vint_u32(val, &mut buf);
|
||||
out += u64::from(buf[0]);
|
||||
}
|
||||
out
|
||||
});
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn bench_vint_rand(b: &mut Bencher) {
|
||||
let vals: Vec<u32> = (0..20_000).choose_multiple(&mut thread_rng(), 100_000);
|
||||
b.iter(|| {
|
||||
let mut out = 0u64;
|
||||
for val in vals.iter().cloned() {
|
||||
let mut buf = [0u8; 8];
|
||||
serialize_vint_u32(val, &mut buf);
|
||||
out += u64::from(buf[0]);
|
||||
}
|
||||
out
|
||||
});
|
||||
}
|
||||
}
|
||||
@@ -4,6 +4,8 @@ use std::{fmt, io, u64};
|
||||
|
||||
use ownedbytes::OwnedBytes;
|
||||
|
||||
use crate::ByteCount;
|
||||
|
||||
#[derive(Clone, Copy, Eq, PartialEq)]
|
||||
pub struct TinySet(u64);
|
||||
|
||||
@@ -386,8 +388,8 @@ impl ReadOnlyBitSet {
|
||||
}
|
||||
|
||||
/// Number of bytes used in the bitset representation.
|
||||
pub fn num_bytes(&self) -> usize {
|
||||
self.data.len()
|
||||
pub fn num_bytes(&self) -> ByteCount {
|
||||
self.data.len().into()
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
114
common/src/byte_count.rs
Normal file
114
common/src/byte_count.rs
Normal file
@@ -0,0 +1,114 @@
|
||||
use std::iter::Sum;
|
||||
use std::ops::{Add, AddAssign};
|
||||
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
/// Indicates space usage in bytes
|
||||
#[derive(Copy, Clone, Default, PartialEq, Eq, PartialOrd, Ord, Serialize, Deserialize)]
|
||||
pub struct ByteCount(u64);
|
||||
|
||||
impl std::fmt::Debug for ByteCount {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
f.write_str(&self.human_readable())
|
||||
}
|
||||
}
|
||||
|
||||
impl std::fmt::Display for ByteCount {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
f.write_str(&self.human_readable())
|
||||
}
|
||||
}
|
||||
|
||||
const SUFFIX_AND_THRESHOLD: [(&str, u64); 5] = [
|
||||
("KB", 1_000),
|
||||
("MB", 1_000_000),
|
||||
("GB", 1_000_000_000),
|
||||
("TB", 1_000_000_000_000),
|
||||
("PB", 1_000_000_000_000_000),
|
||||
];
|
||||
|
||||
impl ByteCount {
|
||||
#[inline]
|
||||
pub fn get_bytes(&self) -> u64 {
|
||||
self.0
|
||||
}
|
||||
|
||||
pub fn human_readable(&self) -> String {
|
||||
for (suffix, threshold) in SUFFIX_AND_THRESHOLD.iter().rev() {
|
||||
if self.get_bytes() >= *threshold {
|
||||
let unit_num = self.get_bytes() as f64 / *threshold as f64;
|
||||
return format!("{unit_num:.2} {suffix}");
|
||||
}
|
||||
}
|
||||
format!("{:.2} B", self.get_bytes())
|
||||
}
|
||||
}
|
||||
|
||||
impl From<u64> for ByteCount {
|
||||
fn from(value: u64) -> Self {
|
||||
ByteCount(value)
|
||||
}
|
||||
}
|
||||
impl From<usize> for ByteCount {
|
||||
fn from(value: usize) -> Self {
|
||||
ByteCount(value as u64)
|
||||
}
|
||||
}
|
||||
|
||||
impl Sum for ByteCount {
|
||||
#[inline]
|
||||
fn sum<I: Iterator<Item = Self>>(iter: I) -> Self {
|
||||
iter.fold(ByteCount::default(), |acc, x| acc + x)
|
||||
}
|
||||
}
|
||||
|
||||
impl PartialEq<u64> for ByteCount {
|
||||
#[inline]
|
||||
fn eq(&self, other: &u64) -> bool {
|
||||
self.get_bytes() == *other
|
||||
}
|
||||
}
|
||||
|
||||
impl PartialOrd<u64> for ByteCount {
|
||||
#[inline]
|
||||
fn partial_cmp(&self, other: &u64) -> Option<std::cmp::Ordering> {
|
||||
self.get_bytes().partial_cmp(other)
|
||||
}
|
||||
}
|
||||
|
||||
impl Add for ByteCount {
|
||||
type Output = Self;
|
||||
|
||||
#[inline]
|
||||
fn add(self, other: Self) -> Self {
|
||||
Self(self.get_bytes() + other.get_bytes())
|
||||
}
|
||||
}
|
||||
|
||||
impl AddAssign for ByteCount {
|
||||
#[inline]
|
||||
fn add_assign(&mut self, other: Self) {
|
||||
*self = Self(self.get_bytes() + other.get_bytes());
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod test {
|
||||
use crate::ByteCount;
|
||||
|
||||
#[test]
|
||||
fn test_bytes() {
|
||||
assert_eq!(ByteCount::from(0u64).human_readable(), "0 B");
|
||||
assert_eq!(ByteCount::from(300u64).human_readable(), "300 B");
|
||||
assert_eq!(ByteCount::from(1_000_000u64).human_readable(), "1.00 MB");
|
||||
assert_eq!(ByteCount::from(1_500_000u64).human_readable(), "1.50 MB");
|
||||
assert_eq!(
|
||||
ByteCount::from(1_500_000_000u64).human_readable(),
|
||||
"1.50 GB"
|
||||
);
|
||||
assert_eq!(
|
||||
ByteCount::from(3_213_000_000_000u64).human_readable(),
|
||||
"3.21 TB"
|
||||
);
|
||||
}
|
||||
}
|
||||
@@ -1,25 +1,33 @@
|
||||
#![allow(deprecated)]
|
||||
|
||||
use std::fmt;
|
||||
|
||||
use serde::{Deserialize, Serialize};
|
||||
use time::format_description::well_known::Rfc3339;
|
||||
use time::{OffsetDateTime, PrimitiveDateTime, UtcOffset};
|
||||
|
||||
/// DateTime Precision
|
||||
/// Precision with which datetimes are truncated when stored in fast fields. This setting is only
|
||||
/// relevant for fast fields. In the docstore, datetimes are always saved with nanosecond precision.
|
||||
#[derive(
|
||||
Clone, Copy, Debug, Hash, PartialEq, Eq, PartialOrd, Ord, Serialize, Deserialize, Default,
|
||||
)]
|
||||
#[serde(rename_all = "lowercase")]
|
||||
pub enum DatePrecision {
|
||||
/// Seconds precision
|
||||
pub enum DateTimePrecision {
|
||||
/// Second precision.
|
||||
#[default]
|
||||
Seconds,
|
||||
/// Milli-seconds precision.
|
||||
/// Millisecond precision.
|
||||
Milliseconds,
|
||||
/// Micro-seconds precision.
|
||||
/// Microsecond precision.
|
||||
Microseconds,
|
||||
/// Nanosecond precision.
|
||||
Nanoseconds,
|
||||
}
|
||||
|
||||
/// A date/time value with microsecond precision.
|
||||
#[deprecated(since = "0.20.0", note = "Use `DateTimePrecision` instead")]
|
||||
pub type DatePrecision = DateTimePrecision;
|
||||
|
||||
/// A date/time value with nanoseconds precision.
|
||||
///
|
||||
/// This timestamp does not carry any explicit time zone information.
|
||||
/// Users are responsible for applying the provided conversion
|
||||
@@ -31,29 +39,46 @@ pub enum DatePrecision {
|
||||
/// to prevent unintended usage.
|
||||
#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
|
||||
pub struct DateTime {
|
||||
// Timestamp in microseconds.
|
||||
pub(crate) timestamp_micros: i64,
|
||||
// Timestamp in nanoseconds.
|
||||
pub(crate) timestamp_nanos: i64,
|
||||
}
|
||||
|
||||
impl DateTime {
|
||||
/// Minimum possible `DateTime` value.
|
||||
pub const MIN: DateTime = DateTime {
|
||||
timestamp_nanos: i64::MIN,
|
||||
};
|
||||
|
||||
/// Maximum possible `DateTime` value.
|
||||
pub const MAX: DateTime = DateTime {
|
||||
timestamp_nanos: i64::MAX,
|
||||
};
|
||||
|
||||
/// Create new from UNIX timestamp in seconds
|
||||
pub const fn from_timestamp_secs(seconds: i64) -> Self {
|
||||
Self {
|
||||
timestamp_micros: seconds * 1_000_000,
|
||||
timestamp_nanos: seconds * 1_000_000_000,
|
||||
}
|
||||
}
|
||||
|
||||
/// Create new from UNIX timestamp in milliseconds
|
||||
pub const fn from_timestamp_millis(milliseconds: i64) -> Self {
|
||||
Self {
|
||||
timestamp_micros: milliseconds * 1_000,
|
||||
timestamp_nanos: milliseconds * 1_000_000,
|
||||
}
|
||||
}
|
||||
|
||||
/// Create new from UNIX timestamp in microseconds.
|
||||
pub const fn from_timestamp_micros(microseconds: i64) -> Self {
|
||||
Self {
|
||||
timestamp_micros: microseconds,
|
||||
timestamp_nanos: microseconds * 1_000,
|
||||
}
|
||||
}
|
||||
|
||||
/// Create new from UNIX timestamp in nanoseconds.
|
||||
pub const fn from_timestamp_nanos(nanoseconds: i64) -> Self {
|
||||
Self {
|
||||
timestamp_nanos: nanoseconds,
|
||||
}
|
||||
}
|
||||
|
||||
@@ -61,9 +86,9 @@ impl DateTime {
|
||||
///
|
||||
/// The given date/time is converted to UTC and the actual
|
||||
/// time zone is discarded.
|
||||
pub const fn from_utc(dt: OffsetDateTime) -> Self {
|
||||
let timestamp_micros = dt.unix_timestamp() * 1_000_000 + dt.microsecond() as i64;
|
||||
Self { timestamp_micros }
|
||||
pub fn from_utc(dt: OffsetDateTime) -> Self {
|
||||
let timestamp_nanos = dt.unix_timestamp_nanos() as i64;
|
||||
Self { timestamp_nanos }
|
||||
}
|
||||
|
||||
/// Create new from `PrimitiveDateTime`
|
||||
@@ -77,23 +102,27 @@ impl DateTime {
|
||||
|
||||
/// Convert to UNIX timestamp in seconds.
|
||||
pub const fn into_timestamp_secs(self) -> i64 {
|
||||
self.timestamp_micros / 1_000_000
|
||||
self.timestamp_nanos / 1_000_000_000
|
||||
}
|
||||
|
||||
/// Convert to UNIX timestamp in milliseconds.
|
||||
pub const fn into_timestamp_millis(self) -> i64 {
|
||||
self.timestamp_micros / 1_000
|
||||
self.timestamp_nanos / 1_000_000
|
||||
}
|
||||
|
||||
/// Convert to UNIX timestamp in microseconds.
|
||||
pub const fn into_timestamp_micros(self) -> i64 {
|
||||
self.timestamp_micros
|
||||
self.timestamp_nanos / 1_000
|
||||
}
|
||||
|
||||
/// Convert to UNIX timestamp in nanoseconds.
|
||||
pub const fn into_timestamp_nanos(self) -> i64 {
|
||||
self.timestamp_nanos
|
||||
}
|
||||
|
||||
/// Convert to UTC `OffsetDateTime`
|
||||
pub fn into_utc(self) -> OffsetDateTime {
|
||||
let timestamp_nanos = self.timestamp_micros as i128 * 1000;
|
||||
let utc_datetime = OffsetDateTime::from_unix_timestamp_nanos(timestamp_nanos)
|
||||
let utc_datetime = OffsetDateTime::from_unix_timestamp_nanos(self.timestamp_nanos as i128)
|
||||
.expect("valid UNIX timestamp");
|
||||
debug_assert_eq!(UtcOffset::UTC, utc_datetime.offset());
|
||||
utc_datetime
|
||||
@@ -116,20 +145,21 @@ impl DateTime {
|
||||
}
|
||||
|
||||
/// Truncates the microseconds value to the corresponding precision.
|
||||
pub fn truncate(self, precision: DatePrecision) -> Self {
|
||||
pub fn truncate(self, precision: DateTimePrecision) -> Self {
|
||||
let truncated_timestamp_micros = match precision {
|
||||
DatePrecision::Seconds => (self.timestamp_micros / 1_000_000) * 1_000_000,
|
||||
DatePrecision::Milliseconds => (self.timestamp_micros / 1_000) * 1_000,
|
||||
DatePrecision::Microseconds => self.timestamp_micros,
|
||||
DateTimePrecision::Seconds => (self.timestamp_nanos / 1_000_000_000) * 1_000_000_000,
|
||||
DateTimePrecision::Milliseconds => (self.timestamp_nanos / 1_000_000) * 1_000_000,
|
||||
DateTimePrecision::Microseconds => (self.timestamp_nanos / 1_000) * 1_000,
|
||||
DateTimePrecision::Nanoseconds => self.timestamp_nanos,
|
||||
};
|
||||
Self {
|
||||
timestamp_micros: truncated_timestamp_micros,
|
||||
timestamp_nanos: truncated_timestamp_micros,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl fmt::Debug for DateTime {
|
||||
fn fmt(&self, f: &mut fmt::Formatter<'_>) -> fmt::Result {
|
||||
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
|
||||
let utc_rfc3339 = self.into_utc().format(&Rfc3339).map_err(|_| fmt::Error)?;
|
||||
f.write_str(&utc_rfc3339)
|
||||
}
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
use std::fs::File;
|
||||
use std::ops::{Deref, Range, RangeBounds};
|
||||
use std::sync::Arc;
|
||||
use std::{fmt, io};
|
||||
@@ -5,7 +6,7 @@ use std::{fmt, io};
|
||||
use async_trait::async_trait;
|
||||
use ownedbytes::{OwnedBytes, StableDeref};
|
||||
|
||||
use crate::HasLen;
|
||||
use crate::{ByteCount, HasLen};
|
||||
|
||||
/// Objects that represents files sections in tantivy.
|
||||
///
|
||||
@@ -32,6 +33,62 @@ pub trait FileHandle: 'static + Send + Sync + HasLen + fmt::Debug {
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Debug)]
|
||||
/// A File with it's length included.
|
||||
pub struct WrapFile {
|
||||
file: File,
|
||||
len: usize,
|
||||
}
|
||||
impl WrapFile {
|
||||
/// Creates a new WrapFile and stores its length.
|
||||
pub fn new(file: File) -> io::Result<Self> {
|
||||
let len = file.metadata()?.len() as usize;
|
||||
Ok(WrapFile { file, len })
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
impl FileHandle for WrapFile {
|
||||
fn read_bytes(&self, range: Range<usize>) -> io::Result<OwnedBytes> {
|
||||
let file_len = self.len();
|
||||
|
||||
// Calculate the actual range to read, ensuring it stays within file boundaries
|
||||
let start = range.start;
|
||||
let end = range.end.min(file_len);
|
||||
|
||||
// Ensure the start is before the end of the range
|
||||
if start >= end {
|
||||
return Err(io::Error::new(io::ErrorKind::InvalidInput, "Invalid range"));
|
||||
}
|
||||
|
||||
let mut buffer = vec![0; end - start];
|
||||
|
||||
#[cfg(unix)]
|
||||
{
|
||||
use std::os::unix::prelude::FileExt;
|
||||
self.file.read_exact_at(&mut buffer, start as u64)?;
|
||||
}
|
||||
|
||||
#[cfg(not(unix))]
|
||||
{
|
||||
use std::io::{Read, Seek};
|
||||
let mut file = self.file.try_clone()?; // Clone the file to read from it separately
|
||||
// Seek to the start position in the file
|
||||
file.seek(io::SeekFrom::Start(start as u64))?;
|
||||
// Read the data into the buffer
|
||||
file.read_exact(&mut buffer)?;
|
||||
}
|
||||
|
||||
Ok(OwnedBytes::new(buffer))
|
||||
}
|
||||
// todo implement async
|
||||
}
|
||||
impl HasLen for WrapFile {
|
||||
fn len(&self) -> usize {
|
||||
self.len
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
impl FileHandle for &'static [u8] {
|
||||
fn read_bytes(&self, range: Range<usize>) -> io::Result<OwnedBytes> {
|
||||
@@ -67,6 +124,30 @@ impl fmt::Debug for FileSlice {
|
||||
}
|
||||
}
|
||||
|
||||
impl FileSlice {
|
||||
pub fn stream_file_chunks(&self) -> impl Iterator<Item = io::Result<OwnedBytes>> + '_ {
|
||||
let len = self.range.end;
|
||||
let mut start = self.range.start;
|
||||
std::iter::from_fn(move || {
|
||||
/// Returns chunks of 1MB of data from the FileHandle.
|
||||
const CHUNK_SIZE: usize = 1024 * 1024; // 1MB
|
||||
|
||||
if start < len {
|
||||
let end = (start + CHUNK_SIZE).min(len);
|
||||
let range = start..end;
|
||||
let chunk = self.data.read_bytes(range);
|
||||
start += CHUNK_SIZE;
|
||||
match chunk {
|
||||
Ok(chunk) => Some(Ok(chunk)),
|
||||
Err(e) => Some(Err(e)),
|
||||
}
|
||||
} else {
|
||||
None
|
||||
}
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
/// Takes a range, a `RangeBounds` object, and returns
|
||||
/// a `Range` that corresponds to the relative application of the
|
||||
/// `RangeBounds` object to the original `Range`.
|
||||
@@ -216,6 +297,11 @@ impl FileSlice {
|
||||
pub fn slice_to(&self, to_offset: usize) -> FileSlice {
|
||||
self.slice(0..to_offset)
|
||||
}
|
||||
|
||||
/// Returns the byte count of the FileSlice.
|
||||
pub fn num_bytes(&self) -> ByteCount {
|
||||
self.range.len().into()
|
||||
}
|
||||
}
|
||||
|
||||
#[async_trait]
|
||||
|
||||
@@ -27,15 +27,15 @@ pub trait GroupByIteratorExtended: Iterator {
|
||||
where
|
||||
Self: Sized,
|
||||
F: FnMut(&Self::Item) -> K,
|
||||
K: PartialEq + Copy,
|
||||
Self::Item: Copy,
|
||||
K: PartialEq + Clone,
|
||||
Self::Item: Clone,
|
||||
{
|
||||
GroupByIterator::new(self, key)
|
||||
}
|
||||
}
|
||||
impl<I: Iterator> GroupByIteratorExtended for I {}
|
||||
|
||||
pub struct GroupByIterator<I, F, K: Copy>
|
||||
pub struct GroupByIterator<I, F, K: Clone>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
@@ -50,7 +50,7 @@ where
|
||||
inner: Rc<RefCell<GroupByShared<I, F, K>>>,
|
||||
}
|
||||
|
||||
struct GroupByShared<I, F, K: Copy>
|
||||
struct GroupByShared<I, F, K: Clone>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
@@ -63,7 +63,7 @@ impl<I, F, K> GroupByIterator<I, F, K>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
K: Copy,
|
||||
K: Clone,
|
||||
{
|
||||
fn new(inner: I, group_by_fn: F) -> Self {
|
||||
let inner = GroupByShared {
|
||||
@@ -80,28 +80,28 @@ where
|
||||
impl<I, F, K> Iterator for GroupByIterator<I, F, K>
|
||||
where
|
||||
I: Iterator,
|
||||
I::Item: Copy,
|
||||
I::Item: Clone,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
K: Copy,
|
||||
K: Clone,
|
||||
{
|
||||
type Item = (K, GroupIterator<I, F, K>);
|
||||
|
||||
fn next(&mut self) -> Option<Self::Item> {
|
||||
let mut inner = self.inner.borrow_mut();
|
||||
let value = *inner.iter.peek()?;
|
||||
let value = inner.iter.peek()?.clone();
|
||||
let key = (inner.group_by_fn)(&value);
|
||||
|
||||
let inner = self.inner.clone();
|
||||
|
||||
let group_iter = GroupIterator {
|
||||
inner,
|
||||
group_key: key,
|
||||
group_key: key.clone(),
|
||||
};
|
||||
Some((key, group_iter))
|
||||
}
|
||||
}
|
||||
|
||||
pub struct GroupIterator<I, F, K: Copy>
|
||||
pub struct GroupIterator<I, F, K: Clone>
|
||||
where
|
||||
I: Iterator,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
@@ -110,10 +110,10 @@ where
|
||||
group_key: K,
|
||||
}
|
||||
|
||||
impl<I, F, K: PartialEq + Copy> Iterator for GroupIterator<I, F, K>
|
||||
impl<I, F, K: PartialEq + Clone> Iterator for GroupIterator<I, F, K>
|
||||
where
|
||||
I: Iterator,
|
||||
I::Item: Copy,
|
||||
I::Item: Clone,
|
||||
F: FnMut(&I::Item) -> K,
|
||||
{
|
||||
type Item = I::Item;
|
||||
@@ -121,7 +121,7 @@ where
|
||||
fn next(&mut self) -> Option<Self::Item> {
|
||||
let mut inner = self.inner.borrow_mut();
|
||||
// peek if next value is in group
|
||||
let peek_val = *inner.iter.peek()?;
|
||||
let peek_val = inner.iter.peek()?.clone();
|
||||
if (inner.group_by_fn)(&peek_val) == self.group_key {
|
||||
inner.iter.next()
|
||||
} else {
|
||||
|
||||
@@ -5,6 +5,7 @@ use std::ops::Deref;
|
||||
pub use byteorder::LittleEndian as Endianness;
|
||||
|
||||
mod bitset;
|
||||
mod byte_count;
|
||||
mod datetime;
|
||||
pub mod file_slice;
|
||||
mod group_by;
|
||||
@@ -12,13 +13,15 @@ mod serialize;
|
||||
mod vint;
|
||||
mod writer;
|
||||
pub use bitset::*;
|
||||
pub use datetime::{DatePrecision, DateTime};
|
||||
pub use byte_count::ByteCount;
|
||||
#[allow(deprecated)]
|
||||
pub use datetime::DatePrecision;
|
||||
pub use datetime::{DateTime, DateTimePrecision};
|
||||
pub use group_by::GroupByIteratorExtended;
|
||||
pub use ownedbytes::{OwnedBytes, StableDeref};
|
||||
pub use serialize::{BinarySerializable, DeserializeFrom, FixedSize};
|
||||
pub use vint::{
|
||||
deserialize_vint_u128, read_u32_vint, read_u32_vint_no_advance, serialize_vint_u128,
|
||||
serialize_vint_u32, write_u32_vint, VInt, VIntU128,
|
||||
read_u32_vint, read_u32_vint_no_advance, serialize_vint_u32, write_u32_vint, VInt, VIntU128,
|
||||
};
|
||||
pub use writer::{AntiCallToken, CountingWriter, TerminatingWrite};
|
||||
|
||||
|
||||
@@ -1,8 +1,6 @@
|
||||
use std::io;
|
||||
use std::io::{Read, Write};
|
||||
|
||||
use byteorder::{ByteOrder, LittleEndian};
|
||||
|
||||
use super::BinarySerializable;
|
||||
|
||||
/// Variable int serializes a u128 number
|
||||
@@ -19,26 +17,6 @@ pub fn serialize_vint_u128(mut val: u128, output: &mut Vec<u8>) {
|
||||
}
|
||||
}
|
||||
|
||||
/// Deserializes a u128 number
|
||||
///
|
||||
/// Returns the number and the slice after the vint
|
||||
pub fn deserialize_vint_u128(data: &[u8]) -> io::Result<(u128, &[u8])> {
|
||||
let mut result = 0u128;
|
||||
let mut shift = 0u64;
|
||||
for i in 0..19 {
|
||||
let b = data[i];
|
||||
result |= u128::from(b % 128u8) << shift;
|
||||
if b >= STOP_BIT {
|
||||
return Ok((result, &data[i + 1..]));
|
||||
}
|
||||
shift += 7;
|
||||
}
|
||||
Err(io::Error::new(
|
||||
io::ErrorKind::InvalidData,
|
||||
"Failed to deserialize u128 vint",
|
||||
))
|
||||
}
|
||||
|
||||
/// Wrapper over a `u128` that serializes as a variable int.
|
||||
#[derive(Clone, Copy, Debug, Eq, PartialEq)]
|
||||
pub struct VIntU128(pub u128);
|
||||
@@ -80,17 +58,13 @@ pub struct VInt(pub u64);
|
||||
|
||||
const STOP_BIT: u8 = 128;
|
||||
|
||||
#[inline]
|
||||
pub fn serialize_vint_u32(val: u32, buf: &mut [u8; 8]) -> &[u8] {
|
||||
const START_2: u64 = 1 << 7;
|
||||
const START_3: u64 = 1 << 14;
|
||||
const START_4: u64 = 1 << 21;
|
||||
const START_5: u64 = 1 << 28;
|
||||
|
||||
const STOP_1: u64 = START_2 - 1;
|
||||
const STOP_2: u64 = START_3 - 1;
|
||||
const STOP_3: u64 = START_4 - 1;
|
||||
const STOP_4: u64 = START_5 - 1;
|
||||
|
||||
const MASK_1: u64 = 127;
|
||||
const MASK_2: u64 = MASK_1 << 7;
|
||||
const MASK_3: u64 = MASK_2 << 7;
|
||||
@@ -99,25 +73,29 @@ pub fn serialize_vint_u32(val: u32, buf: &mut [u8; 8]) -> &[u8] {
|
||||
|
||||
let val = u64::from(val);
|
||||
const STOP_BIT: u64 = 128u64;
|
||||
let (res, num_bytes) = match val {
|
||||
0..=STOP_1 => (val | STOP_BIT, 1),
|
||||
START_2..=STOP_2 => (
|
||||
let (res, num_bytes) = if val < START_2 {
|
||||
(val | STOP_BIT, 1)
|
||||
} else if val < START_3 {
|
||||
(
|
||||
(val & MASK_1) | ((val & MASK_2) << 1) | (STOP_BIT << (8)),
|
||||
2,
|
||||
),
|
||||
START_3..=STOP_3 => (
|
||||
)
|
||||
} else if val < START_4 {
|
||||
(
|
||||
(val & MASK_1) | ((val & MASK_2) << 1) | ((val & MASK_3) << 2) | (STOP_BIT << (8 * 2)),
|
||||
3,
|
||||
),
|
||||
START_4..=STOP_4 => (
|
||||
)
|
||||
} else if val < START_5 {
|
||||
(
|
||||
(val & MASK_1)
|
||||
| ((val & MASK_2) << 1)
|
||||
| ((val & MASK_3) << 2)
|
||||
| ((val & MASK_4) << 3)
|
||||
| (STOP_BIT << (8 * 3)),
|
||||
4,
|
||||
),
|
||||
_ => (
|
||||
)
|
||||
} else {
|
||||
(
|
||||
(val & MASK_1)
|
||||
| ((val & MASK_2) << 1)
|
||||
| ((val & MASK_3) << 2)
|
||||
@@ -125,9 +103,9 @@ pub fn serialize_vint_u32(val: u32, buf: &mut [u8; 8]) -> &[u8] {
|
||||
| ((val & MASK_5) << 4)
|
||||
| (STOP_BIT << (8 * 4)),
|
||||
5,
|
||||
),
|
||||
)
|
||||
};
|
||||
LittleEndian::write_u64(&mut buf[..], res);
|
||||
*buf = res.to_le_bytes();
|
||||
&buf[0..num_bytes]
|
||||
}
|
||||
|
||||
@@ -245,7 +223,6 @@ impl BinarySerializable for VInt {
|
||||
mod tests {
|
||||
|
||||
use super::{serialize_vint_u32, BinarySerializable, VInt};
|
||||
use crate::vint::{deserialize_vint_u128, serialize_vint_u128, VIntU128};
|
||||
|
||||
fn aux_test_vint(val: u64) {
|
||||
let mut v = [14u8; 10];
|
||||
@@ -284,27 +261,7 @@ mod tests {
|
||||
let mut buffer2 = [0u8; 8];
|
||||
let len_vint = VInt(val as u64).serialize_into(&mut buffer);
|
||||
let res2 = serialize_vint_u32(val, &mut buffer2);
|
||||
assert_eq!(&buffer[..len_vint], res2, "array wrong for {}", val);
|
||||
}
|
||||
|
||||
fn aux_test_vint_u128(val: u128) {
|
||||
let mut data = vec![];
|
||||
serialize_vint_u128(val, &mut data);
|
||||
let (deser_val, _data) = deserialize_vint_u128(&data).unwrap();
|
||||
assert_eq!(val, deser_val);
|
||||
|
||||
let mut out = vec![];
|
||||
VIntU128(val).serialize(&mut out).unwrap();
|
||||
let deser_val = VIntU128::deserialize(&mut &out[..]).unwrap();
|
||||
assert_eq!(val, deser_val.0);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_vint_u128() {
|
||||
aux_test_vint_u128(0);
|
||||
aux_test_vint_u128(1);
|
||||
aux_test_vint_u128(u128::MAX / 3);
|
||||
aux_test_vint_u128(u128::MAX);
|
||||
assert_eq!(&buffer[..len_vint], res2, "array wrong for {val}");
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
||||
@@ -7,13 +7,8 @@
|
||||
// ---
|
||||
|
||||
use serde_json::{Deserializer, Value};
|
||||
use tantivy::aggregation::agg_req::{
|
||||
Aggregation, Aggregations, BucketAggregation, BucketAggregationType, MetricAggregation,
|
||||
RangeAggregation,
|
||||
};
|
||||
use tantivy::aggregation::agg_req::Aggregations;
|
||||
use tantivy::aggregation::agg_result::AggregationResults;
|
||||
use tantivy::aggregation::bucket::RangeAggregationRange;
|
||||
use tantivy::aggregation::metric::AverageAggregation;
|
||||
use tantivy::aggregation::AggregationCollector;
|
||||
use tantivy::query::AllQuery;
|
||||
use tantivy::schema::{self, IndexRecordOption, Schema, TextFieldIndexing, FAST};
|
||||
@@ -42,7 +37,7 @@ fn main() -> tantivy::Result<()> {
|
||||
.set_index_option(IndexRecordOption::WithFreqs)
|
||||
.set_tokenizer("raw"),
|
||||
)
|
||||
.set_fast()
|
||||
.set_fast(None)
|
||||
.set_stored();
|
||||
schema_builder.add_text_field("category", text_fieldtype);
|
||||
schema_builder.add_f64_field("stock", FAST);
|
||||
@@ -192,58 +187,11 @@ fn main() -> tantivy::Result<()> {
|
||||
//
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_str(agg_req_str)?;
|
||||
let collector = AggregationCollector::from_aggs(agg_req, None);
|
||||
let collector = AggregationCollector::from_aggs(agg_req, Default::default());
|
||||
|
||||
let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
|
||||
let res2: Value = serde_json::to_value(agg_res)?;
|
||||
|
||||
// ### Request Rust API
|
||||
//
|
||||
// This is exactly the same request as above, but via the rust structures.
|
||||
//
|
||||
|
||||
let agg_req: Aggregations = vec![(
|
||||
"group_by_stock".to_string(),
|
||||
Aggregation::Bucket(BucketAggregation {
|
||||
bucket_agg: BucketAggregationType::Range(RangeAggregation {
|
||||
field: "stock".to_string(),
|
||||
ranges: vec![
|
||||
RangeAggregationRange {
|
||||
key: Some("few".into()),
|
||||
from: None,
|
||||
to: Some(1f64),
|
||||
},
|
||||
RangeAggregationRange {
|
||||
key: Some("some".into()),
|
||||
from: Some(1f64),
|
||||
to: Some(10f64),
|
||||
},
|
||||
RangeAggregationRange {
|
||||
key: Some("many".into()),
|
||||
from: Some(10f64),
|
||||
to: None,
|
||||
},
|
||||
],
|
||||
..Default::default()
|
||||
}),
|
||||
sub_aggregation: vec![(
|
||||
"average_price".to_string(),
|
||||
Aggregation::Metric(MetricAggregation::Average(
|
||||
AverageAggregation::from_field_name("price".to_string()),
|
||||
)),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect(),
|
||||
}),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect();
|
||||
|
||||
let collector = AggregationCollector::from_aggs(agg_req, None);
|
||||
// We use the `AllQuery` which will pass all documents to the AggregationCollector.
|
||||
let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
|
||||
|
||||
let res1: Value = serde_json::to_value(agg_res)?;
|
||||
let res: Value = serde_json::to_value(agg_res)?;
|
||||
|
||||
// ### Aggregation Result
|
||||
//
|
||||
@@ -261,8 +209,7 @@ fn main() -> tantivy::Result<()> {
|
||||
}
|
||||
"#;
|
||||
let expected_json: Value = serde_json::from_str(expected_res)?;
|
||||
assert_eq!(expected_json, res1);
|
||||
assert_eq!(expected_json, res2);
|
||||
assert_eq!(expected_json, res);
|
||||
|
||||
// ### Request 2
|
||||
//
|
||||
@@ -287,7 +234,7 @@ fn main() -> tantivy::Result<()> {
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_str(agg_req_str)?;
|
||||
|
||||
let collector = AggregationCollector::from_aggs(agg_req, None);
|
||||
let collector = AggregationCollector::from_aggs(agg_req, Default::default());
|
||||
|
||||
let agg_res: AggregationResults = searcher.search(&AllQuery, &collector).unwrap();
|
||||
let res: Value = serde_json::to_value(agg_res)?;
|
||||
|
||||
@@ -221,5 +221,19 @@ fn main() -> tantivy::Result<()> {
|
||||
println!("{}", schema.to_json(&retrieved_doc));
|
||||
}
|
||||
|
||||
// We can also get an explanation to understand
|
||||
// how a found document got its score.
|
||||
let query = query_parser.parse_query("title:sea^20 body:whale^70")?;
|
||||
|
||||
let (_score, doc_address) = searcher
|
||||
.search(&query, &TopDocs::with_limit(1))?
|
||||
.into_iter()
|
||||
.next()
|
||||
.unwrap();
|
||||
|
||||
let explanation = query.explain(&searcher, doc_address)?;
|
||||
|
||||
println!("{}", explanation.to_pretty_json());
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
@@ -53,7 +53,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// this will store tokens of 3 characters each
|
||||
index
|
||||
.tokenizers()
|
||||
.register("ngram3", NgramTokenizer::new(3, 3, false));
|
||||
.register("ngram3", NgramTokenizer::new(3, 3, false).unwrap());
|
||||
|
||||
// To insert document we need an index writer.
|
||||
// There must be only one writer at a time.
|
||||
|
||||
@@ -13,7 +13,7 @@ fn main() -> tantivy::Result<()> {
|
||||
let opts = DateOptions::from(INDEXED)
|
||||
.set_stored()
|
||||
.set_fast()
|
||||
.set_precision(tantivy::DatePrecision::Seconds);
|
||||
.set_precision(tantivy::DateTimePrecision::Seconds);
|
||||
// Add `occurred_at` date field type
|
||||
let occurred_at = schema_builder.add_date_field("occurred_at", opts);
|
||||
let event_type = schema_builder.add_text_field("event", STRING | STORED);
|
||||
|
||||
@@ -96,7 +96,7 @@ fn main() -> tantivy::Result<()> {
|
||||
let mut index_writer_wlock = index_writer.write().unwrap();
|
||||
index_writer_wlock.commit()?
|
||||
};
|
||||
println!("committed with opstamp {}", opstamp);
|
||||
println!("committed with opstamp {opstamp}");
|
||||
thread::sleep(Duration::from_millis(500));
|
||||
}
|
||||
|
||||
|
||||
@@ -84,7 +84,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// Doc 0: TermFreq 2: [0, 4]
|
||||
// Doc 2: TermFreq 1: [0]
|
||||
// ```
|
||||
println!("Doc {}: TermFreq {}: {:?}", doc_id, term_freq, positions);
|
||||
println!("Doc {doc_id}: TermFreq {term_freq}: {positions:?}");
|
||||
doc_id = segment_postings.advance();
|
||||
}
|
||||
}
|
||||
@@ -125,7 +125,7 @@ fn main() -> tantivy::Result<()> {
|
||||
// Once again these docs MAY contains deleted documents as well.
|
||||
let docs = block_segment_postings.docs();
|
||||
// Prints `Docs [0, 2].`
|
||||
println!("Docs {:?}", docs);
|
||||
println!("Docs {docs:?}");
|
||||
block_segment_postings.advance();
|
||||
}
|
||||
}
|
||||
|
||||
79
examples/phrase_prefix_search.rs
Normal file
79
examples/phrase_prefix_search.rs
Normal file
@@ -0,0 +1,79 @@
|
||||
use tantivy::collector::TopDocs;
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::{doc, Index, ReloadPolicy, Result};
|
||||
use tempfile::TempDir;
|
||||
|
||||
fn main() -> Result<()> {
|
||||
let index_path = TempDir::new()?;
|
||||
|
||||
let mut schema_builder = Schema::builder();
|
||||
schema_builder.add_text_field("title", TEXT | STORED);
|
||||
schema_builder.add_text_field("body", TEXT);
|
||||
let schema = schema_builder.build();
|
||||
|
||||
let title = schema.get_field("title").unwrap();
|
||||
let body = schema.get_field("body").unwrap();
|
||||
|
||||
let index = Index::create_in_dir(&index_path, schema)?;
|
||||
|
||||
let mut index_writer = index.writer(50_000_000)?;
|
||||
|
||||
index_writer.add_document(doc!(
|
||||
title => "The Old Man and the Sea",
|
||||
body => "He was an old man who fished alone in a skiff in the Gulf Stream and he had gone \
|
||||
eighty-four days now without taking a fish.",
|
||||
))?;
|
||||
|
||||
index_writer.add_document(doc!(
|
||||
title => "Of Mice and Men",
|
||||
body => "A few miles south of Soledad, the Salinas River drops in close to the hillside \
|
||||
bank and runs deep and green. The water is warm too, for it has slipped twinkling \
|
||||
over the yellow sands in the sunlight before reaching the narrow pool. On one \
|
||||
side of the river the golden foothill slopes curve up to the strong and rocky \
|
||||
Gabilan Mountains, but on the valley side the water is lined with trees—willows \
|
||||
fresh and green with every spring, carrying in their lower leaf junctures the \
|
||||
debris of the winter’s flooding; and sycamores with mottled, white, recumbent \
|
||||
limbs and branches that arch over the pool"
|
||||
))?;
|
||||
|
||||
// Multivalued field just need to be repeated.
|
||||
index_writer.add_document(doc!(
|
||||
title => "Frankenstein",
|
||||
title => "The Modern Prometheus",
|
||||
body => "You will rejoice to hear that no disaster has accompanied the commencement of an \
|
||||
enterprise which you have regarded with such evil forebodings. I arrived here \
|
||||
yesterday, and my first task is to assure my dear sister of my welfare and \
|
||||
increasing confidence in the success of my undertaking."
|
||||
))?;
|
||||
|
||||
index_writer.commit()?;
|
||||
|
||||
let reader = index
|
||||
.reader_builder()
|
||||
.reload_policy(ReloadPolicy::OnCommit)
|
||||
.try_into()?;
|
||||
|
||||
let searcher = reader.searcher();
|
||||
|
||||
let query_parser = QueryParser::for_index(&index, vec![title, body]);
|
||||
// This will match documents containing the phrase "in the"
|
||||
// followed by some word starting with "su",
|
||||
// i.e. it will match "in the sunlight" and "in the success",
|
||||
// but not "in the Gulf Stream".
|
||||
let query = query_parser.parse_query("\"in the su\"*")?;
|
||||
|
||||
let top_docs = searcher.search(&query, &TopDocs::with_limit(10))?;
|
||||
let mut titles = top_docs
|
||||
.into_iter()
|
||||
.map(|(_score, doc_address)| {
|
||||
let doc = searcher.doc(doc_address)?;
|
||||
let title = doc.get_first(title).unwrap().as_text().unwrap().to_owned();
|
||||
Ok(title)
|
||||
})
|
||||
.collect::<Result<Vec<_>>>()?;
|
||||
titles.sort_unstable();
|
||||
assert_eq!(titles, ["Frankenstein", "Of Mice and Men"]);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
@@ -12,12 +12,13 @@
|
||||
use tantivy::collector::{Count, TopDocs};
|
||||
use tantivy::query::TermQuery;
|
||||
use tantivy::schema::*;
|
||||
use tantivy::tokenizer::{PreTokenizedString, SimpleTokenizer, Token, Tokenizer};
|
||||
use tantivy::tokenizer::{PreTokenizedString, SimpleTokenizer, Token, TokenStream, Tokenizer};
|
||||
use tantivy::{doc, Index, ReloadPolicy};
|
||||
use tempfile::TempDir;
|
||||
|
||||
fn pre_tokenize_text(text: &str) -> Vec<Token> {
|
||||
let mut token_stream = SimpleTokenizer.token_stream(text);
|
||||
let mut tokenizer = SimpleTokenizer::default();
|
||||
let mut token_stream = tokenizer.token_stream(text);
|
||||
let mut tokens = vec![];
|
||||
while token_stream.advance() {
|
||||
tokens.push(token_stream.token().clone());
|
||||
|
||||
@@ -56,7 +56,7 @@ fn main() -> tantivy::Result<()> {
|
||||
for (score, doc_address) in top_docs {
|
||||
let doc = searcher.doc(doc_address)?;
|
||||
let snippet = snippet_generator.snippet_from_doc(&doc);
|
||||
println!("Document score {}:", score);
|
||||
println!("Document score {score}:");
|
||||
println!(
|
||||
"title: {}",
|
||||
doc.get_first(title).unwrap().as_text().unwrap()
|
||||
|
||||
@@ -50,12 +50,13 @@ fn main() -> tantivy::Result<()> {
|
||||
|
||||
// This tokenizer lowers all of the text (to help with stop word matching)
|
||||
// then removes all instances of `the` and `and` from the corpus
|
||||
let tokenizer = TextAnalyzer::from(SimpleTokenizer)
|
||||
let tokenizer = TextAnalyzer::builder(SimpleTokenizer::default())
|
||||
.filter(LowerCaser)
|
||||
.filter(StopWordFilter::remove(vec![
|
||||
"the".to_string(),
|
||||
"and".to_string(),
|
||||
]));
|
||||
]))
|
||||
.build();
|
||||
|
||||
index.tokenizers().register("stoppy", tokenizer);
|
||||
|
||||
@@ -105,7 +106,7 @@ fn main() -> tantivy::Result<()> {
|
||||
|
||||
for (score, doc_address) in top_docs {
|
||||
let retrieved_doc = searcher.doc(doc_address)?;
|
||||
println!("\n==\nDocument score {}:", score);
|
||||
println!("\n==\nDocument score {score}:");
|
||||
println!("{}", schema.to_json(&retrieved_doc));
|
||||
}
|
||||
|
||||
|
||||
@@ -6,12 +6,14 @@ use tantivy::collector::TopDocs;
|
||||
use tantivy::query::QueryParser;
|
||||
use tantivy::schema::{Schema, FAST, TEXT};
|
||||
use tantivy::{
|
||||
doc, DocAddress, DocId, Index, IndexReader, Opstamp, Searcher, SearcherGeneration, SegmentId,
|
||||
SegmentReader, Warmer,
|
||||
doc, DocAddress, DocId, Index, Opstamp, Searcher, SearcherGeneration, SegmentId, SegmentReader,
|
||||
Warmer,
|
||||
};
|
||||
|
||||
// This example shows how warmers can be used to
|
||||
// load a values from an external sources using the Warmer API.
|
||||
// load values from an external sources and
|
||||
// tie their lifecycle to that of the index segments
|
||||
// using the Warmer API.
|
||||
//
|
||||
// In this example, we assume an e-commerce search engine.
|
||||
|
||||
@@ -23,9 +25,11 @@ pub trait PriceFetcher: Send + Sync + 'static {
|
||||
fn fetch_prices(&self, product_ids: &[ProductId]) -> Vec<Price>;
|
||||
}
|
||||
|
||||
type SegmentKey = (SegmentId, Option<Opstamp>);
|
||||
|
||||
struct DynamicPriceColumn {
|
||||
field: String,
|
||||
price_cache: RwLock<HashMap<(SegmentId, Option<Opstamp>), Arc<Vec<Price>>>>,
|
||||
price_cache: RwLock<HashMap<SegmentKey, Arc<Vec<Price>>>>,
|
||||
price_fetcher: Box<dyn PriceFetcher>,
|
||||
}
|
||||
|
||||
@@ -46,7 +50,6 @@ impl DynamicPriceColumn {
|
||||
impl Warmer for DynamicPriceColumn {
|
||||
fn warm(&self, searcher: &Searcher) -> tantivy::Result<()> {
|
||||
for segment in searcher.segment_readers() {
|
||||
let key = (segment.segment_id(), segment.delete_opstamp());
|
||||
let product_id_reader = segment
|
||||
.fast_fields()
|
||||
.u64(&self.field)?
|
||||
@@ -55,37 +58,40 @@ impl Warmer for DynamicPriceColumn {
|
||||
.doc_ids_alive()
|
||||
.map(|doc| product_id_reader.get_val(doc))
|
||||
.collect();
|
||||
let mut prices_it = self.price_fetcher.fetch_prices(&product_ids).into_iter();
|
||||
let mut price_vals: Vec<Price> = Vec::new();
|
||||
for doc in 0..segment.max_doc() {
|
||||
if segment.is_deleted(doc) {
|
||||
price_vals.push(0);
|
||||
} else {
|
||||
price_vals.push(prices_it.next().unwrap())
|
||||
}
|
||||
}
|
||||
|
||||
let mut prices = self.price_fetcher.fetch_prices(&product_ids).into_iter();
|
||||
|
||||
let prices: Vec<Price> = (0..segment.max_doc())
|
||||
.map(|doc| {
|
||||
if !segment.is_deleted(doc) {
|
||||
prices.next().unwrap()
|
||||
} else {
|
||||
0
|
||||
}
|
||||
})
|
||||
.collect();
|
||||
|
||||
let key = (segment.segment_id(), segment.delete_opstamp());
|
||||
self.price_cache
|
||||
.write()
|
||||
.unwrap()
|
||||
.insert(key, Arc::new(price_vals));
|
||||
.insert(key, Arc::new(prices));
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn garbage_collect(&self, live_generations: &[&SearcherGeneration]) {
|
||||
let live_segment_id_and_delete_ops: HashSet<(SegmentId, Option<Opstamp>)> =
|
||||
live_generations
|
||||
.iter()
|
||||
.flat_map(|gen| gen.segments())
|
||||
.map(|(&segment_id, &opstamp)| (segment_id, opstamp))
|
||||
.collect();
|
||||
let mut price_cache_wrt = self.price_cache.write().unwrap();
|
||||
// let price_cache = std::mem::take(&mut *price_cache_wrt);
|
||||
// Drain would be nicer here.
|
||||
*price_cache_wrt = std::mem::take(&mut *price_cache_wrt)
|
||||
.into_iter()
|
||||
.filter(|(seg_id_and_op, _)| !live_segment_id_and_delete_ops.contains(seg_id_and_op))
|
||||
let live_keys: HashSet<SegmentKey> = live_generations
|
||||
.iter()
|
||||
.flat_map(|gen| gen.segments())
|
||||
.map(|(&segment_id, &opstamp)| (segment_id, opstamp))
|
||||
.collect();
|
||||
|
||||
self.price_cache
|
||||
.write()
|
||||
.unwrap()
|
||||
.retain(|key, _| live_keys.contains(key));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -100,17 +106,17 @@ pub struct ExternalPriceTable {
|
||||
|
||||
impl ExternalPriceTable {
|
||||
pub fn update_price(&self, product_id: ProductId, price: Price) {
|
||||
let mut prices_wrt = self.prices.write().unwrap();
|
||||
prices_wrt.insert(product_id, price);
|
||||
self.prices.write().unwrap().insert(product_id, price);
|
||||
}
|
||||
}
|
||||
|
||||
impl PriceFetcher for ExternalPriceTable {
|
||||
fn fetch_prices(&self, product_ids: &[ProductId]) -> Vec<Price> {
|
||||
let prices_read = self.prices.read().unwrap();
|
||||
let prices = self.prices.read().unwrap();
|
||||
|
||||
product_ids
|
||||
.iter()
|
||||
.map(|product_id| prices_read.get(product_id).cloned().unwrap_or(0))
|
||||
.map(|product_id| prices.get(product_id).cloned().unwrap_or(0))
|
||||
.collect()
|
||||
}
|
||||
}
|
||||
@@ -137,17 +143,14 @@ fn main() -> tantivy::Result<()> {
|
||||
const SNEAKERS: ProductId = 23222;
|
||||
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut writer = index.writer_with_num_threads(1, 10_000_000)?;
|
||||
let mut writer = index.writer_with_num_threads(1, 15_000_000)?;
|
||||
writer.add_document(doc!(product_id=>OLIVE_OIL, text=>"cooking olive oil from greece"))?;
|
||||
writer.add_document(doc!(product_id=>GLOVES, text=>"kitchen gloves, perfect for cooking"))?;
|
||||
writer.add_document(doc!(product_id=>SNEAKERS, text=>"uber sweet sneakers"))?;
|
||||
writer.commit()?;
|
||||
|
||||
let warmers: Vec<Weak<dyn Warmer>> = vec![Arc::downgrade(
|
||||
&(price_dynamic_column.clone() as Arc<dyn Warmer>),
|
||||
)];
|
||||
let reader: IndexReader = index.reader_builder().warmers(warmers).try_into()?;
|
||||
reader.reload()?;
|
||||
let warmers = vec![Arc::downgrade(&price_dynamic_column) as Weak<dyn Warmer>];
|
||||
let reader = index.reader_builder().warmers(warmers).try_into()?;
|
||||
|
||||
let query_parser = QueryParser::for_index(&index, vec![text]);
|
||||
let query = query_parser.parse_query("cooking")?;
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
[package]
|
||||
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
|
||||
name = "ownedbytes"
|
||||
version = "0.5.0"
|
||||
version = "0.6.0"
|
||||
edition = "2021"
|
||||
description = "Expose data as static slice"
|
||||
license = "MIT"
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
use std::convert::TryInto;
|
||||
use std::ops::{Deref, Range};
|
||||
use std::sync::Arc;
|
||||
use std::{fmt, io, mem};
|
||||
use std::{fmt, io};
|
||||
|
||||
pub use stable_deref_trait::StableDeref;
|
||||
|
||||
@@ -26,8 +26,8 @@ impl OwnedBytes {
|
||||
data_holder: T,
|
||||
) -> OwnedBytes {
|
||||
let box_stable_deref = Arc::new(data_holder);
|
||||
let bytes: &[u8] = box_stable_deref.as_ref();
|
||||
let data = unsafe { mem::transmute::<_, &'static [u8]>(bytes.deref()) };
|
||||
let bytes: &[u8] = box_stable_deref.deref();
|
||||
let data = unsafe { &*(bytes as *const [u8]) };
|
||||
OwnedBytes {
|
||||
data,
|
||||
box_stable_deref,
|
||||
@@ -57,6 +57,12 @@ impl OwnedBytes {
|
||||
self.data.len()
|
||||
}
|
||||
|
||||
/// Returns true iff this `OwnedBytes` is empty.
|
||||
#[inline]
|
||||
pub fn is_empty(&self) -> bool {
|
||||
self.data.is_empty()
|
||||
}
|
||||
|
||||
/// Splits the OwnedBytes into two OwnedBytes `(left, right)`.
|
||||
///
|
||||
/// Left will hold `split_len` bytes.
|
||||
@@ -68,13 +74,14 @@ impl OwnedBytes {
|
||||
#[inline]
|
||||
#[must_use]
|
||||
pub fn split(self, split_len: usize) -> (OwnedBytes, OwnedBytes) {
|
||||
let (left_data, right_data) = self.data.split_at(split_len);
|
||||
let right_box_stable_deref = self.box_stable_deref.clone();
|
||||
let left = OwnedBytes {
|
||||
data: &self.data[..split_len],
|
||||
data: left_data,
|
||||
box_stable_deref: self.box_stable_deref,
|
||||
};
|
||||
let right = OwnedBytes {
|
||||
data: &self.data[split_len..],
|
||||
data: right_data,
|
||||
box_stable_deref: right_box_stable_deref,
|
||||
};
|
||||
(left, right)
|
||||
@@ -99,45 +106,45 @@ impl OwnedBytes {
|
||||
///
|
||||
/// `self` is truncated to `split_len`, left with the remaining bytes.
|
||||
pub fn split_off(&mut self, split_len: usize) -> OwnedBytes {
|
||||
let (left, right) = self.data.split_at(split_len);
|
||||
let right_box_stable_deref = self.box_stable_deref.clone();
|
||||
let right_piece = OwnedBytes {
|
||||
data: &self.data[split_len..],
|
||||
data: right,
|
||||
box_stable_deref: right_box_stable_deref,
|
||||
};
|
||||
self.data = &self.data[..split_len];
|
||||
self.data = left;
|
||||
right_piece
|
||||
}
|
||||
|
||||
/// Returns true iff this `OwnedBytes` is empty.
|
||||
#[inline]
|
||||
pub fn is_empty(&self) -> bool {
|
||||
self.as_slice().is_empty()
|
||||
}
|
||||
|
||||
/// Drops the left most `advance_len` bytes.
|
||||
#[inline]
|
||||
pub fn advance(&mut self, advance_len: usize) {
|
||||
self.data = &self.data[advance_len..]
|
||||
pub fn advance(&mut self, advance_len: usize) -> &[u8] {
|
||||
let (data, rest) = self.data.split_at(advance_len);
|
||||
self.data = rest;
|
||||
data
|
||||
}
|
||||
|
||||
/// Reads an `u8` from the `OwnedBytes` and advance by one byte.
|
||||
#[inline]
|
||||
pub fn read_u8(&mut self) -> u8 {
|
||||
assert!(!self.is_empty());
|
||||
self.advance(1)[0]
|
||||
}
|
||||
|
||||
let byte = self.as_slice()[0];
|
||||
self.advance(1);
|
||||
byte
|
||||
#[inline]
|
||||
fn read_n<const N: usize>(&mut self) -> [u8; N] {
|
||||
self.advance(N).try_into().unwrap()
|
||||
}
|
||||
|
||||
/// Reads an `u32` encoded as little-endian from the `OwnedBytes` and advance by 4 bytes.
|
||||
#[inline]
|
||||
pub fn read_u32(&mut self) -> u32 {
|
||||
u32::from_le_bytes(self.read_n())
|
||||
}
|
||||
|
||||
/// Reads an `u64` encoded as little-endian from the `OwnedBytes` and advance by 8 bytes.
|
||||
#[inline]
|
||||
pub fn read_u64(&mut self) -> u64 {
|
||||
assert!(self.len() > 7);
|
||||
|
||||
let octlet: [u8; 8] = self.as_slice()[..8].try_into().unwrap();
|
||||
self.advance(8);
|
||||
u64::from_le_bytes(octlet)
|
||||
u64::from_le_bytes(self.read_n())
|
||||
}
|
||||
}
|
||||
|
||||
@@ -150,7 +157,7 @@ impl fmt::Debug for OwnedBytes {
|
||||
} else {
|
||||
self.as_slice()
|
||||
};
|
||||
write!(f, "OwnedBytes({:?}, len={})", bytes_truncated, self.len())
|
||||
write!(f, "OwnedBytes({bytes_truncated:?}, len={})", self.len())
|
||||
}
|
||||
}
|
||||
|
||||
@@ -191,32 +198,33 @@ impl Deref for OwnedBytes {
|
||||
}
|
||||
}
|
||||
|
||||
impl AsRef<[u8]> for OwnedBytes {
|
||||
#[inline]
|
||||
fn as_ref(&self) -> &[u8] {
|
||||
self.as_slice()
|
||||
}
|
||||
}
|
||||
|
||||
impl io::Read for OwnedBytes {
|
||||
#[inline]
|
||||
fn read(&mut self, buf: &mut [u8]) -> io::Result<usize> {
|
||||
let read_len = {
|
||||
let data = self.as_slice();
|
||||
if data.len() >= buf.len() {
|
||||
let buf_len = buf.len();
|
||||
buf.copy_from_slice(&data[..buf_len]);
|
||||
buf.len()
|
||||
} else {
|
||||
let data_len = data.len();
|
||||
buf[..data_len].copy_from_slice(data);
|
||||
data_len
|
||||
}
|
||||
};
|
||||
self.advance(read_len);
|
||||
Ok(read_len)
|
||||
let data_len = self.data.len();
|
||||
let buf_len = buf.len();
|
||||
if data_len >= buf_len {
|
||||
let data = self.advance(buf_len);
|
||||
buf.copy_from_slice(data);
|
||||
Ok(buf_len)
|
||||
} else {
|
||||
buf[..data_len].copy_from_slice(self.data);
|
||||
self.data = &[];
|
||||
Ok(data_len)
|
||||
}
|
||||
}
|
||||
#[inline]
|
||||
fn read_to_end(&mut self, buf: &mut Vec<u8>) -> io::Result<usize> {
|
||||
let read_len = {
|
||||
let data = self.as_slice();
|
||||
buf.extend(data);
|
||||
data.len()
|
||||
};
|
||||
self.advance(read_len);
|
||||
buf.extend(self.data);
|
||||
let read_len = self.data.len();
|
||||
self.data = &[];
|
||||
Ok(read_len)
|
||||
}
|
||||
#[inline]
|
||||
@@ -232,13 +240,6 @@ impl io::Read for OwnedBytes {
|
||||
}
|
||||
}
|
||||
|
||||
impl AsRef<[u8]> for OwnedBytes {
|
||||
#[inline]
|
||||
fn as_ref(&self) -> &[u8] {
|
||||
self.as_slice()
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use std::io::{self, Read};
|
||||
@@ -249,12 +250,12 @@ mod tests {
|
||||
fn test_owned_bytes_debug() {
|
||||
let short_bytes = OwnedBytes::new(b"abcd".as_ref());
|
||||
assert_eq!(
|
||||
format!("{:?}", short_bytes),
|
||||
format!("{short_bytes:?}"),
|
||||
"OwnedBytes([97, 98, 99, 100], len=4)"
|
||||
);
|
||||
let long_bytes = OwnedBytes::new(b"abcdefghijklmnopq".as_ref());
|
||||
assert_eq!(
|
||||
format!("{:?}", long_bytes),
|
||||
format!("{long_bytes:?}"),
|
||||
"OwnedBytes([97, 98, 99, 100, 101, 102, 103, 104, 105, 106], len=17)"
|
||||
);
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "tantivy-query-grammar"
|
||||
version = "0.19.0"
|
||||
version = "0.21.0"
|
||||
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
|
||||
license = "MIT"
|
||||
categories = ["database-implementations", "data-structures"]
|
||||
@@ -12,6 +12,4 @@ keywords = ["search", "information", "retrieval"]
|
||||
edition = "2021"
|
||||
|
||||
[dependencies]
|
||||
combine = {version="4", default-features=false, features=[] }
|
||||
once_cell = "1.7.2"
|
||||
regex ={ version = "1.5.4", default-features = false, features = ["std", "unicode"] }
|
||||
nom = "7"
|
||||
|
||||
353
query-grammar/src/infallible.rs
Normal file
353
query-grammar/src/infallible.rs
Normal file
@@ -0,0 +1,353 @@
|
||||
//! nom combinators for infallible operations
|
||||
|
||||
use std::convert::Infallible;
|
||||
|
||||
use nom::{AsChar, IResult, InputLength, InputTakeAtPosition};
|
||||
|
||||
pub(crate) type ErrorList = Vec<LenientErrorInternal>;
|
||||
pub(crate) type JResult<I, O> = IResult<I, (O, ErrorList), Infallible>;
|
||||
|
||||
/// An error, with an end-of-string based offset
|
||||
#[derive(Debug)]
|
||||
pub(crate) struct LenientErrorInternal {
|
||||
pub pos: usize,
|
||||
pub message: String,
|
||||
}
|
||||
|
||||
/// A recoverable error and the position it happened at
|
||||
#[derive(Debug, PartialEq)]
|
||||
pub struct LenientError {
|
||||
pub pos: usize,
|
||||
pub message: String,
|
||||
}
|
||||
|
||||
impl LenientError {
|
||||
pub(crate) fn from_internal(internal: LenientErrorInternal, str_len: usize) -> LenientError {
|
||||
LenientError {
|
||||
pos: str_len - internal.pos,
|
||||
message: internal.message,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fn unwrap_infallible<T>(res: Result<T, nom::Err<Infallible>>) -> T {
|
||||
match res {
|
||||
Ok(val) => val,
|
||||
Err(_) => unreachable!(),
|
||||
}
|
||||
}
|
||||
|
||||
// when rfcs#1733 get stabilized, this can make things clearer
|
||||
// trait InfallibleParser<I, O> = nom::Parser<I, (O, ErrorList), std::convert::Infallible>;
|
||||
|
||||
/// A variant of the classical `opt` parser, except it returns an infallible error type.
|
||||
///
|
||||
/// It's less generic than the original to ease type resolution in the rest of the code.
|
||||
pub(crate) fn opt_i<I: Clone, O, F>(mut f: F) -> impl FnMut(I) -> JResult<I, Option<O>>
|
||||
where F: nom::Parser<I, O, nom::error::Error<I>> {
|
||||
move |input: I| {
|
||||
let i = input.clone();
|
||||
match f.parse(input) {
|
||||
Ok((i, o)) => Ok((i, (Some(o), Vec::new()))),
|
||||
Err(_) => Ok((i, (None, Vec::new()))),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn opt_i_err<'a, I: Clone + InputLength, O, F>(
|
||||
mut f: F,
|
||||
message: impl ToString + 'a,
|
||||
) -> impl FnMut(I) -> JResult<I, Option<O>> + 'a
|
||||
where
|
||||
F: nom::Parser<I, O, nom::error::Error<I>> + 'a,
|
||||
{
|
||||
move |input: I| {
|
||||
let i = input.clone();
|
||||
match f.parse(input) {
|
||||
Ok((i, o)) => Ok((i, (Some(o), Vec::new()))),
|
||||
Err(_) => {
|
||||
let errs = vec![LenientErrorInternal {
|
||||
pos: i.input_len(),
|
||||
message: message.to_string(),
|
||||
}];
|
||||
Ok((i, (None, errs)))
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn space0_infallible<T>(input: T) -> JResult<T, T>
|
||||
where
|
||||
T: InputTakeAtPosition + Clone,
|
||||
<T as InputTakeAtPosition>::Item: AsChar + Clone,
|
||||
{
|
||||
opt_i(nom::character::complete::space0)(input)
|
||||
.map(|(left, (spaces, errors))| (left, (spaces.expect("space0 can't fail"), errors)))
|
||||
}
|
||||
|
||||
pub(crate) fn space1_infallible<T>(input: T) -> JResult<T, Option<T>>
|
||||
where
|
||||
T: InputTakeAtPosition + Clone + InputLength,
|
||||
<T as InputTakeAtPosition>::Item: AsChar + Clone,
|
||||
{
|
||||
opt_i(nom::character::complete::space1)(input).map(|(left, (spaces, mut errors))| {
|
||||
if spaces.is_none() {
|
||||
errors.push(LenientErrorInternal {
|
||||
pos: left.input_len(),
|
||||
message: "missing space".to_string(),
|
||||
})
|
||||
}
|
||||
(left, (spaces, errors))
|
||||
})
|
||||
}
|
||||
|
||||
pub(crate) fn fallible<I, O, E: nom::error::ParseError<I>, F>(
|
||||
mut f: F,
|
||||
) -> impl FnMut(I) -> IResult<I, O, E>
|
||||
where F: nom::Parser<I, (O, ErrorList), Infallible> {
|
||||
use nom::Err;
|
||||
move |input: I| match f.parse(input) {
|
||||
Ok((input, (output, _err))) => Ok((input, output)),
|
||||
Err(Err::Incomplete(needed)) => Err(Err::Incomplete(needed)),
|
||||
Err(Err::Error(val)) | Err(Err::Failure(val)) => match val {},
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn delimited_infallible<I, O1, O2, O3, F, G, H>(
|
||||
mut first: F,
|
||||
mut second: G,
|
||||
mut third: H,
|
||||
) -> impl FnMut(I) -> JResult<I, O2>
|
||||
where
|
||||
F: nom::Parser<I, (O1, ErrorList), Infallible>,
|
||||
G: nom::Parser<I, (O2, ErrorList), Infallible>,
|
||||
H: nom::Parser<I, (O3, ErrorList), Infallible>,
|
||||
{
|
||||
move |input: I| {
|
||||
let (input, (_, mut err)) = first.parse(input)?;
|
||||
let (input, (o2, mut err2)) = second.parse(input)?;
|
||||
err.append(&mut err2);
|
||||
let (input, (_, mut err3)) = third.parse(input)?;
|
||||
err.append(&mut err3);
|
||||
Ok((input, (o2, err)))
|
||||
}
|
||||
}
|
||||
|
||||
// Parse nothing. Just a lazy way to not implement terminated/preceded and use delimited instead
|
||||
pub(crate) fn nothing(i: &str) -> JResult<&str, ()> {
|
||||
Ok((i, ((), Vec::new())))
|
||||
}
|
||||
|
||||
pub(crate) trait TupleInfallible<I, O> {
|
||||
/// Parses the input and returns a tuple of results of each parser.
|
||||
fn parse(&mut self, input: I) -> JResult<I, O>;
|
||||
}
|
||||
|
||||
impl<Input, Output, F: nom::Parser<Input, (Output, ErrorList), Infallible>>
|
||||
TupleInfallible<Input, (Output,)> for (F,)
|
||||
{
|
||||
fn parse(&mut self, input: Input) -> JResult<Input, (Output,)> {
|
||||
self.0.parse(input).map(|(i, (o, e))| (i, ((o,), e)))
|
||||
}
|
||||
}
|
||||
|
||||
// these macros are heavily copied from nom, with some minor adaptations for our type
|
||||
macro_rules! tuple_trait(
|
||||
($name1:ident $ty1:ident, $name2: ident $ty2:ident, $($name:ident $ty:ident),*) => (
|
||||
tuple_trait!(__impl $name1 $ty1, $name2 $ty2; $($name $ty),*);
|
||||
);
|
||||
(__impl $($name:ident $ty: ident),+; $name1:ident $ty1:ident, $($name2:ident $ty2:ident),*) => (
|
||||
tuple_trait_impl!($($name $ty),+);
|
||||
tuple_trait!(__impl $($name $ty),+ , $name1 $ty1; $($name2 $ty2),*);
|
||||
);
|
||||
(__impl $($name:ident $ty: ident),+; $name1:ident $ty1:ident) => (
|
||||
tuple_trait_impl!($($name $ty),+);
|
||||
tuple_trait_impl!($($name $ty),+, $name1 $ty1);
|
||||
);
|
||||
);
|
||||
|
||||
macro_rules! tuple_trait_impl(
|
||||
($($name:ident $ty: ident),+) => (
|
||||
impl<
|
||||
Input: Clone, $($ty),+ ,
|
||||
$($name: nom::Parser<Input, ($ty, ErrorList), Infallible>),+
|
||||
> TupleInfallible<Input, ( $($ty),+ )> for ( $($name),+ ) {
|
||||
|
||||
fn parse(&mut self, input: Input) -> JResult<Input, ( $($ty),+ )> {
|
||||
let mut error_list = Vec::new();
|
||||
tuple_trait_inner!(0, self, input, (), error_list, $($name)+)
|
||||
}
|
||||
}
|
||||
);
|
||||
);
|
||||
|
||||
macro_rules! tuple_trait_inner(
|
||||
($it:tt, $self:expr, $input:expr, (), $error_list:expr, $head:ident $($id:ident)+) => ({
|
||||
let (i, (o, mut err)) = $self.$it.parse($input.clone())?;
|
||||
$error_list.append(&mut err);
|
||||
|
||||
succ!($it, tuple_trait_inner!($self, i, ( o ), $error_list, $($id)+))
|
||||
});
|
||||
($it:tt, $self:expr, $input:expr, ($($parsed:tt)*), $error_list:expr, $head:ident $($id:ident)+) => ({
|
||||
let (i, (o, mut err)) = $self.$it.parse($input.clone())?;
|
||||
$error_list.append(&mut err);
|
||||
|
||||
succ!($it, tuple_trait_inner!($self, i, ($($parsed)* , o), $error_list, $($id)+))
|
||||
});
|
||||
($it:tt, $self:expr, $input:expr, ($($parsed:tt)*), $error_list:expr, $head:ident) => ({
|
||||
let (i, (o, mut err)) = $self.$it.parse($input.clone())?;
|
||||
$error_list.append(&mut err);
|
||||
|
||||
Ok((i, (($($parsed)* , o), $error_list)))
|
||||
});
|
||||
);
|
||||
|
||||
macro_rules! succ (
|
||||
(0, $submac:ident ! ($($rest:tt)*)) => ($submac!(1, $($rest)*));
|
||||
(1, $submac:ident ! ($($rest:tt)*)) => ($submac!(2, $($rest)*));
|
||||
(2, $submac:ident ! ($($rest:tt)*)) => ($submac!(3, $($rest)*));
|
||||
(3, $submac:ident ! ($($rest:tt)*)) => ($submac!(4, $($rest)*));
|
||||
(4, $submac:ident ! ($($rest:tt)*)) => ($submac!(5, $($rest)*));
|
||||
(5, $submac:ident ! ($($rest:tt)*)) => ($submac!(6, $($rest)*));
|
||||
(6, $submac:ident ! ($($rest:tt)*)) => ($submac!(7, $($rest)*));
|
||||
(7, $submac:ident ! ($($rest:tt)*)) => ($submac!(8, $($rest)*));
|
||||
(8, $submac:ident ! ($($rest:tt)*)) => ($submac!(9, $($rest)*));
|
||||
(9, $submac:ident ! ($($rest:tt)*)) => ($submac!(10, $($rest)*));
|
||||
(10, $submac:ident ! ($($rest:tt)*)) => ($submac!(11, $($rest)*));
|
||||
(11, $submac:ident ! ($($rest:tt)*)) => ($submac!(12, $($rest)*));
|
||||
(12, $submac:ident ! ($($rest:tt)*)) => ($submac!(13, $($rest)*));
|
||||
(13, $submac:ident ! ($($rest:tt)*)) => ($submac!(14, $($rest)*));
|
||||
(14, $submac:ident ! ($($rest:tt)*)) => ($submac!(15, $($rest)*));
|
||||
(15, $submac:ident ! ($($rest:tt)*)) => ($submac!(16, $($rest)*));
|
||||
(16, $submac:ident ! ($($rest:tt)*)) => ($submac!(17, $($rest)*));
|
||||
(17, $submac:ident ! ($($rest:tt)*)) => ($submac!(18, $($rest)*));
|
||||
(18, $submac:ident ! ($($rest:tt)*)) => ($submac!(19, $($rest)*));
|
||||
(19, $submac:ident ! ($($rest:tt)*)) => ($submac!(20, $($rest)*));
|
||||
(20, $submac:ident ! ($($rest:tt)*)) => ($submac!(21, $($rest)*));
|
||||
);
|
||||
|
||||
tuple_trait!(FnA A, FnB B, FnC C, FnD D, FnE E, FnF F, FnG G, FnH H, FnI I, FnJ J, FnK K, FnL L,
|
||||
FnM M, FnN N, FnO O, FnP P, FnQ Q, FnR R, FnS S, FnT T, FnU U);
|
||||
|
||||
// Special case: implement `TupleInfallible` for `()`, the unit type.
|
||||
// This can come up in macros which accept a variable number of arguments.
|
||||
// Literally, `()` is an empty tuple, so it should simply parse nothing.
|
||||
impl<I> TupleInfallible<I, ()> for () {
|
||||
fn parse(&mut self, input: I) -> JResult<I, ()> {
|
||||
Ok((input, ((), Vec::new())))
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn tuple_infallible<I, O, List: TupleInfallible<I, O>>(
|
||||
mut l: List,
|
||||
) -> impl FnMut(I) -> JResult<I, O> {
|
||||
move |i: I| l.parse(i)
|
||||
}
|
||||
|
||||
pub(crate) fn separated_list_infallible<I, O, O2, F, G>(
|
||||
mut sep: G,
|
||||
mut f: F,
|
||||
) -> impl FnMut(I) -> JResult<I, Vec<O>>
|
||||
where
|
||||
I: Clone + InputLength,
|
||||
F: nom::Parser<I, (O, ErrorList), Infallible>,
|
||||
G: nom::Parser<I, (O2, ErrorList), Infallible>,
|
||||
{
|
||||
move |i: I| {
|
||||
let mut res: Vec<O> = Vec::new();
|
||||
let mut errors: ErrorList = Vec::new();
|
||||
|
||||
let (mut i, (o, mut err)) = unwrap_infallible(f.parse(i.clone()));
|
||||
errors.append(&mut err);
|
||||
res.push(o);
|
||||
|
||||
loop {
|
||||
let (i_sep_parsed, (_, mut err_sep)) = unwrap_infallible(sep.parse(i.clone()));
|
||||
let len_before = i_sep_parsed.input_len();
|
||||
|
||||
let (i_elem_parsed, (o, mut err_elem)) =
|
||||
unwrap_infallible(f.parse(i_sep_parsed.clone()));
|
||||
|
||||
// infinite loop check: the parser must always consume
|
||||
// if we consumed nothing here, don't produce an element.
|
||||
if i_elem_parsed.input_len() == len_before {
|
||||
return Ok((i, (res, errors)));
|
||||
}
|
||||
res.push(o);
|
||||
errors.append(&mut err_sep);
|
||||
errors.append(&mut err_elem);
|
||||
i = i_elem_parsed;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) trait Alt<I, O> {
|
||||
/// Tests each parser in the tuple and returns the result of the first one that succeeds
|
||||
fn choice(&mut self, input: I) -> Option<JResult<I, O>>;
|
||||
}
|
||||
|
||||
macro_rules! alt_trait(
|
||||
($first_cond:ident $first:ident, $($id_cond:ident $id: ident),+) => (
|
||||
alt_trait!(__impl $first_cond $first; $($id_cond $id),+);
|
||||
);
|
||||
(__impl $($current_cond:ident $current:ident),*; $head_cond:ident $head:ident, $($id_cond:ident $id:ident),+) => (
|
||||
alt_trait_impl!($($current_cond $current),*);
|
||||
|
||||
alt_trait!(__impl $($current_cond $current,)* $head_cond $head; $($id_cond $id),+);
|
||||
);
|
||||
(__impl $($current_cond:ident $current:ident),*; $head_cond:ident $head:ident) => (
|
||||
alt_trait_impl!($($current_cond $current),*);
|
||||
alt_trait_impl!($($current_cond $current,)* $head_cond $head);
|
||||
);
|
||||
);
|
||||
|
||||
macro_rules! alt_trait_impl(
|
||||
($($id_cond:ident $id:ident),+) => (
|
||||
impl<
|
||||
Input: Clone, Output,
|
||||
$(
|
||||
// () are to make things easier on me, but I'm not entirely sure whether we can do better
|
||||
// with rule E0207
|
||||
$id_cond: nom::Parser<Input, (), ()>,
|
||||
$id: nom::Parser<Input, (Output, ErrorList), Infallible>
|
||||
),+
|
||||
> Alt<Input, Output> for ( $(($id_cond, $id),)+ ) {
|
||||
|
||||
fn choice(&mut self, input: Input) -> Option<JResult<Input, Output>> {
|
||||
match self.0.0.parse(input.clone()) {
|
||||
Err(_) => alt_trait_inner!(1, self, input, $($id_cond $id),+),
|
||||
Ok((input_left, _)) => Some(self.0.1.parse(input_left)),
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
);
|
||||
|
||||
macro_rules! alt_trait_inner(
|
||||
($it:tt, $self:expr, $input:expr, $head_cond:ident $head:ident, $($id_cond:ident $id:ident),+) => (
|
||||
match $self.$it.0.parse($input.clone()) {
|
||||
Err(_) => succ!($it, alt_trait_inner!($self, $input, $($id_cond $id),+)),
|
||||
Ok((input_left, _)) => Some($self.$it.1.parse(input_left)),
|
||||
}
|
||||
);
|
||||
($it:tt, $self:expr, $input:expr, $head_cond:ident $head:ident) => (
|
||||
None
|
||||
);
|
||||
);
|
||||
|
||||
alt_trait!(A1 A, B1 B, C1 C, D1 D, E1 E, F1 F, G1 G, H1 H, I1 I, J1 J, K1 K,
|
||||
L1 L, M1 M, N1 N, O1 O, P1 P, Q1 Q, R1 R, S1 S, T1 T, U1 U);
|
||||
|
||||
/// An alt() like combinator. For each branch, it first tries a fallible parser, which commits to
|
||||
/// this branch, or tells to check next branch, and the execute the infallible parser which follow.
|
||||
///
|
||||
/// In case no branch match, the default (fallible) parser is executed.
|
||||
pub(crate) fn alt_infallible<I: Clone, O, F, List: Alt<I, O>>(
|
||||
mut l: List,
|
||||
mut default: F,
|
||||
) -> impl FnMut(I) -> JResult<I, O>
|
||||
where
|
||||
F: nom::Parser<I, (O, ErrorList), Infallible>,
|
||||
{
|
||||
move |i: I| l.choice(i.clone()).unwrap_or_else(|| default.parse(i))
|
||||
}
|
||||
@@ -1,17 +1,26 @@
|
||||
#![allow(clippy::derive_partial_eq_without_eq)]
|
||||
|
||||
mod infallible;
|
||||
mod occur;
|
||||
mod query_grammar;
|
||||
mod user_input_ast;
|
||||
use combine::parser::Parser;
|
||||
|
||||
pub use crate::infallible::LenientError;
|
||||
pub use crate::occur::Occur;
|
||||
use crate::query_grammar::parse_to_ast;
|
||||
pub use crate::user_input_ast::{UserInputAst, UserInputBound, UserInputLeaf, UserInputLiteral};
|
||||
use crate::query_grammar::{parse_to_ast, parse_to_ast_lenient};
|
||||
pub use crate::user_input_ast::{
|
||||
Delimiter, UserInputAst, UserInputBound, UserInputLeaf, UserInputLiteral,
|
||||
};
|
||||
|
||||
pub struct Error;
|
||||
|
||||
/// Parse a query
|
||||
pub fn parse_query(query: &str) -> Result<UserInputAst, Error> {
|
||||
let (user_input_ast, _remaining) = parse_to_ast().parse(query).map_err(|_| Error)?;
|
||||
let (_remaining, user_input_ast) = parse_to_ast(query).map_err(|_| Error)?;
|
||||
Ok(user_input_ast)
|
||||
}
|
||||
|
||||
/// Parse a query, trying to recover from syntax errors, and giving hints toward fixing errors.
|
||||
pub fn parse_query_lenient(query: &str) -> (UserInputAst, Vec<LenientError>) {
|
||||
parse_to_ast_lenient(query)
|
||||
}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -3,7 +3,7 @@ use std::fmt::{Debug, Formatter};
|
||||
|
||||
use crate::Occur;
|
||||
|
||||
#[derive(PartialEq)]
|
||||
#[derive(PartialEq, Clone)]
|
||||
pub enum UserInputLeaf {
|
||||
Literal(UserInputLiteral),
|
||||
All,
|
||||
@@ -16,10 +16,38 @@ pub enum UserInputLeaf {
|
||||
field: Option<String>,
|
||||
elements: Vec<String>,
|
||||
},
|
||||
Exists {
|
||||
field: String,
|
||||
},
|
||||
}
|
||||
|
||||
impl UserInputLeaf {
|
||||
pub(crate) fn set_field(self, field: Option<String>) -> Self {
|
||||
match self {
|
||||
UserInputLeaf::Literal(mut literal) => {
|
||||
literal.field_name = field;
|
||||
UserInputLeaf::Literal(literal)
|
||||
}
|
||||
UserInputLeaf::All => UserInputLeaf::All,
|
||||
UserInputLeaf::Range {
|
||||
field: _,
|
||||
lower,
|
||||
upper,
|
||||
} => UserInputLeaf::Range {
|
||||
field,
|
||||
lower,
|
||||
upper,
|
||||
},
|
||||
UserInputLeaf::Set { field: _, elements } => UserInputLeaf::Set { field, elements },
|
||||
UserInputLeaf::Exists { field: _ } => UserInputLeaf::Exists {
|
||||
field: field.expect("Exist query without a field isn't allowed"),
|
||||
},
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl Debug for UserInputLeaf {
|
||||
fn fmt(&self, formatter: &mut Formatter<'_>) -> Result<(), fmt::Error> {
|
||||
fn fmt(&self, formatter: &mut Formatter) -> Result<(), fmt::Error> {
|
||||
match self {
|
||||
UserInputLeaf::Literal(literal) => literal.fmt(formatter),
|
||||
UserInputLeaf::Range {
|
||||
@@ -28,7 +56,8 @@ impl Debug for UserInputLeaf {
|
||||
ref upper,
|
||||
} => {
|
||||
if let Some(ref field) = field {
|
||||
write!(formatter, "\"{}\":", field)?;
|
||||
// TODO properly escape field (in case of \")
|
||||
write!(formatter, "\"{field}\":")?;
|
||||
}
|
||||
lower.display_lower(formatter)?;
|
||||
write!(formatter, " TO ")?;
|
||||
@@ -37,43 +66,73 @@ impl Debug for UserInputLeaf {
|
||||
}
|
||||
UserInputLeaf::Set { field, elements } => {
|
||||
if let Some(ref field) = field {
|
||||
write!(formatter, "\"{}\": ", field)?;
|
||||
// TODO properly escape field (in case of \")
|
||||
write!(formatter, "\"{field}\": ")?;
|
||||
}
|
||||
write!(formatter, "IN [")?;
|
||||
for (i, element) in elements.iter().enumerate() {
|
||||
for (i, text) in elements.iter().enumerate() {
|
||||
if i != 0 {
|
||||
write!(formatter, " ")?;
|
||||
}
|
||||
write!(formatter, "\"{}\"", element)?;
|
||||
// TODO properly escape element
|
||||
write!(formatter, "\"{text}\"")?;
|
||||
}
|
||||
write!(formatter, "]")
|
||||
}
|
||||
UserInputLeaf::All => write!(formatter, "*"),
|
||||
UserInputLeaf::Exists { field } => {
|
||||
write!(formatter, "\"{field}\":*")
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(PartialEq)]
|
||||
#[derive(Copy, Clone, Eq, PartialEq, Debug)]
|
||||
pub enum Delimiter {
|
||||
SingleQuotes,
|
||||
DoubleQuotes,
|
||||
None,
|
||||
}
|
||||
|
||||
#[derive(PartialEq, Clone)]
|
||||
pub struct UserInputLiteral {
|
||||
pub field_name: Option<String>,
|
||||
pub phrase: String,
|
||||
pub delimiter: Delimiter,
|
||||
pub slop: u32,
|
||||
pub prefix: bool,
|
||||
}
|
||||
|
||||
impl fmt::Debug for UserInputLiteral {
|
||||
fn fmt(&self, formatter: &mut fmt::Formatter<'_>) -> Result<(), fmt::Error> {
|
||||
fn fmt(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
|
||||
if let Some(ref field) = self.field_name {
|
||||
write!(formatter, "\"{}\":", field)?;
|
||||
// TODO properly escape field (in case of \")
|
||||
write!(formatter, "\"{field}\":")?;
|
||||
}
|
||||
match self.delimiter {
|
||||
Delimiter::SingleQuotes => {
|
||||
// TODO properly escape element (in case of \')
|
||||
write!(formatter, "'{}'", self.phrase)?;
|
||||
}
|
||||
Delimiter::DoubleQuotes => {
|
||||
// TODO properly escape element (in case of \")
|
||||
write!(formatter, "\"{}\"", self.phrase)?;
|
||||
}
|
||||
Delimiter::None => {
|
||||
// TODO properly escape element
|
||||
write!(formatter, "{}", self.phrase)?;
|
||||
}
|
||||
}
|
||||
write!(formatter, "\"{}\"", self.phrase)?;
|
||||
if self.slop > 0 {
|
||||
write!(formatter, "~{}", self.slop)?;
|
||||
} else if self.prefix {
|
||||
write!(formatter, "*")?;
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(PartialEq)]
|
||||
#[derive(PartialEq, Debug, Clone)]
|
||||
pub enum UserInputBound {
|
||||
Inclusive(String),
|
||||
Exclusive(String),
|
||||
@@ -83,16 +142,18 @@ pub enum UserInputBound {
|
||||
impl UserInputBound {
|
||||
fn display_lower(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
|
||||
match *self {
|
||||
UserInputBound::Inclusive(ref word) => write!(formatter, "[\"{}\"", word),
|
||||
UserInputBound::Exclusive(ref word) => write!(formatter, "{{\"{}\"", word),
|
||||
// TODO properly escape word if required
|
||||
UserInputBound::Inclusive(ref word) => write!(formatter, "[\"{word}\""),
|
||||
UserInputBound::Exclusive(ref word) => write!(formatter, "{{\"{word}\""),
|
||||
UserInputBound::Unbounded => write!(formatter, "{{\"*\""),
|
||||
}
|
||||
}
|
||||
|
||||
fn display_upper(&self, formatter: &mut fmt::Formatter) -> Result<(), fmt::Error> {
|
||||
match *self {
|
||||
UserInputBound::Inclusive(ref word) => write!(formatter, "\"{}\"]", word),
|
||||
UserInputBound::Exclusive(ref word) => write!(formatter, "\"{}\"}}", word),
|
||||
// TODO properly escape word if required
|
||||
UserInputBound::Inclusive(ref word) => write!(formatter, "\"{word}\"]"),
|
||||
UserInputBound::Exclusive(ref word) => write!(formatter, "\"{word}\"}}"),
|
||||
UserInputBound::Unbounded => write!(formatter, "\"*\"}}"),
|
||||
}
|
||||
}
|
||||
@@ -106,6 +167,7 @@ impl UserInputBound {
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(PartialEq, Clone)]
|
||||
pub enum UserInputAst {
|
||||
Clause(Vec<(Option<Occur>, UserInputAst)>),
|
||||
Leaf(Box<UserInputLeaf>),
|
||||
@@ -163,9 +225,9 @@ fn print_occur_ast(
|
||||
formatter: &mut fmt::Formatter,
|
||||
) -> fmt::Result {
|
||||
if let Some(occur) = occur_opt {
|
||||
write!(formatter, "{}{:?}", occur, ast)?;
|
||||
write!(formatter, "{occur}{ast:?}")?;
|
||||
} else {
|
||||
write!(formatter, "*{:?}", ast)?;
|
||||
write!(formatter, "*{ast:?}")?;
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
@@ -175,6 +237,7 @@ impl fmt::Debug for UserInputAst {
|
||||
match *self {
|
||||
UserInputAst::Clause(ref subqueries) => {
|
||||
if subqueries.is_empty() {
|
||||
// TODO this will break ast reserialization, is writing "( )" enought?
|
||||
write!(formatter, "<emptyclause>")?;
|
||||
} else {
|
||||
write!(formatter, "(")?;
|
||||
@@ -187,8 +250,8 @@ impl fmt::Debug for UserInputAst {
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
UserInputAst::Leaf(ref subquery) => write!(formatter, "{:?}", subquery),
|
||||
UserInputAst::Boost(ref leaf, boost) => write!(formatter, "({:?})^{}", leaf, boost),
|
||||
UserInputAst::Leaf(ref subquery) => write!(formatter, "{subquery:?}"),
|
||||
UserInputAst::Boost(ref leaf, boost) => write!(formatter, "({leaf:?})^{boost}"),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
550
src/aggregation/agg_bench.rs
Normal file
550
src/aggregation/agg_bench.rs
Normal file
@@ -0,0 +1,550 @@
|
||||
#[cfg(all(test, feature = "unstable"))]
|
||||
mod bench {
|
||||
|
||||
use rand::prelude::SliceRandom;
|
||||
use rand::rngs::StdRng;
|
||||
use rand::{Rng, SeedableRng};
|
||||
use rand_distr::Distribution;
|
||||
use serde_json::json;
|
||||
use test::{self, Bencher};
|
||||
|
||||
use crate::aggregation::agg_req::Aggregations;
|
||||
use crate::aggregation::AggregationCollector;
|
||||
use crate::query::{AllQuery, TermQuery};
|
||||
use crate::schema::{IndexRecordOption, Schema, TextFieldIndexing, FAST, STRING};
|
||||
use crate::{Index, Term};
|
||||
|
||||
#[derive(Clone, Copy, Hash, Default, Debug, PartialEq, Eq, PartialOrd, Ord)]
|
||||
enum Cardinality {
|
||||
/// All documents contain exactly one value.
|
||||
/// `Full` is the default for auto-detecting the Cardinality, since it is the most strict.
|
||||
#[default]
|
||||
Full = 0,
|
||||
/// All documents contain at most one value.
|
||||
Optional = 1,
|
||||
/// All documents may contain any number of values.
|
||||
Multivalued = 2,
|
||||
/// 1 / 20 documents has a value
|
||||
Sparse = 3,
|
||||
}
|
||||
|
||||
fn get_collector(agg_req: Aggregations) -> AggregationCollector {
|
||||
AggregationCollector::from_aggs(agg_req, Default::default())
|
||||
}
|
||||
|
||||
fn get_test_index_bench(cardinality: Cardinality) -> crate::Result<Index> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let text_fieldtype = crate::schema::TextOptions::default()
|
||||
.set_indexing_options(
|
||||
TextFieldIndexing::default().set_index_option(IndexRecordOption::WithFreqs),
|
||||
)
|
||||
.set_stored();
|
||||
let text_field = schema_builder.add_text_field("text", text_fieldtype);
|
||||
let json_field = schema_builder.add_json_field("json", FAST);
|
||||
let text_field_many_terms = schema_builder.add_text_field("text_many_terms", STRING | FAST);
|
||||
let text_field_few_terms = schema_builder.add_text_field("text_few_terms", STRING | FAST);
|
||||
let score_fieldtype = crate::schema::NumericOptions::default().set_fast();
|
||||
let score_field = schema_builder.add_u64_field("score", score_fieldtype.clone());
|
||||
let score_field_f64 = schema_builder.add_f64_field("score_f64", score_fieldtype.clone());
|
||||
let score_field_i64 = schema_builder.add_i64_field("score_i64", score_fieldtype);
|
||||
let index = Index::create_from_tempdir(schema_builder.build())?;
|
||||
let few_terms_data = vec!["INFO", "ERROR", "WARN", "DEBUG"];
|
||||
|
||||
let lg_norm = rand_distr::LogNormal::new(2.996f64, 0.979f64).unwrap();
|
||||
|
||||
let many_terms_data = (0..150_000)
|
||||
.map(|num| format!("author{}", num))
|
||||
.collect::<Vec<_>>();
|
||||
{
|
||||
let mut rng = StdRng::from_seed([1u8; 32]);
|
||||
let mut index_writer = index.writer_with_num_threads(1, 200_000_000)?;
|
||||
// To make the different test cases comparable we just change one doc to force the
|
||||
// cardinality
|
||||
if cardinality == Cardinality::Optional {
|
||||
index_writer.add_document(doc!())?;
|
||||
}
|
||||
if cardinality == Cardinality::Multivalued {
|
||||
index_writer.add_document(doc!(
|
||||
json_field => json!({"mixed_type": 10.0}),
|
||||
json_field => json!({"mixed_type": 10.0}),
|
||||
text_field => "cool",
|
||||
text_field => "cool",
|
||||
text_field_many_terms => "cool",
|
||||
text_field_many_terms => "cool",
|
||||
text_field_few_terms => "cool",
|
||||
text_field_few_terms => "cool",
|
||||
score_field => 1u64,
|
||||
score_field => 1u64,
|
||||
score_field_f64 => lg_norm.sample(&mut rng),
|
||||
score_field_f64 => lg_norm.sample(&mut rng),
|
||||
score_field_i64 => 1i64,
|
||||
score_field_i64 => 1i64,
|
||||
))?;
|
||||
}
|
||||
let mut doc_with_value = 1_000_000;
|
||||
if cardinality == Cardinality::Sparse {
|
||||
doc_with_value /= 20;
|
||||
}
|
||||
let val_max = 1_000_000.0;
|
||||
for _ in 0..doc_with_value {
|
||||
let val: f64 = rng.gen_range(0.0..1_000_000.0);
|
||||
let json = if rng.gen_bool(0.1) {
|
||||
// 10% are numeric values
|
||||
json!({ "mixed_type": val })
|
||||
} else {
|
||||
json!({"mixed_type": many_terms_data.choose(&mut rng).unwrap().to_string()})
|
||||
};
|
||||
index_writer.add_document(doc!(
|
||||
text_field => "cool",
|
||||
json_field => json,
|
||||
text_field_many_terms => many_terms_data.choose(&mut rng).unwrap().to_string(),
|
||||
text_field_few_terms => few_terms_data.choose(&mut rng).unwrap().to_string(),
|
||||
score_field => val as u64,
|
||||
score_field_f64 => lg_norm.sample(&mut rng),
|
||||
score_field_i64 => val as i64,
|
||||
))?;
|
||||
if cardinality == Cardinality::Sparse {
|
||||
for _ in 0..20 {
|
||||
index_writer.add_document(doc!(text_field => "cool"))?;
|
||||
}
|
||||
}
|
||||
}
|
||||
// writing the segment
|
||||
index_writer.commit()?;
|
||||
}
|
||||
|
||||
Ok(index)
|
||||
}
|
||||
|
||||
use paste::paste;
|
||||
#[macro_export]
|
||||
macro_rules! bench_all_cardinalities {
|
||||
( $x:ident ) => {
|
||||
paste! {
|
||||
#[bench]
|
||||
fn $x(b: &mut Bencher) {
|
||||
[<$x _card>](b, Cardinality::Full)
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn [<$x _opt>](b: &mut Bencher) {
|
||||
[<$x _card>](b, Cardinality::Optional)
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn [<$x _multi>](b: &mut Bencher) {
|
||||
[<$x _card>](b, Cardinality::Multivalued)
|
||||
}
|
||||
|
||||
#[bench]
|
||||
fn [<$x _sparse>](b: &mut Bencher) {
|
||||
[<$x _card>](b, Cardinality::Sparse)
|
||||
}
|
||||
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_average_u64);
|
||||
|
||||
fn bench_aggregation_average_u64_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
let text_field = reader.searcher().schema().get_field("text").unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let term_query = TermQuery::new(
|
||||
Term::from_field_text(text_field, "cool"),
|
||||
IndexRecordOption::Basic,
|
||||
);
|
||||
|
||||
let agg_req_1: Aggregations = serde_json::from_value(json!({
|
||||
"average": { "avg": { "field": "score", } }
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&term_query, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_stats_f64);
|
||||
|
||||
fn bench_aggregation_stats_f64_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
let text_field = reader.searcher().schema().get_field("text").unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let term_query = TermQuery::new(
|
||||
Term::from_field_text(text_field, "cool"),
|
||||
IndexRecordOption::Basic,
|
||||
);
|
||||
|
||||
let agg_req_1: Aggregations = serde_json::from_value(json!({
|
||||
"average_f64": { "stats": { "field": "score_f64", } }
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&term_query, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_average_f64);
|
||||
|
||||
fn bench_aggregation_average_f64_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
let text_field = reader.searcher().schema().get_field("text").unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let term_query = TermQuery::new(
|
||||
Term::from_field_text(text_field, "cool"),
|
||||
IndexRecordOption::Basic,
|
||||
);
|
||||
|
||||
let agg_req_1: Aggregations = serde_json::from_value(json!({
|
||||
"average_f64": { "avg": { "field": "score_f64", } }
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&term_query, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_percentiles_f64);
|
||||
|
||||
fn bench_aggregation_percentiles_f64_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req_str = r#"
|
||||
{
|
||||
"mypercentiles": {
|
||||
"percentiles": {
|
||||
"field": "score_f64",
|
||||
"percents": [ 95, 99, 99.9 ]
|
||||
}
|
||||
}
|
||||
} "#;
|
||||
let agg_req_1: Aggregations = serde_json::from_str(agg_req_str).unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_average_u64_and_f64);
|
||||
|
||||
fn bench_aggregation_average_u64_and_f64_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
let text_field = reader.searcher().schema().get_field("text").unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let term_query = TermQuery::new(
|
||||
Term::from_field_text(text_field, "cool"),
|
||||
IndexRecordOption::Basic,
|
||||
);
|
||||
|
||||
let agg_req_1: Aggregations = serde_json::from_value(json!({
|
||||
"average_f64": { "avg": { "field": "score_f64" } },
|
||||
"average": { "avg": { "field": "score" } },
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&term_query, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_terms_few);
|
||||
|
||||
fn bench_aggregation_terms_few_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_texts": { "terms": { "field": "text_few_terms" } },
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_terms_many_with_sub_agg);
|
||||
|
||||
fn bench_aggregation_terms_many_with_sub_agg_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_texts": {
|
||||
"terms": { "field": "text_many_terms" },
|
||||
"aggs": {
|
||||
"average_f64": { "avg": { "field": "score_f64" } }
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_terms_many_json_mixed_type_with_sub_agg);
|
||||
|
||||
fn bench_aggregation_terms_many_json_mixed_type_with_sub_agg_card(
|
||||
b: &mut Bencher,
|
||||
cardinality: Cardinality,
|
||||
) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_texts": {
|
||||
"terms": { "field": "json.mixed_type" },
|
||||
"aggs": {
|
||||
"average_f64": { "avg": { "field": "score_f64" } }
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_terms_many2);
|
||||
|
||||
fn bench_aggregation_terms_many2_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_texts": { "terms": { "field": "text_many_terms" } },
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_terms_many_order_by_term);
|
||||
|
||||
fn bench_aggregation_terms_many_order_by_term_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"my_texts": { "terms": { "field": "text_many_terms", "order": { "_key": "desc" } } },
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_range_only);
|
||||
|
||||
fn bench_aggregation_range_only_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req_1: Aggregations = serde_json::from_value(json!({
|
||||
"range_f64": { "range": { "field": "score_f64", "ranges": [
|
||||
{ "from": 3, "to": 7000 },
|
||||
{ "from": 7000, "to": 20000 },
|
||||
{ "from": 20000, "to": 30000 },
|
||||
{ "from": 30000, "to": 40000 },
|
||||
{ "from": 40000, "to": 50000 },
|
||||
{ "from": 50000, "to": 60000 }
|
||||
] } },
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_range_with_avg);
|
||||
|
||||
fn bench_aggregation_range_with_avg_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req_1: Aggregations = serde_json::from_value(json!({
|
||||
"rangef64": {
|
||||
"range": {
|
||||
"field": "score_f64",
|
||||
"ranges": [
|
||||
{ "from": 3, "to": 7000 },
|
||||
{ "from": 7000, "to": 20000 },
|
||||
{ "from": 20000, "to": 30000 },
|
||||
{ "from": 30000, "to": 40000 },
|
||||
{ "from": 40000, "to": 50000 },
|
||||
{ "from": 50000, "to": 60000 }
|
||||
]
|
||||
},
|
||||
"aggs": {
|
||||
"average_f64": { "avg": { "field": "score_f64" } }
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
// hard bounds has a different algorithm, because it actually limits collection range
|
||||
//
|
||||
bench_all_cardinalities!(bench_aggregation_histogram_only_hard_bounds);
|
||||
|
||||
fn bench_aggregation_histogram_only_hard_bounds_card(
|
||||
b: &mut Bencher,
|
||||
cardinality: Cardinality,
|
||||
) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req_1: Aggregations = serde_json::from_value(json!({
|
||||
"rangef64": { "histogram": { "field": "score_f64", "interval": 100, "hard_bounds": { "min": 1000, "max": 300000 } } },
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_histogram_with_avg);
|
||||
|
||||
fn bench_aggregation_histogram_with_avg_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req_1: Aggregations = serde_json::from_value(json!({
|
||||
"rangef64": {
|
||||
"histogram": { "field": "score_f64", "interval": 100 },
|
||||
"aggs": {
|
||||
"average_f64": { "avg": { "field": "score_f64" } }
|
||||
}
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_histogram_only);
|
||||
|
||||
fn bench_aggregation_histogram_only_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let agg_req_1: Aggregations = serde_json::from_value(json!({
|
||||
"rangef64": {
|
||||
"histogram": {
|
||||
"field": "score_f64",
|
||||
"interval": 100 // 1000 buckets
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&AllQuery, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
|
||||
bench_all_cardinalities!(bench_aggregation_avg_and_range_with_avg);
|
||||
|
||||
fn bench_aggregation_avg_and_range_with_avg_card(b: &mut Bencher, cardinality: Cardinality) {
|
||||
let index = get_test_index_bench(cardinality).unwrap();
|
||||
let reader = index.reader().unwrap();
|
||||
let text_field = reader.searcher().schema().get_field("text").unwrap();
|
||||
|
||||
b.iter(|| {
|
||||
let term_query = TermQuery::new(
|
||||
Term::from_field_text(text_field, "cool"),
|
||||
IndexRecordOption::Basic,
|
||||
);
|
||||
|
||||
let agg_req_1: Aggregations = serde_json::from_value(json!({
|
||||
"rangef64": {
|
||||
"range": {
|
||||
"field": "score_f64",
|
||||
"ranges": [
|
||||
{ "from": 3, "to": 7000 },
|
||||
{ "from": 7000, "to": 20000 },
|
||||
{ "from": 20000, "to": 60000 }
|
||||
]
|
||||
},
|
||||
"aggs": {
|
||||
"average_in_range": { "avg": { "field": "score" } }
|
||||
}
|
||||
},
|
||||
"average": { "avg": { "field": "score" } }
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let collector = get_collector(agg_req_1);
|
||||
|
||||
let searcher = reader.searcher();
|
||||
searcher.search(&term_query, &collector).unwrap()
|
||||
});
|
||||
}
|
||||
}
|
||||
136
src/aggregation/agg_limits.rs
Normal file
136
src/aggregation/agg_limits.rs
Normal file
@@ -0,0 +1,136 @@
|
||||
use std::collections::HashMap;
|
||||
use std::sync::atomic::{AtomicU64, Ordering};
|
||||
use std::sync::Arc;
|
||||
|
||||
use common::ByteCount;
|
||||
|
||||
use super::collector::DEFAULT_MEMORY_LIMIT;
|
||||
use super::{AggregationError, DEFAULT_BUCKET_LIMIT};
|
||||
|
||||
/// An estimate for memory consumption. Non recursive
|
||||
pub trait MemoryConsumption {
|
||||
fn memory_consumption(&self) -> usize;
|
||||
}
|
||||
|
||||
impl<K, V, S> MemoryConsumption for HashMap<K, V, S> {
|
||||
fn memory_consumption(&self) -> usize {
|
||||
let capacity = self.capacity();
|
||||
(std::mem::size_of::<K>() + std::mem::size_of::<V>() + 1) * capacity
|
||||
}
|
||||
}
|
||||
|
||||
/// Aggregation memory limit after which the request fails. Defaults to DEFAULT_MEMORY_LIMIT
|
||||
/// (500MB). The limit is shared by all SegmentCollectors
|
||||
pub struct AggregationLimits {
|
||||
/// The counter which is shared between the aggregations for one request.
|
||||
memory_consumption: Arc<AtomicU64>,
|
||||
/// The memory_limit in bytes
|
||||
memory_limit: ByteCount,
|
||||
/// The maximum number of buckets _returned_
|
||||
/// This is not counting intermediate buckets.
|
||||
bucket_limit: u32,
|
||||
}
|
||||
impl Clone for AggregationLimits {
|
||||
fn clone(&self) -> Self {
|
||||
Self {
|
||||
memory_consumption: Arc::clone(&self.memory_consumption),
|
||||
memory_limit: self.memory_limit,
|
||||
bucket_limit: self.bucket_limit,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl Default for AggregationLimits {
|
||||
fn default() -> Self {
|
||||
Self {
|
||||
memory_consumption: Default::default(),
|
||||
memory_limit: DEFAULT_MEMORY_LIMIT.into(),
|
||||
bucket_limit: DEFAULT_BUCKET_LIMIT,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl AggregationLimits {
|
||||
/// *memory_limit*
|
||||
/// memory_limit is defined in bytes.
|
||||
/// Aggregation fails when the estimated memory consumption of the aggregation is higher than
|
||||
/// memory_limit.
|
||||
/// memory_limit will default to `DEFAULT_MEMORY_LIMIT` (500MB)
|
||||
///
|
||||
/// *bucket_limit*
|
||||
/// Limits the maximum number of buckets returned from an aggregation request.
|
||||
/// bucket_limit will default to `DEFAULT_BUCKET_LIMIT` (65000)
|
||||
///
|
||||
/// Note: The returned instance contains a Arc shared counter to track memory consumption.
|
||||
pub fn new(memory_limit: Option<u64>, bucket_limit: Option<u32>) -> Self {
|
||||
Self {
|
||||
memory_consumption: Default::default(),
|
||||
memory_limit: memory_limit.unwrap_or(DEFAULT_MEMORY_LIMIT).into(),
|
||||
bucket_limit: bucket_limit.unwrap_or(DEFAULT_BUCKET_LIMIT),
|
||||
}
|
||||
}
|
||||
|
||||
/// Create a new ResourceLimitGuard, that will release the memory when dropped.
|
||||
pub fn new_guard(&self) -> ResourceLimitGuard {
|
||||
ResourceLimitGuard {
|
||||
/// The counter which is shared between the aggregations for one request.
|
||||
memory_consumption: Arc::clone(&self.memory_consumption),
|
||||
/// The memory_limit in bytes
|
||||
memory_limit: self.memory_limit,
|
||||
allocated_with_the_guard: 0,
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn add_memory_consumed(&self, num_bytes: u64) -> crate::Result<()> {
|
||||
self.memory_consumption
|
||||
.fetch_add(num_bytes, Ordering::Relaxed);
|
||||
validate_memory_consumption(&self.memory_consumption, self.memory_limit)?;
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub(crate) fn get_bucket_limit(&self) -> u32 {
|
||||
self.bucket_limit
|
||||
}
|
||||
}
|
||||
|
||||
fn validate_memory_consumption(
|
||||
memory_consumption: &AtomicU64,
|
||||
memory_limit: ByteCount,
|
||||
) -> Result<(), AggregationError> {
|
||||
// Load the estimated memory consumed by the aggregations
|
||||
let memory_consumed: ByteCount = memory_consumption.load(Ordering::Relaxed).into();
|
||||
if memory_consumed > memory_limit {
|
||||
return Err(AggregationError::MemoryExceeded {
|
||||
limit: memory_limit,
|
||||
current: memory_consumed,
|
||||
});
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
pub struct ResourceLimitGuard {
|
||||
/// The counter which is shared between the aggregations for one request.
|
||||
memory_consumption: Arc<AtomicU64>,
|
||||
/// The memory_limit in bytes
|
||||
memory_limit: ByteCount,
|
||||
/// Allocated memory with this guard.
|
||||
allocated_with_the_guard: u64,
|
||||
}
|
||||
|
||||
impl ResourceLimitGuard {
|
||||
pub(crate) fn add_memory_consumed(&self, num_bytes: u64) -> crate::Result<()> {
|
||||
self.memory_consumption
|
||||
.fetch_add(num_bytes, Ordering::Relaxed);
|
||||
validate_memory_consumption(&self.memory_consumption, self.memory_limit)?;
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
impl Drop for ResourceLimitGuard {
|
||||
/// Removes the memory consumed tracked by this _instance_ of AggregationLimits.
|
||||
/// This is used to clear the segment specific memory consumption all at once.
|
||||
fn drop(&mut self) {
|
||||
self.memory_consumption
|
||||
.fetch_sub(self.allocated_with_the_guard, Ordering::Relaxed);
|
||||
}
|
||||
}
|
||||
@@ -9,25 +9,7 @@
|
||||
//! # Example
|
||||
//!
|
||||
//! ```
|
||||
//! use tantivy::aggregation::bucket::RangeAggregation;
|
||||
//! use tantivy::aggregation::agg_req::BucketAggregationType;
|
||||
//! use tantivy::aggregation::agg_req::{Aggregation, Aggregations};
|
||||
//! use tantivy::aggregation::agg_req::BucketAggregation;
|
||||
//! let agg_req1: Aggregations = vec![
|
||||
//! (
|
||||
//! "range".to_string(),
|
||||
//! Aggregation::Bucket(BucketAggregation {
|
||||
//! bucket_agg: BucketAggregationType::Range(RangeAggregation{
|
||||
//! field: "score".to_string(),
|
||||
//! ranges: vec![(3f64..7f64).into(), (7f64..20f64).into()],
|
||||
//! keyed: false,
|
||||
//! }),
|
||||
//! sub_aggregation: Default::default(),
|
||||
//! }),
|
||||
//! ),
|
||||
//! ]
|
||||
//! .into_iter()
|
||||
//! .collect();
|
||||
//! use tantivy::aggregation::agg_req::Aggregations;
|
||||
//!
|
||||
//! let elasticsearch_compatible_json_req = r#"
|
||||
//! {
|
||||
@@ -41,89 +23,78 @@
|
||||
//! }
|
||||
//! }
|
||||
//! }"#;
|
||||
//! let agg_req2: Aggregations = serde_json::from_str(elasticsearch_compatible_json_req).unwrap();
|
||||
//! assert_eq!(agg_req1, agg_req2);
|
||||
//! let _agg_req: Aggregations = serde_json::from_str(elasticsearch_compatible_json_req).unwrap();
|
||||
//! ```
|
||||
|
||||
use std::collections::{HashMap, HashSet};
|
||||
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
pub use super::bucket::RangeAggregation;
|
||||
use super::bucket::{DateHistogramAggregationReq, HistogramAggregation, TermsAggregation};
|
||||
use super::metric::{
|
||||
AverageAggregation, CountAggregation, MaxAggregation, MinAggregation, StatsAggregation,
|
||||
SumAggregation,
|
||||
use super::bucket::{
|
||||
DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
|
||||
};
|
||||
use super::metric::{
|
||||
AverageAggregation, CountAggregation, MaxAggregation, MinAggregation,
|
||||
PercentilesAggregationReq, StatsAggregation, SumAggregation,
|
||||
};
|
||||
use super::VecWithNames;
|
||||
|
||||
/// The top-level aggregation request structure, which contains [`Aggregation`] and their user
|
||||
/// defined names. It is also used in [buckets](BucketAggregation) to define sub-aggregations.
|
||||
/// defined names. It is also used in buckets aggregations to define sub-aggregations.
|
||||
///
|
||||
/// The key is the user defined name of the aggregation.
|
||||
pub type Aggregations = HashMap<String, Aggregation>;
|
||||
|
||||
/// Like Aggregations, but optimized to work with the aggregation result
|
||||
#[derive(Clone, Debug)]
|
||||
pub(crate) struct AggregationsInternal {
|
||||
pub(crate) metrics: VecWithNames<MetricAggregation>,
|
||||
pub(crate) buckets: VecWithNames<BucketAggregationInternal>,
|
||||
/// Aggregation request.
|
||||
///
|
||||
/// An aggregation is either a bucket or a metric.
|
||||
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
|
||||
#[serde(try_from = "AggregationForDeserialization")]
|
||||
pub struct Aggregation {
|
||||
/// The aggregation variant, which can be either a bucket or a metric.
|
||||
#[serde(flatten)]
|
||||
pub agg: AggregationVariants,
|
||||
/// on the document set in the bucket.
|
||||
#[serde(rename = "aggs")]
|
||||
#[serde(skip_serializing_if = "Aggregations::is_empty")]
|
||||
pub sub_aggregation: Aggregations,
|
||||
}
|
||||
|
||||
impl From<Aggregations> for AggregationsInternal {
|
||||
fn from(aggs: Aggregations) -> Self {
|
||||
let mut metrics = vec![];
|
||||
let mut buckets = vec![];
|
||||
for (key, agg) in aggs {
|
||||
match agg {
|
||||
Aggregation::Bucket(bucket) => buckets.push((
|
||||
key,
|
||||
BucketAggregationInternal {
|
||||
bucket_agg: bucket.bucket_agg,
|
||||
sub_aggregation: bucket.sub_aggregation.into(),
|
||||
},
|
||||
)),
|
||||
Aggregation::Metric(metric) => metrics.push((key, metric)),
|
||||
}
|
||||
}
|
||||
Self {
|
||||
metrics: VecWithNames::from_entries(metrics),
|
||||
buckets: VecWithNames::from_entries(buckets),
|
||||
}
|
||||
/// In order to display proper error message, we cannot rely on flattening
|
||||
/// the json enum. Instead we introduce an intermediary struct to separate
|
||||
/// the aggregation from the subaggregation.
|
||||
#[derive(Deserialize)]
|
||||
struct AggregationForDeserialization {
|
||||
#[serde(flatten)]
|
||||
pub aggs_remaining_json: serde_json::Value,
|
||||
#[serde(rename = "aggs")]
|
||||
#[serde(default)]
|
||||
pub sub_aggregation: Aggregations,
|
||||
}
|
||||
|
||||
impl TryFrom<AggregationForDeserialization> for Aggregation {
|
||||
type Error = serde_json::Error;
|
||||
|
||||
fn try_from(value: AggregationForDeserialization) -> serde_json::Result<Self> {
|
||||
let AggregationForDeserialization {
|
||||
aggs_remaining_json,
|
||||
sub_aggregation,
|
||||
} = value;
|
||||
let agg: AggregationVariants = serde_json::from_value(aggs_remaining_json)?;
|
||||
Ok(Aggregation {
|
||||
agg,
|
||||
sub_aggregation,
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Clone, Debug)]
|
||||
// Like BucketAggregation, but optimized to work with the result
|
||||
pub(crate) struct BucketAggregationInternal {
|
||||
/// Bucket aggregation strategy to group documents.
|
||||
pub bucket_agg: BucketAggregationType,
|
||||
/// The sub_aggregations in the buckets. Each bucket will aggregate on the document set in the
|
||||
/// bucket.
|
||||
pub sub_aggregation: AggregationsInternal,
|
||||
}
|
||||
impl Aggregation {
|
||||
pub(crate) fn sub_aggregation(&self) -> &Aggregations {
|
||||
&self.sub_aggregation
|
||||
}
|
||||
|
||||
impl BucketAggregationInternal {
|
||||
pub(crate) fn as_range(&self) -> Option<&RangeAggregation> {
|
||||
match &self.bucket_agg {
|
||||
BucketAggregationType::Range(range) => Some(range),
|
||||
_ => None,
|
||||
}
|
||||
}
|
||||
pub(crate) fn as_histogram(&self) -> crate::Result<Option<HistogramAggregation>> {
|
||||
match &self.bucket_agg {
|
||||
BucketAggregationType::Histogram(histogram) => Ok(Some(histogram.clone())),
|
||||
BucketAggregationType::DateHistogram(histogram) => {
|
||||
Ok(Some(histogram.to_histogram_req()?))
|
||||
}
|
||||
_ => Ok(None),
|
||||
}
|
||||
}
|
||||
pub(crate) fn as_term(&self) -> Option<&TermsAggregation> {
|
||||
match &self.bucket_agg {
|
||||
BucketAggregationType::Terms(terms) => Some(terms),
|
||||
_ => None,
|
||||
}
|
||||
fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
|
||||
fast_field_names.insert(self.agg.get_fast_field_name().to_string());
|
||||
fast_field_names.extend(get_fast_field_names(&self.sub_aggregation));
|
||||
}
|
||||
}
|
||||
|
||||
@@ -136,97 +107,24 @@ pub fn get_fast_field_names(aggs: &Aggregations) -> HashSet<String> {
|
||||
fast_field_names
|
||||
}
|
||||
|
||||
/// Aggregation request of [`BucketAggregation`] or [`MetricAggregation`].
|
||||
///
|
||||
/// An aggregation is either a bucket or a metric.
|
||||
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
|
||||
#[serde(untagged)]
|
||||
pub enum Aggregation {
|
||||
/// Bucket aggregation, see [`BucketAggregation`] for details.
|
||||
Bucket(BucketAggregation),
|
||||
/// Metric aggregation, see [`MetricAggregation`] for details.
|
||||
Metric(MetricAggregation),
|
||||
}
|
||||
|
||||
impl Aggregation {
|
||||
fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
|
||||
match self {
|
||||
Aggregation::Bucket(bucket) => bucket.get_fast_field_names(fast_field_names),
|
||||
Aggregation::Metric(metric) => {
|
||||
fast_field_names.insert(metric.get_fast_field_name().to_string());
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// BucketAggregations create buckets of documents. Each bucket is associated with a rule which
|
||||
/// determines whether or not a document in the falls into it. In other words, the buckets
|
||||
/// effectively define document sets. Buckets are not necessarily disjunct, therefore a document can
|
||||
/// fall into multiple buckets. In addition to the buckets themselves, the bucket aggregations also
|
||||
/// compute and return the number of documents for each bucket. Bucket aggregations, as opposed to
|
||||
/// metric aggregations, can hold sub-aggregations. These sub-aggregations will be aggregated for
|
||||
/// the buckets created by their "parent" bucket aggregation. There are different bucket
|
||||
/// aggregators, each with a different "bucketing" strategy. Some define a single bucket, some
|
||||
/// define fixed number of multiple buckets, and others dynamically create the buckets during the
|
||||
/// aggregation process.
|
||||
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
|
||||
pub struct BucketAggregation {
|
||||
/// Bucket aggregation strategy to group documents.
|
||||
#[serde(flatten)]
|
||||
pub bucket_agg: BucketAggregationType,
|
||||
/// The sub_aggregations in the buckets. Each bucket will aggregate on the document set in the
|
||||
/// bucket.
|
||||
#[serde(rename = "aggs")]
|
||||
#[serde(default)]
|
||||
#[serde(skip_serializing_if = "Aggregations::is_empty")]
|
||||
pub sub_aggregation: Aggregations,
|
||||
}
|
||||
|
||||
impl BucketAggregation {
|
||||
fn get_fast_field_names(&self, fast_field_names: &mut HashSet<String>) {
|
||||
let fast_field_name = self.bucket_agg.get_fast_field_name();
|
||||
fast_field_names.insert(fast_field_name.to_string());
|
||||
fast_field_names.extend(get_fast_field_names(&self.sub_aggregation));
|
||||
}
|
||||
}
|
||||
|
||||
/// The bucket aggregation types.
|
||||
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
|
||||
pub enum BucketAggregationType {
|
||||
/// All aggregation types.
|
||||
pub enum AggregationVariants {
|
||||
// Bucket aggregation types
|
||||
/// Put data into buckets of user-defined ranges.
|
||||
#[serde(rename = "range")]
|
||||
Range(RangeAggregation),
|
||||
/// Put data into buckets of user-defined ranges.
|
||||
/// Put data into a histogram.
|
||||
#[serde(rename = "histogram")]
|
||||
Histogram(HistogramAggregation),
|
||||
/// Put data into buckets of user-defined ranges.
|
||||
/// Put data into a date histogram.
|
||||
#[serde(rename = "date_histogram")]
|
||||
DateHistogram(DateHistogramAggregationReq),
|
||||
/// Put data into buckets of terms.
|
||||
#[serde(rename = "terms")]
|
||||
Terms(TermsAggregation),
|
||||
}
|
||||
|
||||
impl BucketAggregationType {
|
||||
fn get_fast_field_name(&self) -> &str {
|
||||
match self {
|
||||
BucketAggregationType::Terms(terms) => terms.field.as_str(),
|
||||
BucketAggregationType::Range(range) => range.field.as_str(),
|
||||
BucketAggregationType::Histogram(histogram) => histogram.field.as_str(),
|
||||
BucketAggregationType::DateHistogram(histogram) => histogram.field.as_str(),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// The aggregations in this family compute metrics based on values extracted
|
||||
/// from the documents that are being aggregated. Values are extracted from the fast field of
|
||||
/// the document.
|
||||
|
||||
/// Some aggregations output a single numeric metric (e.g. Average) and are called
|
||||
/// single-value numeric metrics aggregation, others generate multiple metrics (e.g. Stats) and are
|
||||
/// called multi-value numeric metrics aggregation.
|
||||
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
|
||||
pub enum MetricAggregation {
|
||||
// Metric aggregation types
|
||||
/// Computes the average of the extracted values.
|
||||
#[serde(rename = "avg")]
|
||||
Average(AverageAggregation),
|
||||
@@ -246,25 +144,108 @@ pub enum MetricAggregation {
|
||||
/// Computes the sum of the extracted values.
|
||||
#[serde(rename = "sum")]
|
||||
Sum(SumAggregation),
|
||||
/// Computes the sum of the extracted values.
|
||||
#[serde(rename = "percentiles")]
|
||||
Percentiles(PercentilesAggregationReq),
|
||||
}
|
||||
|
||||
impl MetricAggregation {
|
||||
fn get_fast_field_name(&self) -> &str {
|
||||
impl AggregationVariants {
|
||||
/// Returns the name of the field used by the aggregation.
|
||||
pub fn get_fast_field_name(&self) -> &str {
|
||||
match self {
|
||||
MetricAggregation::Average(avg) => avg.field_name(),
|
||||
MetricAggregation::Count(count) => count.field_name(),
|
||||
MetricAggregation::Max(max) => max.field_name(),
|
||||
MetricAggregation::Min(min) => min.field_name(),
|
||||
MetricAggregation::Stats(stats) => stats.field_name(),
|
||||
MetricAggregation::Sum(sum) => sum.field_name(),
|
||||
AggregationVariants::Terms(terms) => terms.field.as_str(),
|
||||
AggregationVariants::Range(range) => range.field.as_str(),
|
||||
AggregationVariants::Histogram(histogram) => histogram.field.as_str(),
|
||||
AggregationVariants::DateHistogram(histogram) => histogram.field.as_str(),
|
||||
AggregationVariants::Average(avg) => avg.field_name(),
|
||||
AggregationVariants::Count(count) => count.field_name(),
|
||||
AggregationVariants::Max(max) => max.field_name(),
|
||||
AggregationVariants::Min(min) => min.field_name(),
|
||||
AggregationVariants::Stats(stats) => stats.field_name(),
|
||||
AggregationVariants::Sum(sum) => sum.field_name(),
|
||||
AggregationVariants::Percentiles(per) => per.field_name(),
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn as_range(&self) -> Option<&RangeAggregation> {
|
||||
match &self {
|
||||
AggregationVariants::Range(range) => Some(range),
|
||||
_ => None,
|
||||
}
|
||||
}
|
||||
pub(crate) fn as_histogram(&self) -> crate::Result<Option<HistogramAggregation>> {
|
||||
match &self {
|
||||
AggregationVariants::Histogram(histogram) => Ok(Some(histogram.clone())),
|
||||
AggregationVariants::DateHistogram(histogram) => {
|
||||
Ok(Some(histogram.to_histogram_req()?))
|
||||
}
|
||||
_ => Ok(None),
|
||||
}
|
||||
}
|
||||
pub(crate) fn as_term(&self) -> Option<&TermsAggregation> {
|
||||
match &self {
|
||||
AggregationVariants::Terms(terms) => Some(terms),
|
||||
_ => None,
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn as_percentile(&self) -> Option<&PercentilesAggregationReq> {
|
||||
match &self {
|
||||
AggregationVariants::Percentiles(percentile_req) => Some(percentile_req),
|
||||
_ => None,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
|
||||
use super::*;
|
||||
|
||||
#[test]
|
||||
fn deser_json_test() {
|
||||
let agg_req_json = r#"{
|
||||
"price_avg": { "avg": { "field": "price" } },
|
||||
"price_count": { "value_count": { "field": "price" } },
|
||||
"price_max": { "max": { "field": "price" } },
|
||||
"price_min": { "min": { "field": "price" } },
|
||||
"price_stats": { "stats": { "field": "price" } },
|
||||
"price_sum": { "sum": { "field": "price" } }
|
||||
}"#;
|
||||
let _agg_req: Aggregations = serde_json::from_str(agg_req_json).unwrap();
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn deser_json_test_bucket() {
|
||||
let agg_req_json = r#"
|
||||
{
|
||||
"termagg": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"order": { "min_price": "desc" }
|
||||
},
|
||||
"aggs": {
|
||||
"min_price": { "min": { "field": "json.mixed_type" } }
|
||||
}
|
||||
},
|
||||
"rangeagg": {
|
||||
"range": {
|
||||
"field": "json.mixed_type",
|
||||
"ranges": [
|
||||
{ "to": 3.0 },
|
||||
{ "from": 19.0, "to": 20.0 },
|
||||
{ "from": 20.0 }
|
||||
]
|
||||
},
|
||||
"aggs": {
|
||||
"average_in_range": { "avg": { "field": "json.mixed_type" } }
|
||||
}
|
||||
}
|
||||
} "#;
|
||||
|
||||
let _agg_req: Aggregations = serde_json::from_str(agg_req_json).unwrap();
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_metric_aggregations_deser() {
|
||||
let agg_req_json = r#"{
|
||||
@@ -278,46 +259,27 @@ mod tests {
|
||||
let agg_req: Aggregations = serde_json::from_str(agg_req_json).unwrap();
|
||||
|
||||
assert!(
|
||||
matches!(agg_req.get("price_avg").unwrap(), Aggregation::Metric(MetricAggregation::Average(avg)) if avg.field == "price")
|
||||
matches!(&agg_req.get("price_avg").unwrap().agg, AggregationVariants::Average(avg) if avg.field == "price")
|
||||
);
|
||||
assert!(
|
||||
matches!(agg_req.get("price_count").unwrap(), Aggregation::Metric(MetricAggregation::Count(count)) if count.field == "price")
|
||||
matches!(&agg_req.get("price_count").unwrap().agg, AggregationVariants::Count(count) if count.field == "price")
|
||||
);
|
||||
assert!(
|
||||
matches!(agg_req.get("price_max").unwrap(), Aggregation::Metric(MetricAggregation::Max(max)) if max.field == "price")
|
||||
matches!(&agg_req.get("price_max").unwrap().agg, AggregationVariants::Max(max) if max.field == "price")
|
||||
);
|
||||
assert!(
|
||||
matches!(agg_req.get("price_min").unwrap(), Aggregation::Metric(MetricAggregation::Min(min)) if min.field == "price")
|
||||
matches!(&agg_req.get("price_min").unwrap().agg, AggregationVariants::Min(min) if min.field == "price")
|
||||
);
|
||||
assert!(
|
||||
matches!(agg_req.get("price_stats").unwrap(), Aggregation::Metric(MetricAggregation::Stats(stats)) if stats.field == "price")
|
||||
matches!(&agg_req.get("price_stats").unwrap().agg, AggregationVariants::Stats(stats) if stats.field == "price")
|
||||
);
|
||||
assert!(
|
||||
matches!(agg_req.get("price_sum").unwrap(), Aggregation::Metric(MetricAggregation::Sum(sum)) if sum.field == "price")
|
||||
matches!(&agg_req.get("price_sum").unwrap().agg, AggregationVariants::Sum(sum) if sum.field == "price")
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn serialize_to_json_test() {
|
||||
let agg_req1: Aggregations = vec![(
|
||||
"range".to_string(),
|
||||
Aggregation::Bucket(BucketAggregation {
|
||||
bucket_agg: BucketAggregationType::Range(RangeAggregation {
|
||||
field: "score".to_string(),
|
||||
ranges: vec![
|
||||
(f64::MIN..3f64).into(),
|
||||
(3f64..7f64).into(),
|
||||
(7f64..20f64).into(),
|
||||
(20f64..f64::MAX).into(),
|
||||
],
|
||||
keyed: true,
|
||||
}),
|
||||
sub_aggregation: Default::default(),
|
||||
}),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect();
|
||||
|
||||
let elasticsearch_compatible_json_req = r#"{
|
||||
"range": {
|
||||
"range": {
|
||||
@@ -342,57 +304,56 @@ mod tests {
|
||||
}
|
||||
}
|
||||
}"#;
|
||||
|
||||
let agg_req1: Aggregations =
|
||||
{ serde_json::from_str(elasticsearch_compatible_json_req).unwrap() };
|
||||
|
||||
let agg_req2: String = serde_json::to_string_pretty(&agg_req1).unwrap();
|
||||
assert_eq!(agg_req2, elasticsearch_compatible_json_req);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_get_fast_field_names() {
|
||||
let agg_req2: Aggregations = vec![
|
||||
(
|
||||
"range".to_string(),
|
||||
Aggregation::Bucket(BucketAggregation {
|
||||
bucket_agg: BucketAggregationType::Range(RangeAggregation {
|
||||
field: "score2".to_string(),
|
||||
ranges: vec![
|
||||
(f64::MIN..3f64).into(),
|
||||
(3f64..7f64).into(),
|
||||
(7f64..20f64).into(),
|
||||
(20f64..f64::MAX).into(),
|
||||
],
|
||||
..Default::default()
|
||||
}),
|
||||
sub_aggregation: Default::default(),
|
||||
}),
|
||||
),
|
||||
(
|
||||
"metric".to_string(),
|
||||
Aggregation::Metric(MetricAggregation::Average(
|
||||
AverageAggregation::from_field_name("field123".to_string()),
|
||||
)),
|
||||
),
|
||||
]
|
||||
.into_iter()
|
||||
.collect();
|
||||
|
||||
let agg_req1: Aggregations = vec![(
|
||||
"range".to_string(),
|
||||
Aggregation::Bucket(BucketAggregation {
|
||||
bucket_agg: BucketAggregationType::Range(RangeAggregation {
|
||||
field: "score".to_string(),
|
||||
ranges: vec![
|
||||
(f64::MIN..3f64).into(),
|
||||
(3f64..7f64).into(),
|
||||
(7f64..20f64).into(),
|
||||
(20f64..f64::MAX).into(),
|
||||
let range_agg: Aggregation = {
|
||||
serde_json::from_value(json!({
|
||||
"range": {
|
||||
"field": "score",
|
||||
"ranges": [
|
||||
{ "to": 3.0 },
|
||||
{ "from": 3.0, "to": 7.0 },
|
||||
{ "from": 7.0, "to": 20.0 },
|
||||
{ "from": 20.0 }
|
||||
],
|
||||
..Default::default()
|
||||
}),
|
||||
sub_aggregation: agg_req2,
|
||||
}),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect();
|
||||
}
|
||||
|
||||
}))
|
||||
.unwrap()
|
||||
};
|
||||
|
||||
let agg_req1: Aggregations = {
|
||||
serde_json::from_value(json!({
|
||||
"range1": range_agg,
|
||||
"range2":{
|
||||
"range": {
|
||||
"field": "score2",
|
||||
"ranges": [
|
||||
{ "to": 3.0 },
|
||||
{ "from": 3.0, "to": 7.0 },
|
||||
{ "from": 7.0, "to": 20.0 },
|
||||
{ "from": 20.0 }
|
||||
],
|
||||
},
|
||||
"aggs": {
|
||||
"metric": {
|
||||
"avg": {
|
||||
"field": "field123"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}))
|
||||
.unwrap()
|
||||
};
|
||||
|
||||
assert_eq!(
|
||||
get_fast_field_names(&agg_req1),
|
||||
|
||||
@@ -1,11 +1,9 @@
|
||||
//! This will enhance the request tree with access to the fastfield and metadata.
|
||||
|
||||
use std::rc::Rc;
|
||||
use std::sync::atomic::AtomicU32;
|
||||
use columnar::{Column, ColumnBlockAccessor, ColumnType, StrColumn};
|
||||
|
||||
use columnar::{Column, ColumnType, StrColumn};
|
||||
|
||||
use super::agg_req::{Aggregation, Aggregations, BucketAggregationType, MetricAggregation};
|
||||
use super::agg_limits::ResourceLimitGuard;
|
||||
use super::agg_req::{Aggregation, AggregationVariants, Aggregations};
|
||||
use super::bucket::{
|
||||
DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
|
||||
};
|
||||
@@ -13,162 +11,329 @@ use super::metric::{
|
||||
AverageAggregation, CountAggregation, MaxAggregation, MinAggregation, StatsAggregation,
|
||||
SumAggregation,
|
||||
};
|
||||
use super::segment_agg_result::BucketCount;
|
||||
use super::segment_agg_result::AggregationLimits;
|
||||
use super::VecWithNames;
|
||||
use crate::{SegmentReader, TantivyError};
|
||||
use crate::aggregation::{f64_to_fastfield_u64, Key};
|
||||
use crate::SegmentReader;
|
||||
|
||||
#[derive(Clone, Default)]
|
||||
#[derive(Default)]
|
||||
pub(crate) struct AggregationsWithAccessor {
|
||||
pub metrics: VecWithNames<MetricAggregationWithAccessor>,
|
||||
pub buckets: VecWithNames<BucketAggregationWithAccessor>,
|
||||
pub aggs: VecWithNames<AggregationWithAccessor>,
|
||||
}
|
||||
|
||||
impl AggregationsWithAccessor {
|
||||
fn from_data(
|
||||
metrics: VecWithNames<MetricAggregationWithAccessor>,
|
||||
buckets: VecWithNames<BucketAggregationWithAccessor>,
|
||||
) -> Self {
|
||||
Self { metrics, buckets }
|
||||
fn from_data(aggs: VecWithNames<AggregationWithAccessor>) -> Self {
|
||||
Self { aggs }
|
||||
}
|
||||
|
||||
pub fn is_empty(&self) -> bool {
|
||||
self.metrics.is_empty() && self.buckets.is_empty()
|
||||
self.aggs.is_empty()
|
||||
}
|
||||
}
|
||||
|
||||
#[derive(Clone)]
|
||||
pub struct BucketAggregationWithAccessor {
|
||||
pub struct AggregationWithAccessor {
|
||||
/// In general there can be buckets without fast field access, e.g. buckets that are created
|
||||
/// based on search terms. So eventually this needs to be Option or moved.
|
||||
/// based on search terms. That is not that case currently, but eventually this needs to be
|
||||
/// Option or moved.
|
||||
pub(crate) accessor: Column<u64>,
|
||||
/// Load insert u64 for missing use case
|
||||
pub(crate) missing_value_for_accessor: Option<u64>,
|
||||
pub(crate) str_dict_column: Option<StrColumn>,
|
||||
pub(crate) field_type: ColumnType,
|
||||
pub(crate) bucket_agg: BucketAggregationType,
|
||||
pub(crate) sub_aggregation: AggregationsWithAccessor,
|
||||
pub(crate) bucket_count: BucketCount,
|
||||
pub(crate) limits: ResourceLimitGuard,
|
||||
pub(crate) column_block_accessor: ColumnBlockAccessor<u64>,
|
||||
/// Used for missing term aggregation, which checks all columns for existence.
|
||||
/// By convention the missing aggregation is chosen, when this property is set
|
||||
/// (instead bein set in `agg`).
|
||||
/// If this needs to used by other aggregations, we need to refactor this.
|
||||
pub(crate) accessors: Vec<Column<u64>>,
|
||||
pub(crate) agg: Aggregation,
|
||||
}
|
||||
|
||||
impl BucketAggregationWithAccessor {
|
||||
fn try_from_bucket(
|
||||
bucket: &BucketAggregationType,
|
||||
impl AggregationWithAccessor {
|
||||
/// May return multiple accessors if the aggregation is e.g. on mixed field types.
|
||||
fn try_from_agg(
|
||||
agg: &Aggregation,
|
||||
sub_aggregation: &Aggregations,
|
||||
reader: &SegmentReader,
|
||||
bucket_count: Rc<AtomicU32>,
|
||||
max_bucket_count: u32,
|
||||
) -> crate::Result<BucketAggregationWithAccessor> {
|
||||
let mut str_dict_column = None;
|
||||
let (accessor, field_type) = match &bucket {
|
||||
BucketAggregationType::Range(RangeAggregation {
|
||||
field: field_name, ..
|
||||
}) => get_ff_reader_and_validate(reader, field_name)?,
|
||||
BucketAggregationType::Histogram(HistogramAggregation {
|
||||
field: field_name, ..
|
||||
}) => get_ff_reader_and_validate(reader, field_name)?,
|
||||
BucketAggregationType::DateHistogram(DateHistogramAggregationReq {
|
||||
field: field_name,
|
||||
..
|
||||
}) => get_ff_reader_and_validate(reader, field_name)?,
|
||||
BucketAggregationType::Terms(TermsAggregation {
|
||||
limits: AggregationLimits,
|
||||
) -> crate::Result<Vec<AggregationWithAccessor>> {
|
||||
let add_agg_with_accessor = |accessor: Column<u64>,
|
||||
column_type: ColumnType,
|
||||
aggs: &mut Vec<AggregationWithAccessor>|
|
||||
-> crate::Result<()> {
|
||||
let res = AggregationWithAccessor {
|
||||
accessor,
|
||||
accessors: Vec::new(),
|
||||
field_type: column_type,
|
||||
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
|
||||
sub_aggregation,
|
||||
reader,
|
||||
&limits,
|
||||
)?,
|
||||
agg: agg.clone(),
|
||||
limits: limits.new_guard(),
|
||||
missing_value_for_accessor: None,
|
||||
str_dict_column: None,
|
||||
column_block_accessor: Default::default(),
|
||||
};
|
||||
aggs.push(res);
|
||||
Ok(())
|
||||
};
|
||||
|
||||
let mut res: Vec<AggregationWithAccessor> = Vec::new();
|
||||
use AggregationVariants::*;
|
||||
match &agg.agg {
|
||||
Range(RangeAggregation {
|
||||
field: field_name, ..
|
||||
}) => {
|
||||
str_dict_column = reader.fast_fields().str(field_name)?;
|
||||
get_ff_reader_and_validate(reader, field_name)?
|
||||
let (accessor, column_type) =
|
||||
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
|
||||
add_agg_with_accessor(accessor, column_type, &mut res)?;
|
||||
}
|
||||
Histogram(HistogramAggregation {
|
||||
field: field_name, ..
|
||||
}) => {
|
||||
let (accessor, column_type) =
|
||||
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
|
||||
add_agg_with_accessor(accessor, column_type, &mut res)?;
|
||||
}
|
||||
DateHistogram(DateHistogramAggregationReq {
|
||||
field: field_name, ..
|
||||
}) => {
|
||||
let (accessor, column_type) =
|
||||
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
|
||||
add_agg_with_accessor(accessor, column_type, &mut res)?;
|
||||
}
|
||||
Terms(TermsAggregation {
|
||||
field: field_name,
|
||||
missing,
|
||||
..
|
||||
}) => {
|
||||
let str_dict_column = reader.fast_fields().str(field_name)?;
|
||||
let allowed_column_types = [
|
||||
ColumnType::I64,
|
||||
ColumnType::U64,
|
||||
ColumnType::F64,
|
||||
ColumnType::Str,
|
||||
ColumnType::DateTime,
|
||||
// ColumnType::Bytes Unsupported
|
||||
// ColumnType::Bool Unsupported
|
||||
// ColumnType::IpAddr Unsupported
|
||||
];
|
||||
|
||||
// In case the column is empty we want the shim column to match the missing type
|
||||
let fallback_type = missing
|
||||
.as_ref()
|
||||
.map(|missing| match missing {
|
||||
Key::Str(_) => ColumnType::Str,
|
||||
Key::F64(_) => ColumnType::F64,
|
||||
})
|
||||
.unwrap_or(ColumnType::U64);
|
||||
let column_and_types = get_all_ff_reader_or_empty(
|
||||
reader,
|
||||
field_name,
|
||||
Some(&allowed_column_types),
|
||||
fallback_type,
|
||||
)?;
|
||||
let missing_and_more_than_one_col = column_and_types.len() > 1 && missing.is_some();
|
||||
let text_on_non_text_col = column_and_types.len() == 1
|
||||
&& column_and_types[0].1.numerical_type().is_some()
|
||||
&& missing
|
||||
.as_ref()
|
||||
.map(|m| matches!(m, Key::Str(_)))
|
||||
.unwrap_or(false);
|
||||
|
||||
// Actually we could convert the text to a number and have the fast path, if it is
|
||||
// provided in Rfc3339 format. But this use case is probably common
|
||||
// enough to justify the effort.
|
||||
let text_on_date_col = column_and_types.len() == 1
|
||||
&& column_and_types[0].1 == ColumnType::DateTime
|
||||
&& missing
|
||||
.as_ref()
|
||||
.map(|m| matches!(m, Key::Str(_)))
|
||||
.unwrap_or(false);
|
||||
|
||||
let use_special_missing_agg =
|
||||
missing_and_more_than_one_col || text_on_non_text_col || text_on_date_col;
|
||||
if use_special_missing_agg {
|
||||
let column_and_types =
|
||||
get_all_ff_reader_or_empty(reader, field_name, None, fallback_type)?;
|
||||
|
||||
let accessors: Vec<Column> =
|
||||
column_and_types.iter().map(|(a, _)| a.clone()).collect();
|
||||
let agg_wit_acc = AggregationWithAccessor {
|
||||
missing_value_for_accessor: None,
|
||||
accessor: accessors[0].clone(),
|
||||
accessors,
|
||||
field_type: ColumnType::U64,
|
||||
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
|
||||
sub_aggregation,
|
||||
reader,
|
||||
&limits,
|
||||
)?,
|
||||
agg: agg.clone(),
|
||||
str_dict_column: str_dict_column.clone(),
|
||||
limits: limits.new_guard(),
|
||||
column_block_accessor: Default::default(),
|
||||
};
|
||||
res.push(agg_wit_acc);
|
||||
}
|
||||
|
||||
for (accessor, column_type) in column_and_types {
|
||||
let missing_value_term_agg = if use_special_missing_agg {
|
||||
None
|
||||
} else {
|
||||
missing.clone()
|
||||
};
|
||||
|
||||
let missing_value_for_accessor =
|
||||
if let Some(missing) = missing_value_term_agg.as_ref() {
|
||||
get_missing_val(column_type, missing, agg.agg.get_fast_field_name())?
|
||||
} else {
|
||||
None
|
||||
};
|
||||
|
||||
let agg = AggregationWithAccessor {
|
||||
missing_value_for_accessor,
|
||||
accessor,
|
||||
accessors: Vec::new(),
|
||||
field_type: column_type,
|
||||
sub_aggregation: get_aggs_with_segment_accessor_and_validate(
|
||||
sub_aggregation,
|
||||
reader,
|
||||
&limits,
|
||||
)?,
|
||||
agg: agg.clone(),
|
||||
str_dict_column: str_dict_column.clone(),
|
||||
limits: limits.new_guard(),
|
||||
column_block_accessor: Default::default(),
|
||||
};
|
||||
res.push(agg);
|
||||
}
|
||||
}
|
||||
Average(AverageAggregation {
|
||||
field: field_name, ..
|
||||
})
|
||||
| Count(CountAggregation {
|
||||
field: field_name, ..
|
||||
})
|
||||
| Max(MaxAggregation {
|
||||
field: field_name, ..
|
||||
})
|
||||
| Min(MinAggregation {
|
||||
field: field_name, ..
|
||||
})
|
||||
| Stats(StatsAggregation {
|
||||
field: field_name, ..
|
||||
})
|
||||
| Sum(SumAggregation {
|
||||
field: field_name, ..
|
||||
}) => {
|
||||
let (accessor, column_type) =
|
||||
get_ff_reader(reader, field_name, Some(get_numeric_or_date_column_types()))?;
|
||||
add_agg_with_accessor(accessor, column_type, &mut res)?;
|
||||
}
|
||||
Percentiles(percentiles) => {
|
||||
let (accessor, column_type) = get_ff_reader(
|
||||
reader,
|
||||
percentiles.field_name(),
|
||||
Some(get_numeric_or_date_column_types()),
|
||||
)?;
|
||||
add_agg_with_accessor(accessor, column_type, &mut res)?;
|
||||
}
|
||||
};
|
||||
let sub_aggregation = sub_aggregation.clone();
|
||||
Ok(BucketAggregationWithAccessor {
|
||||
accessor,
|
||||
field_type,
|
||||
sub_aggregation: get_aggs_with_accessor_and_validate(
|
||||
&sub_aggregation,
|
||||
reader,
|
||||
bucket_count.clone(),
|
||||
max_bucket_count,
|
||||
)?,
|
||||
bucket_agg: bucket.clone(),
|
||||
str_dict_column,
|
||||
bucket_count: BucketCount {
|
||||
bucket_count,
|
||||
max_bucket_count,
|
||||
},
|
||||
})
|
||||
|
||||
Ok(res)
|
||||
}
|
||||
}
|
||||
|
||||
/// Contains the metric request and the fast field accessor.
|
||||
#[derive(Clone)]
|
||||
pub struct MetricAggregationWithAccessor {
|
||||
pub metric: MetricAggregation,
|
||||
pub field_type: ColumnType,
|
||||
pub accessor: Column<u64>,
|
||||
}
|
||||
|
||||
impl MetricAggregationWithAccessor {
|
||||
fn try_from_metric(
|
||||
metric: &MetricAggregation,
|
||||
reader: &SegmentReader,
|
||||
) -> crate::Result<MetricAggregationWithAccessor> {
|
||||
match &metric {
|
||||
MetricAggregation::Average(AverageAggregation { field: field_name })
|
||||
| MetricAggregation::Count(CountAggregation { field: field_name })
|
||||
| MetricAggregation::Max(MaxAggregation { field: field_name })
|
||||
| MetricAggregation::Min(MinAggregation { field: field_name })
|
||||
| MetricAggregation::Stats(StatsAggregation { field: field_name })
|
||||
| MetricAggregation::Sum(SumAggregation { field: field_name }) => {
|
||||
let (accessor, field_type) = get_ff_reader_and_validate(reader, field_name)?;
|
||||
|
||||
Ok(MetricAggregationWithAccessor {
|
||||
accessor,
|
||||
field_type,
|
||||
metric: metric.clone(),
|
||||
})
|
||||
}
|
||||
fn get_missing_val(
|
||||
column_type: ColumnType,
|
||||
missing: &Key,
|
||||
field_name: &str,
|
||||
) -> crate::Result<Option<u64>> {
|
||||
let missing_val = match missing {
|
||||
Key::Str(_) if column_type == ColumnType::Str => Some(u64::MAX),
|
||||
// Allow fallback to number on text fields
|
||||
Key::F64(_) if column_type == ColumnType::Str => Some(u64::MAX),
|
||||
Key::F64(val) if column_type.numerical_type().is_some() => {
|
||||
f64_to_fastfield_u64(*val, &column_type)
|
||||
}
|
||||
}
|
||||
_ => {
|
||||
return Err(crate::TantivyError::InvalidArgument(format!(
|
||||
"Missing value {:?} for field {} is not supported for column type {:?}",
|
||||
missing, field_name, column_type
|
||||
)));
|
||||
}
|
||||
};
|
||||
Ok(missing_val)
|
||||
}
|
||||
|
||||
pub(crate) fn get_aggs_with_accessor_and_validate(
|
||||
fn get_numeric_or_date_column_types() -> &'static [ColumnType] {
|
||||
&[
|
||||
ColumnType::F64,
|
||||
ColumnType::U64,
|
||||
ColumnType::I64,
|
||||
ColumnType::DateTime,
|
||||
]
|
||||
}
|
||||
|
||||
pub(crate) fn get_aggs_with_segment_accessor_and_validate(
|
||||
aggs: &Aggregations,
|
||||
reader: &SegmentReader,
|
||||
bucket_count: Rc<AtomicU32>,
|
||||
max_bucket_count: u32,
|
||||
limits: &AggregationLimits,
|
||||
) -> crate::Result<AggregationsWithAccessor> {
|
||||
let mut metrics = vec![];
|
||||
let mut buckets = vec![];
|
||||
let mut aggss = Vec::new();
|
||||
for (key, agg) in aggs.iter() {
|
||||
match agg {
|
||||
Aggregation::Bucket(bucket) => buckets.push((
|
||||
key.to_string(),
|
||||
BucketAggregationWithAccessor::try_from_bucket(
|
||||
&bucket.bucket_agg,
|
||||
&bucket.sub_aggregation,
|
||||
reader,
|
||||
Rc::clone(&bucket_count),
|
||||
max_bucket_count,
|
||||
)?,
|
||||
)),
|
||||
Aggregation::Metric(metric) => metrics.push((
|
||||
key.to_string(),
|
||||
MetricAggregationWithAccessor::try_from_metric(metric, reader)?,
|
||||
)),
|
||||
let aggs = AggregationWithAccessor::try_from_agg(
|
||||
agg,
|
||||
agg.sub_aggregation(),
|
||||
reader,
|
||||
limits.clone(),
|
||||
)?;
|
||||
for agg in aggs {
|
||||
aggss.push((key.to_string(), agg));
|
||||
}
|
||||
}
|
||||
Ok(AggregationsWithAccessor::from_data(
|
||||
VecWithNames::from_entries(metrics),
|
||||
VecWithNames::from_entries(buckets),
|
||||
VecWithNames::from_entries(aggss),
|
||||
))
|
||||
}
|
||||
|
||||
/// Get fast field reader with given cardinatility.
|
||||
fn get_ff_reader_and_validate(
|
||||
/// Get fast field reader or empty as default.
|
||||
fn get_ff_reader(
|
||||
reader: &SegmentReader,
|
||||
field_name: &str,
|
||||
allowed_column_types: Option<&[ColumnType]>,
|
||||
) -> crate::Result<(columnar::Column<u64>, ColumnType)> {
|
||||
let ff_fields = reader.fast_fields();
|
||||
let ff_field_with_type = ff_fields
|
||||
.u64_lenient_with_type(field_name)?
|
||||
.ok_or_else(|| {
|
||||
TantivyError::InvalidArgument(format!("No fast field found for field: {}", field_name))
|
||||
})?;
|
||||
.u64_lenient_for_type(allowed_column_types, field_name)?
|
||||
.unwrap_or_else(|| {
|
||||
(
|
||||
Column::build_empty_column(reader.num_docs()),
|
||||
ColumnType::U64,
|
||||
)
|
||||
});
|
||||
Ok(ff_field_with_type)
|
||||
}
|
||||
|
||||
/// Get all fast field reader or empty as default.
|
||||
///
|
||||
/// Is guaranteed to return at least one column.
|
||||
fn get_all_ff_reader_or_empty(
|
||||
reader: &SegmentReader,
|
||||
field_name: &str,
|
||||
allowed_column_types: Option<&[ColumnType]>,
|
||||
fallback_type: ColumnType,
|
||||
) -> crate::Result<Vec<(columnar::Column<u64>, ColumnType)>> {
|
||||
let ff_fields = reader.fast_fields();
|
||||
let mut ff_field_with_type =
|
||||
ff_fields.u64_lenient_for_type_all(allowed_column_types, field_name)?;
|
||||
if ff_field_with_type.is_empty() {
|
||||
ff_field_with_type.push((Column::build_empty_column(reader.num_docs()), fallback_type));
|
||||
}
|
||||
Ok(ff_field_with_type)
|
||||
}
|
||||
|
||||
@@ -7,11 +7,9 @@
|
||||
use rustc_hash::FxHashMap;
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
use super::agg_req::BucketAggregationInternal;
|
||||
use super::bucket::GetDocCount;
|
||||
use super::intermediate_agg_result::{IntermediateBucketResult, IntermediateMetricResult};
|
||||
use super::metric::{SingleMetricResult, Stats};
|
||||
use super::Key;
|
||||
use super::metric::{PercentilesMetricResult, SingleMetricResult, Stats};
|
||||
use super::{AggregationError, Key};
|
||||
use crate::TantivyError;
|
||||
|
||||
#[derive(Clone, Default, Debug, PartialEq, Serialize, Deserialize)]
|
||||
@@ -19,6 +17,13 @@ use crate::TantivyError;
|
||||
pub struct AggregationResults(pub FxHashMap<String, AggregationResult>);
|
||||
|
||||
impl AggregationResults {
|
||||
pub(crate) fn get_bucket_count(&self) -> u64 {
|
||||
self.0
|
||||
.values()
|
||||
.map(|agg| agg.get_bucket_count())
|
||||
.sum::<u64>()
|
||||
}
|
||||
|
||||
pub(crate) fn get_value_from_aggregation(
|
||||
&self,
|
||||
name: &str,
|
||||
@@ -29,8 +34,7 @@ impl AggregationResults {
|
||||
} else {
|
||||
// Validation is be done during request parsing, so we can't reach this state.
|
||||
Err(TantivyError::InternalError(format!(
|
||||
"Can't find aggregation {:?} in sub-aggregations",
|
||||
name
|
||||
"Can't find aggregation {name:?} in sub-aggregations"
|
||||
)))
|
||||
}
|
||||
}
|
||||
@@ -47,6 +51,13 @@ pub enum AggregationResult {
|
||||
}
|
||||
|
||||
impl AggregationResult {
|
||||
pub(crate) fn get_bucket_count(&self) -> u64 {
|
||||
match self {
|
||||
AggregationResult::BucketResult(bucket) => bucket.get_bucket_count(),
|
||||
AggregationResult::MetricResult(_) => 0,
|
||||
}
|
||||
}
|
||||
|
||||
pub(crate) fn get_value_from_aggregation(
|
||||
&self,
|
||||
_name: &str,
|
||||
@@ -79,6 +90,8 @@ pub enum MetricResult {
|
||||
Stats(Stats),
|
||||
/// Sum metric result.
|
||||
Sum(SingleMetricResult),
|
||||
/// Sum metric result.
|
||||
Percentiles(PercentilesMetricResult),
|
||||
}
|
||||
|
||||
impl MetricResult {
|
||||
@@ -90,30 +103,9 @@ impl MetricResult {
|
||||
MetricResult::Min(min) => Ok(min.value),
|
||||
MetricResult::Stats(stats) => stats.get_value(agg_property),
|
||||
MetricResult::Sum(sum) => Ok(sum.value),
|
||||
}
|
||||
}
|
||||
}
|
||||
impl From<IntermediateMetricResult> for MetricResult {
|
||||
fn from(metric: IntermediateMetricResult) -> Self {
|
||||
match metric {
|
||||
IntermediateMetricResult::Average(intermediate_avg) => {
|
||||
MetricResult::Average(intermediate_avg.finalize().into())
|
||||
}
|
||||
IntermediateMetricResult::Count(intermediate_count) => {
|
||||
MetricResult::Count(intermediate_count.finalize().into())
|
||||
}
|
||||
IntermediateMetricResult::Max(intermediate_max) => {
|
||||
MetricResult::Max(intermediate_max.finalize().into())
|
||||
}
|
||||
IntermediateMetricResult::Min(intermediate_min) => {
|
||||
MetricResult::Min(intermediate_min.finalize().into())
|
||||
}
|
||||
IntermediateMetricResult::Stats(intermediate_stats) => {
|
||||
MetricResult::Stats(intermediate_stats.finalize())
|
||||
}
|
||||
IntermediateMetricResult::Sum(intermediate_sum) => {
|
||||
MetricResult::Sum(intermediate_sum.finalize().into())
|
||||
}
|
||||
MetricResult::Percentiles(_) => Err(TantivyError::AggregationError(
|
||||
AggregationError::InvalidRequest("percentiles can't be used to order".to_string()),
|
||||
)),
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -153,9 +145,20 @@ pub enum BucketResult {
|
||||
}
|
||||
|
||||
impl BucketResult {
|
||||
pub(crate) fn empty_from_req(req: &BucketAggregationInternal) -> crate::Result<Self> {
|
||||
let empty_bucket = IntermediateBucketResult::empty_from_req(&req.bucket_agg);
|
||||
empty_bucket.into_final_bucket_result(req)
|
||||
pub(crate) fn get_bucket_count(&self) -> u64 {
|
||||
match self {
|
||||
BucketResult::Range { buckets } => {
|
||||
buckets.iter().map(|bucket| bucket.get_bucket_count()).sum()
|
||||
}
|
||||
BucketResult::Histogram { buckets } => {
|
||||
buckets.iter().map(|bucket| bucket.get_bucket_count()).sum()
|
||||
}
|
||||
BucketResult::Terms {
|
||||
buckets,
|
||||
sum_other_doc_count: _,
|
||||
doc_count_error_upper_bound: _,
|
||||
} => buckets.iter().map(|bucket| bucket.get_bucket_count()).sum(),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -170,6 +173,15 @@ pub enum BucketEntries<T> {
|
||||
HashMap(FxHashMap<String, T>),
|
||||
}
|
||||
|
||||
impl<T> BucketEntries<T> {
|
||||
fn iter<'a>(&'a self) -> Box<dyn Iterator<Item = &T> + 'a> {
|
||||
match self {
|
||||
BucketEntries::Vec(vec) => Box::new(vec.iter()),
|
||||
BucketEntries::HashMap(map) => Box::new(map.values()),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// This is the default entry for a bucket, which contains a key, count, and optionally
|
||||
/// sub-aggregations.
|
||||
///
|
||||
@@ -209,6 +221,11 @@ pub struct BucketEntry {
|
||||
/// Sub-aggregations in this bucket.
|
||||
pub sub_aggregation: AggregationResults,
|
||||
}
|
||||
impl BucketEntry {
|
||||
pub(crate) fn get_bucket_count(&self) -> u64 {
|
||||
1 + self.sub_aggregation.get_bucket_count()
|
||||
}
|
||||
}
|
||||
impl GetDocCount for &BucketEntry {
|
||||
fn doc_count(&self) -> u64 {
|
||||
self.doc_count
|
||||
@@ -272,3 +289,8 @@ pub struct RangeBucketEntry {
|
||||
#[serde(skip_serializing_if = "Option::is_none")]
|
||||
pub to_as_string: Option<String>,
|
||||
}
|
||||
impl RangeBucketEntry {
|
||||
pub(crate) fn get_bucket_count(&self) -> u64 {
|
||||
1 + self.sub_aggregation.get_bucket_count()
|
||||
}
|
||||
}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -37,10 +37,10 @@ pub struct DateHistogramAggregationReq {
|
||||
interval: Option<String>,
|
||||
#[doc(hidden)]
|
||||
/// Only for validation
|
||||
date_interval: Option<String>,
|
||||
calendar_interval: Option<String>,
|
||||
/// The field to aggregate on.
|
||||
pub field: String,
|
||||
/// The format to format dates.
|
||||
/// The format to format dates. Unsupported currently.
|
||||
pub format: Option<String>,
|
||||
/// The interval to chunk your data range. Each bucket spans a value range of
|
||||
/// [0..fixed_interval). Accepted values
|
||||
@@ -62,9 +62,18 @@ pub struct DateHistogramAggregationReq {
|
||||
///
|
||||
/// Fractional time values are not supported, but you can address this by shifting to another
|
||||
/// time unit (e.g., `1.5h` could instead be specified as `90m`).
|
||||
pub fixed_interval: String,
|
||||
///
|
||||
/// `Option` for validation, the parameter is not optional
|
||||
pub fixed_interval: Option<String>,
|
||||
/// Intervals implicitly defines an absolute grid of buckets `[interval * k, interval * (k +
|
||||
/// 1))`.
|
||||
///
|
||||
/// Offset makes it possible to shift this grid into
|
||||
/// `[offset + interval * k, offset + interval * (k + 1))`. Offset has to be in the range [0,
|
||||
/// interval).
|
||||
///
|
||||
/// The `offset` parameter is has the same syntax as the `fixed_interval` parameter, but
|
||||
/// also allows for negative values.
|
||||
pub offset: Option<String>,
|
||||
/// The minimum number of documents in a bucket to be returned. Defaults to 0.
|
||||
pub min_doc_count: Option<u64>,
|
||||
@@ -75,7 +84,7 @@ pub struct DateHistogramAggregationReq {
|
||||
/// hard_bounds only limits the buckets, to force a range set both extended_bounds and
|
||||
/// hard_bounds to the same range.
|
||||
///
|
||||
/// Needs to be provided as timestamp in microseconds precision.
|
||||
/// Needs to be provided as timestamp in millisecond precision.
|
||||
///
|
||||
/// ## Example
|
||||
/// ```json
|
||||
@@ -86,7 +95,7 @@ pub struct DateHistogramAggregationReq {
|
||||
/// "interval": "1d",
|
||||
/// "hard_bounds": {
|
||||
/// "min": 0,
|
||||
/// "max": 1420502400000000
|
||||
/// "max": 1420502400000
|
||||
/// }
|
||||
/// }
|
||||
/// }
|
||||
@@ -112,26 +121,31 @@ impl DateHistogramAggregationReq {
|
||||
self.validate()?;
|
||||
Ok(HistogramAggregation {
|
||||
field: self.field.to_string(),
|
||||
interval: parse_into_microseconds(&self.fixed_interval)? as f64,
|
||||
interval: parse_into_milliseconds(self.fixed_interval.as_ref().unwrap())? as f64,
|
||||
offset: self
|
||||
.offset
|
||||
.as_ref()
|
||||
.map(|offset| parse_offset_into_microseconds(offset))
|
||||
.map(|offset| parse_offset_into_milliseconds(offset))
|
||||
.transpose()?
|
||||
.map(|el| el as f64),
|
||||
min_doc_count: self.min_doc_count,
|
||||
hard_bounds: None,
|
||||
extended_bounds: None,
|
||||
hard_bounds: self.hard_bounds,
|
||||
extended_bounds: self.extended_bounds,
|
||||
keyed: self.keyed,
|
||||
})
|
||||
}
|
||||
|
||||
fn validate(&self) -> crate::Result<()> {
|
||||
if self.interval.is_some() {
|
||||
if let Some(interval) = self.interval.as_ref() {
|
||||
return Err(crate::TantivyError::InvalidArgument(format!(
|
||||
"`interval` parameter {:?} in date histogram is unsupported, only \
|
||||
`fixed_interval` is supported",
|
||||
self.interval
|
||||
"`interval` parameter {interval:?} in date histogram is unsupported, only \
|
||||
`fixed_interval` is supported"
|
||||
)));
|
||||
}
|
||||
if let Some(interval) = self.calendar_interval.as_ref() {
|
||||
return Err(crate::TantivyError::InvalidArgument(format!(
|
||||
"`calendar_interval` parameter {interval:?} in date histogram is unsupported, \
|
||||
only `fixed_interval` is supported"
|
||||
)));
|
||||
}
|
||||
if self.format.is_some() {
|
||||
@@ -140,15 +154,13 @@ impl DateHistogramAggregationReq {
|
||||
));
|
||||
}
|
||||
|
||||
if self.date_interval.is_some() {
|
||||
if self.fixed_interval.is_none() {
|
||||
return Err(crate::TantivyError::InvalidArgument(
|
||||
"date_interval in date histogram is unsupported, only `fixed_interval` is \
|
||||
supported"
|
||||
.to_string(),
|
||||
"fixed_interval in date histogram is missing".to_string(),
|
||||
));
|
||||
}
|
||||
|
||||
parse_into_microseconds(&self.fixed_interval)?;
|
||||
parse_into_milliseconds(self.fixed_interval.as_ref().unwrap())?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
@@ -169,9 +181,12 @@ pub enum DateHistogramParseError {
|
||||
/// Offset invalid
|
||||
#[error("passed offset is invalid {0:?}")]
|
||||
InvalidOffset(String),
|
||||
/// Value out of bounds
|
||||
#[error("passed value is out of bounds: {0:?}")]
|
||||
OutOfBounds(String),
|
||||
}
|
||||
|
||||
fn parse_offset_into_microseconds(input: &str) -> Result<i64, AggregationError> {
|
||||
fn parse_offset_into_milliseconds(input: &str) -> Result<i64, AggregationError> {
|
||||
let is_sign = |byte| &[byte] == b"-" || &[byte] == b"+";
|
||||
if input.is_empty() {
|
||||
return Err(DateHistogramParseError::InvalidOffset(input.to_string()).into());
|
||||
@@ -180,18 +195,18 @@ fn parse_offset_into_microseconds(input: &str) -> Result<i64, AggregationError>
|
||||
let has_sign = is_sign(input.as_bytes()[0]);
|
||||
if has_sign {
|
||||
let (sign, input) = input.split_at(1);
|
||||
let val = parse_into_microseconds(input)?;
|
||||
let val = parse_into_milliseconds(input)?;
|
||||
if sign == "-" {
|
||||
Ok(-val)
|
||||
} else {
|
||||
Ok(val)
|
||||
}
|
||||
} else {
|
||||
parse_into_microseconds(input)
|
||||
parse_into_milliseconds(input)
|
||||
}
|
||||
}
|
||||
|
||||
fn parse_into_microseconds(input: &str) -> Result<i64, AggregationError> {
|
||||
fn parse_into_milliseconds(input: &str) -> Result<i64, AggregationError> {
|
||||
let split_boundary = input
|
||||
.as_bytes()
|
||||
.iter()
|
||||
@@ -210,16 +225,21 @@ fn parse_into_microseconds(input: &str) -> Result<i64, AggregationError> {
|
||||
// here and being defensive does not hurt.
|
||||
.map_err(|_err| DateHistogramParseError::NumberMissing(input.to_string()))?;
|
||||
|
||||
let multiplier_from_unit = match unit {
|
||||
"ms" => 1,
|
||||
"s" => 1000,
|
||||
"m" => 60 * 1000,
|
||||
"h" => 60 * 60 * 1000,
|
||||
"d" => 24 * 60 * 60 * 1000,
|
||||
let unit_in_ms = match unit {
|
||||
"ms" | "milliseconds" => 1,
|
||||
"s" | "seconds" => 1000,
|
||||
"m" | "minutes" => 60 * 1000,
|
||||
"h" | "hours" => 60 * 60 * 1000,
|
||||
"d" | "days" => 24 * 60 * 60 * 1000,
|
||||
_ => return Err(DateHistogramParseError::UnitNotRecognized(unit.to_string()).into()),
|
||||
};
|
||||
|
||||
Ok(number * multiplier_from_unit * 1000)
|
||||
let val = number * unit_in_ms;
|
||||
// The field type is in nanoseconds precision, so validate the value to fit the range
|
||||
val.checked_mul(1_000_000)
|
||||
.ok_or_else(|| DateHistogramParseError::OutOfBounds(input.to_string()))?;
|
||||
|
||||
Ok(val)
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
@@ -234,49 +254,50 @@ mod tests {
|
||||
use crate::Index;
|
||||
|
||||
#[test]
|
||||
fn test_parse_into_microseconds() {
|
||||
assert_eq!(parse_into_microseconds("1m").unwrap(), 60_000_000);
|
||||
assert_eq!(parse_into_microseconds("2m").unwrap(), 120_000_000);
|
||||
fn test_parse_into_millisecs() {
|
||||
assert_eq!(parse_into_milliseconds("1m").unwrap(), 60_000);
|
||||
assert_eq!(parse_into_milliseconds("2m").unwrap(), 120_000);
|
||||
assert_eq!(parse_into_milliseconds("2minutes").unwrap(), 120_000);
|
||||
assert_eq!(
|
||||
parse_into_microseconds("2y").unwrap_err(),
|
||||
parse_into_milliseconds("2y").unwrap_err(),
|
||||
DateHistogramParseError::UnitNotRecognized("y".to_string()).into()
|
||||
);
|
||||
assert_eq!(
|
||||
parse_into_microseconds("2000").unwrap_err(),
|
||||
parse_into_milliseconds("2000").unwrap_err(),
|
||||
DateHistogramParseError::UnitMissing("2000".to_string()).into()
|
||||
);
|
||||
assert_eq!(
|
||||
parse_into_microseconds("ms").unwrap_err(),
|
||||
parse_into_milliseconds("ms").unwrap_err(),
|
||||
DateHistogramParseError::NumberMissing("ms".to_string()).into()
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_parse_offset_into_microseconds() {
|
||||
assert_eq!(parse_offset_into_microseconds("1m").unwrap(), 60_000_000);
|
||||
assert_eq!(parse_offset_into_microseconds("+1m").unwrap(), 60_000_000);
|
||||
assert_eq!(parse_offset_into_microseconds("-1m").unwrap(), -60_000_000);
|
||||
assert_eq!(parse_offset_into_microseconds("2m").unwrap(), 120_000_000);
|
||||
assert_eq!(parse_offset_into_microseconds("+2m").unwrap(), 120_000_000);
|
||||
assert_eq!(parse_offset_into_microseconds("-2m").unwrap(), -120_000_000);
|
||||
assert_eq!(parse_offset_into_microseconds("-2ms").unwrap(), -2_000);
|
||||
fn test_parse_offset_into_milliseconds() {
|
||||
assert_eq!(parse_offset_into_milliseconds("1m").unwrap(), 60_000);
|
||||
assert_eq!(parse_offset_into_milliseconds("+1m").unwrap(), 60_000);
|
||||
assert_eq!(parse_offset_into_milliseconds("-1m").unwrap(), -60_000);
|
||||
assert_eq!(parse_offset_into_milliseconds("2m").unwrap(), 120_000);
|
||||
assert_eq!(parse_offset_into_milliseconds("+2m").unwrap(), 120_000);
|
||||
assert_eq!(parse_offset_into_milliseconds("-2m").unwrap(), -120_000);
|
||||
assert_eq!(parse_offset_into_milliseconds("-2ms").unwrap(), -2);
|
||||
assert_eq!(
|
||||
parse_offset_into_microseconds("2y").unwrap_err(),
|
||||
parse_offset_into_milliseconds("2y").unwrap_err(),
|
||||
DateHistogramParseError::UnitNotRecognized("y".to_string()).into()
|
||||
);
|
||||
assert_eq!(
|
||||
parse_offset_into_microseconds("2000").unwrap_err(),
|
||||
parse_offset_into_milliseconds("2000").unwrap_err(),
|
||||
DateHistogramParseError::UnitMissing("2000".to_string()).into()
|
||||
);
|
||||
assert_eq!(
|
||||
parse_offset_into_microseconds("ms").unwrap_err(),
|
||||
parse_offset_into_milliseconds("ms").unwrap_err(),
|
||||
DateHistogramParseError::NumberMissing("ms".to_string()).into()
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn test_parse_into_milliseconds_do_not_accept_non_ascii() {
|
||||
assert!(parse_into_microseconds("1m").is_err());
|
||||
assert!(parse_into_milliseconds("1m").is_err());
|
||||
}
|
||||
|
||||
pub fn get_test_index_from_docs(
|
||||
@@ -315,30 +336,322 @@ mod tests {
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn histogram_test_date_force_merge_segments() -> crate::Result<()> {
|
||||
fn histogram_test_date_force_merge_segments() {
|
||||
histogram_test_date_merge_segments(true)
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn histogram_test_date() -> crate::Result<()> {
|
||||
fn histogram_test_date() {
|
||||
histogram_test_date_merge_segments(false)
|
||||
}
|
||||
fn histogram_test_date_merge_segments(merge_segments: bool) -> crate::Result<()> {
|
||||
|
||||
fn histogram_test_date_merge_segments(merge_segments: bool) {
|
||||
let docs = vec![
|
||||
vec![r#"{ "date": "2015-01-01T12:10:30Z", "text": "aaa" }"#],
|
||||
vec![r#"{ "date": "2015-01-01T11:11:30Z", "text": "bbb" }"#],
|
||||
vec![r#"{ "date": "2015-01-02T00:00:00Z", "text": "bbb" }"#],
|
||||
vec![r#"{ "date": "2015-01-06T00:00:00Z", "text": "ccc" }"#],
|
||||
];
|
||||
let index = get_test_index_from_docs(merge_segments, &docs).unwrap();
|
||||
|
||||
let index = get_test_index_from_docs(merge_segments, &docs)?;
|
||||
// 30day + offset
|
||||
{
|
||||
// 30day + offset
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"sales_over_time": {
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "30d",
|
||||
"offset": "-4d"
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_str(
|
||||
&serde_json::to_string(&elasticsearch_compatible_json).unwrap(),
|
||||
)
|
||||
.unwrap();
|
||||
let res = exec_request(agg_req, &index).unwrap();
|
||||
let expected_res = json!({
|
||||
"sales_over_time" : {
|
||||
"buckets" : [
|
||||
{
|
||||
"key_as_string" : "2015-01-01T00:00:00Z",
|
||||
"key" : 1420070400000.0,
|
||||
"doc_count" : 4
|
||||
}
|
||||
]
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
}
|
||||
|
||||
{
|
||||
// 30day + offset + sub_agg
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"sales_over_time": {
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "30d",
|
||||
"offset": "-4d"
|
||||
},
|
||||
"aggs": {
|
||||
"texts": {
|
||||
"terms": {"field": "text"}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_str(
|
||||
&serde_json::to_string(&elasticsearch_compatible_json).unwrap(),
|
||||
)
|
||||
.unwrap();
|
||||
let res = exec_request(agg_req, &index).unwrap();
|
||||
let expected_res = json!({
|
||||
"sales_over_time" : {
|
||||
"buckets" : [
|
||||
{
|
||||
"key_as_string" : "2015-01-01T00:00:00Z",
|
||||
"key" : 1420070400000.0,
|
||||
"doc_count" : 4,
|
||||
"texts": {
|
||||
"buckets": [
|
||||
{
|
||||
"doc_count": 2,
|
||||
"key": "bbb"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": "ccc"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": "aaa"
|
||||
}
|
||||
],
|
||||
"doc_count_error_upper_bound": 0,
|
||||
"sum_other_doc_count": 0
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
}
|
||||
{
|
||||
// 1day
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"sales_over_time": {
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "1d"
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_str(
|
||||
&serde_json::to_string(&elasticsearch_compatible_json).unwrap(),
|
||||
)
|
||||
.unwrap();
|
||||
let res = exec_request(agg_req, &index).unwrap();
|
||||
let expected_res = json!( {
|
||||
"sales_over_time": {
|
||||
"buckets": [
|
||||
{
|
||||
"doc_count": 2,
|
||||
"key": 1420070400000.0,
|
||||
"key_as_string": "2015-01-01T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": 1420156800000.0,
|
||||
"key_as_string": "2015-01-02T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1420243200000.0,
|
||||
"key_as_string": "2015-01-03T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1420329600000.0,
|
||||
"key_as_string": "2015-01-04T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1420416000000.0,
|
||||
"key_as_string": "2015-01-05T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": 1420502400000.0,
|
||||
"key_as_string": "2015-01-06T00:00:00Z"
|
||||
}
|
||||
]
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
}
|
||||
|
||||
{
|
||||
// 1day + extended_bounds
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"sales_over_time": {
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "1d",
|
||||
"extended_bounds": {
|
||||
"min": 1419984000000.0,
|
||||
"max": 1420588800000.0
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_str(
|
||||
&serde_json::to_string(&elasticsearch_compatible_json).unwrap(),
|
||||
)
|
||||
.unwrap();
|
||||
let res = exec_request(agg_req, &index).unwrap();
|
||||
let expected_res = json!({
|
||||
"sales_over_time" : {
|
||||
"buckets": [
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1419984000000.0,
|
||||
"key_as_string": "2014-12-31T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 2,
|
||||
"key": 1420070400000.0,
|
||||
"key_as_string": "2015-01-01T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": 1420156800000.0,
|
||||
"key_as_string": "2015-01-02T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1420243200000.0,
|
||||
"key_as_string": "2015-01-03T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1420329600000.0,
|
||||
"key_as_string": "2015-01-04T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1420416000000.0,
|
||||
"key_as_string": "2015-01-05T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": 1420502400000.0,
|
||||
"key_as_string": "2015-01-06T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1420588800000.0,
|
||||
"key_as_string": "2015-01-07T00:00:00Z"
|
||||
}
|
||||
]
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
}
|
||||
{
|
||||
// 1day + hard_bounds + extended_bounds
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"sales_over_time": {
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "1d",
|
||||
"hard_bounds": {
|
||||
"min": 1420156800000.0,
|
||||
"max": 1420243200000.0
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_str(
|
||||
&serde_json::to_string(&elasticsearch_compatible_json).unwrap(),
|
||||
)
|
||||
.unwrap();
|
||||
let res = exec_request(agg_req, &index).unwrap();
|
||||
let expected_res = json!({
|
||||
"sales_over_time" : {
|
||||
"buckets": [
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": 1420156800000.0,
|
||||
"key_as_string": "2015-01-02T00:00:00Z"
|
||||
}
|
||||
]
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
}
|
||||
|
||||
{
|
||||
// 1day + hard_bounds as Rfc3339
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"sales_over_time": {
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "1d",
|
||||
"hard_bounds": {
|
||||
"min": "2015-01-02T00:00:00Z",
|
||||
"max": "2015-01-02T12:00:00Z"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_str(
|
||||
&serde_json::to_string(&elasticsearch_compatible_json).unwrap(),
|
||||
)
|
||||
.unwrap();
|
||||
let res = exec_request(agg_req, &index).unwrap();
|
||||
let expected_res = json!({
|
||||
"sales_over_time" : {
|
||||
"buckets": [
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": 1420156800000.0,
|
||||
"key_as_string": "2015-01-02T00:00:00Z"
|
||||
}
|
||||
]
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
}
|
||||
}
|
||||
#[test]
|
||||
fn histogram_test_invalid_req() {
|
||||
let docs = vec![];
|
||||
|
||||
let index = get_test_index_from_docs(false, &docs).unwrap();
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"sales_over_time": {
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "30d",
|
||||
"interval": "30d",
|
||||
"offset": "-4d"
|
||||
}
|
||||
}
|
||||
@@ -348,128 +661,10 @@ mod tests {
|
||||
let agg_req: Aggregations =
|
||||
serde_json::from_str(&serde_json::to_string(&elasticsearch_compatible_json).unwrap())
|
||||
.unwrap();
|
||||
let res = exec_request(agg_req, &index)?;
|
||||
let expected_res = json!({
|
||||
"sales_over_time" : {
|
||||
"buckets" : [
|
||||
{
|
||||
"key_as_string" : "2015-01-01T00:00:00Z",
|
||||
"key" : 1420070400000000.0,
|
||||
"doc_count" : 4
|
||||
}
|
||||
]
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
|
||||
// 30day + offset + sub_agg
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"sales_over_time": {
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "30d",
|
||||
"offset": "-4d"
|
||||
},
|
||||
"aggs": {
|
||||
"texts": {
|
||||
"terms": {"field": "text"}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
let err = exec_request(agg_req, &index).unwrap_err();
|
||||
assert_eq!(
|
||||
err.to_string(),
|
||||
r#"An invalid argument was passed: '`interval` parameter "30d" in date histogram is unsupported, only `fixed_interval` is supported'"#
|
||||
);
|
||||
|
||||
let agg_req: Aggregations =
|
||||
serde_json::from_str(&serde_json::to_string(&elasticsearch_compatible_json).unwrap())
|
||||
.unwrap();
|
||||
let res = exec_request(agg_req, &index)?;
|
||||
println!("{}", serde_json::to_string_pretty(&res).unwrap());
|
||||
let expected_res = json!({
|
||||
"sales_over_time" : {
|
||||
"buckets" : [
|
||||
{
|
||||
"key_as_string" : "2015-01-01T00:00:00Z",
|
||||
"key" : 1420070400000000.0,
|
||||
"doc_count" : 4,
|
||||
"texts": {
|
||||
"buckets": [
|
||||
{
|
||||
"doc_count": 2,
|
||||
"key": "bbb"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": "ccc"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": "aaa"
|
||||
}
|
||||
],
|
||||
"doc_count_error_upper_bound": 0,
|
||||
"sum_other_doc_count": 0
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
|
||||
// 1day
|
||||
let elasticsearch_compatible_json = json!(
|
||||
{
|
||||
"sales_over_time": {
|
||||
"date_histogram": {
|
||||
"field": "date",
|
||||
"fixed_interval": "1d"
|
||||
}
|
||||
}
|
||||
}
|
||||
);
|
||||
|
||||
let agg_req: Aggregations =
|
||||
serde_json::from_str(&serde_json::to_string(&elasticsearch_compatible_json).unwrap())
|
||||
.unwrap();
|
||||
let res = exec_request(agg_req, &index)?;
|
||||
let expected_res = json!( {
|
||||
"sales_over_time": {
|
||||
"buckets": [
|
||||
{
|
||||
"doc_count": 2,
|
||||
"key": 1420070400000000.0,
|
||||
"key_as_string": "2015-01-01T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": 1420156800000000.0,
|
||||
"key_as_string": "2015-01-02T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1420243200000000.0,
|
||||
"key_as_string": "2015-01-03T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1420329600000000.0,
|
||||
"key_as_string": "2015-01-04T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 0,
|
||||
"key": 1420416000000000.0,
|
||||
"key_as_string": "2015-01-05T00:00:00Z"
|
||||
},
|
||||
{
|
||||
"doc_count": 1,
|
||||
"key": 1420502400000000.0,
|
||||
"key_as_string": "2015-01-06T00:00:00Z"
|
||||
}
|
||||
]
|
||||
}
|
||||
});
|
||||
assert_eq!(res, expected_res);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
@@ -1,24 +1,39 @@
|
||||
//! Module for all bucket aggregations.
|
||||
//!
|
||||
//! BucketAggregations create buckets of documents
|
||||
//! [`BucketAggregation`](super::agg_req::BucketAggregation).
|
||||
//! BucketAggregations create buckets of documents.
|
||||
//! Each bucket is associated with a rule which
|
||||
//! determines whether or not a document in the falls into it. In other words, the buckets
|
||||
//! effectively define document sets. Buckets are not necessarily disjunct, therefore a document can
|
||||
//! fall into multiple buckets. In addition to the buckets themselves, the bucket aggregations also
|
||||
//! compute and return the number of documents for each bucket. Bucket aggregations, as opposed to
|
||||
//! metric aggregations, can hold sub-aggregations. These sub-aggregations will be aggregated for
|
||||
//! the buckets created by their "parent" bucket aggregation. There are different bucket
|
||||
//! aggregators, each with a different "bucketing" strategy. Some define a single bucket, some
|
||||
//! define fixed number of multiple buckets, and others dynamically create the buckets during the
|
||||
//! aggregation process.
|
||||
//!
|
||||
//! Results of final buckets are [`BucketResult`](super::agg_result::BucketResult).
|
||||
//! Results of intermediate buckets are
|
||||
//! [`IntermediateBucketResult`](super::intermediate_agg_result::IntermediateBucketResult)
|
||||
//!
|
||||
//! ## Supported Bucket Aggregations
|
||||
//! - [Histogram](HistogramAggregation)
|
||||
//! - [DateHistogram](DateHistogramAggregationReq)
|
||||
//! - [Range](RangeAggregation)
|
||||
//! - [Terms](TermsAggregation)
|
||||
|
||||
mod histogram;
|
||||
mod range;
|
||||
mod term_agg;
|
||||
mod term_missing_agg;
|
||||
|
||||
use std::collections::HashMap;
|
||||
|
||||
pub(crate) use histogram::SegmentHistogramCollector;
|
||||
pub use histogram::*;
|
||||
pub(crate) use range::SegmentRangeCollector;
|
||||
pub use range::*;
|
||||
use serde::{de, Deserialize, Deserializer, Serialize, Serializer};
|
||||
pub use term_agg::*;
|
||||
pub use term_missing_agg::*;
|
||||
|
||||
/// Order for buckets in a bucket aggregation.
|
||||
#[derive(Clone, Copy, Debug, PartialEq, Serialize, Deserialize, Default)]
|
||||
|
||||
@@ -5,16 +5,17 @@ use columnar::{ColumnType, MonotonicallyMappableToU64};
|
||||
use rustc_hash::FxHashMap;
|
||||
use serde::{Deserialize, Serialize};
|
||||
|
||||
use crate::aggregation::agg_limits::ResourceLimitGuard;
|
||||
use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
|
||||
use crate::aggregation::intermediate_agg_result::{
|
||||
IntermediateAggregationResults, IntermediateBucketResult, IntermediateRangeBucketEntry,
|
||||
IntermediateRangeBucketResult,
|
||||
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
|
||||
IntermediateRangeBucketEntry, IntermediateRangeBucketResult,
|
||||
};
|
||||
use crate::aggregation::segment_agg_result::{
|
||||
build_segment_agg_collector, BucketCount, SegmentAggregationCollector,
|
||||
build_segment_agg_collector, SegmentAggregationCollector,
|
||||
};
|
||||
use crate::aggregation::{
|
||||
f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey, VecWithNames,
|
||||
f64_from_fastfield_u64, f64_to_fastfield_u64, format_date, Key, SerializedKey,
|
||||
};
|
||||
use crate::TantivyError;
|
||||
|
||||
@@ -157,16 +158,18 @@ impl SegmentRangeBucketEntry {
|
||||
self,
|
||||
agg_with_accessor: &AggregationsWithAccessor,
|
||||
) -> crate::Result<IntermediateRangeBucketEntry> {
|
||||
let sub_aggregation = if let Some(sub_aggregation) = self.sub_aggregation {
|
||||
sub_aggregation.into_intermediate_aggregations_result(agg_with_accessor)?
|
||||
let mut sub_aggregation_res = IntermediateAggregationResults::default();
|
||||
if let Some(sub_aggregation) = self.sub_aggregation {
|
||||
sub_aggregation
|
||||
.add_intermediate_aggregation_result(agg_with_accessor, &mut sub_aggregation_res)?
|
||||
} else {
|
||||
Default::default()
|
||||
};
|
||||
|
||||
Ok(IntermediateRangeBucketEntry {
|
||||
key: self.key,
|
||||
key: self.key.into(),
|
||||
doc_count: self.doc_count,
|
||||
sub_aggregation,
|
||||
sub_aggregation: sub_aggregation_res,
|
||||
from: self.from,
|
||||
to: self.to,
|
||||
})
|
||||
@@ -174,13 +177,14 @@ impl SegmentRangeBucketEntry {
|
||||
}
|
||||
|
||||
impl SegmentAggregationCollector for SegmentRangeCollector {
|
||||
fn into_intermediate_aggregations_result(
|
||||
fn add_intermediate_aggregation_result(
|
||||
self: Box<Self>,
|
||||
agg_with_accessor: &AggregationsWithAccessor,
|
||||
) -> crate::Result<IntermediateAggregationResults> {
|
||||
results: &mut IntermediateAggregationResults,
|
||||
) -> crate::Result<()> {
|
||||
let field_type = self.column_type;
|
||||
let name = agg_with_accessor.buckets.keys[self.accessor_idx].to_string();
|
||||
let sub_agg = &agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
|
||||
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
|
||||
let sub_agg = &agg_with_accessor.aggs.values[self.accessor_idx].sub_aggregation;
|
||||
|
||||
let buckets: FxHashMap<SerializedKey, IntermediateRangeBucketEntry> = self
|
||||
.buckets
|
||||
@@ -200,49 +204,49 @@ impl SegmentAggregationCollector for SegmentRangeCollector {
|
||||
column_type: Some(self.column_type),
|
||||
});
|
||||
|
||||
let buckets = Some(VecWithNames::from_entries(vec![(name, bucket)]));
|
||||
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
|
||||
|
||||
Ok(IntermediateAggregationResults {
|
||||
metrics: None,
|
||||
buckets,
|
||||
})
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn collect(
|
||||
&mut self,
|
||||
doc: crate::DocId,
|
||||
agg_with_accessor: &AggregationsWithAccessor,
|
||||
agg_with_accessor: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<()> {
|
||||
self.collect_block(&[doc], agg_with_accessor)
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn collect_block(
|
||||
&mut self,
|
||||
docs: &[crate::DocId],
|
||||
agg_with_accessor: &AggregationsWithAccessor,
|
||||
agg_with_accessor: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<()> {
|
||||
let accessor = &agg_with_accessor.buckets.values[self.accessor_idx].accessor;
|
||||
let sub_aggregation_accessor =
|
||||
&agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
|
||||
for doc in docs {
|
||||
for val in accessor.values_for_doc(*doc) {
|
||||
let bucket_pos = self.get_bucket_pos(val);
|
||||
let bucket_agg_accessor = &mut agg_with_accessor.aggs.values[self.accessor_idx];
|
||||
|
||||
let bucket = &mut self.buckets[bucket_pos];
|
||||
bucket_agg_accessor
|
||||
.column_block_accessor
|
||||
.fetch_block(docs, &bucket_agg_accessor.accessor);
|
||||
|
||||
bucket.bucket.doc_count += 1;
|
||||
if let Some(sub_aggregation) = &mut bucket.bucket.sub_aggregation {
|
||||
sub_aggregation.collect(*doc, sub_aggregation_accessor)?;
|
||||
}
|
||||
for (doc, val) in bucket_agg_accessor.column_block_accessor.iter_docid_vals() {
|
||||
let bucket_pos = self.get_bucket_pos(val);
|
||||
|
||||
let bucket = &mut self.buckets[bucket_pos];
|
||||
|
||||
bucket.bucket.doc_count += 1;
|
||||
if let Some(sub_aggregation) = &mut bucket.bucket.sub_aggregation {
|
||||
sub_aggregation.collect(doc, &mut bucket_agg_accessor.sub_aggregation)?;
|
||||
}
|
||||
}
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn flush(&mut self, agg_with_accessor: &AggregationsWithAccessor) -> crate::Result<()> {
|
||||
fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
|
||||
let sub_aggregation_accessor =
|
||||
&agg_with_accessor.buckets.values[self.accessor_idx].sub_aggregation;
|
||||
&mut agg_with_accessor.aggs.values[self.accessor_idx].sub_aggregation;
|
||||
|
||||
for bucket in self.buckets.iter_mut() {
|
||||
if let Some(sub_agg) = bucket.bucket.sub_aggregation.as_mut() {
|
||||
@@ -257,8 +261,8 @@ impl SegmentAggregationCollector for SegmentRangeCollector {
|
||||
impl SegmentRangeCollector {
|
||||
pub(crate) fn from_req_and_validate(
|
||||
req: &RangeAggregation,
|
||||
sub_aggregation: &AggregationsWithAccessor,
|
||||
bucket_count: &BucketCount,
|
||||
sub_aggregation: &mut AggregationsWithAccessor,
|
||||
limits: &ResourceLimitGuard,
|
||||
field_type: ColumnType,
|
||||
accessor_idx: usize,
|
||||
) -> crate::Result<Self> {
|
||||
@@ -302,8 +306,9 @@ impl SegmentRangeCollector {
|
||||
})
|
||||
.collect::<crate::Result<_>>()?;
|
||||
|
||||
bucket_count.add_count(buckets.len() as u32);
|
||||
bucket_count.validate_bucket_count()?;
|
||||
limits.add_memory_consumed(
|
||||
buckets.len() as u64 * std::mem::size_of::<SegmentRangeAndBucketEntry>() as u64,
|
||||
)?;
|
||||
|
||||
Ok(SegmentRangeCollector {
|
||||
buckets,
|
||||
@@ -440,14 +445,12 @@ mod tests {
|
||||
use serde_json::Value;
|
||||
|
||||
use super::*;
|
||||
use crate::aggregation::agg_req::{
|
||||
Aggregation, Aggregations, BucketAggregation, BucketAggregationType, MetricAggregation,
|
||||
};
|
||||
use crate::aggregation::metric::AverageAggregation;
|
||||
use crate::aggregation::agg_req::Aggregations;
|
||||
use crate::aggregation::tests::{
|
||||
exec_request, exec_request_with_query, get_test_index_2_segments,
|
||||
get_test_index_with_num_docs,
|
||||
};
|
||||
use crate::aggregation::AggregationLimits;
|
||||
|
||||
pub fn get_collector_from_ranges(
|
||||
ranges: Vec<RangeAggregationRange>,
|
||||
@@ -461,8 +464,8 @@ mod tests {
|
||||
|
||||
SegmentRangeCollector::from_req_and_validate(
|
||||
&req,
|
||||
&Default::default(),
|
||||
&Default::default(),
|
||||
&mut Default::default(),
|
||||
&AggregationLimits::default().new_guard(),
|
||||
field_type,
|
||||
0,
|
||||
)
|
||||
@@ -473,19 +476,18 @@ mod tests {
|
||||
fn range_fraction_test() -> crate::Result<()> {
|
||||
let index = get_test_index_with_num_docs(false, 100)?;
|
||||
|
||||
let agg_req: Aggregations = vec![(
|
||||
"range".to_string(),
|
||||
Aggregation::Bucket(BucketAggregation {
|
||||
bucket_agg: BucketAggregationType::Range(RangeAggregation {
|
||||
field: "fraction_f64".to_string(),
|
||||
ranges: vec![(0f64..0.1f64).into(), (0.1f64..0.2f64).into()],
|
||||
..Default::default()
|
||||
}),
|
||||
sub_aggregation: Default::default(),
|
||||
}),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"range": {
|
||||
"range": {
|
||||
"field": "fraction_f64",
|
||||
"ranges": [
|
||||
{"from": 0.0, "to": 0.1},
|
||||
{"from": 0.1, "to": 0.2},
|
||||
]
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
@@ -505,28 +507,25 @@ mod tests {
|
||||
fn range_fraction_test_with_sub_agg() -> crate::Result<()> {
|
||||
let index = get_test_index_with_num_docs(false, 100)?;
|
||||
|
||||
let sub_agg_req: Aggregations = vec![(
|
||||
"score_f64".to_string(),
|
||||
Aggregation::Metric(MetricAggregation::Average(
|
||||
AverageAggregation::from_field_name("score_f64".to_string()),
|
||||
)),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect();
|
||||
let sub_agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"avg": { "avg": { "field": "score_f64", } }
|
||||
|
||||
let agg_req: Aggregations = vec![(
|
||||
"range".to_string(),
|
||||
Aggregation::Bucket(BucketAggregation {
|
||||
bucket_agg: BucketAggregationType::Range(RangeAggregation {
|
||||
field: "fraction_f64".to_string(),
|
||||
ranges: vec![(0f64..0.1f64).into(), (0.1f64..0.2f64).into()],
|
||||
..Default::default()
|
||||
}),
|
||||
sub_aggregation: sub_agg_req,
|
||||
}),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect();
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"range": {
|
||||
"range": {
|
||||
"field": "fraction_f64",
|
||||
"ranges": [
|
||||
{"from": 0.0, "to": 0.1},
|
||||
{"from": 0.1, "to": 0.2},
|
||||
]
|
||||
},
|
||||
"aggs": sub_agg_req
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
@@ -546,19 +545,19 @@ mod tests {
|
||||
fn range_keyed_buckets_test() -> crate::Result<()> {
|
||||
let index = get_test_index_with_num_docs(false, 100)?;
|
||||
|
||||
let agg_req: Aggregations = vec![(
|
||||
"range".to_string(),
|
||||
Aggregation::Bucket(BucketAggregation {
|
||||
bucket_agg: BucketAggregationType::Range(RangeAggregation {
|
||||
field: "fraction_f64".to_string(),
|
||||
ranges: vec![(0f64..0.1f64).into(), (0.1f64..0.2f64).into()],
|
||||
keyed: true,
|
||||
}),
|
||||
sub_aggregation: Default::default(),
|
||||
}),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"range": {
|
||||
"range": {
|
||||
"field": "fraction_f64",
|
||||
"ranges": [
|
||||
{"from": 0.0, "to": 0.1},
|
||||
{"from": 0.1, "to": 0.2},
|
||||
],
|
||||
"keyed": true
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
@@ -583,30 +582,19 @@ mod tests {
|
||||
fn range_custom_key_test() -> crate::Result<()> {
|
||||
let index = get_test_index_with_num_docs(false, 100)?;
|
||||
|
||||
let agg_req: Aggregations = vec![(
|
||||
"range".to_string(),
|
||||
Aggregation::Bucket(BucketAggregation {
|
||||
bucket_agg: BucketAggregationType::Range(RangeAggregation {
|
||||
field: "fraction_f64".to_string(),
|
||||
ranges: vec![
|
||||
RangeAggregationRange {
|
||||
key: Some("custom-key-0-to-0.1".to_string()),
|
||||
from: Some(0f64),
|
||||
to: Some(0.1f64),
|
||||
},
|
||||
RangeAggregationRange {
|
||||
key: None,
|
||||
from: Some(0.1f64),
|
||||
to: Some(0.2f64),
|
||||
},
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"range": {
|
||||
"range": {
|
||||
"field": "fraction_f64",
|
||||
"ranges": [
|
||||
{"key": "custom-key-0-to-0.1", "from": 0.0, "to": 0.1},
|
||||
{"from": 0.1, "to": 0.2},
|
||||
],
|
||||
keyed: false,
|
||||
}),
|
||||
sub_aggregation: Default::default(),
|
||||
}),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect();
|
||||
"keyed": false
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
@@ -640,30 +628,19 @@ mod tests {
|
||||
fn range_date_test_with_opt(merge_segments: bool) -> crate::Result<()> {
|
||||
let index = get_test_index_2_segments(merge_segments)?;
|
||||
|
||||
let agg_req: Aggregations = vec![(
|
||||
"date_ranges".to_string(),
|
||||
Aggregation::Bucket(BucketAggregation {
|
||||
bucket_agg: BucketAggregationType::Range(RangeAggregation {
|
||||
field: "date".to_string(),
|
||||
ranges: vec![
|
||||
RangeAggregationRange {
|
||||
key: None,
|
||||
from: None,
|
||||
to: Some(1546300800000000.0f64),
|
||||
},
|
||||
RangeAggregationRange {
|
||||
key: None,
|
||||
from: Some(1546300800000000.0f64),
|
||||
to: Some(1546387200000000.0f64),
|
||||
},
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"date_ranges": {
|
||||
"range": {
|
||||
"field": "date",
|
||||
"ranges": [
|
||||
{"to": 1546300800000000000i64},
|
||||
{"from": 1546300800000000000i64, "to": 1546387200000000000i64},
|
||||
],
|
||||
keyed: false,
|
||||
}),
|
||||
sub_aggregation: Default::default(),
|
||||
}),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect();
|
||||
"keyed": false
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let agg_res = exec_request(agg_req, &index)?;
|
||||
|
||||
@@ -702,23 +679,18 @@ mod tests {
|
||||
fn range_custom_key_keyed_buckets_test() -> crate::Result<()> {
|
||||
let index = get_test_index_with_num_docs(false, 100)?;
|
||||
|
||||
let agg_req: Aggregations = vec![(
|
||||
"range".to_string(),
|
||||
Aggregation::Bucket(BucketAggregation {
|
||||
bucket_agg: BucketAggregationType::Range(RangeAggregation {
|
||||
field: "fraction_f64".to_string(),
|
||||
ranges: vec![RangeAggregationRange {
|
||||
key: Some("custom-key-0-to-0.1".to_string()),
|
||||
from: Some(0f64),
|
||||
to: Some(0.1f64),
|
||||
}],
|
||||
keyed: true,
|
||||
}),
|
||||
sub_aggregation: Default::default(),
|
||||
}),
|
||||
)]
|
||||
.into_iter()
|
||||
.collect();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"range": {
|
||||
"range": {
|
||||
"field": "fraction_f64",
|
||||
"ranges": [
|
||||
{"key": "custom-key-0-to-0.1", "from": 0.0, "to": 0.1},
|
||||
],
|
||||
"keyed": true
|
||||
},
|
||||
}
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
476
src/aggregation/bucket/term_missing_agg.rs
Normal file
476
src/aggregation/bucket/term_missing_agg.rs
Normal file
@@ -0,0 +1,476 @@
|
||||
use rustc_hash::FxHashMap;
|
||||
|
||||
use crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor;
|
||||
use crate::aggregation::intermediate_agg_result::{
|
||||
IntermediateAggregationResult, IntermediateAggregationResults, IntermediateBucketResult,
|
||||
IntermediateKey, IntermediateTermBucketEntry, IntermediateTermBucketResult,
|
||||
};
|
||||
use crate::aggregation::segment_agg_result::{
|
||||
build_segment_agg_collector, SegmentAggregationCollector,
|
||||
};
|
||||
|
||||
/// The specialized missing term aggregation.
|
||||
#[derive(Default, Debug, Clone)]
|
||||
pub struct TermMissingAgg {
|
||||
missing_count: u32,
|
||||
accessor_idx: usize,
|
||||
sub_agg: Option<Box<dyn SegmentAggregationCollector>>,
|
||||
}
|
||||
impl TermMissingAgg {
|
||||
pub(crate) fn new(
|
||||
accessor_idx: usize,
|
||||
sub_aggregations: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<Self> {
|
||||
let has_sub_aggregations = !sub_aggregations.is_empty();
|
||||
let sub_agg = if has_sub_aggregations {
|
||||
let sub_aggregation = build_segment_agg_collector(sub_aggregations)?;
|
||||
Some(sub_aggregation)
|
||||
} else {
|
||||
None
|
||||
};
|
||||
|
||||
Ok(Self {
|
||||
accessor_idx,
|
||||
sub_agg,
|
||||
..Default::default()
|
||||
})
|
||||
}
|
||||
}
|
||||
|
||||
impl SegmentAggregationCollector for TermMissingAgg {
|
||||
fn add_intermediate_aggregation_result(
|
||||
self: Box<Self>,
|
||||
agg_with_accessor: &AggregationsWithAccessor,
|
||||
results: &mut IntermediateAggregationResults,
|
||||
) -> crate::Result<()> {
|
||||
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
|
||||
let agg_with_accessor = &agg_with_accessor.aggs.values[self.accessor_idx];
|
||||
let term_agg = agg_with_accessor
|
||||
.agg
|
||||
.agg
|
||||
.as_term()
|
||||
.expect("TermMissingAgg collector must be term agg req");
|
||||
let missing = term_agg
|
||||
.missing
|
||||
.as_ref()
|
||||
.expect("TermMissingAgg collector, but no missing found in agg req")
|
||||
.clone();
|
||||
let mut entries: FxHashMap<IntermediateKey, IntermediateTermBucketEntry> =
|
||||
Default::default();
|
||||
|
||||
let mut missing_entry = IntermediateTermBucketEntry {
|
||||
doc_count: self.missing_count,
|
||||
sub_aggregation: Default::default(),
|
||||
};
|
||||
if let Some(sub_agg) = self.sub_agg {
|
||||
let mut res = IntermediateAggregationResults::default();
|
||||
sub_agg.add_intermediate_aggregation_result(
|
||||
&agg_with_accessor.sub_aggregation,
|
||||
&mut res,
|
||||
)?;
|
||||
missing_entry.sub_aggregation = res;
|
||||
}
|
||||
|
||||
entries.insert(missing.into(), missing_entry);
|
||||
|
||||
let bucket = IntermediateBucketResult::Terms(IntermediateTermBucketResult {
|
||||
entries,
|
||||
sum_other_doc_count: 0,
|
||||
doc_count_error_upper_bound: 0,
|
||||
});
|
||||
|
||||
results.push(name, IntermediateAggregationResult::Bucket(bucket))?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn collect(
|
||||
&mut self,
|
||||
doc: crate::DocId,
|
||||
agg_with_accessor: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<()> {
|
||||
let agg = &mut agg_with_accessor.aggs.values[self.accessor_idx];
|
||||
let has_value = agg.accessors.iter().any(|acc| acc.index.has_value(doc));
|
||||
if !has_value {
|
||||
self.missing_count += 1;
|
||||
if let Some(sub_agg) = self.sub_agg.as_mut() {
|
||||
sub_agg.collect(doc, &mut agg.sub_aggregation)?;
|
||||
}
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn collect_block(
|
||||
&mut self,
|
||||
docs: &[crate::DocId],
|
||||
agg_with_accessor: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<()> {
|
||||
for doc in docs {
|
||||
self.collect(*doc, agg_with_accessor)?;
|
||||
}
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use crate::aggregation::agg_req::Aggregations;
|
||||
use crate::aggregation::tests::exec_request_with_query;
|
||||
use crate::schema::{Schema, FAST};
|
||||
use crate::Index;
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_mixed_type_mult_seg_sub_agg() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let score = schema_builder.add_f64_field("score", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer = index.writer_for_tests().unwrap();
|
||||
// => Segment with all values numeric
|
||||
index_writer
|
||||
.add_document(doc!(score => 1.0, json => json!({"mixed_type": 10.0})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
// index_writer.commit().unwrap();
|
||||
//// => Segment with all values text
|
||||
index_writer
|
||||
.add_document(doc!(score => 1.0, json => json!({"mixed_type": "blue"})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
// index_writer.commit().unwrap();
|
||||
|
||||
// => Segment with mixed values
|
||||
index_writer.add_document(doc!(json => json!({"mixed_type": "red"})))?;
|
||||
index_writer.add_document(doc!(json => json!({"mixed_type": -20.5})))?;
|
||||
index_writer.add_document(doc!(json => json!({"mixed_type": true})))?;
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
"aggs": {
|
||||
"sum_score": {
|
||||
"sum": {
|
||||
"field": "score"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(
|
||||
res["replace_null"]["buckets"][0]["sum_score"]["value"],
|
||||
15.0
|
||||
);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_mixed_type_sub_agg_reg1() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let score = schema_builder.add_f64_field("score", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer = index.writer_for_tests().unwrap();
|
||||
// => Segment with all values numeric
|
||||
index_writer.add_document(doc!(score => 1.0, json => json!({"mixed_type": 10.0})))?;
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
"aggs": {
|
||||
"sum_score": {
|
||||
"sum": {
|
||||
"field": "score"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 2);
|
||||
assert_eq!(
|
||||
res["replace_null"]["buckets"][0]["sum_score"]["value"],
|
||||
10.0
|
||||
);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_mult_seg_empty() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let score = schema_builder.add_f64_field("score", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer = index.writer_for_tests().unwrap();
|
||||
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
index_writer.commit().unwrap();
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
index_writer.commit().unwrap();
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
"aggs": {
|
||||
"sum_score": {
|
||||
"sum": {
|
||||
"field": "score"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(
|
||||
res["replace_null"]["buckets"][0]["sum_score"]["value"],
|
||||
15.0
|
||||
);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_single_seg_empty() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let score = schema_builder.add_f64_field("score", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer = index.writer_for_tests().unwrap();
|
||||
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
index_writer.add_document(doc!(score => 5.0))?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
"aggs": {
|
||||
"sum_score": {
|
||||
"sum": {
|
||||
"field": "score"
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(
|
||||
res["replace_null"]["buckets"][0]["sum_score"]["value"],
|
||||
15.0
|
||||
);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_mixed_type_mult_seg() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer = index.writer_for_tests().unwrap();
|
||||
// => Segment with all values numeric
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": 10.0})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.commit().unwrap();
|
||||
//// => Segment with all values text
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": "blue"})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.commit().unwrap();
|
||||
|
||||
// => Segment with mixed values
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": "red"})))
|
||||
.unwrap();
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": -20.5})))
|
||||
.unwrap();
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": true})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
},
|
||||
"replace_num": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": 1337
|
||||
},
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(res["replace_num"]["buckets"][0]["key"], 1337.0);
|
||||
assert_eq!(res["replace_num"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_str_on_numeric_field() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer = index.writer_for_tests().unwrap();
|
||||
// => Segment with all values numeric
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": 10.0})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
index_writer.add_document(doc!())?;
|
||||
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": -20.5})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn terms_aggregation_missing_mixed_type_one_seg() -> crate::Result<()> {
|
||||
let mut schema_builder = Schema::builder();
|
||||
let json = schema_builder.add_json_field("json", FAST);
|
||||
let schema = schema_builder.build();
|
||||
let index = Index::create_in_ram(schema);
|
||||
let mut index_writer = index.writer_for_tests().unwrap();
|
||||
// => Segment with all values numeric
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": 10.0})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
//// => Segment with all values text
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": "blue"})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
|
||||
// => Segment with mixed values
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": "red"})))
|
||||
.unwrap();
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": -20.5})))
|
||||
.unwrap();
|
||||
index_writer
|
||||
.add_document(doc!(json => json!({"mixed_type": true})))
|
||||
.unwrap();
|
||||
index_writer.add_document(doc!())?;
|
||||
|
||||
index_writer.commit().unwrap();
|
||||
|
||||
let agg_req: Aggregations = serde_json::from_value(json!({
|
||||
"replace_null": {
|
||||
"terms": {
|
||||
"field": "json.mixed_type",
|
||||
"missing": "NULL"
|
||||
},
|
||||
},
|
||||
}))
|
||||
.unwrap();
|
||||
|
||||
let res = exec_request_with_query(agg_req, &index, None)?;
|
||||
|
||||
// text field
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["key"], "NULL");
|
||||
assert_eq!(res["replace_null"]["buckets"][0]["doc_count"], 3);
|
||||
assert_eq!(res["replace_null"]["sum_other_doc_count"], 0);
|
||||
assert_eq!(res["replace_null"]["doc_count_error_upper_bound"], 0);
|
||||
|
||||
Ok(())
|
||||
}
|
||||
}
|
||||
@@ -34,17 +34,20 @@ impl BufAggregationCollector {
|
||||
}
|
||||
|
||||
impl SegmentAggregationCollector for BufAggregationCollector {
|
||||
fn into_intermediate_aggregations_result(
|
||||
#[inline]
|
||||
fn add_intermediate_aggregation_result(
|
||||
self: Box<Self>,
|
||||
agg_with_accessor: &AggregationsWithAccessor,
|
||||
) -> crate::Result<IntermediateAggregationResults> {
|
||||
Box::new(self.collector).into_intermediate_aggregations_result(agg_with_accessor)
|
||||
results: &mut IntermediateAggregationResults,
|
||||
) -> crate::Result<()> {
|
||||
Box::new(self.collector).add_intermediate_aggregation_result(agg_with_accessor, results)
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn collect(
|
||||
&mut self,
|
||||
doc: crate::DocId,
|
||||
agg_with_accessor: &AggregationsWithAccessor,
|
||||
agg_with_accessor: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<()> {
|
||||
self.staged_docs[self.num_staged_docs] = doc;
|
||||
self.num_staged_docs += 1;
|
||||
@@ -56,18 +59,19 @@ impl SegmentAggregationCollector for BufAggregationCollector {
|
||||
Ok(())
|
||||
}
|
||||
|
||||
#[inline]
|
||||
fn collect_block(
|
||||
&mut self,
|
||||
docs: &[crate::DocId],
|
||||
agg_with_accessor: &AggregationsWithAccessor,
|
||||
agg_with_accessor: &mut AggregationsWithAccessor,
|
||||
) -> crate::Result<()> {
|
||||
for doc in docs {
|
||||
self.collect(*doc, agg_with_accessor)?;
|
||||
}
|
||||
self.collector.collect_block(docs, agg_with_accessor)?;
|
||||
|
||||
Ok(())
|
||||
}
|
||||
|
||||
fn flush(&mut self, agg_with_accessor: &AggregationsWithAccessor) -> crate::Result<()> {
|
||||
#[inline]
|
||||
fn flush(&mut self, agg_with_accessor: &mut AggregationsWithAccessor) -> crate::Result<()> {
|
||||
self.collector
|
||||
.collect_block(&self.staged_docs[..self.num_staged_docs], agg_with_accessor)?;
|
||||
self.num_staged_docs = 0;
|
||||
|
||||
@@ -1,36 +1,36 @@
|
||||
use std::rc::Rc;
|
||||
|
||||
use super::agg_req::Aggregations;
|
||||
use super::agg_req_with_accessor::AggregationsWithAccessor;
|
||||
use super::agg_result::AggregationResults;
|
||||
use super::buf_collector::BufAggregationCollector;
|
||||
use super::intermediate_agg_result::IntermediateAggregationResults;
|
||||
use super::segment_agg_result::{build_segment_agg_collector, SegmentAggregationCollector};
|
||||
use crate::aggregation::agg_req_with_accessor::get_aggs_with_accessor_and_validate;
|
||||
use super::segment_agg_result::{
|
||||
build_segment_agg_collector, AggregationLimits, SegmentAggregationCollector,
|
||||
};
|
||||
use crate::aggregation::agg_req_with_accessor::get_aggs_with_segment_accessor_and_validate;
|
||||
use crate::collector::{Collector, SegmentCollector};
|
||||
use crate::{SegmentReader, TantivyError};
|
||||
use crate::{DocId, SegmentReader, TantivyError};
|
||||
|
||||
/// The default max bucket count, before the aggregation fails.
|
||||
pub const MAX_BUCKET_COUNT: u32 = 65000;
|
||||
pub const DEFAULT_BUCKET_LIMIT: u32 = 65000;
|
||||
|
||||
/// The default memory limit in bytes before the aggregation fails. 500MB
|
||||
pub const DEFAULT_MEMORY_LIMIT: u64 = 500_000_000;
|
||||
|
||||
/// Collector for aggregations.
|
||||
///
|
||||
/// The collector collects all aggregations by the underlying aggregation request.
|
||||
pub struct AggregationCollector {
|
||||
agg: Aggregations,
|
||||
max_bucket_count: u32,
|
||||
limits: AggregationLimits,
|
||||
}
|
||||
|
||||
impl AggregationCollector {
|
||||
/// Create collector from aggregation request.
|
||||
///
|
||||
/// Aggregation fails when the total bucket count is higher than max_bucket_count.
|
||||
/// max_bucket_count will default to `MAX_BUCKET_COUNT` (65000) when unset
|
||||
pub fn from_aggs(agg: Aggregations, max_bucket_count: Option<u32>) -> Self {
|
||||
Self {
|
||||
agg,
|
||||
max_bucket_count: max_bucket_count.unwrap_or(MAX_BUCKET_COUNT),
|
||||
}
|
||||
/// Aggregation fails when the limits in `AggregationLimits` is exceeded. (memory limit and
|
||||
/// bucket limit)
|
||||
pub fn from_aggs(agg: Aggregations, limits: AggregationLimits) -> Self {
|
||||
Self { agg, limits }
|
||||
}
|
||||
}
|
||||
|
||||
@@ -44,18 +44,16 @@ impl AggregationCollector {
|
||||
/// into the final `AggregationResults` via the `into_final_result()` method.
|
||||
pub struct DistributedAggregationCollector {
|
||||
agg: Aggregations,
|
||||
max_bucket_count: u32,
|
||||
limits: AggregationLimits,
|
||||
}
|
||||
|
||||
impl DistributedAggregationCollector {
|
||||
/// Create collector from aggregation request.
|
||||
///
|
||||
/// max_bucket_count will default to `MAX_BUCKET_COUNT` (65000) when unset
|
||||
pub fn from_aggs(agg: Aggregations, max_bucket_count: Option<u32>) -> Self {
|
||||
Self {
|
||||
agg,
|
||||
max_bucket_count: max_bucket_count.unwrap_or(MAX_BUCKET_COUNT),
|
||||
}
|
||||
/// Aggregation fails when the limits in `AggregationLimits` is exceeded. (memory limit and
|
||||
/// bucket limit)
|
||||
pub fn from_aggs(agg: Aggregations, limits: AggregationLimits) -> Self {
|
||||
Self { agg, limits }
|
||||
}
|
||||
}
|
||||
|
||||
@@ -69,11 +67,7 @@ impl Collector for DistributedAggregationCollector {
|
||||
_segment_local_id: crate::SegmentOrdinal,
|
||||
reader: &crate::SegmentReader,
|
||||
) -> crate::Result<Self::Child> {
|
||||
AggregationSegmentCollector::from_agg_req_and_reader(
|
||||
&self.agg,
|
||||
reader,
|
||||
self.max_bucket_count,
|
||||
)
|
||||
AggregationSegmentCollector::from_agg_req_and_reader(&self.agg, reader, &self.limits)
|
||||
}
|
||||
|
||||
fn requires_scoring(&self) -> bool {
|
||||
@@ -98,11 +92,7 @@ impl Collector for AggregationCollector {
|
||||
_segment_local_id: crate::SegmentOrdinal,
|
||||
reader: &crate::SegmentReader,
|
||||
) -> crate::Result<Self::Child> {
|
||||
AggregationSegmentCollector::from_agg_req_and_reader(
|
||||
&self.agg,
|
||||
reader,
|
||||
self.max_bucket_count,
|
||||
)
|
||||
AggregationSegmentCollector::from_agg_req_and_reader(&self.agg, reader, &self.limits)
|
||||
}
|
||||
|
||||
fn requires_scoring(&self) -> bool {
|
||||
@@ -114,7 +104,7 @@ impl Collector for AggregationCollector {
|
||||
segment_fruits: Vec<<Self::Child as SegmentCollector>::Fruit>,
|
||||
) -> crate::Result<Self::Fruit> {
|
||||
let res = merge_fruits(segment_fruits)?;
|
||||
res.into_final_bucket_result(self.agg.clone())
|
||||
res.into_final_result(self.agg.clone(), &self.limits)
|
||||
}
|
||||
}
|
||||
|
||||
@@ -124,7 +114,7 @@ fn merge_fruits(
|
||||
if let Some(fruit) = segment_fruits.pop() {
|
||||
let mut fruit = fruit?;
|
||||
for next_fruit in segment_fruits {
|
||||
fruit.merge_fruits(next_fruit?);
|
||||
fruit.merge_fruits(next_fruit?)?;
|
||||
}
|
||||
Ok(fruit)
|
||||
} else {
|
||||
@@ -135,7 +125,7 @@ fn merge_fruits(
|
||||
/// `AggregationSegmentCollector` does the aggregation collection on a segment.
|
||||
pub struct AggregationSegmentCollector {
|
||||
aggs_with_accessor: AggregationsWithAccessor,
|
||||
result: BufAggregationCollector,
|
||||
agg_collector: BufAggregationCollector,
|
||||
error: Option<TantivyError>,
|
||||
}
|
||||
|
||||
@@ -145,15 +135,15 @@ impl AggregationSegmentCollector {
|
||||
pub fn from_agg_req_and_reader(
|
||||
agg: &Aggregations,
|
||||
reader: &SegmentReader,
|
||||
max_bucket_count: u32,
|
||||
limits: &AggregationLimits,
|
||||
) -> crate::Result<Self> {
|
||||
let aggs_with_accessor =
|
||||
get_aggs_with_accessor_and_validate(agg, reader, Rc::default(), max_bucket_count)?;
|
||||
let mut aggs_with_accessor =
|
||||
get_aggs_with_segment_accessor_and_validate(agg, reader, limits)?;
|
||||
let result =
|
||||
BufAggregationCollector::new(build_segment_agg_collector(&aggs_with_accessor)?);
|
||||
BufAggregationCollector::new(build_segment_agg_collector(&mut aggs_with_accessor)?);
|
||||
Ok(AggregationSegmentCollector {
|
||||
aggs_with_accessor,
|
||||
result,
|
||||
agg_collector: result,
|
||||
error: None,
|
||||
})
|
||||
}
|
||||
@@ -163,11 +153,29 @@ impl SegmentCollector for AggregationSegmentCollector {
|
||||
type Fruit = crate::Result<IntermediateAggregationResults>;
|
||||
|
||||
#[inline]
|
||||
fn collect(&mut self, doc: crate::DocId, _score: crate::Score) {
|
||||
fn collect(&mut self, doc: DocId, _score: crate::Score) {
|
||||
if self.error.is_some() {
|
||||
return;
|
||||
}
|
||||
if let Err(err) = self.result.collect(doc, &self.aggs_with_accessor) {
|
||||
if let Err(err) = self
|
||||
.agg_collector
|
||||
.collect(doc, &mut self.aggs_with_accessor)
|
||||
{
|
||||
self.error = Some(err);
|
||||
}
|
||||
}
|
||||
|
||||
/// The query pushes the documents to the collector via this method.
|
||||
///
|
||||
/// Only valid for Collectors that ignore docs
|
||||
fn collect_block(&mut self, docs: &[DocId]) {
|
||||
if self.error.is_some() {
|
||||
return;
|
||||
}
|
||||
if let Err(err) = self
|
||||
.agg_collector
|
||||
.collect_block(docs, &mut self.aggs_with_accessor)
|
||||
{
|
||||
self.error = Some(err);
|
||||
}
|
||||
}
|
||||
@@ -176,7 +184,14 @@ impl SegmentCollector for AggregationSegmentCollector {
|
||||
if let Some(err) = self.error {
|
||||
return Err(err);
|
||||
}
|
||||
self.result.flush(&self.aggs_with_accessor)?;
|
||||
Box::new(self.result).into_intermediate_aggregations_result(&self.aggs_with_accessor)
|
||||
self.agg_collector.flush(&mut self.aggs_with_accessor)?;
|
||||
|
||||
let mut sub_aggregation_res = IntermediateAggregationResults::default();
|
||||
Box::new(self.agg_collector).add_intermediate_aggregation_result(
|
||||
&self.aggs_with_accessor,
|
||||
&mut sub_aggregation_res,
|
||||
)?;
|
||||
|
||||
Ok(sub_aggregation_res)
|
||||
}
|
||||
}
|
||||
|
||||
@@ -4,13 +4,11 @@ use time::OffsetDateTime;
|
||||
use crate::TantivyError;
|
||||
|
||||
pub(crate) fn format_date(val: i64) -> crate::Result<String> {
|
||||
let datetime =
|
||||
OffsetDateTime::from_unix_timestamp_nanos(1_000 * (val as i128)).map_err(|err| {
|
||||
TantivyError::InvalidArgument(format!(
|
||||
"Could not convert {:?} to OffsetDateTime, err {:?}",
|
||||
val, err
|
||||
))
|
||||
})?;
|
||||
let datetime = OffsetDateTime::from_unix_timestamp_nanos(val as i128).map_err(|err| {
|
||||
TantivyError::InvalidArgument(format!(
|
||||
"Could not convert {val:?} to OffsetDateTime, err {err:?}"
|
||||
))
|
||||
})?;
|
||||
let key_as_string = datetime
|
||||
.format(&Rfc3339)
|
||||
.map_err(|_err| TantivyError::InvalidArgument("Could not serialize date".to_string()))?;
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user