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Author SHA1 Message Date
Raphaël Marinier
0890503fc2 Speed up searches by removing repeated memsets coming from vec.resize()
Also, reserve exactly the size needed, which is surprisingly needed to
get the full speedup of ~5% on a good fraction of the queries.
2024-03-12 17:50:23 +01:00
206 changed files with 5082 additions and 6763 deletions

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@@ -15,11 +15,11 @@ jobs:
steps:
- uses: actions/checkout@v4
- name: Install Rust
run: rustup toolchain install nightly-2024-04-10 --profile minimal --component llvm-tools-preview
run: rustup toolchain install nightly-2023-09-10 --profile minimal --component llvm-tools-preview
- uses: Swatinem/rust-cache@v2
- uses: taiki-e/install-action@cargo-llvm-cov
- name: Generate code coverage
run: cargo +nightly-2024-04-10 llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
run: cargo +nightly-2023-09-10 llvm-cov --all-features --workspace --doctests --lcov --output-path lcov.info
- name: Upload coverage to Codecov
uses: codecov/codecov-action@v3
continue-on-error: true

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@@ -1,65 +1,3 @@
Tantivy 0.22
================================
Tantivy 0.22 will be able to read indices created with Tantivy 0.21.
#### Bugfixes
- Fix null byte handling in JSON paths (null bytes in json keys caused panic during indexing) [#2345](https://github.com/quickwit-oss/tantivy/pull/2345)(@PSeitz)
- Fix bug that can cause `get_docids_for_value_range` to panic. [#2295](https://github.com/quickwit-oss/tantivy/pull/2295)(@fulmicoton)
- Avoid 1 document indices by increase min memory to 15MB for indexing [#2176](https://github.com/quickwit-oss/tantivy/pull/2176)(@PSeitz)
- Fix merge panic for JSON fields [#2284](https://github.com/quickwit-oss/tantivy/pull/2284)(@PSeitz)
- Fix bug occuring when merging JSON object indexed with positions. [#2253](https://github.com/quickwit-oss/tantivy/pull/2253)(@fulmicoton)
- Fix empty DateHistogram gap bug [#2183](https://github.com/quickwit-oss/tantivy/pull/2183)(@PSeitz)
- Fix range query end check (fields with less than 1 value per doc are affected) [#2226](https://github.com/quickwit-oss/tantivy/pull/2226)(@PSeitz)
- Handle exclusive out of bounds ranges on fastfield range queries [#2174](https://github.com/quickwit-oss/tantivy/pull/2174)(@PSeitz)
#### Breaking API Changes
- rename ReloadPolicy onCommit to onCommitWithDelay [#2235](https://github.com/quickwit-oss/tantivy/pull/2235)(@giovannicuccu)
- Move exports from the root into modules [#2220](https://github.com/quickwit-oss/tantivy/pull/2220)(@PSeitz)
- Accept field name instead of `Field` in FilterCollector [#2196](https://github.com/quickwit-oss/tantivy/pull/2196)(@PSeitz)
- remove deprecated IntOptions and DateTime [#2353](https://github.com/quickwit-oss/tantivy/pull/2353)(@PSeitz)
#### Features/Improvements
- Tantivy documents as a trait: Index data directly without converting to tantivy types first [#2071](https://github.com/quickwit-oss/tantivy/pull/2071)(@ChillFish8)
- encode some part of posting list as -1 instead of direct values (smaller inverted indices) [#2185](https://github.com/quickwit-oss/tantivy/pull/2185)(@trinity-1686a)
- **Aggregation**
- Support to deserialize f64 from string [#2311](https://github.com/quickwit-oss/tantivy/pull/2311)(@PSeitz)
- Add a top_hits aggregator [#2198](https://github.com/quickwit-oss/tantivy/pull/2198)(@ditsuke)
- Support bool type in term aggregation [#2318](https://github.com/quickwit-oss/tantivy/pull/2318)(@PSeitz)
- Support ip adresses in term aggregation [#2319](https://github.com/quickwit-oss/tantivy/pull/2319)(@PSeitz)
- Support date type in term aggregation [#2172](https://github.com/quickwit-oss/tantivy/pull/2172)(@PSeitz)
- Support escaped dot when addressing field [#2250](https://github.com/quickwit-oss/tantivy/pull/2250)(@PSeitz)
- Add ExistsQuery to check documents that have a value [#2160](https://github.com/quickwit-oss/tantivy/pull/2160)(@imotov)
- Expose TopDocs::order_by_u64_field again [#2282](https://github.com/quickwit-oss/tantivy/pull/2282)(@ditsuke)
- **Memory/Performance**
- Faster TopN: replace BinaryHeap with TopNComputer [#2186](https://github.com/quickwit-oss/tantivy/pull/2186)(@PSeitz)
- reduce number of allocations during indexing [#2257](https://github.com/quickwit-oss/tantivy/pull/2257)(@PSeitz)
- Less Memory while indexing: docid deltas while indexing [#2249](https://github.com/quickwit-oss/tantivy/pull/2249)(@PSeitz)
- Faster indexing: use term hashmap in fastfield [#2243](https://github.com/quickwit-oss/tantivy/pull/2243)(@PSeitz)
- term hashmap remove copy in is_empty, unused unordered_id [#2229](https://github.com/quickwit-oss/tantivy/pull/2229)(@PSeitz)
- add method to fetch block of first values in columnar [#2330](https://github.com/quickwit-oss/tantivy/pull/2330)(@PSeitz)
- Faster aggregations: add fast path for full columns in fetch_block [#2328](https://github.com/quickwit-oss/tantivy/pull/2328)(@PSeitz)
- Faster sstable loading: use fst for sstable index [#2268](https://github.com/quickwit-oss/tantivy/pull/2268)(@trinity-1686a)
- **QueryParser**
- allow newline where we allow space in query parser [#2302](https://github.com/quickwit-oss/tantivy/pull/2302)(@trinity-1686a)
- allow some mixing of occur and bool in strict query parser [#2323](https://github.com/quickwit-oss/tantivy/pull/2323)(@trinity-1686a)
- handle * inside term in lenient query parser [#2228](https://github.com/quickwit-oss/tantivy/pull/2228)(@trinity-1686a)
- add support for exists query syntax in query parser [#2170](https://github.com/quickwit-oss/tantivy/pull/2170)(@trinity-1686a)
- Add shared search executor [#2312](https://github.com/quickwit-oss/tantivy/pull/2312)(@MochiXu)
- Truncate keys to u16::MAX in term hashmap [#2299](https://github.com/quickwit-oss/tantivy/pull/2299)(@PSeitz)
- report if a term matched when warming up posting list [#2309](https://github.com/quickwit-oss/tantivy/pull/2309)(@trinity-1686a)
- Support json fields in FuzzyTermQuery [#2173](https://github.com/quickwit-oss/tantivy/pull/2173)(@PingXia-at)
- Read list of fields encoded in term dictionary for JSON fields [#2184](https://github.com/quickwit-oss/tantivy/pull/2184)(@PSeitz)
- add collect_block to BoxableSegmentCollector [#2331](https://github.com/quickwit-oss/tantivy/pull/2331)(@PSeitz)
- expose collect_block buffer size [#2326](https://github.com/quickwit-oss/tantivy/pull/2326)(@PSeitz)
- Forward regex parser errors [#2288](https://github.com/quickwit-oss/tantivy/pull/2288)(@adamreichold)
- Make FacetCounts defaultable and cloneable. [#2322](https://github.com/quickwit-oss/tantivy/pull/2322)(@adamreichold)
- Derive Debug for SchemaBuilder [#2254](https://github.com/quickwit-oss/tantivy/pull/2254)(@GodTamIt)
- add missing inlines to tantivy options [#2245](https://github.com/quickwit-oss/tantivy/pull/2245)(@PSeitz)
Tantivy 0.21.1
================================
#### Bugfixes

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@@ -1,6 +1,6 @@
[package]
name = "tantivy"
version = "0.23.0"
version = "0.22.0-dev"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
categories = ["database-implementations", "data-structures"]
@@ -11,19 +11,16 @@ repository = "https://github.com/quickwit-oss/tantivy"
readme = "README.md"
keywords = ["search", "information", "retrieval"]
edition = "2021"
rust-version = "1.63"
rust-version = "1.62"
exclude = ["benches/*.json", "benches/*.txt"]
[dependencies]
oneshot = "0.1.7"
base64 = "0.22.0"
oneshot = "0.1.5"
base64 = "0.21.0"
byteorder = "1.4.3"
crc32fast = "1.3.2"
once_cell = "1.10.0"
regex = { version = "1.5.5", default-features = false, features = [
"std",
"unicode",
] }
regex = { version = "1.5.5", default-features = false, features = ["std", "unicode"] }
aho-corasick = "1.0"
tantivy-fst = "0.5"
memmap2 = { version = "0.9.0", optional = true }
@@ -33,15 +30,14 @@ 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"
fs4 = { version = "0.8.0", optional = true }
levenshtein_automata = "0.2.1"
uuid = { version = "1.0.0", features = ["v4", "serde"] }
crossbeam-channel = "0.5.4"
rust-stemmers = "1.2.0"
downcast-rs = "1.2.0"
bitpacking = { version = "0.9.2", default-features = false, features = [
"bitpacker4x",
] }
bitpacking = { version = "0.9.2", default-features = false, features = ["bitpacker4x"] }
census = "0.4.2"
rustc-hash = "1.1.0"
thiserror = "1.0.30"
@@ -52,18 +48,18 @@ smallvec = "1.8.0"
rayon = "1.5.2"
lru = "0.12.0"
fastdivide = "0.4.0"
itertools = "0.13.0"
itertools = "0.12.0"
measure_time = "0.8.2"
arc-swap = "1.5.0"
columnar = { version = "0.3", path = "./columnar", package = "tantivy-columnar" }
sstable = { version = "0.3", path = "./sstable", package = "tantivy-sstable", optional = true }
stacker = { version = "0.3", path = "./stacker", package = "tantivy-stacker" }
query-grammar = { version = "0.22.0", path = "./query-grammar", package = "tantivy-query-grammar" }
tantivy-bitpacker = { version = "0.6", path = "./bitpacker" }
common = { version = "0.7", path = "./common/", package = "tantivy-common" }
tokenizer-api = { version = "0.3", path = "./tokenizer-api", package = "tantivy-tokenizer-api" }
sketches-ddsketch = { version = "0.3.0", features = ["use_serde"] }
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 }
fnv = "1.0.7"
@@ -71,7 +67,6 @@ fnv = "1.0.7"
winapi = "0.3.9"
[dev-dependencies]
binggan = "0.8.0"
rand = "0.8.5"
maplit = "1.0.2"
matches = "0.1.9"
@@ -83,9 +78,6 @@ paste = "1.0.11"
more-asserts = "0.3.1"
rand_distr = "0.4.3"
time = { version = "0.3.10", features = ["serde-well-known", "macros"] }
postcard = { version = "1.0.4", features = [
"use-std",
], default-features = false }
[target.'cfg(not(windows))'.dev-dependencies]
criterion = { version = "0.5", default-features = false }
@@ -117,26 +109,17 @@ lz4-compression = ["lz4_flex"]
zstd-compression = ["zstd"]
failpoints = ["fail", "fail/failpoints"]
unstable = [] # useful for benches.
unstable = [] # useful for benches.
quickwit = ["sstable", "futures-util"]
# Compares only the hash of a string when indexing data.
# Compares only the hash of a string when indexing data.
# Increases indexing speed, but may lead to extremely rare missing terms, when there's a hash collision.
# Uses 64bit ahash.
compare_hash_only = ["stacker/compare_hash_only"]
[workspace]
members = [
"query-grammar",
"bitpacker",
"common",
"ownedbytes",
"stacker",
"sstable",
"tokenizer-api",
"columnar",
]
members = ["query-grammar", "bitpacker", "common", "ownedbytes", "stacker", "sstable", "tokenizer-api", "columnar"]
# Following the "fail" crate best practises, we isolate
# tests that define specific behavior in fail check points
@@ -157,7 +140,3 @@ harness = false
[[bench]]
name = "index-bench"
harness = false
[[bench]]
name = "agg_bench"
harness = false

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@@ -101,8 +101,7 @@ cargo test
## Companies Using Tantivy
<p align="left">
<img align="center" src="doc/assets/images/etsy.png" alt="Etsy" height="25" width="auto" /> &nbsp;
<img align="center" src="doc/assets/images/paradedb.png" alt="ParadeDB" height="25" width="auto" /> &nbsp;
<img align="center" src="doc/assets/images/etsy.png" alt="Etsy" height="25" width="auto" />&nbsp;
<img align="center" src="doc/assets/images/Nuclia.png#gh-light-mode-only" alt="Nuclia" height="25" width="auto" /> &nbsp;
<img align="center" src="doc/assets/images/humanfirst.png#gh-light-mode-only" alt="Humanfirst.ai" height="30" width="auto" />
<img align="center" src="doc/assets/images/element.io.svg#gh-light-mode-only" alt="Element.io" height="25" width="auto" />

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@@ -1,419 +0,0 @@
use binggan::{black_box, InputGroup, PeakMemAlloc, INSTRUMENTED_SYSTEM};
use rand::prelude::SliceRandom;
use rand::rngs::StdRng;
use rand::{Rng, SeedableRng};
use rand_distr::Distribution;
use serde_json::json;
use tantivy::aggregation::agg_req::Aggregations;
use tantivy::aggregation::AggregationCollector;
use tantivy::query::{AllQuery, TermQuery};
use tantivy::schema::{IndexRecordOption, Schema, TextFieldIndexing, FAST, STRING};
use tantivy::{doc, Index, Term};
#[global_allocator]
pub static GLOBAL: &PeakMemAlloc<std::alloc::System> = &INSTRUMENTED_SYSTEM;
/// Mini macro to register a function via its name
/// runner.register("average_u64", move |index| average_u64(index));
macro_rules! register {
($runner:expr, $func:ident) => {
$runner.register(stringify!($func), move |index| $func(index))
};
}
fn main() {
let inputs = vec![
("full", get_test_index_bench(Cardinality::Full).unwrap()),
(
"dense",
get_test_index_bench(Cardinality::OptionalDense).unwrap(),
),
(
"sparse",
get_test_index_bench(Cardinality::OptionalSparse).unwrap(),
),
(
"multivalue",
get_test_index_bench(Cardinality::Multivalued).unwrap(),
),
];
bench_agg(InputGroup::new_with_inputs(inputs));
}
fn bench_agg(mut group: InputGroup<Index>) {
group.set_alloc(GLOBAL); // Set the peak mem allocator. This will enable peak memory reporting.
register!(group, average_u64);
register!(group, average_f64);
register!(group, average_f64_u64);
register!(group, stats_f64);
register!(group, extendedstats_f64);
register!(group, percentiles_f64);
register!(group, terms_few);
register!(group, terms_many);
register!(group, terms_many_order_by_term);
register!(group, terms_many_with_top_hits);
register!(group, terms_many_with_avg_sub_agg);
register!(group, terms_many_json_mixed_type_with_sub_agg_card);
register!(group, range_agg);
register!(group, range_agg_with_avg_sub_agg);
register!(group, range_agg_with_term_agg_few);
register!(group, range_agg_with_term_agg_many);
register!(group, histogram);
register!(group, histogram_hard_bounds);
register!(group, histogram_with_avg_sub_agg);
register!(group, avg_and_range_with_avg_sub_agg);
group.run();
}
fn exec_term_with_agg(index: &Index, agg_req: serde_json::Value) {
let agg_req: Aggregations = serde_json::from_value(agg_req).unwrap();
let reader = index.reader().unwrap();
let text_field = reader.searcher().schema().get_field("text").unwrap();
let term_query = TermQuery::new(
Term::from_field_text(text_field, "cool"),
IndexRecordOption::Basic,
);
let collector = get_collector(agg_req);
let searcher = reader.searcher();
black_box(searcher.search(&term_query, &collector).unwrap());
}
fn average_u64(index: &Index) {
let agg_req = json!({
"average": { "avg": { "field": "score", } }
});
exec_term_with_agg(index, agg_req)
}
fn average_f64(index: &Index) {
let agg_req = json!({
"average": { "avg": { "field": "score_f64", } }
});
exec_term_with_agg(index, agg_req)
}
fn average_f64_u64(index: &Index) {
let agg_req = json!({
"average_f64": { "avg": { "field": "score_f64" } },
"average": { "avg": { "field": "score" } },
});
exec_term_with_agg(index, agg_req)
}
fn stats_f64(index: &Index) {
let agg_req = json!({
"average_f64": { "stats": { "field": "score_f64", } }
});
exec_term_with_agg(index, agg_req)
}
fn extendedstats_f64(index: &Index) {
let agg_req = json!({
"extendedstats_f64": { "extended_stats": { "field": "score_f64", } }
});
exec_term_with_agg(index, agg_req)
}
fn percentiles_f64(index: &Index) {
let agg_req = json!({
"mypercentiles": {
"percentiles": {
"field": "score_f64",
"percents": [ 95, 99, 99.9 ]
}
}
});
execute_agg(index, agg_req);
}
fn terms_few(index: &Index) {
let agg_req = json!({
"my_texts": { "terms": { "field": "text_few_terms" } },
});
execute_agg(index, agg_req);
}
fn terms_many(index: &Index) {
let agg_req = json!({
"my_texts": { "terms": { "field": "text_many_terms" } },
});
execute_agg(index, agg_req);
}
fn terms_many_order_by_term(index: &Index) {
let agg_req = json!({
"my_texts": { "terms": { "field": "text_many_terms", "order": { "_key": "desc" } } },
});
execute_agg(index, agg_req);
}
fn terms_many_with_top_hits(index: &Index) {
let agg_req = json!({
"my_texts": {
"terms": { "field": "text_many_terms" },
"aggs": {
"top_hits": { "top_hits":
{
"sort": [
{ "score": "desc" }
],
"size": 2,
"doc_value_fields": ["score_f64"]
}
}
}
},
});
execute_agg(index, agg_req);
}
fn terms_many_with_avg_sub_agg(index: &Index) {
let agg_req = json!({
"my_texts": {
"terms": { "field": "text_many_terms" },
"aggs": {
"average_f64": { "avg": { "field": "score_f64" } }
}
},
});
execute_agg(index, agg_req);
}
fn terms_many_json_mixed_type_with_sub_agg_card(index: &Index) {
let agg_req = json!({
"my_texts": {
"terms": { "field": "json.mixed_type" },
"aggs": {
"average_f64": { "avg": { "field": "score_f64" } }
}
},
});
execute_agg(index, agg_req);
}
fn execute_agg(index: &Index, agg_req: serde_json::Value) {
let agg_req: Aggregations = serde_json::from_value(agg_req).unwrap();
let collector = get_collector(agg_req);
let reader = index.reader().unwrap();
let searcher = reader.searcher();
black_box(searcher.search(&AllQuery, &collector).unwrap());
}
fn range_agg(index: &Index) {
let agg_req = 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 }
] } },
});
execute_agg(index, agg_req);
}
fn range_agg_with_avg_sub_agg(index: &Index) {
let agg_req = 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" } }
}
},
});
execute_agg(index, agg_req);
}
fn range_agg_with_term_agg_few(index: &Index) {
let agg_req = 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": {
"my_texts": { "terms": { "field": "text_few_terms" } },
}
},
});
execute_agg(index, agg_req);
}
fn range_agg_with_term_agg_many(index: &Index) {
let agg_req = 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": {
"my_texts": { "terms": { "field": "text_many_terms" } },
}
},
});
execute_agg(index, agg_req);
}
fn histogram(index: &Index) {
let agg_req = json!({
"rangef64": {
"histogram": {
"field": "score_f64",
"interval": 100 // 1000 buckets
},
}
});
execute_agg(index, agg_req);
}
fn histogram_hard_bounds(index: &Index) {
let agg_req = json!({
"rangef64": { "histogram": { "field": "score_f64", "interval": 100, "hard_bounds": { "min": 1000, "max": 300000 } } },
});
execute_agg(index, agg_req);
}
fn histogram_with_avg_sub_agg(index: &Index) {
let agg_req = json!({
"rangef64": {
"histogram": { "field": "score_f64", "interval": 100 },
"aggs": {
"average_f64": { "avg": { "field": "score_f64" } }
}
}
});
execute_agg(index, agg_req);
}
fn avg_and_range_with_avg_sub_agg(index: &Index) {
let agg_req = 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" } }
});
execute_agg(index, agg_req);
}
#[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.
OptionalDense = 1,
/// All documents may contain any number of values.
Multivalued = 2,
/// 1 / 20 documents has a value
OptionalSparse = 3,
}
fn get_collector(agg_req: Aggregations) -> AggregationCollector {
AggregationCollector::from_aggs(agg_req, Default::default())
}
fn get_test_index_bench(cardinality: Cardinality) -> tantivy::Result<Index> {
let mut schema_builder = Schema::builder();
let text_fieldtype = tantivy::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 = tantivy::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 = ["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::OptionalDense {
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::OptionalSparse {
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::OptionalSparse {
for _ in 0..20 {
index_writer.add_document(doc!(text_field => "cool"))?;
}
}
}
// writing the segment
index_writer.commit()?;
}
Ok(index)
}

View File

@@ -18,7 +18,7 @@ fn benchmark(
benchmark_dynamic_json(b, input, schema, commit, parse_json)
} else {
_benchmark(b, input, schema, commit, parse_json, |schema, doc_json| {
TantivyDocument::parse_json(schema, doc_json).unwrap()
TantivyDocument::parse_json(&schema, doc_json).unwrap()
})
}
}
@@ -90,7 +90,8 @@ fn benchmark_dynamic_json(
) {
let json_field = schema.get_field("json").unwrap();
_benchmark(b, input, schema, commit, parse_json, |_schema, doc_json| {
let json_val: serde_json::Value = serde_json::from_str(doc_json).unwrap();
let json_val: serde_json::Map<String, serde_json::Value> =
serde_json::from_str(doc_json).unwrap();
tantivy::doc!(json_field=>json_val)
})
}
@@ -137,16 +138,15 @@ pub fn hdfs_index_benchmark(c: &mut Criterion) {
for (prefix, schema, is_dynamic) in benches {
for commit in [false, true] {
let suffix = if commit { "with-commit" } else { "no-commit" };
{
let parse_json = false;
for parse_json in [false] {
// for parse_json in [false, true] {
let suffix = if parse_json {
format!("{suffix}-with-json-parsing")
format!("{}-with-json-parsing", suffix)
} else {
suffix.to_string()
format!("{}", suffix)
};
let bench_name = format!("{prefix}{suffix}");
let bench_name = format!("{}{}", prefix, suffix);
group.bench_function(bench_name, |b| {
benchmark(b, HDFS_LOGS, schema.clone(), commit, parse_json, is_dynamic)
});

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-bitpacker"
version = "0.6.0"
version = "0.5.0"
edition = "2021"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"

View File

@@ -1,3 +1,4 @@
use std::convert::TryInto;
use std::io;
use std::ops::{Range, RangeInclusive};
@@ -124,6 +125,8 @@ impl BitUnpacker {
// Decodes the range of bitpacked `u32` values with idx
// in [start_idx, start_idx + output.len()).
// It is guaranteed to completely fill `output` and not read from it, so passing a vector with
// un-initialized values is safe.
//
// #Panics
//
@@ -236,7 +239,19 @@ impl BitUnpacker {
data: &[u8],
positions: &mut Vec<u32>,
) {
positions.resize(id_range.len(), 0u32);
// We use the code below instead of positions.resize(id_range.len(), 0u32) for performance
// reasons: on some queries, the CPU cost of memsetting the array and of using a bigger
// vector than necessary is noticeable (~5%).
// In particular, searches are a few percent faster when using reserve_exact() as below
// instead of reserve().
// The un-initialized values are safe as get_batch_u32s() completely fills `positions`
// and does not read from it.
positions.clear();
positions.reserve_exact(id_range.len());
#[allow(clippy::uninit_vec)]
unsafe {
positions.set_len(id_range.len());
}
self.get_batch_u32s(id_range.start, data, positions);
crate::filter_vec::filter_vec_in_place(value_range, id_range.start, positions)
}

View File

@@ -1,10 +1,6 @@
# configuration file for git-cliff{ pattern = "foo", replace = "bar"}
# see https://github.com/orhun/git-cliff#configuration-file
[remote.github]
owner = "quickwit-oss"
repo = "tantivy"
[changelog]
# changelog header
header = """
@@ -12,43 +8,15 @@ header = """
# template for the changelog body
# https://tera.netlify.app/docs/#introduction
body = """
## What's Changed
{%- if version %} in {{ version }}{%- endif -%}
{% if version %}\
{{ version | trim_start_matches(pat="v") }} ({{ timestamp | date(format="%Y-%m-%d") }})
==================
{% else %}\
## [unreleased]
{% endif %}\
{% for commit in commits %}
{% if commit.github.pr_title -%}
{%- set commit_message = commit.github.pr_title -%}
{%- else -%}
{%- set commit_message = commit.message -%}
{%- endif -%}
- {{ commit_message | split(pat="\n") | first | trim }}\
{% if commit.github.pr_number %} \
[#{{ commit.github.pr_number }}]({{ self::remote_url() }}/pull/{{ commit.github.pr_number }}){% if commit.github.username %}(@{{ commit.github.username }}){%- endif -%} \
{%- endif %}
{%- endfor -%}
{% if github.contributors | filter(attribute="is_first_time", value=true) | length != 0 %}
{% raw %}\n{% endraw -%}
## New Contributors
{%- endif %}\
{% for contributor in github.contributors | filter(attribute="is_first_time", value=true) %}
* @{{ contributor.username }} made their first contribution
{%- if contributor.pr_number %} in \
[#{{ contributor.pr_number }}]({{ self::remote_url() }}/pull/{{ contributor.pr_number }}) \
{%- endif %}
{%- endfor -%}
{% if version %}
{% if previous.version %}
**Full Changelog**: {{ self::remote_url() }}/compare/{{ previous.version }}...{{ version }}
{% endif %}
{% else -%}
{% raw %}\n{% endraw %}
{% endif %}
{%- macro remote_url() -%}
https://github.com/{{ remote.github.owner }}/{{ remote.github.repo }}
{%- endmacro -%}
- {% 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
@@ -57,24 +25,53 @@ 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 = false
conventional_commits = true
# filter out the commits that are not conventional
filter_unconventional = true
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 = ""},
{ 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

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-columnar"
version = "0.3.0"
version = "0.2.0"
edition = "2021"
license = "MIT"
homepage = "https://github.com/quickwit-oss/tantivy"
@@ -9,30 +9,19 @@ description = "column oriented storage for tantivy"
categories = ["database-implementations", "data-structures", "compression"]
[dependencies]
itertools = "0.13.0"
itertools = "0.12.0"
fastdivide = "0.4.0"
stacker = { version= "0.3", path = "../stacker", package="tantivy-stacker"}
sstable = { version= "0.3", path = "../sstable", package = "tantivy-sstable" }
common = { version= "0.7", path = "../common", package = "tantivy-common" }
tantivy-bitpacker = { version= "0.6", 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"
downcast-rs = "1.2.0"
[dev-dependencies]
proptest = "1"
more-asserts = "0.3.1"
rand = "0.8"
binggan = "0.8.1"
[[bench]]
name = "bench_merge"
harness = false
[[bench]]
name = "bench_access"
harness = false
[features]
unstable = []

View File

@@ -1,67 +0,0 @@
use binggan::{black_box, InputGroup};
use common::*;
use tantivy_columnar::Column;
pub mod common;
const NUM_DOCS: u32 = 2_000_000;
pub fn generate_columnar_and_open(card: Card, num_docs: u32) -> Column {
let reader = generate_columnar_with_name(card, num_docs, "price");
reader.read_columns("price").unwrap()[0]
.open_u64_lenient()
.unwrap()
.unwrap()
}
fn main() {
let mut inputs = Vec::new();
let mut add_card = |card1: Card| {
inputs.push((
format!("{card1}"),
generate_columnar_and_open(card1, NUM_DOCS),
));
};
add_card(Card::MultiSparse);
add_card(Card::Multi);
add_card(Card::Sparse);
add_card(Card::Dense);
add_card(Card::Full);
bench_group(InputGroup::new_with_inputs(inputs));
}
fn bench_group(mut runner: InputGroup<Column>) {
runner.register("access_values_for_doc", |column| {
let mut sum = 0;
for i in 0..NUM_DOCS {
for value in column.values_for_doc(i) {
sum += value;
}
}
black_box(sum);
});
runner.register("access_first_vals", |column| {
let mut sum = 0;
const BLOCK_SIZE: usize = 32;
let mut docs = vec![0; BLOCK_SIZE];
let mut buffer = vec![None; BLOCK_SIZE];
for i in (0..NUM_DOCS).step_by(BLOCK_SIZE) {
// fill docs
for idx in 0..BLOCK_SIZE {
docs[idx] = idx as u32 + i;
}
column.first_vals(&docs, &mut buffer);
for val in buffer.iter() {
let Some(val) = val else { continue };
sum += *val;
}
}
black_box(sum);
});
runner.run();
}

View File

@@ -1,155 +0,0 @@
#![feature(test)]
extern crate test;
use std::sync::Arc;
use rand::prelude::*;
use tantivy_columnar::column_values::{serialize_and_load_u64_based_column_values, CodecType};
use tantivy_columnar::*;
use test::{black_box, Bencher};
struct Columns {
pub optional: Column,
pub full: Column,
pub multi: Column,
}
fn get_test_columns() -> Columns {
let data = generate_permutation();
let mut dataframe_writer = ColumnarWriter::default();
for (idx, val) in data.iter().enumerate() {
dataframe_writer.record_numerical(idx as u32, "full_values", NumericalValue::U64(*val));
if idx % 2 == 0 {
dataframe_writer.record_numerical(
idx as u32,
"optional_values",
NumericalValue::U64(*val),
);
}
dataframe_writer.record_numerical(idx as u32, "multi_values", NumericalValue::U64(*val));
dataframe_writer.record_numerical(idx as u32, "multi_values", NumericalValue::U64(*val));
}
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer
.serialize(data.len() as u32, &mut buffer)
.unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("optional_values").unwrap();
assert_eq!(cols.len(), 1);
let optional = cols[0].open_u64_lenient().unwrap().unwrap();
assert_eq!(optional.index.get_cardinality(), Cardinality::Optional);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("full_values").unwrap();
assert_eq!(cols.len(), 1);
let column_full = cols[0].open_u64_lenient().unwrap().unwrap();
assert_eq!(column_full.index.get_cardinality(), Cardinality::Full);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("multi_values").unwrap();
assert_eq!(cols.len(), 1);
let multi = cols[0].open_u64_lenient().unwrap().unwrap();
assert_eq!(multi.index.get_cardinality(), Cardinality::Multivalued);
Columns {
optional,
full: column_full,
multi,
}
}
const NUM_VALUES: u64 = 100_000;
fn generate_permutation() -> Vec<u64> {
let mut permutation: Vec<u64> = (0u64..NUM_VALUES).collect();
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
pub fn serialize_and_load(column: &[u64], codec_type: CodecType) -> Arc<dyn ColumnValues<u64>> {
serialize_and_load_u64_based_column_values(&column, &[codec_type])
}
fn run_bench_on_column_full_scan(b: &mut Bencher, column: Column) {
let num_iter = black_box(NUM_VALUES);
b.iter(|| {
let mut sum = 0u64;
for i in 0..num_iter as u32 {
let val = column.first(i);
sum += val.unwrap_or(0);
}
sum
});
}
fn run_bench_on_column_block_fetch(b: &mut Bencher, column: Column) {
let mut block: Vec<Option<u64>> = vec![None; 64];
let fetch_docids = (0..64).collect::<Vec<_>>();
b.iter(move || {
column.first_vals(&fetch_docids, &mut block);
block[0]
});
}
fn run_bench_on_column_block_single_calls(b: &mut Bencher, column: Column) {
let mut block: Vec<Option<u64>> = vec![None; 64];
let fetch_docids = (0..64).collect::<Vec<_>>();
b.iter(move || {
for i in 0..fetch_docids.len() {
block[i] = column.first(fetch_docids[i]);
}
block[0]
});
}
/// Column first method
#[bench]
fn bench_get_first_on_full_column_full_scan(b: &mut Bencher) {
let column = get_test_columns().full;
run_bench_on_column_full_scan(b, column);
}
#[bench]
fn bench_get_first_on_optional_column_full_scan(b: &mut Bencher) {
let column = get_test_columns().optional;
run_bench_on_column_full_scan(b, column);
}
#[bench]
fn bench_get_first_on_multi_column_full_scan(b: &mut Bencher) {
let column = get_test_columns().multi;
run_bench_on_column_full_scan(b, column);
}
/// Block fetch column accessor
#[bench]
fn bench_get_block_first_on_optional_column(b: &mut Bencher) {
let column = get_test_columns().optional;
run_bench_on_column_block_fetch(b, column);
}
#[bench]
fn bench_get_block_first_on_multi_column(b: &mut Bencher) {
let column = get_test_columns().multi;
run_bench_on_column_block_fetch(b, column);
}
#[bench]
fn bench_get_block_first_on_full_column(b: &mut Bencher) {
let column = get_test_columns().full;
run_bench_on_column_block_fetch(b, column);
}
#[bench]
fn bench_get_block_first_on_optional_column_single_calls(b: &mut Bencher) {
let column = get_test_columns().optional;
run_bench_on_column_block_single_calls(b, column);
}
#[bench]
fn bench_get_block_first_on_multi_column_single_calls(b: &mut Bencher) {
let column = get_test_columns().multi;
run_bench_on_column_block_single_calls(b, column);
}
#[bench]
fn bench_get_block_first_on_full_column_single_calls(b: &mut Bencher) {
let column = get_test_columns().full;
run_bench_on_column_block_single_calls(b, column);
}

View File

@@ -1,49 +0,0 @@
pub mod common;
use binggan::{black_box, BenchRunner};
use common::{generate_columnar_with_name, Card};
use tantivy_columnar::*;
const NUM_DOCS: u32 = 100_000;
fn main() {
let mut inputs = Vec::new();
let mut add_combo = |card1: Card, card2: Card| {
inputs.push((
format!("merge_{card1}_and_{card2}"),
vec![
generate_columnar_with_name(card1, NUM_DOCS, "price"),
generate_columnar_with_name(card2, NUM_DOCS, "price"),
],
));
};
add_combo(Card::Multi, Card::Multi);
add_combo(Card::MultiSparse, Card::MultiSparse);
add_combo(Card::Dense, Card::Dense);
add_combo(Card::Sparse, Card::Sparse);
add_combo(Card::Sparse, Card::Dense);
add_combo(Card::MultiSparse, Card::Dense);
add_combo(Card::MultiSparse, Card::Sparse);
add_combo(Card::Multi, Card::Dense);
add_combo(Card::Multi, Card::Sparse);
let runner: BenchRunner = BenchRunner::new();
let mut group = runner.new_group();
for (input_name, columnar_readers) in inputs.iter() {
group.register_with_input(
input_name,
columnar_readers,
move |columnar_readers: &Vec<ColumnarReader>| {
let mut out = Vec::new();
let columnar_readers = columnar_readers.iter().collect::<Vec<_>>();
let merge_row_order = StackMergeOrder::stack(&columnar_readers[..]);
merge_columnar(&columnar_readers, &[], merge_row_order.into(), &mut out).unwrap();
black_box(out);
},
);
}
group.run();
}

View File

@@ -16,6 +16,14 @@ fn generate_permutation() -> Vec<u64> {
permutation
}
fn generate_random() -> Vec<u64> {
let mut permutation: Vec<u64> = (0u64..100_000u64)
.map(|el| el + random::<u16>() as u64)
.collect();
permutation.shuffle(&mut StdRng::from_seed([1u8; 32]));
permutation
}
// Warning: this generates the same permutation at each call
fn generate_permutation_gcd() -> Vec<u64> {
let mut permutation: Vec<u64> = (1u64..100_000u64).map(|el| el * 1000).collect();

View File

@@ -1,59 +0,0 @@
extern crate tantivy_columnar;
use core::fmt;
use std::fmt::{Display, Formatter};
use tantivy_columnar::{ColumnarReader, ColumnarWriter};
pub enum Card {
MultiSparse,
Multi,
Sparse,
Dense,
Full,
}
impl Display for Card {
fn fmt(&self, f: &mut Formatter) -> fmt::Result {
match self {
Card::MultiSparse => write!(f, "multi sparse 1/13"),
Card::Multi => write!(f, "multi 2x"),
Card::Sparse => write!(f, "sparse 1/13"),
Card::Dense => write!(f, "dense 1/12"),
Card::Full => write!(f, "full"),
}
}
}
pub fn generate_columnar_with_name(card: Card, num_docs: u32, column_name: &str) -> ColumnarReader {
let mut columnar_writer = ColumnarWriter::default();
if let Card::MultiSparse = card {
columnar_writer.record_numerical(0, column_name, 10u64);
columnar_writer.record_numerical(0, column_name, 10u64);
}
for i in 0..num_docs {
match card {
Card::MultiSparse | Card::Sparse => {
if i % 13 == 0 {
columnar_writer.record_numerical(i, column_name, i as u64);
}
}
Card::Dense => {
if i % 12 == 0 {
columnar_writer.record_numerical(i, column_name, i as u64);
}
}
Card::Full => {
columnar_writer.record_numerical(i, column_name, i as u64);
}
Card::Multi => {
columnar_writer.record_numerical(i, column_name, i as u64);
columnar_writer.record_numerical(i, column_name, i as u64);
}
}
}
let mut wrt: Vec<u8> = Vec::new();
columnar_writer.serialize(num_docs, &mut wrt).unwrap();
ColumnarReader::open(wrt).unwrap()
}

View File

@@ -14,32 +14,20 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
ColumnBlockAccessor<T>
{
#[inline]
pub fn fetch_block<'a>(&'a mut self, docs: &'a [u32], accessor: &Column<T>) {
if accessor.index.get_cardinality().is_full() {
self.val_cache.resize(docs.len(), T::default());
accessor.values.get_vals(docs, &mut self.val_cache);
} else {
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);
}
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);
// no missing values
if accessor.index.get_cardinality().is_full() {
return;
}
// We can compare docid_cache length with docs to find missing docs
// For multi value columns we can't rely on the length and always need to scan
if accessor.index.get_cardinality().is_multivalue() || docs.len() != self.docid_cache.len()
{
// 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);
@@ -56,25 +44,11 @@ impl<T: PartialOrd + Copy + std::fmt::Debug + Send + Sync + 'static + Default>
}
#[inline]
/// Returns an iterator over the docids and values
/// The passed in `docs` slice needs to be the same slice that was passed to `fetch_block` or
/// `fetch_block_with_missing`.
///
/// The docs is used if the column is full (each docs has exactly one value), otherwise the
/// internal docid vec is used for the iterator, which e.g. may contain duplicate docs.
pub fn iter_docid_vals<'a>(
&'a self,
docs: &'a [u32],
accessor: &Column<T>,
) -> impl Iterator<Item = (DocId, T)> + '_ {
if accessor.index.get_cardinality().is_full() {
docs.iter().cloned().zip(self.val_cache.iter().cloned())
} else {
self.docid_cache
.iter()
.cloned()
.zip(self.val_cache.iter().cloned())
}
pub fn iter_docid_vals(&self) -> impl Iterator<Item = (DocId, T)> + '_ {
self.docid_cache
.iter()
.cloned()
.zip(self.val_cache.iter().cloned())
}
}

View File

@@ -3,17 +3,17 @@ mod serialize;
use std::fmt::{self, Debug};
use std::io::Write;
use std::ops::{Range, RangeInclusive};
use std::ops::{Deref, Range, RangeInclusive};
use std::sync::Arc;
use common::BinarySerializable;
pub use dictionary_encoded::{BytesColumn, StrColumn};
pub use serialize::{
open_column_bytes, open_column_str, open_column_u128, open_column_u128_as_compact_u64,
open_column_u64, serialize_column_mappable_to_u128, serialize_column_mappable_to_u64,
open_column_bytes, open_column_str, open_column_u128, open_column_u64,
serialize_column_mappable_to_u128, serialize_column_mappable_to_u64,
};
use crate::column_index::{ColumnIndex, Set};
use crate::column_index::ColumnIndex;
use crate::column_values::monotonic_mapping::StrictlyMonotonicMappingToInternal;
use crate::column_values::{monotonic_map_column, ColumnValues};
use crate::{Cardinality, DocId, EmptyColumnValues, MonotonicallyMappableToU64, RowId};
@@ -83,36 +83,10 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
self.values.max_value()
}
#[inline]
pub fn first(&self, row_id: RowId) -> Option<T> {
self.values_for_doc(row_id).next()
}
/// Load the first value for each docid in the provided slice.
#[inline]
pub fn first_vals(&self, docids: &[DocId], output: &mut [Option<T>]) {
match &self.index {
ColumnIndex::Empty { .. } => {}
ColumnIndex::Full => self.values.get_vals_opt(docids, output),
ColumnIndex::Optional(optional_index) => {
for (i, docid) in docids.iter().enumerate() {
output[i] = optional_index
.rank_if_exists(*docid)
.map(|rowid| self.values.get_val(rowid));
}
}
ColumnIndex::Multivalued(multivalued_index) => {
for (i, docid) in docids.iter().enumerate() {
let range = multivalued_index.range(*docid);
let is_empty = range.start == range.end;
if !is_empty {
output[i] = Some(self.values.get_val(range.start));
}
}
}
}
}
/// Translates a block of docis to row_ids.
///
/// returns the row_ids and the matching docids on the same index
@@ -131,12 +105,11 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
}
pub fn values_for_doc(&self, doc_id: DocId) -> impl Iterator<Item = T> + '_ {
self.index
.value_row_ids(doc_id)
self.value_row_ids(doc_id)
.map(|value_row_id: RowId| self.values.get_val(value_row_id))
}
/// Get the docids of values which are in the provided value and docid range.
/// Get the docids of values which are in the provided value range.
#[inline]
pub fn get_docids_for_value_range(
&self,
@@ -174,6 +147,14 @@ impl<T: PartialOrd + Copy + Debug + Send + Sync + 'static> Column<T> {
}
}
impl<T> Deref for Column<T> {
type Target = ColumnIndex;
fn deref(&self) -> &Self::Target {
&self.index
}
}
impl BinarySerializable for Cardinality {
fn serialize<W: Write + ?Sized>(&self, writer: &mut W) -> std::io::Result<()> {
self.to_code().serialize(writer)
@@ -195,7 +176,6 @@ struct FirstValueWithDefault<T: Copy> {
impl<T: PartialOrd + Debug + Send + Sync + Copy + 'static> ColumnValues<T>
for FirstValueWithDefault<T>
{
#[inline(always)]
fn get_val(&self, idx: u32) -> T {
self.column.first(idx).unwrap_or(self.default_value)
}

View File

@@ -12,7 +12,7 @@ use crate::column_values::{
CodecType, MonotonicallyMappableToU128, MonotonicallyMappableToU64,
};
use crate::iterable::Iterable;
use crate::{StrColumn, Version};
use crate::StrColumn;
pub fn serialize_column_mappable_to_u128<T: MonotonicallyMappableToU128>(
column_index: SerializableColumnIndex<'_>,
@@ -40,10 +40,7 @@ pub fn serialize_column_mappable_to_u64<T: MonotonicallyMappableToU64>(
Ok(())
}
pub fn open_column_u64<T: MonotonicallyMappableToU64>(
bytes: OwnedBytes,
format_version: Version,
) -> io::Result<Column<T>> {
pub fn open_column_u64<T: MonotonicallyMappableToU64>(bytes: OwnedBytes) -> io::Result<Column<T>> {
let (body, column_index_num_bytes_payload) = bytes.rsplit(4);
let column_index_num_bytes = u32::from_le_bytes(
column_index_num_bytes_payload
@@ -52,7 +49,7 @@ pub fn open_column_u64<T: MonotonicallyMappableToU64>(
.unwrap(),
);
let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
let column_index = crate::column_index::open_column_index(column_index_data, format_version)?;
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 {
index: column_index,
@@ -62,7 +59,6 @@ pub fn open_column_u64<T: MonotonicallyMappableToU64>(
pub fn open_column_u128<T: MonotonicallyMappableToU128>(
bytes: OwnedBytes,
format_version: Version,
) -> io::Result<Column<T>> {
let (body, column_index_num_bytes_payload) = bytes.rsplit(4);
let column_index_num_bytes = u32::from_le_bytes(
@@ -72,7 +68,7 @@ pub fn open_column_u128<T: MonotonicallyMappableToU128>(
.unwrap(),
);
let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
let column_index = crate::column_index::open_column_index(column_index_data, format_version)?;
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 {
index: column_index,
@@ -80,42 +76,19 @@ pub fn open_column_u128<T: MonotonicallyMappableToU128>(
})
}
/// Open the column as u64.
///
/// See [`open_u128_as_compact_u64`] for more details.
pub fn open_column_u128_as_compact_u64(
bytes: OwnedBytes,
format_version: Version,
) -> io::Result<Column<u64>> {
let (body, column_index_num_bytes_payload) = bytes.rsplit(4);
let column_index_num_bytes = u32::from_le_bytes(
column_index_num_bytes_payload
.as_slice()
.try_into()
.unwrap(),
);
let (column_index_data, column_values_data) = body.split(column_index_num_bytes as usize);
let column_index = crate::column_index::open_column_index(column_index_data, format_version)?;
let column_values = crate::column_values::open_u128_as_compact_u64(column_values_data)?;
Ok(Column {
index: column_index,
values: column_values,
})
}
pub fn open_column_bytes(data: OwnedBytes, format_version: Version) -> io::Result<BytesColumn> {
pub fn open_column_bytes(data: OwnedBytes) -> io::Result<BytesColumn> {
let (body, dictionary_len_bytes) = data.rsplit(4);
let dictionary_len = u32::from_le_bytes(dictionary_len_bytes.as_slice().try_into().unwrap());
let (dictionary_bytes, column_bytes) = body.split(dictionary_len as usize);
let dictionary = Arc::new(Dictionary::from_bytes(dictionary_bytes)?);
let term_ord_column = crate::column::open_column_u64::<u64>(column_bytes, format_version)?;
let term_ord_column = crate::column::open_column_u64::<u64>(column_bytes)?;
Ok(BytesColumn {
dictionary,
term_ord_column,
})
}
pub fn open_column_str(data: OwnedBytes, format_version: Version) -> io::Result<StrColumn> {
let bytes_column = open_column_bytes(data, format_version)?;
pub fn open_column_str(data: OwnedBytes) -> io::Result<StrColumn> {
let bytes_column = open_column_bytes(data)?;
Ok(StrColumn::wrap(bytes_column))
}

View File

@@ -95,12 +95,8 @@ pub fn merge_column_index<'a>(
#[cfg(test)]
mod tests {
use common::OwnedBytes;
use crate::column_index::merge::detect_cardinality;
use crate::column_index::multivalued_index::{
open_multivalued_index, serialize_multivalued_index, MultiValueIndex,
};
use crate::column_index::multivalued_index::MultiValueIndex;
use crate::column_index::{merge_column_index, OptionalIndex, SerializableColumnIndex};
use crate::{
Cardinality, ColumnIndex, MergeRowOrder, RowAddr, RowId, ShuffleMergeOrder, StackMergeOrder,
@@ -175,11 +171,7 @@ mod tests {
let SerializableColumnIndex::Multivalued(start_index_iterable) = merged_column_index else {
panic!("Excpected a multivalued index")
};
let mut output = Vec::new();
serialize_multivalued_index(&start_index_iterable, &mut output).unwrap();
let multivalue =
open_multivalued_index(OwnedBytes::new(output), crate::Version::V2).unwrap();
let start_indexes: Vec<RowId> = multivalue.get_start_index_column().iter().collect();
let start_indexes: Vec<RowId> = start_index_iterable.boxed_iter().collect();
assert_eq!(&start_indexes, &[0, 3, 5]);
}
@@ -208,16 +200,11 @@ 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 mut output = Vec::new();
serialize_multivalued_index(&start_index_iterable, &mut output).unwrap();
let multivalue =
open_multivalued_index(OwnedBytes::new(output), crate::Version::V2).unwrap();
let start_indexes: Vec<RowId> = multivalue.get_start_index_column().iter().collect();
let start_indexes: Vec<RowId> = start_index_iterable.boxed_iter().collect();
assert_eq!(&start_indexes, &[0, 3, 5, 6]);
}
}

View File

@@ -1,8 +1,6 @@
use std::iter;
use crate::column_index::{
SerializableColumnIndex, SerializableMultivalueIndex, SerializableOptionalIndex, Set,
};
use crate::column_index::{SerializableColumnIndex, Set};
use crate::iterable::Iterable;
use crate::{Cardinality, ColumnIndex, RowId, ShuffleMergeOrder};
@@ -16,24 +14,15 @@ pub fn merge_column_index_shuffled<'a>(
Cardinality::Optional => {
let non_null_row_ids =
merge_column_index_shuffled_optional(column_indexes, shuffle_merge_order);
SerializableColumnIndex::Optional(SerializableOptionalIndex {
SerializableColumnIndex::Optional {
non_null_row_ids,
num_rows: shuffle_merge_order.num_rows(),
})
}
}
Cardinality::Multivalued => {
let non_null_row_ids =
merge_column_index_shuffled_optional(column_indexes, shuffle_merge_order);
SerializableColumnIndex::Multivalued(SerializableMultivalueIndex {
doc_ids_with_values: SerializableOptionalIndex {
non_null_row_ids,
num_rows: shuffle_merge_order.num_rows(),
},
start_offsets: merge_column_index_shuffled_multivalued(
column_indexes,
shuffle_merge_order,
),
})
let multivalue_start_index =
merge_column_index_shuffled_multivalued(column_indexes, shuffle_merge_order);
SerializableColumnIndex::Multivalued(multivalue_start_index)
}
}
}
@@ -113,18 +102,11 @@ fn iter_num_values<'a>(
/// Transforms an iterator containing the number of vals per row (with `num_rows` elements)
/// into a `start_offset` iterator starting at 0 and (with `num_rows + 1` element)
///
/// This will filter values with 0 values as these are covered by the optional index in the
/// multivalue index.
fn integrate_num_vals(num_vals: impl Iterator<Item = u32>) -> impl Iterator<Item = RowId> {
iter::once(0u32).chain(
num_vals
.filter(|num_vals| *num_vals != 0)
.scan(0, |state, num_vals| {
*state += num_vals;
Some(*state)
}),
)
iter::once(0u32).chain(num_vals.scan(0, |state, num_vals| {
*state += num_vals;
Some(*state)
}))
}
impl<'a> Iterable<u32> for ShuffledMultivaluedIndex<'a> {
@@ -152,13 +134,13 @@ mod tests {
#[test]
fn test_integrate_num_vals_several() {
assert!(integrate_num_vals([3, 0, 10, 20].into_iter()).eq([0, 3, 13, 33].into_iter()));
assert!(integrate_num_vals([3, 0, 10, 20].into_iter()).eq([0, 3, 3, 13, 33].into_iter()));
}
#[test]
fn test_merge_column_index_optional_shuffle() {
let optional_index: ColumnIndex = OptionalIndex::for_test(2, &[0]).into();
let column_indexes = [optional_index, ColumnIndex::Full];
let column_indexes = vec![optional_index, ColumnIndex::Full];
let row_addrs = vec![
RowAddr {
segment_ord: 0u32,
@@ -175,10 +157,10 @@ mod tests {
Cardinality::Optional,
&shuffle_merge_order,
);
let SerializableColumnIndex::Optional(SerializableOptionalIndex {
let SerializableColumnIndex::Optional {
non_null_row_ids,
num_rows,
}) = serializable_index
} = serializable_index
else {
panic!()
};

View File

@@ -1,8 +1,6 @@
use std::ops::Range;
use std::iter;
use crate::column_index::multivalued_index::{MultiValueIndex, SerializableMultivalueIndex};
use crate::column_index::serialize::SerializableOptionalIndex;
use crate::column_index::SerializableColumnIndex;
use crate::column_index::{SerializableColumnIndex, Set};
use crate::iterable::Iterable;
use crate::{Cardinality, ColumnIndex, RowId, StackMergeOrder};
@@ -17,146 +15,20 @@ pub fn merge_column_index_stacked<'a>(
) -> SerializableColumnIndex<'a> {
match cardinality_after_merge {
Cardinality::Full => SerializableColumnIndex::Full,
Cardinality::Optional => SerializableColumnIndex::Optional(SerializableOptionalIndex {
Cardinality::Optional => SerializableColumnIndex::Optional {
non_null_row_ids: Box::new(StackedOptionalIndex {
columns,
stack_merge_order,
}),
num_rows: stack_merge_order.num_rows(),
}),
Cardinality::Multivalued => {
let serializable_multivalue_index =
make_serializable_multivalued_index(columns, stack_merge_order);
SerializableColumnIndex::Multivalued(serializable_multivalue_index)
}
}
}
struct StackedDocIdsWithValues<'a> {
column_indexes: &'a [ColumnIndex],
stack_merge_order: &'a StackMergeOrder,
}
impl Iterable<u32> for StackedDocIdsWithValues<'_> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
Box::new((0..self.column_indexes.len()).flat_map(|i| {
let column_index = &self.column_indexes[i];
let doc_range = self.stack_merge_order.columnar_range(i);
get_doc_ids_with_values(column_index, doc_range)
}))
}
}
fn get_doc_ids_with_values<'a>(
column_index: &'a ColumnIndex,
doc_range: Range<u32>,
) -> Box<dyn Iterator<Item = u32> + 'a> {
match column_index {
ColumnIndex::Empty { .. } => Box::new(0..0),
ColumnIndex::Full => Box::new(doc_range),
ColumnIndex::Optional(optional_index) => Box::new(
optional_index
.iter_rows()
.map(move |row| row + doc_range.start),
),
ColumnIndex::Multivalued(multivalued_index) => match multivalued_index {
MultiValueIndex::MultiValueIndexV1(multivalued_index) => {
Box::new((0..multivalued_index.num_docs()).filter_map(move |docid| {
let range = multivalued_index.range(docid);
if range.is_empty() {
None
} else {
Some(docid + doc_range.start)
}
}))
}
MultiValueIndex::MultiValueIndexV2(multivalued_index) => Box::new(
multivalued_index
.optional_index
.iter_rows()
.map(move |row| row + doc_range.start),
),
},
}
}
fn stack_doc_ids_with_values<'a>(
column_indexes: &'a [ColumnIndex],
stack_merge_order: &'a StackMergeOrder,
) -> SerializableOptionalIndex<'a> {
let num_rows = stack_merge_order.num_rows();
SerializableOptionalIndex {
non_null_row_ids: Box::new(StackedDocIdsWithValues {
column_indexes,
stack_merge_order,
}),
num_rows,
}
}
struct StackedStartOffsets<'a> {
column_indexes: &'a [ColumnIndex],
stack_merge_order: &'a StackMergeOrder,
}
fn get_num_values_iterator<'a>(
column_index: &'a ColumnIndex,
num_docs: u32,
) -> Box<dyn Iterator<Item = u32> + 'a> {
match column_index {
ColumnIndex::Empty { .. } => Box::new(std::iter::empty()),
ColumnIndex::Full => Box::new(std::iter::repeat(1u32).take(num_docs as usize)),
ColumnIndex::Optional(optional_index) => {
Box::new(std::iter::repeat(1u32).take(optional_index.num_non_nulls() as usize))
Cardinality::Multivalued => {
let stacked_multivalued_index = StackedMultivaluedIndex {
columns,
stack_merge_order,
};
SerializableColumnIndex::Multivalued(Box::new(stacked_multivalued_index))
}
ColumnIndex::Multivalued(multivalued_index) => Box::new(
multivalued_index
.get_start_index_column()
.iter()
.scan(0u32, |previous_start_offset, current_start_offset| {
let num_vals = current_start_offset - *previous_start_offset;
*previous_start_offset = current_start_offset;
Some(num_vals)
})
.skip(1),
),
}
}
impl<'a> Iterable<u32> for StackedStartOffsets<'a> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
let num_values_it = (0..self.column_indexes.len()).flat_map(|columnar_id| {
let num_docs = self.stack_merge_order.columnar_range(columnar_id).len() as u32;
let column_index = &self.column_indexes[columnar_id];
get_num_values_iterator(column_index, num_docs)
});
Box::new(std::iter::once(0u32).chain(num_values_it.into_iter().scan(
0u32,
|cumulated, el| {
*cumulated += el;
Some(*cumulated)
},
)))
}
}
fn stack_start_offsets<'a>(
column_indexes: &'a [ColumnIndex],
stack_merge_order: &'a StackMergeOrder,
) -> Box<dyn Iterable<u32> + 'a> {
Box::new(StackedStartOffsets {
column_indexes,
stack_merge_order,
})
}
fn make_serializable_multivalued_index<'a>(
columns: &'a [ColumnIndex],
stack_merge_order: &'a StackMergeOrder,
) -> SerializableMultivalueIndex<'a> {
SerializableMultivalueIndex {
doc_ids_with_values: stack_doc_ids_with_values(columns, stack_merge_order),
start_offsets: stack_start_offsets(columns, stack_merge_order),
}
}
@@ -190,3 +62,87 @@ impl<'a> Iterable<RowId> for StackedOptionalIndex<'a> {
)
}
}
#[derive(Clone, Copy)]
struct StackedMultivaluedIndex<'a> {
columns: &'a [ColumnIndex],
stack_merge_order: &'a StackMergeOrder,
}
fn convert_column_opt_to_multivalued_index<'a>(
column_index_opt: &'a ColumnIndex,
num_rows: RowId,
) -> Box<dyn Iterator<Item = RowId> + 'a> {
match column_index_opt {
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
.map(|row_id| optional_index.rank(row_id))
.chain(std::iter::once(optional_index.num_non_nulls())),
)
}
ColumnIndex::Multivalued(multivalued_index) => multivalued_index.start_index_column.iter(),
}
}
impl<'a> Iterable<RowId> for StackedMultivaluedIndex<'a> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = RowId> + '_> {
let multivalued_indexes =
self.columns
.iter()
.enumerate()
.map(|(columnar_id, column_opt)| {
let num_rows =
self.stack_merge_order.columnar_range(columnar_id).len() as RowId;
convert_column_opt_to_multivalued_index(column_opt, num_rows)
});
stack_multivalued_indexes(multivalued_indexes)
}
}
// Refactor me
fn stack_multivalued_indexes<'a>(
mut multivalued_indexes: impl Iterator<Item = Box<dyn Iterator<Item = RowId> + 'a>> + 'a,
) -> Box<dyn Iterator<Item = RowId> + 'a> {
let mut offset = 0;
let mut last_row_id = 0;
let mut current_it = multivalued_indexes.next();
Box::new(std::iter::from_fn(move || loop {
if let Some(row_id) = current_it.as_mut()?.next() {
last_row_id = offset + row_id;
return Some(last_row_id);
}
offset = last_row_id;
loop {
current_it = multivalued_indexes.next();
if current_it.as_mut()?.next().is_some() {
break;
}
}
}))
}
#[cfg(test)]
mod tests {
use crate::RowId;
fn it<'a>(row_ids: &'a [RowId]) -> Box<dyn Iterator<Item = RowId> + 'a> {
Box::new(row_ids.iter().copied())
}
#[test]
fn test_stack() {
let columns = [
it(&[0u32, 0u32]),
it(&[0u32, 1u32, 1u32, 4u32]),
it(&[0u32, 3u32, 5u32]),
it(&[0u32, 4u32]),
]
.into_iter();
let start_offsets: Vec<RowId> = super::stack_multivalued_indexes(columns).collect();
assert_eq!(start_offsets, &[0, 0, 1, 1, 4, 7, 9, 13]);
}
}

View File

@@ -11,11 +11,8 @@ mod serialize;
use std::ops::Range;
pub use merge::merge_column_index;
pub(crate) use multivalued_index::SerializableMultivalueIndex;
pub use optional_index::{OptionalIndex, Set};
pub use serialize::{
open_column_index, serialize_column_index, SerializableColumnIndex, SerializableOptionalIndex,
};
pub use serialize::{open_column_index, serialize_column_index, SerializableColumnIndex};
use crate::column_index::multivalued_index::MultiValueIndex;
use crate::{Cardinality, DocId, RowId};
@@ -45,6 +42,10 @@ 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
@@ -134,41 +135,15 @@ impl ColumnIndex {
let row_end = optional_index.rank(doc_id_range.end);
row_start..row_end
}
ColumnIndex::Multivalued(multivalued_index) => match multivalued_index {
MultiValueIndex::MultiValueIndexV1(index) => {
let row_start = index.start_index_column.get_val(doc_id_range.start);
let row_end = index.start_index_column.get_val(doc_id_range.end);
row_start..row_end
}
MultiValueIndex::MultiValueIndexV2(index) => {
// In this case we will use the optional_index select the next values
// that are valid. There are different cases to consider:
// Not exists below means does not exist in the optional
// index, because it has no values.
// * doc_id_range may cover a range of docids which are non existent
// => rank
// will give us the next document outside the range with a value. They both
// get the same rank and therefore return a zero range
//
// * doc_id_range.start and doc_id_range.end may not exist, but docids in
// between may have values
// => rank will give us the next document outside the range with a value.
//
// * doc_id_range.start may be not existent but doc_id_range.end may exist
// * doc_id_range.start may exist but doc_id_range.end may not exist
// * doc_id_range.start and doc_id_range.end may exist
// => rank on doc_id_range.end will give use the next value, which matches
// how the `start_index_column` works, so we get the value start of the next
// docid which we use to create the exclusive range.
//
let rank_start = index.optional_index.rank(doc_id_range.start);
let row_start = index.start_index_column.get_val(rank_start);
let rank_end = index.optional_index.rank(doc_id_range.end);
let row_end = index.start_index_column.get_val(rank_end);
ColumnIndex::Multivalued(multivalued_index) => {
let end_docid = doc_id_range.end.min(multivalued_index.num_docs() - 1) + 1;
let start_docid = doc_id_range.start.min(end_docid);
row_start..row_end
}
},
let row_start = multivalued_index.start_index_column.get_val(start_docid);
let row_end = multivalued_index.start_index_column.get_val(end_docid);
row_start..row_end
}
}
}

View File

@@ -3,98 +3,64 @@ use std::io::Write;
use std::ops::Range;
use std::sync::Arc;
use common::{CountingWriter, OwnedBytes};
use common::OwnedBytes;
use super::optional_index::{open_optional_index, serialize_optional_index};
use super::{OptionalIndex, SerializableOptionalIndex, Set};
use crate::column_values::{
load_u64_based_column_values, serialize_u64_based_column_values, CodecType, ColumnValues,
};
use crate::iterable::Iterable;
use crate::{DocId, RowId, Version};
pub struct SerializableMultivalueIndex<'a> {
pub doc_ids_with_values: SerializableOptionalIndex<'a>,
pub start_offsets: Box<dyn Iterable<u32> + 'a>,
}
use crate::{DocId, RowId};
pub fn serialize_multivalued_index(
multivalued_index: &SerializableMultivalueIndex,
multivalued_index: &dyn Iterable<RowId>,
output: &mut impl Write,
) -> io::Result<()> {
let SerializableMultivalueIndex {
doc_ids_with_values,
start_offsets,
} = multivalued_index;
let mut count_writer = CountingWriter::wrap(output);
let SerializableOptionalIndex {
non_null_row_ids,
num_rows,
} = doc_ids_with_values;
serialize_optional_index(&**non_null_row_ids, *num_rows, &mut count_writer)?;
let optional_len = count_writer.written_bytes() as u32;
let output = count_writer.finish();
serialize_u64_based_column_values(
&**start_offsets,
multivalued_index,
&[CodecType::Bitpacked, CodecType::Linear],
output,
)?;
output.write_all(&optional_len.to_le_bytes())?;
Ok(())
}
pub fn open_multivalued_index(
bytes: OwnedBytes,
format_version: Version,
) -> io::Result<MultiValueIndex> {
match format_version {
Version::V1 => {
let start_index_column: Arc<dyn ColumnValues<RowId>> =
load_u64_based_column_values(bytes)?;
Ok(MultiValueIndex::MultiValueIndexV1(MultiValueIndexV1 {
start_index_column,
}))
}
Version::V2 => {
let (body_bytes, optional_index_len) = bytes.rsplit(4);
let optional_index_len =
u32::from_le_bytes(optional_index_len.as_slice().try_into().unwrap());
let (optional_index_bytes, start_index_bytes) =
body_bytes.split(optional_index_len as usize);
let optional_index = open_optional_index(optional_index_bytes)?;
let start_index_column: Arc<dyn ColumnValues<RowId>> =
load_u64_based_column_values(start_index_bytes)?;
Ok(MultiValueIndex::MultiValueIndexV2(MultiValueIndexV2 {
optional_index,
start_index_column,
}))
}
}
pub fn open_multivalued_index(bytes: OwnedBytes) -> io::Result<MultiValueIndex> {
let start_index_column: Arc<dyn ColumnValues<RowId>> = load_u64_based_column_values(bytes)?;
Ok(MultiValueIndex { start_index_column })
}
#[derive(Clone)]
/// Index to resolve value range for given doc_id.
/// Starts at 0.
pub enum MultiValueIndex {
MultiValueIndexV1(MultiValueIndexV1),
MultiValueIndexV2(MultiValueIndexV2),
}
#[derive(Clone)]
/// Index to resolve value range for given doc_id.
/// Starts at 0.
pub struct MultiValueIndexV1 {
pub struct MultiValueIndex {
pub start_index_column: Arc<dyn crate::ColumnValues<RowId>>,
}
impl MultiValueIndexV1 {
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 }
}
}
impl MultiValueIndex {
pub fn for_test(start_offsets: &[RowId]) -> MultiValueIndex {
let mut buffer = Vec::new();
serialize_multivalued_index(&start_offsets, &mut buffer).unwrap();
let bytes = OwnedBytes::new(buffer);
open_multivalued_index(bytes).unwrap()
}
/// Returns `[start, end)`, such that the values associated with
/// the given document are `start..end`.
#[inline]
pub(crate) fn range(&self, doc_id: DocId) -> Range<RowId> {
if doc_id >= self.num_docs() {
return 0..0;
}
let start = self.start_index_column.get_val(doc_id);
let end = self.start_index_column.get_val(doc_id + 1);
start..end
@@ -117,6 +83,7 @@ impl MultiValueIndexV1 {
///
/// TODO: Instead of a linear scan we can employ a exponential search into binary search to
/// match a docid to its value position.
#[allow(clippy::bool_to_int_with_if)]
pub(crate) fn select_batch_in_place(&self, docid_start: DocId, ranks: &mut Vec<u32>) {
if ranks.is_empty() {
return;
@@ -144,170 +111,11 @@ impl MultiValueIndexV1 {
}
}
#[derive(Clone)]
/// Index to resolve value range for given doc_id.
/// Starts at 0.
pub struct MultiValueIndexV2 {
pub optional_index: OptionalIndex,
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 {
let index = match self {
MultiValueIndex::MultiValueIndexV1(idx) => &idx.start_index_column,
MultiValueIndex::MultiValueIndexV2(idx) => &idx.start_index_column,
};
f.debug_struct("MultiValuedIndex")
.field("num_rows", &index.num_vals())
.finish_non_exhaustive()
}
}
impl MultiValueIndex {
pub fn for_test(start_offsets: &[RowId]) -> MultiValueIndex {
assert!(!start_offsets.is_empty());
assert_eq!(start_offsets[0], 0);
let mut doc_with_values = Vec::new();
let mut compact_start_offsets: Vec<u32> = vec![0];
for doc in 0..start_offsets.len() - 1 {
if start_offsets[doc] < start_offsets[doc + 1] {
doc_with_values.push(doc as RowId);
compact_start_offsets.push(start_offsets[doc + 1]);
}
}
let serializable_multivalued_index = SerializableMultivalueIndex {
doc_ids_with_values: SerializableOptionalIndex {
non_null_row_ids: Box::new(&doc_with_values[..]),
num_rows: start_offsets.len() as u32 - 1,
},
start_offsets: Box::new(&compact_start_offsets[..]),
};
let mut buffer = Vec::new();
serialize_multivalued_index(&serializable_multivalued_index, &mut buffer).unwrap();
let bytes = OwnedBytes::new(buffer);
open_multivalued_index(bytes, Version::V2).unwrap()
}
pub fn get_start_index_column(&self) -> &Arc<dyn crate::ColumnValues<RowId>> {
match self {
MultiValueIndex::MultiValueIndexV1(idx) => &idx.start_index_column,
MultiValueIndex::MultiValueIndexV2(idx) => &idx.start_index_column,
}
}
/// Returns `[start, end)` values range, such that the values associated with
/// the given document are `start..end`.
#[inline]
pub(crate) fn range(&self, doc_id: DocId) -> Range<RowId> {
match self {
MultiValueIndex::MultiValueIndexV1(idx) => idx.range(doc_id),
MultiValueIndex::MultiValueIndexV2(idx) => idx.range(doc_id),
}
}
/// Returns the number of documents in the index.
#[inline]
pub fn num_docs(&self) -> u32 {
match self {
MultiValueIndex::MultiValueIndexV1(idx) => idx.start_index_column.num_vals() - 1,
MultiValueIndex::MultiValueIndexV2(idx) => idx.optional_index.num_docs(),
}
}
/// Converts a list of ranks (row ids of values) in a 1:n index to the corresponding list of
/// docids. Positions are converted inplace to docids.
///
/// Since there is no index for value pos -> docid, but docid -> value pos range, we scan the
/// index.
///
/// Correctness: positions needs to be sorted. idx_reader needs to contain monotonically
/// increasing positions.
///
/// TODO: Instead of a linear scan we can employ a exponential search into binary search to
/// match a docid to its value position.
pub(crate) fn select_batch_in_place(&self, docid_start: DocId, ranks: &mut Vec<u32>) {
match self {
MultiValueIndex::MultiValueIndexV1(idx) => {
idx.select_batch_in_place(docid_start, ranks)
}
MultiValueIndex::MultiValueIndexV2(idx) => {
idx.select_batch_in_place(docid_start, ranks)
}
}
}
}
impl MultiValueIndexV2 {
/// Returns `[start, end)`, such that the values associated with
/// the given document are `start..end`.
#[inline]
pub(crate) fn range(&self, doc_id: DocId) -> Range<RowId> {
let Some(rank) = self.optional_index.rank_if_exists(doc_id) else {
return 0..0;
};
let start = self.start_index_column.get_val(rank);
let end = self.start_index_column.get_val(rank + 1);
start..end
}
/// Returns the number of documents in the index.
#[inline]
pub fn num_docs(&self) -> u32 {
self.optional_index.num_docs()
}
/// Converts a list of ranks (row ids of values) in a 1:n index to the corresponding list of
/// docids. Positions are converted inplace to docids.
///
/// Since there is no index for value pos -> docid, but docid -> value pos range, we scan the
/// index.
///
/// Correctness: positions needs to be sorted. idx_reader needs to contain monotonically
/// increasing positions.
///
/// TODO: Instead of a linear scan we can employ a exponential search into binary search to
/// match a docid to its value position.
pub(crate) fn select_batch_in_place(&self, docid_start: DocId, ranks: &mut Vec<u32>) {
if ranks.is_empty() {
return;
}
let mut cur_pos_in_idx = self.optional_index.rank(docid_start);
let mut last_doc = None;
assert!(cur_pos_in_idx <= ranks[0]);
let mut write_doc_pos = 0;
for i in 0..ranks.len() {
let pos = ranks[i];
loop {
let end = self.start_index_column.get_val(cur_pos_in_idx + 1);
if end > pos {
ranks[write_doc_pos] = cur_pos_in_idx;
write_doc_pos += if last_doc == Some(cur_pos_in_idx) {
0
} else {
1
};
last_doc = Some(cur_pos_in_idx);
break;
}
cur_pos_in_idx += 1;
}
}
ranks.truncate(write_doc_pos);
for rank in ranks.iter_mut() {
*rank = self.optional_index.select(*rank);
}
}
}
#[cfg(test)]
mod tests {
use std::ops::Range;
use super::MultiValueIndex;
use crate::{ColumnarReader, DynamicColumn};
fn index_to_pos_helper(
index: &MultiValueIndex,
@@ -326,7 +134,6 @@ mod tests {
let positions = &[10u32, 11, 15, 20, 21, 22];
assert_eq!(index_to_pos_helper(&index, 0..5, positions), vec![1, 3, 4]);
assert_eq!(index_to_pos_helper(&index, 1..5, positions), vec![1, 3, 4]);
assert_eq!(index_to_pos_helper(&index, 0..5, &[9]), vec![0]);
assert_eq!(index_to_pos_helper(&index, 1..5, &[10]), vec![1]);
assert_eq!(index_to_pos_helper(&index, 1..5, &[11]), vec![1]);
@@ -334,67 +141,4 @@ mod tests {
assert_eq!(index_to_pos_helper(&index, 2..5, &[12, 14]), vec![2]);
assert_eq!(index_to_pos_helper(&index, 2..5, &[12, 14, 15]), vec![2, 3]);
}
#[test]
fn test_range_to_rowids() {
use crate::ColumnarWriter;
let mut columnar_writer = ColumnarWriter::default();
// This column gets coerced to u64
columnar_writer.record_numerical(1, "full", u64::MAX);
columnar_writer.record_numerical(1, "full", u64::MAX);
columnar_writer.record_numerical(5, "full", u64::MAX);
columnar_writer.record_numerical(5, "full", u64::MAX);
let mut wrt: Vec<u8> = Vec::new();
columnar_writer.serialize(7, &mut wrt).unwrap();
let reader = ColumnarReader::open(wrt).unwrap();
// Open the column as u64
let column = reader.read_columns("full").unwrap()[0]
.open()
.unwrap()
.coerce_numerical(crate::NumericalType::U64)
.unwrap();
let DynamicColumn::U64(column) = column else {
panic!();
};
let row_id_range = column.index.docid_range_to_rowids(1..2);
assert_eq!(row_id_range, 0..2);
let row_id_range = column.index.docid_range_to_rowids(0..2);
assert_eq!(row_id_range, 0..2);
let row_id_range = column.index.docid_range_to_rowids(0..4);
assert_eq!(row_id_range, 0..2);
let row_id_range = column.index.docid_range_to_rowids(3..4);
assert_eq!(row_id_range, 2..2);
let row_id_range = column.index.docid_range_to_rowids(1..6);
assert_eq!(row_id_range, 0..4);
let row_id_range = column.index.docid_range_to_rowids(3..6);
assert_eq!(row_id_range, 2..4);
let row_id_range = column.index.docid_range_to_rowids(0..6);
assert_eq!(row_id_range, 0..4);
let row_id_range = column.index.docid_range_to_rowids(0..6);
assert_eq!(row_id_range, 0..4);
let check = |range, expected| {
let full_range = 0..=u64::MAX;
let mut docids = Vec::new();
column.get_docids_for_value_range(full_range, range, &mut docids);
assert_eq!(docids, expected);
};
// check(0..1, vec![]);
// check(0..2, vec![1]);
check(1..2, vec![1]);
}
}

View File

@@ -86,14 +86,8 @@ pub struct OptionalIndex {
block_metas: Arc<[BlockMeta]>,
}
impl<'a> Iterable<u32> for &'a OptionalIndex {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u32> + '_> {
Box::new(self.iter_rows())
}
}
impl std::fmt::Debug for OptionalIndex {
fn fmt(&self, f: &mut std::fmt::Formatter) -> std::fmt::Result {
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)
@@ -202,7 +196,6 @@ impl Set<RowId> for OptionalIndex {
} = row_addr_from_row_id(doc_id);
let block_meta = self.block_metas[block_id as usize];
let block = self.block(block_meta);
let block_offset_row_id = match block {
Block::Dense(dense_block) => dense_block.rank(in_block_row_id),
Block::Sparse(sparse_block) => sparse_block.rank(in_block_row_id),

View File

@@ -28,11 +28,10 @@ pub trait Set<T> {
/// Returns true if the elements is contained in the Set
fn contains(&self, el: T) -> bool;
/// Returns the element's rank (its position in the set).
/// If the set does not contain the element, it will return the next existing elements rank.
/// Returns the number of rows in the set that are < `el`
fn rank(&self, el: T) -> T;
/// If the set contains `el`, returns the element's rank (its position in the set).
/// If the set contains `el` returns the element rank.
/// If the set does not contain the element, it returns `None`.
fn rank_if_exists(&self, el: T) -> Option<T>;

View File

@@ -1,3 +1,4 @@
use std::convert::TryInto;
use std::io::{self, Write};
use common::BinarySerializable;

View File

@@ -22,8 +22,8 @@ fn test_set_helper<C: SetCodec<Item = u16>>(vals: &[u16]) -> usize {
vals.iter().cloned().take_while(|v| *v < val).count() as u16
);
}
for (rank, val) in vals.iter().enumerate() {
assert_eq!(tested_set.select(rank as u16), *val);
for rank in 0..vals.len() {
assert_eq!(tested_set.select(rank as u16), vals[rank]);
}
buffer.len()
}
@@ -107,41 +107,3 @@ fn test_simple_translate_codec_idx_to_original_idx_dense() {
assert_eq!(i, select_cursor.select(i));
}
}
#[test]
fn test_simple_translate_idx_to_value_idx_dense() {
let mut buffer = Vec::new();
DenseBlockCodec::serialize([1, 10].iter().copied(), &mut buffer).unwrap();
let tested_set = DenseBlockCodec::open(buffer.as_slice());
assert!(tested_set.contains(1));
assert!(!tested_set.contains(2));
assert_eq!(tested_set.rank(0), 0);
assert_eq!(tested_set.rank(1), 0);
for rank in 2..10 {
// ranks that don't exist select the next highest one
assert_eq!(tested_set.rank_if_exists(rank), None);
assert_eq!(tested_set.rank(rank), 1);
}
assert_eq!(tested_set.rank(10), 1);
}
#[test]
fn test_simple_translate_idx_to_value_idx_sparse() {
let mut buffer = Vec::new();
SparseBlockCodec::serialize([1, 10].iter().copied(), &mut buffer).unwrap();
let tested_set = SparseBlockCodec::open(buffer.as_slice());
assert!(tested_set.contains(1));
assert!(!tested_set.contains(2));
assert_eq!(tested_set.rank(0), 0);
assert_eq!(tested_set.select(tested_set.rank(0)), 1);
assert_eq!(tested_set.rank(1), 0);
assert_eq!(tested_set.select(tested_set.rank(1)), 1);
for rank in 2..10 {
// ranks that don't exist select the next highest one
assert_eq!(tested_set.rank_if_exists(rank), None);
assert_eq!(tested_set.rank(rank), 1);
assert_eq!(tested_set.select(tested_set.rank(rank)), 10);
}
assert_eq!(tested_set.rank(10), 1);
assert_eq!(tested_set.select(tested_set.rank(10)), 10);
}

View File

@@ -1,4 +1,5 @@
use proptest::prelude::*;
use proptest::prelude::{any, prop, *};
use proptest::strategy::Strategy;
use proptest::{prop_oneof, proptest};
use super::*;
@@ -15,7 +16,9 @@ fn test_optional_index_with_num_docs(num_docs: u32) {
let mut dataframe_writer = ColumnarWriter::default();
dataframe_writer.record_numerical(100, "score", 80i64);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(num_docs, &mut buffer).unwrap();
dataframe_writer
.serialize(num_docs, None, &mut buffer)
.unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("score").unwrap();

View File

@@ -3,39 +3,28 @@ use std::io::Write;
use common::{CountingWriter, OwnedBytes};
use super::multivalued_index::SerializableMultivalueIndex;
use super::OptionalIndex;
use crate::column_index::multivalued_index::serialize_multivalued_index;
use crate::column_index::optional_index::serialize_optional_index;
use crate::column_index::ColumnIndex;
use crate::iterable::Iterable;
use crate::{Cardinality, RowId, Version};
pub struct SerializableOptionalIndex<'a> {
pub non_null_row_ids: Box<dyn Iterable<RowId> + 'a>,
pub num_rows: RowId,
}
impl<'a> From<&'a OptionalIndex> for SerializableOptionalIndex<'a> {
fn from(optional_index: &'a OptionalIndex) -> Self {
SerializableOptionalIndex {
non_null_row_ids: Box::new(optional_index),
num_rows: optional_index.num_docs(),
}
}
}
use crate::{Cardinality, RowId};
pub enum SerializableColumnIndex<'a> {
Full,
Optional(SerializableOptionalIndex<'a>),
Multivalued(SerializableMultivalueIndex<'a>),
Optional {
non_null_row_ids: Box<dyn Iterable<RowId> + 'a>,
num_rows: RowId,
},
// TODO remove the Arc<dyn> apart from serialization this is not
// dynamic at all.
Multivalued(Box<dyn Iterable<RowId> + 'a>),
}
impl<'a> SerializableColumnIndex<'a> {
pub fn get_cardinality(&self) -> Cardinality {
match self {
SerializableColumnIndex::Full => Cardinality::Full,
SerializableColumnIndex::Optional(_) => Cardinality::Optional,
SerializableColumnIndex::Optional { .. } => Cardinality::Optional,
SerializableColumnIndex::Multivalued(_) => Cardinality::Multivalued,
}
}
@@ -51,12 +40,12 @@ pub fn serialize_column_index(
output.write_all(&[cardinality])?;
match column_index {
SerializableColumnIndex::Full => {}
SerializableColumnIndex::Optional(SerializableOptionalIndex {
SerializableColumnIndex::Optional {
non_null_row_ids,
num_rows,
}) => serialize_optional_index(non_null_row_ids.as_ref(), num_rows, &mut output)?,
} => serialize_optional_index(non_null_row_ids.as_ref(), num_rows, &mut output)?,
SerializableColumnIndex::Multivalued(multivalued_index) => {
serialize_multivalued_index(&multivalued_index, &mut output)?
serialize_multivalued_index(&*multivalued_index, &mut output)?
}
}
let column_index_num_bytes = output.written_bytes() as u32;
@@ -64,10 +53,7 @@ pub fn serialize_column_index(
}
/// Open a serialized column index.
pub fn open_column_index(
mut bytes: OwnedBytes,
format_version: Version,
) -> io::Result<ColumnIndex> {
pub fn open_column_index(mut bytes: OwnedBytes) -> io::Result<ColumnIndex> {
if bytes.is_empty() {
return Err(io::Error::new(
io::ErrorKind::UnexpectedEof,
@@ -84,8 +70,7 @@ pub fn open_column_index(
Ok(ColumnIndex::Optional(optional_index))
}
Cardinality::Multivalued => {
let multivalue_index =
super::multivalued_index::open_multivalued_index(bytes, format_version)?;
let multivalue_index = super::multivalued_index::open_multivalued_index(bytes)?;
Ok(ColumnIndex::Multivalued(multivalue_index))
}
}

View File

@@ -10,7 +10,7 @@ pub(crate) struct MergedColumnValues<'a, T> {
pub(crate) merge_row_order: &'a MergeRowOrder,
}
impl<'a, T: Copy + PartialOrd + Debug + 'static> Iterable<T> for MergedColumnValues<'a, T> {
impl<'a, T: Copy + PartialOrd + Debug> Iterable<T> for MergedColumnValues<'a, T> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_> {
match self.merge_row_order {
MergeRowOrder::Stack(_) => Box::new(

View File

@@ -10,7 +10,6 @@ use std::fmt::Debug;
use std::ops::{Range, RangeInclusive};
use std::sync::Arc;
use downcast_rs::DowncastSync;
pub use monotonic_mapping::{MonotonicallyMappableToU64, StrictlyMonotonicFn};
pub use monotonic_mapping_u128::MonotonicallyMappableToU128;
@@ -26,10 +25,7 @@ mod monotonic_column;
pub(crate) use merge::MergedColumnValues;
pub use stats::ColumnStats;
pub use u128_based::{
open_u128_as_compact_u64, open_u128_mapped, serialize_column_values_u128,
CompactSpaceU64Accessor,
};
pub use u128_based::{open_u128_mapped, serialize_column_values_u128};
pub use u64_based::{
load_u64_based_column_values, serialize_and_load_u64_based_column_values,
serialize_u64_based_column_values, CodecType, ALL_U64_CODEC_TYPES,
@@ -45,7 +41,7 @@ use crate::RowId;
///
/// Any methods with a default and specialized implementation need to be called in the
/// wrappers that implement the trait: Arc and MonotonicMappingColumn
pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync + DowncastSync {
pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync {
/// Return the value associated with the given idx.
///
/// This accessor should return as fast as possible.
@@ -72,40 +68,11 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync + DowncastSync {
out_x4[3] = self.get_val(idx_x4[3]);
}
let out_and_idx_chunks = output
.chunks_exact_mut(4)
.into_remainder()
.iter_mut()
.zip(indexes.chunks_exact(4).remainder());
for (out, idx) in out_and_idx_chunks {
*out = self.get_val(*idx);
}
}
let step_size = 4;
let cutoff = indexes.len() - indexes.len() % step_size;
/// Allows to push down multiple fetch calls, to avoid dynamic dispatch overhead.
/// The slightly weird `Option<T>` in output allows pushdown to full columns.
///
/// idx and output should have the same length
///
/// # Panics
///
/// May panic if `idx` is greater than the column length.
fn get_vals_opt(&self, indexes: &[u32], output: &mut [Option<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] = Some(self.get_val(idx_x4[0]));
out_x4[1] = Some(self.get_val(idx_x4[1]));
out_x4[2] = Some(self.get_val(idx_x4[2]));
out_x4[3] = Some(self.get_val(idx_x4[3]));
}
let out_and_idx_chunks = output
.chunks_exact_mut(4)
.into_remainder()
.iter_mut()
.zip(indexes.chunks_exact(4).remainder());
for (out, idx) in out_and_idx_chunks {
*out = Some(self.get_val(*idx));
for idx in cutoff..indexes.len() {
output[idx] = self.get_val(indexes[idx]);
}
}
@@ -172,7 +139,6 @@ pub trait ColumnValues<T: PartialOrd = u64>: Send + Sync + DowncastSync {
Box::new((0..self.num_vals()).map(|idx| self.get_val(idx)))
}
}
downcast_rs::impl_downcast!(sync ColumnValues<T> where T: PartialOrd);
/// Empty column of values.
pub struct EmptyColumnValues;
@@ -195,17 +161,12 @@ impl<T: PartialOrd + Default> ColumnValues<T> for EmptyColumnValues {
}
}
impl<T: Copy + PartialOrd + Debug + 'static> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
impl<T: Copy + PartialOrd + Debug> ColumnValues<T> for Arc<dyn ColumnValues<T>> {
#[inline(always)]
fn get_val(&self, idx: u32) -> T {
self.as_ref().get_val(idx)
}
#[inline(always)]
fn get_vals_opt(&self, indexes: &[u32], output: &mut [Option<T>]) {
self.as_ref().get_vals_opt(indexes, output)
}
#[inline(always)]
fn min_value(&self) -> T {
self.as_ref().min_value()

View File

@@ -31,10 +31,10 @@ pub fn monotonic_map_column<C, T, Input, Output>(
monotonic_mapping: T,
) -> impl ColumnValues<Output>
where
C: ColumnValues<Input> + 'static,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync + 'static,
Input: PartialOrd + Debug + Send + Sync + Clone + 'static,
Output: PartialOrd + Debug + Send + Sync + Clone + 'static,
C: ColumnValues<Input>,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
Input: PartialOrd + Debug + Send + Sync + Clone,
Output: PartialOrd + Debug + Send + Sync + Clone,
{
MonotonicMappingColumn {
from_column,
@@ -45,10 +45,10 @@ where
impl<C, T, Input, Output> ColumnValues<Output> for MonotonicMappingColumn<C, T, Input>
where
C: ColumnValues<Input> + 'static,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync + 'static,
Input: PartialOrd + Send + Debug + Sync + Clone + 'static,
Output: PartialOrd + Send + Debug + Sync + Clone + 'static,
C: ColumnValues<Input>,
T: StrictlyMonotonicFn<Input, Output> + Send + Sync,
Input: PartialOrd + Send + Debug + Sync + Clone,
Output: PartialOrd + Send + Debug + Sync + Clone,
{
#[inline(always)]
fn get_val(&self, idx: u32) -> Output {
@@ -107,7 +107,7 @@ mod tests {
#[test]
fn test_monotonic_mapping_iter() {
let vals: Vec<u64> = (0..100u64).map(|el| el * 10).collect();
let col = VecColumn::from(vals);
let col = VecColumn::from(&vals);
let mapped = monotonic_map_column(
col,
StrictlyMonotonicMappingInverter::from(StrictlyMonotonicMappingToInternal::<i64>::new()),

View File

@@ -22,7 +22,7 @@ mod build_compact_space;
use build_compact_space::get_compact_space;
use common::{BinarySerializable, CountingWriter, OwnedBytes, VInt, VIntU128};
use tantivy_bitpacker::{BitPacker, BitUnpacker};
use tantivy_bitpacker::{self, BitPacker, BitUnpacker};
use crate::column_values::ColumnValues;
use crate::RowId;
@@ -148,7 +148,7 @@ impl CompactSpace {
.binary_search_by_key(&compact, |range_mapping| range_mapping.compact_start)
// Correctness: Overflow. The first range starts at compact space 0, the error from
// binary search can never be 0
.unwrap_or_else(|e| e - 1);
.map_or_else(|e| e - 1, |v| v);
let range_mapping = &self.ranges_mapping[pos];
let diff = compact - range_mapping.compact_start;
@@ -292,63 +292,6 @@ impl BinarySerializable for IPCodecParams {
}
}
/// Exposes the compact space compressed values as u64.
///
/// This allows faster access to the values, as u64 is faster to work with than u128.
/// It also allows to handle u128 values like u64, via the `open_u64_lenient` as a uniform
/// access interface.
///
/// When converting from the internal u64 to u128 `compact_to_u128` can be used.
pub struct CompactSpaceU64Accessor(CompactSpaceDecompressor);
impl CompactSpaceU64Accessor {
pub(crate) fn open(data: OwnedBytes) -> io::Result<CompactSpaceU64Accessor> {
let decompressor = CompactSpaceU64Accessor(CompactSpaceDecompressor::open(data)?);
Ok(decompressor)
}
/// Convert a compact space value to u128
pub fn compact_to_u128(&self, compact: u32) -> u128 {
self.0.compact_to_u128(compact)
}
}
impl ColumnValues<u64> for CompactSpaceU64Accessor {
#[inline]
fn get_val(&self, doc: u32) -> u64 {
let compact = self.0.get_compact(doc);
compact as u64
}
fn min_value(&self) -> u64 {
self.0.u128_to_compact(self.0.min_value()).unwrap() as u64
}
fn max_value(&self) -> u64 {
self.0.u128_to_compact(self.0.max_value()).unwrap() as u64
}
fn num_vals(&self) -> u32 {
self.0.params.num_vals
}
#[inline]
fn iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(self.0.iter_compact().map(|el| el as u64))
}
#[inline]
fn get_row_ids_for_value_range(
&self,
value_range: RangeInclusive<u64>,
position_range: Range<u32>,
positions: &mut Vec<u32>,
) {
let value_range = self.0.compact_to_u128(*value_range.start() as u32)
..=self.0.compact_to_u128(*value_range.end() as u32);
self.0
.get_row_ids_for_value_range(value_range, position_range, positions)
}
}
impl ColumnValues<u128> for CompactSpaceDecompressor {
#[inline]
fn get_val(&self, doc: u32) -> u128 {
@@ -459,14 +402,9 @@ impl CompactSpaceDecompressor {
.map(|compact| self.compact_to_u128(compact))
}
#[inline]
pub fn get_compact(&self, idx: u32) -> u32 {
self.params.bit_unpacker.get(idx, &self.data) as u32
}
#[inline]
pub fn get(&self, idx: u32) -> u128 {
let compact = self.get_compact(idx);
let compact = self.params.bit_unpacker.get(idx, &self.data) as u32;
self.compact_to_u128(compact)
}

View File

@@ -6,9 +6,7 @@ use std::sync::Arc;
mod compact_space;
use common::{BinarySerializable, OwnedBytes, VInt};
pub use compact_space::{
CompactSpaceCompressor, CompactSpaceDecompressor, CompactSpaceU64Accessor,
};
use compact_space::{CompactSpaceCompressor, CompactSpaceDecompressor};
use crate::column_values::monotonic_map_column;
use crate::column_values::monotonic_mapping::{
@@ -110,23 +108,6 @@ pub fn open_u128_mapped<T: MonotonicallyMappableToU128 + Debug>(
StrictlyMonotonicMappingToInternal::<T>::new().into();
Ok(Arc::new(monotonic_map_column(reader, inverted)))
}
/// Returns the u64 representation of the u128 data.
/// The internal representation of the data as u64 is useful for faster processing.
///
/// In order to convert to u128 back cast to `CompactSpaceU64Accessor` and call
/// `compact_to_u128`.
///
/// # Notice
/// In case there are new codecs added, check for usages of `CompactSpaceDecompressorU64` and
/// also handle the new codecs.
pub fn open_u128_as_compact_u64(mut bytes: OwnedBytes) -> io::Result<Arc<dyn ColumnValues<u64>>> {
let header = U128Header::deserialize(&mut bytes)?;
assert_eq!(header.codec_type, U128FastFieldCodecType::CompactSpace);
let reader = CompactSpaceU64Accessor::open(bytes)?;
Ok(Arc::new(reader))
}
#[cfg(test)]
pub mod tests {
use super::*;

View File

@@ -63,6 +63,7 @@ impl ColumnValues for BitpackedReader {
fn get_val(&self, doc: u32) -> u64 {
self.stats.min_value + self.stats.gcd.get() * self.bit_unpacker.get(doc, &self.data)
}
#[inline]
fn min_value(&self) -> u64 {
self.stats.min_value

View File

@@ -63,10 +63,7 @@ impl BlockwiseLinearEstimator {
if self.block.is_empty() {
return;
}
let column = VecColumn::from(std::mem::take(&mut self.block));
let line = Line::train(&column);
self.block = column.into();
let line = Line::train(&VecColumn::from(&self.block));
let mut max_value = 0u64;
for (i, buffer_val) in self.block.iter().enumerate() {
let interpolated_val = line.eval(i as u32);
@@ -128,7 +125,7 @@ impl ColumnCodecEstimator for BlockwiseLinearEstimator {
*buffer_val = gcd_divider.divide(*buffer_val - stats.min_value);
}
let line = Line::train(&VecColumn::from(buffer.to_vec()));
let line = Line::train(&VecColumn::from(&buffer));
assert!(!buffer.is_empty());

View File

@@ -184,7 +184,7 @@ mod tests {
}
fn test_eval_max_err(ys: &[u64]) -> Option<u64> {
let line = Line::train(&VecColumn::from(ys.to_vec()));
let line = Line::train(&VecColumn::from(&ys));
ys.iter()
.enumerate()
.map(|(x, y)| y.wrapping_sub(line.eval(x as u32)))

View File

@@ -173,9 +173,7 @@ impl LinearCodecEstimator {
fn collect_before_line_estimation(&mut self, value: u64) {
self.block.push(value);
if self.block.len() == LINE_ESTIMATION_BLOCK_LEN {
let column = VecColumn::from(std::mem::take(&mut self.block));
let line = Line::train(&column);
self.block = column.into();
let line = Line::train(&VecColumn::from(&self.block));
let block = std::mem::take(&mut self.block);
for val in block {
self.collect_after_line_estimation(&line, val);

View File

@@ -1,4 +1,5 @@
use proptest::prelude::*;
use proptest::strategy::Strategy;
use proptest::{prop_oneof, proptest};
#[test]

View File

@@ -4,14 +4,14 @@ use tantivy_bitpacker::minmax;
use crate::ColumnValues;
/// VecColumn provides `Column` over a `Vec<T>`.
pub struct VecColumn<T = u64> {
pub(crate) values: Vec<T>,
/// VecColumn provides `Column` over a slice.
pub struct VecColumn<'a, T = u64> {
pub(crate) values: &'a [T],
pub(crate) min_value: T,
pub(crate) max_value: T,
}
impl<T: Copy + PartialOrd + Send + Sync + Debug + 'static> ColumnValues<T> for VecColumn<T> {
impl<'a, T: Copy + PartialOrd + Send + Sync + Debug> ColumnValues<T> for VecColumn<'a, T> {
fn get_val(&self, position: u32) -> T {
self.values[position as usize]
}
@@ -37,8 +37,11 @@ impl<T: Copy + PartialOrd + Send + Sync + Debug + 'static> ColumnValues<T> for V
}
}
impl<T: Copy + PartialOrd + Default> From<Vec<T>> for VecColumn<T> {
fn from(values: Vec<T>) -> Self {
impl<'a, T: Copy + PartialOrd + Default, V> From<&'a V> for VecColumn<'a, T>
where V: AsRef<[T]> + ?Sized
{
fn from(values: &'a V) -> Self {
let values = values.as_ref();
let (min_value, max_value) = minmax(values.iter().copied()).unwrap_or_default();
Self {
values,
@@ -47,8 +50,3 @@ impl<T: Copy + PartialOrd + Default> From<Vec<T>> for VecColumn<T> {
}
}
}
impl From<VecColumn> for Vec<u64> {
fn from(column: VecColumn) -> Self {
column.values
}
}

View File

@@ -1,6 +1,3 @@
use core::fmt;
use std::fmt::{Display, Formatter};
use crate::InvalidData;
pub const VERSION_FOOTER_NUM_BYTES: usize = MAGIC_BYTES.len() + std::mem::size_of::<u32>();
@@ -11,7 +8,7 @@ const MAGIC_BYTES: [u8; 4] = [2, 113, 119, 66];
pub fn footer() -> [u8; VERSION_FOOTER_NUM_BYTES] {
let mut footer_bytes = [0u8; VERSION_FOOTER_NUM_BYTES];
footer_bytes[0..4].copy_from_slice(&CURRENT_VERSION.to_bytes());
footer_bytes[0..4].copy_from_slice(&Version::V1.to_bytes());
footer_bytes[4..8].copy_from_slice(&MAGIC_BYTES[..]);
footer_bytes
}
@@ -23,22 +20,10 @@ pub fn parse_footer(footer_bytes: [u8; VERSION_FOOTER_NUM_BYTES]) -> Result<Vers
Version::try_from_bytes(footer_bytes[0..4].try_into().unwrap())
}
pub const CURRENT_VERSION: Version = Version::V2;
#[derive(Debug, Copy, Clone, Eq, PartialEq)]
#[repr(u32)]
pub enum Version {
V1 = 1u32,
V2 = 2u32,
}
impl Display for Version {
fn fmt(&self, f: &mut Formatter) -> fmt::Result {
match self {
Version::V1 => write!(f, "v1"),
Version::V2 => write!(f, "v2"),
}
}
}
impl Version {
@@ -50,7 +35,6 @@ impl Version {
let code = u32::from_le_bytes(bytes);
match code {
1u32 => Ok(Version::V1),
2u32 => Ok(Version::V2),
_ => Err(InvalidData),
}
}
@@ -63,9 +47,9 @@ mod tests {
use super::*;
#[test]
fn test_footer_deserialization() {
fn test_footer_dserialization() {
let parsed_version: Version = parse_footer(footer()).unwrap();
assert_eq!(Version::V2, parsed_version);
assert_eq!(Version::V1, parsed_version);
}
#[test]
@@ -79,10 +63,11 @@ mod tests {
for &i in &version_to_tests {
let version_res = Version::try_from_bytes(i.to_le_bytes());
if let Ok(version) = version_res {
assert_eq!(version, Version::V1);
assert_eq!(version.to_bytes(), i.to_le_bytes());
valid_versions.insert(i);
}
}
assert_eq!(valid_versions.len(), 2);
assert_eq!(valid_versions.len(), 1);
}
}

View File

@@ -7,6 +7,7 @@ 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;
@@ -370,8 +371,20 @@ fn is_empty_after_merge(
true
}
ColumnIndex::Multivalued(multivalued_index) => {
for alive_docid in alive_bitset.iter() {
if !multivalued_index.range(alive_docid).is_empty() {
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;
}
}

View File

@@ -1,3 +1,5 @@
use std::collections::BTreeMap;
use itertools::Itertools;
use super::*;
@@ -14,7 +16,7 @@ fn make_columnar<T: Into<NumericalValue> + HasAssociatedColumnType + Copy>(
}
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer
.serialize(vals.len() as RowId, &mut buffer)
.serialize(vals.len() as RowId, None, &mut buffer)
.unwrap();
ColumnarReader::open(buffer).unwrap()
}
@@ -159,7 +161,9 @@ fn make_numerical_columnar_multiple_columns(
.max()
.unwrap_or(0u32);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
dataframe_writer
.serialize(num_rows, None, &mut buffer)
.unwrap();
ColumnarReader::open(buffer).unwrap()
}
@@ -182,7 +186,9 @@ fn make_byte_columnar_multiple_columns(
}
}
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
dataframe_writer
.serialize(num_rows, None, &mut buffer)
.unwrap();
ColumnarReader::open(buffer).unwrap()
}
@@ -201,7 +207,9 @@ fn make_text_columnar_multiple_columns(columns: &[(&str, &[&[&str]])]) -> Column
.max()
.unwrap_or(0u32);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(num_rows, &mut buffer).unwrap();
dataframe_writer
.serialize(num_rows, None, &mut buffer)
.unwrap();
ColumnarReader::open(buffer).unwrap()
}

View File

@@ -5,7 +5,6 @@ mod reader;
mod writer;
pub use column_type::{ColumnType, HasAssociatedColumnType};
pub use format_version::{Version, CURRENT_VERSION};
#[cfg(test)]
pub(crate) use merge::ColumnTypeCategory;
pub use merge::{merge_columnar, MergeRowOrder, ShuffleMergeOrder, StackMergeOrder};

View File

@@ -6,7 +6,7 @@ use sstable::{Dictionary, RangeSSTable};
use crate::columnar::{format_version, ColumnType};
use crate::dynamic_column::DynamicColumnHandle;
use crate::{RowId, Version};
use crate::RowId;
fn io_invalid_data(msg: String) -> io::Error {
io::Error::new(io::ErrorKind::InvalidData, msg)
@@ -19,7 +19,6 @@ pub struct ColumnarReader {
column_dictionary: Dictionary<RangeSSTable>,
column_data: FileSlice,
num_rows: RowId,
format_version: Version,
}
impl fmt::Debug for ColumnarReader {
@@ -54,7 +53,6 @@ impl fmt::Debug for ColumnarReader {
fn read_all_columns_in_stream(
mut stream: sstable::Streamer<'_, RangeSSTable>,
column_data: &FileSlice,
format_version: Version,
) -> io::Result<Vec<DynamicColumnHandle>> {
let mut results = Vec::new();
while stream.advance() {
@@ -69,7 +67,6 @@ fn read_all_columns_in_stream(
let dynamic_column_handle = DynamicColumnHandle {
file_slice,
column_type,
format_version,
};
results.push(dynamic_column_handle);
}
@@ -91,7 +88,7 @@ impl ColumnarReader {
let num_rows = u32::deserialize(&mut &footer_bytes[8..12])?;
let version_footer_bytes: [u8; format_version::VERSION_FOOTER_NUM_BYTES] =
footer_bytes[12..].try_into().unwrap();
let format_version = format_version::parse_footer(version_footer_bytes)?;
let _version = format_version::parse_footer(version_footer_bytes)?;
let (column_data, sstable) =
file_slice_without_sstable_len.split_from_end(sstable_len as usize);
let column_dictionary = Dictionary::open(sstable)?;
@@ -99,7 +96,6 @@ impl ColumnarReader {
column_dictionary,
column_data,
num_rows,
format_version,
})
}
@@ -130,7 +126,6 @@ impl ColumnarReader {
let column_handle = DynamicColumnHandle {
file_slice,
column_type,
format_version: self.format_version,
};
Some((column_name, column_handle))
} else {
@@ -172,7 +167,7 @@ impl ColumnarReader {
.stream_for_column_range(column_name)
.into_stream_async()
.await?;
read_all_columns_in_stream(stream, &self.column_data, self.format_version)
read_all_columns_in_stream(stream, &self.column_data)
}
/// Get all columns for the given column name.
@@ -181,7 +176,7 @@ impl ColumnarReader {
/// different types.
pub fn read_columns(&self, column_name: &str) -> io::Result<Vec<DynamicColumnHandle>> {
let stream = self.stream_for_column_range(column_name).into_stream()?;
read_all_columns_in_stream(stream, &self.column_data, self.format_version)
read_all_columns_in_stream(stream, &self.column_data)
}
/// Return the number of columns in the columnar.
@@ -200,7 +195,7 @@ mod tests {
columnar_writer.record_column_type("col1", ColumnType::Str, false);
columnar_writer.record_column_type("col2", ColumnType::U64, false);
let mut buffer = Vec::new();
columnar_writer.serialize(1, &mut buffer).unwrap();
columnar_writer.serialize(1, None, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
let columns = columnar.list_columns().unwrap();
assert_eq!(columns.len(), 2);
@@ -216,7 +211,7 @@ mod tests {
columnar_writer.record_column_type("count", ColumnType::U64, false);
columnar_writer.record_numerical(1, "count", 1u64);
let mut buffer = Vec::new();
columnar_writer.serialize(2, &mut buffer).unwrap();
columnar_writer.serialize(2, None, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
let columns = columnar.list_columns().unwrap();
assert_eq!(columns.len(), 1);

View File

@@ -41,10 +41,31 @@ impl ColumnWriter {
pub(super) fn operation_iterator<'a, V: SymbolValue>(
&self,
arena: &MemoryArena,
old_to_new_ids_opt: Option<&[RowId]>,
buffer: &'a mut Vec<u8>,
) -> impl Iterator<Item = ColumnOperation<V>> + 'a {
buffer.clear();
self.values.read_to_end(arena, buffer);
if let Some(old_to_new_ids) = old_to_new_ids_opt {
// TODO avoid the extra deserialization / serialization.
let mut sorted_ops: Vec<(RowId, ColumnOperation<V>)> = Vec::new();
let mut new_doc = 0u32;
let mut cursor = &buffer[..];
for op in std::iter::from_fn(|| ColumnOperation::<V>::deserialize(&mut cursor)) {
if let ColumnOperation::NewDoc(doc) = &op {
new_doc = old_to_new_ids[*doc as usize];
sorted_ops.push((new_doc, ColumnOperation::NewDoc(new_doc)));
} else {
sorted_ops.push((new_doc, op));
}
}
// stable sort is crucial here.
sorted_ops.sort_by_key(|(new_doc_id, _)| *new_doc_id);
buffer.clear();
for (_, op) in sorted_ops {
buffer.extend_from_slice(op.serialize().as_ref());
}
}
let mut cursor: &[u8] = &buffer[..];
std::iter::from_fn(move || ColumnOperation::deserialize(&mut cursor))
}
@@ -210,9 +231,11 @@ impl NumericalColumnWriter {
pub(super) fn operation_iterator<'a>(
self,
arena: &MemoryArena,
old_to_new_ids: Option<&[RowId]>,
buffer: &'a mut Vec<u8>,
) -> impl Iterator<Item = ColumnOperation<NumericalValue>> + 'a {
self.column_writer.operation_iterator(arena, buffer)
self.column_writer
.operation_iterator(arena, old_to_new_ids, buffer)
}
}
@@ -254,9 +277,11 @@ impl StrOrBytesColumnWriter {
pub(super) fn operation_iterator<'a>(
&self,
arena: &MemoryArena,
old_to_new_ids: Option<&[RowId]>,
byte_buffer: &'a mut Vec<u8>,
) -> impl Iterator<Item = ColumnOperation<UnorderedId>> + 'a {
self.column_writer.operation_iterator(arena, byte_buffer)
self.column_writer
.operation_iterator(arena, old_to_new_ids, byte_buffer)
}
}

View File

@@ -12,8 +12,10 @@ use common::CountingWriter;
pub(crate) use serializer::ColumnarSerializer;
use stacker::{Addr, ArenaHashMap, MemoryArena};
use crate::column_index::{SerializableColumnIndex, SerializableOptionalIndex};
use crate::column_values::{MonotonicallyMappableToU128, MonotonicallyMappableToU64};
use crate::column_index::SerializableColumnIndex;
use crate::column_values::{
ColumnValues, MonotonicallyMappableToU128, MonotonicallyMappableToU64, VecColumn,
};
use crate::columnar::column_type::ColumnType;
use crate::columnar::writer::column_writers::{
ColumnWriter, NumericalColumnWriter, StrOrBytesColumnWriter,
@@ -43,7 +45,7 @@ struct SpareBuffers {
/// columnar_writer.record_str(1u32 /* doc id */, "product_name", "Apple");
/// columnar_writer.record_numerical(0u32 /* doc id */, "price", 10.5f64); //< uh oh we ended up mixing integer and floats.
/// let mut wrt: Vec<u8> = Vec::new();
/// columnar_writer.serialize(2u32, &mut wrt).unwrap();
/// columnar_writer.serialize(2u32, None, &mut wrt).unwrap();
/// ```
#[derive(Default)]
pub struct ColumnarWriter {
@@ -59,6 +61,22 @@ pub struct ColumnarWriter {
buffers: SpareBuffers,
}
#[inline]
fn mutate_or_create_column<V, TMutator>(
arena_hash_map: &mut ArenaHashMap,
column_name: &str,
updater: TMutator,
) where
V: Copy + 'static,
TMutator: FnMut(Option<V>) -> V,
{
assert!(
!column_name.as_bytes().contains(&0u8),
"key may not contain the 0 byte"
);
arena_hash_map.mutate_or_create(column_name.as_bytes(), updater);
}
impl ColumnarWriter {
pub fn mem_usage(&self) -> usize {
self.arena.mem_usage()
@@ -75,6 +93,63 @@ impl ColumnarWriter {
.sum::<usize>()
}
/// Returns the list of doc ids from 0..num_docs sorted by the `sort_field`
/// column.
///
/// If the column is multivalued, use the first value for scoring.
/// If no value is associated to a specific row, the document is assigned
/// the lowest possible score.
///
/// 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())
.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 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) => {
current_doc_opt = Some(doc);
}
ColumnOperation::Value(numerical_value) => {
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, current_doc));
}
}
}
}
for doc in values.len() as u32..num_docs {
values.push((0.0f32, doc));
}
values.sort_by(|(left_score, _), (right_score, _)| {
if reversed {
right_score.total_cmp(left_score)
} else {
left_score.total_cmp(right_score)
}
});
values.into_iter().map(|(_score, doc)| doc).collect()
}
/// Records a column type. This is useful to bypass the coercion process,
/// makes sure the empty is present in the resulting columnar, or set
/// the `sort_values_within_row`.
@@ -102,8 +177,9 @@ impl ColumnarWriter {
},
&mut self.dictionaries,
);
hash_map.mutate_or_create(
column_name.as_bytes(),
mutate_or_create_column(
hash_map,
column_name,
|column_opt: Option<StrOrBytesColumnWriter>| {
let mut column_writer = if let Some(column_writer) = column_opt {
column_writer
@@ -118,21 +194,24 @@ impl ColumnarWriter {
);
}
ColumnType::Bool => {
self.bool_field_hash_map.mutate_or_create(
column_name.as_bytes(),
mutate_or_create_column(
&mut self.bool_field_hash_map,
column_name,
|column_opt: Option<ColumnWriter>| column_opt.unwrap_or_default(),
);
}
ColumnType::DateTime => {
self.datetime_field_hash_map.mutate_or_create(
column_name.as_bytes(),
mutate_or_create_column(
&mut self.datetime_field_hash_map,
column_name,
|column_opt: Option<ColumnWriter>| column_opt.unwrap_or_default(),
);
}
ColumnType::I64 | ColumnType::F64 | ColumnType::U64 => {
let numerical_type = column_type.numerical_type().unwrap();
self.numerical_field_hash_map.mutate_or_create(
column_name.as_bytes(),
mutate_or_create_column(
&mut self.numerical_field_hash_map,
column_name,
|column_opt: Option<NumericalColumnWriter>| {
let mut column: NumericalColumnWriter = column_opt.unwrap_or_default();
column.force_numerical_type(numerical_type);
@@ -140,8 +219,9 @@ impl ColumnarWriter {
},
);
}
ColumnType::IpAddr => self.ip_addr_field_hash_map.mutate_or_create(
column_name.as_bytes(),
ColumnType::IpAddr => mutate_or_create_column(
&mut self.ip_addr_field_hash_map,
column_name,
|column_opt: Option<ColumnWriter>| column_opt.unwrap_or_default(),
),
}
@@ -154,8 +234,9 @@ impl ColumnarWriter {
numerical_value: T,
) {
let (hash_map, arena) = (&mut self.numerical_field_hash_map, &mut self.arena);
hash_map.mutate_or_create(
column_name.as_bytes(),
mutate_or_create_column(
hash_map,
column_name,
|column_opt: Option<NumericalColumnWriter>| {
let mut column: NumericalColumnWriter = column_opt.unwrap_or_default();
column.record_numerical_value(doc, numerical_value.into(), arena);
@@ -165,6 +246,10 @@ impl ColumnarWriter {
}
pub fn record_ip_addr(&mut self, doc: RowId, column_name: &str, ip_addr: Ipv6Addr) {
assert!(
!column_name.as_bytes().contains(&0u8),
"key may not contain the 0 byte"
);
let (hash_map, arena) = (&mut self.ip_addr_field_hash_map, &mut self.arena);
hash_map.mutate_or_create(
column_name.as_bytes(),
@@ -178,30 +263,24 @@ impl ColumnarWriter {
pub fn record_bool(&mut self, doc: RowId, column_name: &str, val: bool) {
let (hash_map, arena) = (&mut self.bool_field_hash_map, &mut self.arena);
hash_map.mutate_or_create(
column_name.as_bytes(),
|column_opt: Option<ColumnWriter>| {
let mut column: ColumnWriter = column_opt.unwrap_or_default();
column.record(doc, val, arena);
column
},
);
mutate_or_create_column(hash_map, column_name, |column_opt: Option<ColumnWriter>| {
let mut column: ColumnWriter = column_opt.unwrap_or_default();
column.record(doc, val, arena);
column
});
}
pub fn record_datetime(&mut self, doc: RowId, column_name: &str, datetime: common::DateTime) {
let (hash_map, arena) = (&mut self.datetime_field_hash_map, &mut self.arena);
hash_map.mutate_or_create(
column_name.as_bytes(),
|column_opt: Option<ColumnWriter>| {
let mut column: ColumnWriter = column_opt.unwrap_or_default();
column.record(
doc,
NumericalValue::I64(datetime.into_timestamp_nanos()),
arena,
);
column
},
);
mutate_or_create_column(hash_map, column_name, |column_opt: Option<ColumnWriter>| {
let mut column: ColumnWriter = column_opt.unwrap_or_default();
column.record(
doc,
NumericalValue::I64(datetime.into_timestamp_nanos()),
arena,
);
column
});
}
pub fn record_str(&mut self, doc: RowId, column_name: &str, value: &str) {
@@ -226,6 +305,10 @@ impl ColumnarWriter {
}
pub fn record_bytes(&mut self, doc: RowId, column_name: &str, value: &[u8]) {
assert!(
!column_name.as_bytes().contains(&0u8),
"key may not contain the 0 byte"
);
let (hash_map, arena, dictionaries) = (
&mut self.bytes_field_hash_map,
&mut self.arena,
@@ -245,9 +328,13 @@ impl ColumnarWriter {
},
);
}
pub fn serialize(&mut self, num_docs: RowId, wrt: &mut dyn io::Write) -> io::Result<()> {
pub fn serialize(
&mut self,
num_docs: RowId,
old_to_new_row_ids: Option<&[RowId]>,
wrt: &mut dyn io::Write,
) -> io::Result<()> {
let mut serializer = ColumnarSerializer::new(wrt);
let mut columns: Vec<(&[u8], ColumnType, Addr)> = self
.numerical_field_hash_map
.iter()
@@ -261,7 +348,7 @@ impl ColumnarWriter {
columns.extend(
self.bytes_field_hash_map
.iter()
.map(|(column_name, addr)| (column_name, ColumnType::Bytes, addr)),
.map(|(term, addr)| (term, ColumnType::Bytes, addr)),
);
columns.extend(
self.str_field_hash_map
@@ -283,7 +370,6 @@ impl ColumnarWriter {
.iter()
.map(|(column_name, addr)| (column_name, ColumnType::DateTime, addr)),
);
// TODO: replace JSON_END_OF_PATH with b'0' in columns
columns.sort_unstable_by_key(|(column_name, col_type, _)| (*column_name, *col_type));
let (arena, buffers, dictionaries) = (&self.arena, &mut self.buffers, &self.dictionaries);
@@ -298,7 +384,11 @@ impl ColumnarWriter {
serialize_bool_column(
cardinality,
num_docs,
column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
column_writer.operation_iterator(
arena,
old_to_new_row_ids,
&mut symbol_byte_buffer,
),
buffers,
&mut column_serializer,
)?;
@@ -312,7 +402,11 @@ impl ColumnarWriter {
serialize_ip_addr_column(
cardinality,
num_docs,
column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
column_writer.operation_iterator(
arena,
old_to_new_row_ids,
&mut symbol_byte_buffer,
),
buffers,
&mut column_serializer,
)?;
@@ -337,8 +431,11 @@ impl ColumnarWriter {
num_docs,
str_or_bytes_column_writer.sort_values_within_row,
dictionary_builder,
str_or_bytes_column_writer
.operation_iterator(arena, &mut symbol_byte_buffer),
str_or_bytes_column_writer.operation_iterator(
arena,
old_to_new_row_ids,
&mut symbol_byte_buffer,
),
buffers,
&self.arena,
&mut column_serializer,
@@ -356,7 +453,11 @@ impl ColumnarWriter {
cardinality,
num_docs,
numerical_type,
numerical_column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
numerical_column_writer.operation_iterator(
arena,
old_to_new_row_ids,
&mut symbol_byte_buffer,
),
buffers,
&mut column_serializer,
)?;
@@ -371,7 +472,11 @@ impl ColumnarWriter {
cardinality,
num_docs,
NumericalType::I64,
column_writer.operation_iterator(arena, &mut symbol_byte_buffer),
column_writer.operation_iterator(
arena,
old_to_new_row_ids,
&mut symbol_byte_buffer,
),
buffers,
&mut column_serializer,
)?;
@@ -540,7 +645,10 @@ fn send_to_serialize_column_mappable_to_u128<
value_index_builders: &mut PreallocatedIndexBuilders,
values: &mut Vec<T>,
mut wrt: impl io::Write,
) -> io::Result<()> {
) -> io::Result<()>
where
for<'a> VecColumn<'a, T>: ColumnValues<T>,
{
values.clear();
// TODO: split index and values
let serializable_column_index = match cardinality {
@@ -556,16 +664,16 @@ fn send_to_serialize_column_mappable_to_u128<
let optional_index_builder = value_index_builders.borrow_optional_index_builder();
consume_operation_iterator(op_iterator, optional_index_builder, values);
let optional_index = optional_index_builder.finish(num_rows);
SerializableColumnIndex::Optional(SerializableOptionalIndex {
SerializableColumnIndex::Optional {
num_rows,
non_null_row_ids: Box::new(optional_index),
})
}
}
Cardinality::Multivalued => {
let multivalued_index_builder = value_index_builders.borrow_multivalued_index_builder();
consume_operation_iterator(op_iterator, multivalued_index_builder, values);
let serializable_multivalued_index = multivalued_index_builder.finish(num_rows);
SerializableColumnIndex::Multivalued(serializable_multivalued_index)
let multivalued_index = multivalued_index_builder.finish(num_rows);
SerializableColumnIndex::Multivalued(Box::new(multivalued_index))
}
};
crate::column::serialize_column_mappable_to_u128(
@@ -576,6 +684,15 @@ fn send_to_serialize_column_mappable_to_u128<
Ok(())
}
fn sort_values_within_row_in_place(multivalued_index: &[RowId], values: &mut [u64]) {
let mut start_index: usize = 0;
for end_index in multivalued_index.iter().copied() {
let end_index = end_index as usize;
values[start_index..end_index].sort_unstable();
start_index = end_index;
}
}
fn send_to_serialize_column_mappable_to_u64(
op_iterator: impl Iterator<Item = ColumnOperation<u64>>,
cardinality: Cardinality,
@@ -584,7 +701,10 @@ fn send_to_serialize_column_mappable_to_u64(
value_index_builders: &mut PreallocatedIndexBuilders,
values: &mut Vec<u64>,
mut wrt: impl io::Write,
) -> io::Result<()> {
) -> io::Result<()>
where
for<'a> VecColumn<'a, u64>: ColumnValues<u64>,
{
values.clear();
let serializable_column_index = match cardinality {
Cardinality::Full => {
@@ -599,22 +719,19 @@ fn send_to_serialize_column_mappable_to_u64(
let optional_index_builder = value_index_builders.borrow_optional_index_builder();
consume_operation_iterator(op_iterator, optional_index_builder, values);
let optional_index = optional_index_builder.finish(num_rows);
SerializableColumnIndex::Optional(SerializableOptionalIndex {
SerializableColumnIndex::Optional {
non_null_row_ids: Box::new(optional_index),
num_rows,
})
}
}
Cardinality::Multivalued => {
let multivalued_index_builder = value_index_builders.borrow_multivalued_index_builder();
consume_operation_iterator(op_iterator, multivalued_index_builder, values);
let serializable_multivalued_index = multivalued_index_builder.finish(num_rows);
let multivalued_index = multivalued_index_builder.finish(num_rows);
if sort_values_within_row {
sort_values_within_row_in_place(
serializable_multivalued_index.start_offsets.boxed_iter(),
values,
);
sort_values_within_row_in_place(multivalued_index, values);
}
SerializableColumnIndex::Multivalued(serializable_multivalued_index)
SerializableColumnIndex::Multivalued(Box::new(multivalued_index))
}
};
crate::column::serialize_column_mappable_to_u64(
@@ -625,18 +742,6 @@ fn send_to_serialize_column_mappable_to_u64(
Ok(())
}
fn sort_values_within_row_in_place(
multivalued_index: impl Iterator<Item = RowId>,
values: &mut [u64],
) {
let mut start_index: usize = 0;
for end_index in multivalued_index {
let end_index = end_index as usize;
values[start_index..end_index].sort_unstable();
start_index = end_index;
}
}
fn coerce_numerical_symbol<T>(
operation_iterator: impl Iterator<Item = ColumnOperation<NumericalValue>>,
) -> impl Iterator<Item = ColumnOperation<u64>>
@@ -684,7 +789,7 @@ mod tests {
assert_eq!(column_writer.get_cardinality(3), Cardinality::Full);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&arena, &mut buffer)
.operation_iterator(&arena, None, &mut buffer)
.collect();
assert_eq!(symbols.len(), 6);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -713,7 +818,7 @@ mod tests {
assert_eq!(column_writer.get_cardinality(3), Cardinality::Optional);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&arena, &mut buffer)
.operation_iterator(&arena, None, &mut buffer)
.collect();
assert_eq!(symbols.len(), 4);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(1u32)));
@@ -736,7 +841,7 @@ mod tests {
assert_eq!(column_writer.get_cardinality(2), Cardinality::Optional);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&arena, &mut buffer)
.operation_iterator(&arena, None, &mut buffer)
.collect();
assert_eq!(symbols.len(), 2);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));
@@ -755,7 +860,7 @@ mod tests {
assert_eq!(column_writer.get_cardinality(1), Cardinality::Multivalued);
let mut buffer = Vec::new();
let symbols: Vec<ColumnOperation<NumericalValue>> = column_writer
.operation_iterator(&arena, &mut buffer)
.operation_iterator(&arena, None, &mut buffer)
.collect();
assert_eq!(symbols.len(), 3);
assert!(matches!(symbols[0], ColumnOperation::NewDoc(0u32)));

View File

@@ -1,7 +1,6 @@
use std::io;
use std::io::Write;
use common::json_path_writer::JSON_END_OF_PATH;
use common::{BinarySerializable, CountingWriter};
use sstable::value::RangeValueWriter;
use sstable::RangeSSTable;
@@ -20,7 +19,7 @@ pub struct ColumnarSerializer<W: io::Write> {
fn prepare_key(key: &[u8], column_type: ColumnType, buffer: &mut Vec<u8>) {
buffer.clear();
buffer.extend_from_slice(key);
buffer.push(JSON_END_OF_PATH);
buffer.push(0u8);
buffer.push(column_type.to_code());
}
@@ -97,13 +96,14 @@ impl<'a, W: io::Write> io::Write for ColumnSerializer<'a, W> {
#[cfg(test)]
mod tests {
use super::*;
use crate::columnar::column_type::ColumnType;
#[test]
fn test_prepare_key_bytes() {
let mut buffer: Vec<u8> = b"somegarbage".to_vec();
prepare_key(b"root\0child", ColumnType::Str, &mut buffer);
assert_eq!(buffer.len(), 12);
assert_eq!(&buffer[..10], b"root0child");
assert_eq!(&buffer[..10], b"root\0child");
assert_eq!(buffer[10], 0u8);
assert_eq!(buffer[11], ColumnType::Str.to_code());
}

View File

@@ -1,4 +1,3 @@
use crate::column_index::{SerializableMultivalueIndex, SerializableOptionalIndex};
use crate::iterable::Iterable;
use crate::RowId;
@@ -60,47 +59,31 @@ impl IndexBuilder for OptionalIndexBuilder {
#[derive(Default)]
pub struct MultivaluedIndexBuilder {
doc_with_values: Vec<RowId>,
start_offsets: Vec<u32>,
start_offsets: Vec<RowId>,
total_num_vals_seen: u32,
current_row: RowId,
current_row_has_value: bool,
}
impl MultivaluedIndexBuilder {
pub fn finish(&mut self, num_docs: RowId) -> SerializableMultivalueIndex<'_> {
self.start_offsets.push(self.total_num_vals_seen);
let non_null_row_ids: Box<dyn Iterable<RowId>> = Box::new(&self.doc_with_values[..]);
SerializableMultivalueIndex {
doc_ids_with_values: SerializableOptionalIndex {
non_null_row_ids,
num_rows: num_docs,
},
start_offsets: Box::new(&self.start_offsets[..]),
}
pub fn finish(&mut self, num_docs: RowId) -> &[u32] {
self.start_offsets
.resize(num_docs as usize + 1, self.total_num_vals_seen);
&self.start_offsets[..]
}
fn reset(&mut self) {
self.doc_with_values.clear();
self.start_offsets.clear();
self.start_offsets.push(0u32);
self.total_num_vals_seen = 0;
self.current_row = 0;
self.current_row_has_value = false;
}
}
impl IndexBuilder for MultivaluedIndexBuilder {
fn record_row(&mut self, row_id: RowId) {
self.current_row = row_id;
self.current_row_has_value = false;
self.start_offsets
.resize(row_id as usize + 1, self.total_num_vals_seen);
}
fn record_value(&mut self) {
if !self.current_row_has_value {
self.current_row_has_value = true;
self.doc_with_values.push(self.current_row);
self.start_offsets.push(self.total_num_vals_seen);
}
self.total_num_vals_seen += 1;
}
}
@@ -158,32 +141,6 @@ mod tests {
);
}
#[test]
fn test_multivalued_value_index_builder_simple() {
let mut multivalued_value_index_builder = MultivaluedIndexBuilder::default();
{
multivalued_value_index_builder.record_row(0u32);
multivalued_value_index_builder.record_value();
multivalued_value_index_builder.record_value();
let serialized_multivalue_index = multivalued_value_index_builder.finish(1u32);
let start_offsets: Vec<u32> = serialized_multivalue_index
.start_offsets
.boxed_iter()
.collect();
assert_eq!(&start_offsets, &[0, 2]);
}
multivalued_value_index_builder.reset();
multivalued_value_index_builder.record_row(0u32);
multivalued_value_index_builder.record_value();
multivalued_value_index_builder.record_value();
let serialized_multivalue_index = multivalued_value_index_builder.finish(1u32);
let start_offsets: Vec<u32> = serialized_multivalue_index
.start_offsets
.boxed_iter()
.collect();
assert_eq!(&start_offsets, &[0, 2]);
}
#[test]
fn test_multivalued_value_index_builder() {
let mut multivalued_value_index_builder = MultivaluedIndexBuilder::default();
@@ -192,15 +149,17 @@ mod tests {
multivalued_value_index_builder.record_value();
multivalued_value_index_builder.record_row(2u32);
multivalued_value_index_builder.record_value();
let SerializableMultivalueIndex {
doc_ids_with_values,
start_offsets,
} = multivalued_value_index_builder.finish(4u32);
assert_eq!(doc_ids_with_values.num_rows, 4u32);
let doc_ids_with_values: Vec<u32> =
doc_ids_with_values.non_null_row_ids.boxed_iter().collect();
assert_eq!(&doc_ids_with_values, &[1u32, 2u32]);
let start_offsets: Vec<u32> = start_offsets.boxed_iter().collect();
assert_eq!(&start_offsets[..], &[0, 2, 3]);
assert_eq!(
multivalued_value_index_builder.finish(4u32).to_vec(),
vec![0, 0, 2, 3, 3]
);
multivalued_value_index_builder.reset();
multivalued_value_index_builder.record_row(2u32);
multivalued_value_index_builder.record_value();
multivalued_value_index_builder.record_value();
assert_eq!(
multivalued_value_index_builder.finish(4u32).to_vec(),
vec![0, 0, 0, 2, 2]
);
}
}

View File

@@ -1,183 +0,0 @@
use std::path::PathBuf;
use itertools::Itertools;
use crate::{
merge_columnar, Cardinality, Column, ColumnarReader, DynamicColumn, StackMergeOrder,
CURRENT_VERSION,
};
const NUM_DOCS: u32 = u16::MAX as u32;
fn generate_columnar(num_docs: u32, value_offset: u64) -> Vec<u8> {
use crate::ColumnarWriter;
let mut columnar_writer = ColumnarWriter::default();
for i in 0..num_docs {
if i % 100 == 0 {
columnar_writer.record_numerical(i, "sparse", value_offset + i as u64);
}
if i % 5 == 0 {
columnar_writer.record_numerical(i, "dense", value_offset + i as u64);
}
columnar_writer.record_numerical(i, "full", value_offset + i as u64);
columnar_writer.record_numerical(i, "multi", value_offset + i as u64);
columnar_writer.record_numerical(i, "multi", value_offset + i as u64);
}
let mut wrt: Vec<u8> = Vec::new();
columnar_writer.serialize(num_docs, &mut wrt).unwrap();
wrt
}
#[test]
/// Writes a columnar for the CURRENT_VERSION to disk.
fn create_format() {
let version = CURRENT_VERSION.to_string();
let file_path = path_for_version(&version);
if PathBuf::from(file_path.clone()).exists() {
return;
}
let columnar = generate_columnar(NUM_DOCS, 0);
std::fs::write(file_path, columnar).unwrap();
}
fn path_for_version(version: &str) -> String {
format!("./compat_tests_data/{}.columnar", version)
}
#[test]
fn test_format_v1() {
let path = path_for_version("v1");
test_format(&path);
}
#[test]
fn test_format_v2() {
let path = path_for_version("v2");
test_format(&path);
}
fn test_format(path: &str) {
let file_content = std::fs::read(path).unwrap();
let reader = ColumnarReader::open(file_content).unwrap();
check_columns(&reader);
// Test merge
let reader2 = ColumnarReader::open(generate_columnar(NUM_DOCS, NUM_DOCS as u64)).unwrap();
let columnar_readers = vec![&reader, &reader2];
let merge_row_order = StackMergeOrder::stack(&columnar_readers[..]);
let mut out = Vec::new();
merge_columnar(&columnar_readers, &[], merge_row_order.into(), &mut out).unwrap();
let reader = ColumnarReader::open(out).unwrap();
check_columns(&reader);
}
fn check_columns(reader: &ColumnarReader) {
let column = open_column(reader, "full");
check_column(&column, |doc_id| vec![(doc_id, doc_id as u64).into()]);
assert_eq!(column.get_cardinality(), Cardinality::Full);
let column = open_column(reader, "multi");
check_column(&column, |doc_id| {
vec![
(doc_id * 2, doc_id as u64).into(),
(doc_id * 2 + 1, doc_id as u64).into(),
]
});
assert_eq!(column.get_cardinality(), Cardinality::Multivalued);
let column = open_column(reader, "sparse");
check_column(&column, |doc_id| {
if doc_id % 100 == 0 {
vec![(doc_id / 100, doc_id as u64).into()]
} else {
vec![]
}
});
assert_eq!(column.get_cardinality(), Cardinality::Optional);
let column = open_column(reader, "dense");
check_column(&column, |doc_id| {
if doc_id % 5 == 0 {
vec![(doc_id / 5, doc_id as u64).into()]
} else {
vec![]
}
});
assert_eq!(column.get_cardinality(), Cardinality::Optional);
}
struct RowIdAndValue {
row_id: u32,
value: u64,
}
impl From<(u32, u64)> for RowIdAndValue {
fn from((row_id, value): (u32, u64)) -> Self {
Self { row_id, value }
}
}
fn check_column<F: Fn(u32) -> Vec<RowIdAndValue>>(column: &Column<u64>, expected: F) {
let num_docs = column.num_docs();
let test_doc = |doc: u32| {
if expected(doc).is_empty() {
assert_eq!(column.first(doc), None);
} else {
assert_eq!(column.first(doc), Some(expected(doc)[0].value));
}
let values = column.values_for_doc(doc).collect_vec();
assert_eq!(values, expected(doc).iter().map(|x| x.value).collect_vec());
let mut row_ids = Vec::new();
column.row_ids_for_docs(&[doc], &mut vec![], &mut row_ids);
assert_eq!(
row_ids,
expected(doc).iter().map(|x| x.row_id).collect_vec()
);
let values = column.values_for_doc(doc).collect_vec();
assert_eq!(values, expected(doc).iter().map(|x| x.value).collect_vec());
// Docid rowid conversion
let mut row_ids = Vec::new();
let safe_next_doc = |doc: u32| (doc + 1).min(num_docs - 1);
column
.index
.docids_to_rowids(&[doc, safe_next_doc(doc)], &mut vec![], &mut row_ids);
let expected_rowids = expected(doc)
.iter()
.map(|x| x.row_id)
.chain(expected(safe_next_doc(doc)).iter().map(|x| x.row_id))
.collect_vec();
assert_eq!(row_ids, expected_rowids);
let rowid_range = column
.index
.docid_range_to_rowids(doc..safe_next_doc(doc) + 1);
if expected_rowids.is_empty() {
assert!(rowid_range.is_empty());
} else {
assert_eq!(
rowid_range,
expected_rowids[0]..expected_rowids.last().unwrap() + 1
);
}
};
test_doc(0);
test_doc(num_docs - 1);
test_doc(num_docs - 2);
test_doc(65000);
}
fn open_column(reader: &ColumnarReader, name: &str) -> Column<u64> {
let column = reader.read_columns(name).unwrap()[0]
.open()
.unwrap()
.coerce_numerical(crate::NumericalType::U64)
.unwrap();
let DynamicColumn::U64(column) = column else {
panic!();
};
column
}

View File

@@ -8,7 +8,7 @@ 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, ColumnIndex, ColumnValues, NumericalType, Version};
use crate::{Cardinality, ColumnIndex, NumericalType};
#[derive(Clone)]
pub enum DynamicColumn {
@@ -232,7 +232,6 @@ static_dynamic_conversions!(Column<Ipv6Addr>, IpAddr);
pub struct DynamicColumnHandle {
pub(crate) file_slice: FileSlice,
pub(crate) column_type: ColumnType,
pub(crate) format_version: Version,
}
impl DynamicColumnHandle {
@@ -248,12 +247,7 @@ impl DynamicColumnHandle {
}
/// Returns the `u64` fast field reader reader associated with `fields` of types
/// Str, u64, i64, f64, bool, ip, or datetime.
///
/// Notice that for IpAddr, the fastfield reader will return the u64 representation of the
/// IpAddr.
/// In order to convert to u128 back cast to `CompactSpaceU64Accessor` and call
/// `compact_to_u128`.
/// Str, u64, i64, f64, bool, or datetime.
///
/// If not, the fastfield reader will returns the u64-value associated with the original
/// FastValue.
@@ -261,24 +255,16 @@ impl DynamicColumnHandle {
let column_bytes = self.file_slice.read_bytes()?;
match self.column_type {
ColumnType::Str | ColumnType::Bytes => {
let column: BytesColumn =
crate::column::open_column_bytes(column_bytes, self.format_version)?;
let column: BytesColumn = crate::column::open_column_bytes(column_bytes)?;
Ok(Some(column.term_ord_column))
}
ColumnType::IpAddr => {
let column = crate::column::open_column_u128_as_compact_u64(
column_bytes,
self.format_version,
)?;
Ok(Some(column))
}
ColumnType::IpAddr => Ok(None),
ColumnType::Bool
| ColumnType::I64
| ColumnType::U64
| ColumnType::F64
| ColumnType::DateTime => {
let column =
crate::column::open_column_u64::<u64>(column_bytes, self.format_version)?;
let column = crate::column::open_column_u64::<u64>(column_bytes)?;
Ok(Some(column))
}
}
@@ -286,31 +272,15 @@ impl DynamicColumnHandle {
fn open_internal(&self, column_bytes: OwnedBytes) -> io::Result<DynamicColumn> {
let dynamic_column: DynamicColumn = match self.column_type {
ColumnType::Bytes => {
crate::column::open_column_bytes(column_bytes, self.format_version)?.into()
}
ColumnType::Str => {
crate::column::open_column_str(column_bytes, self.format_version)?.into()
}
ColumnType::I64 => {
crate::column::open_column_u64::<i64>(column_bytes, self.format_version)?.into()
}
ColumnType::U64 => {
crate::column::open_column_u64::<u64>(column_bytes, self.format_version)?.into()
}
ColumnType::F64 => {
crate::column::open_column_u64::<f64>(column_bytes, self.format_version)?.into()
}
ColumnType::Bool => {
crate::column::open_column_u64::<bool>(column_bytes, self.format_version)?.into()
}
ColumnType::IpAddr => {
crate::column::open_column_u128::<Ipv6Addr>(column_bytes, self.format_version)?
.into()
}
ColumnType::Bytes => crate::column::open_column_bytes(column_bytes)?.into(),
ColumnType::Str => crate::column::open_column_str(column_bytes)?.into(),
ColumnType::I64 => crate::column::open_column_u64::<i64>(column_bytes)?.into(),
ColumnType::U64 => crate::column::open_column_u64::<u64>(column_bytes)?.into(),
ColumnType::F64 => crate::column::open_column_u64::<f64>(column_bytes)?.into(),
ColumnType::Bool => crate::column::open_column_u64::<bool>(column_bytes)?.into(),
ColumnType::IpAddr => crate::column::open_column_u128::<Ipv6Addr>(column_bytes)?.into(),
ColumnType::DateTime => {
crate::column::open_column_u64::<DateTime>(column_bytes, self.format_version)?
.into()
crate::column::open_column_u64::<DateTime>(column_bytes)?.into()
}
};
Ok(dynamic_column)

View File

@@ -1,7 +1,4 @@
use std::ops::Range;
use std::sync::Arc;
use crate::{ColumnValues, RowId};
pub trait Iterable<T = u64> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = T> + '_>;
@@ -20,9 +17,3 @@ where Range<T>: Iterator<Item = T>
Box::new(self.clone())
}
}
impl Iterable for Arc<dyn crate::ColumnValues<RowId>> {
fn boxed_iter(&self) -> Box<dyn Iterator<Item = u64> + '_> {
Box::new(self.iter().map(|row_id| row_id as u64))
}
}

View File

@@ -48,7 +48,7 @@ pub use column_values::{
};
pub use columnar::{
merge_columnar, ColumnType, ColumnarReader, ColumnarWriter, HasAssociatedColumnType,
MergeRowOrder, ShuffleMergeOrder, StackMergeOrder, Version, CURRENT_VERSION,
MergeRowOrder, ShuffleMergeOrder, StackMergeOrder,
};
use sstable::VoidSSTable;
pub use value::{NumericalType, NumericalValue};
@@ -113,9 +113,6 @@ impl Cardinality {
pub fn is_multivalue(&self) -> bool {
matches!(self, Cardinality::Multivalued)
}
pub fn is_full(&self) -> bool {
matches!(self, Cardinality::Full)
}
pub(crate) fn to_code(self) -> u8 {
self as u8
}
@@ -131,6 +128,3 @@ impl Cardinality {
#[cfg(test)]
mod tests;
#[cfg(test)]
mod compat_tests;

View File

@@ -21,7 +21,7 @@ fn test_dataframe_writer_str() {
dataframe_writer.record_str(1u32, "my_string", "hello");
dataframe_writer.record_str(3u32, "my_string", "helloeee");
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
dataframe_writer.serialize(5, None, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
@@ -35,7 +35,7 @@ fn test_dataframe_writer_bytes() {
dataframe_writer.record_bytes(1u32, "my_string", b"hello");
dataframe_writer.record_bytes(3u32, "my_string", b"helloeee");
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
dataframe_writer.serialize(5, None, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("my_string").unwrap();
@@ -49,7 +49,7 @@ fn test_dataframe_writer_bool() {
dataframe_writer.record_bool(1u32, "bool.value", false);
dataframe_writer.record_bool(3u32, "bool.value", true);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
dataframe_writer.serialize(5, None, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("bool.value").unwrap();
@@ -74,12 +74,12 @@ fn test_dataframe_writer_u64_multivalued() {
dataframe_writer.record_numerical(6u32, "divisor", 2u64);
dataframe_writer.record_numerical(6u32, "divisor", 3u64);
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(7, &mut buffer).unwrap();
dataframe_writer.serialize(7, None, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("divisor").unwrap();
assert_eq!(cols.len(), 1);
assert_eq!(cols[0].num_bytes(), 50);
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!();
@@ -97,7 +97,7 @@ fn test_dataframe_writer_ip_addr() {
dataframe_writer.record_ip_addr(1, "ip_addr", Ipv6Addr::from_u128(1001));
dataframe_writer.record_ip_addr(3, "ip_addr", Ipv6Addr::from_u128(1050));
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(5, &mut buffer).unwrap();
dataframe_writer.serialize(5, None, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("ip_addr").unwrap();
@@ -128,7 +128,7 @@ fn test_dataframe_writer_numerical() {
dataframe_writer.record_numerical(2u32, "srical.value", NumericalValue::U64(13u64));
dataframe_writer.record_numerical(4u32, "srical.value", NumericalValue::U64(15u64));
let mut buffer: Vec<u8> = Vec::new();
dataframe_writer.serialize(6, &mut buffer).unwrap();
dataframe_writer.serialize(6, None, &mut buffer).unwrap();
let columnar = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar.num_columns(), 1);
let cols: Vec<DynamicColumnHandle> = columnar.read_columns("srical.value").unwrap();
@@ -153,6 +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();
@@ -161,7 +201,7 @@ fn test_dictionary_encoded_str() {
columnar_writer.record_str(3, "my.column", "c");
columnar_writer.record_str(3, "my.column2", "different_column!");
columnar_writer.record_str(4, "my.column", "b");
columnar_writer.serialize(5, &mut buffer).unwrap();
columnar_writer.serialize(5, None, &mut buffer).unwrap();
let columnar_reader = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar_reader.num_columns(), 2);
let col_handles = columnar_reader.read_columns("my.column").unwrap();
@@ -195,7 +235,7 @@ fn test_dictionary_encoded_bytes() {
columnar_writer.record_bytes(3, "my.column", b"c");
columnar_writer.record_bytes(3, "my.column2", b"different_column!");
columnar_writer.record_bytes(4, "my.column", b"b");
columnar_writer.serialize(5, &mut buffer).unwrap();
columnar_writer.serialize(5, None, &mut buffer).unwrap();
let columnar_reader = ColumnarReader::open(buffer).unwrap();
assert_eq!(columnar_reader.num_columns(), 2);
let col_handles = columnar_reader.read_columns("my.column").unwrap();
@@ -304,7 +344,7 @@ fn column_value_strategy() -> impl Strategy<Value = ColumnValue> {
ip_addr_byte
))),
1 => any::<bool>().prop_map(ColumnValue::Bool),
1 => (679_723_993i64..1_679_723_995i64)
1 => (0_679_723_993i64..1_679_723_995i64)
.prop_map(|val| { ColumnValue::DateTime(DateTime::from_timestamp_secs(val)) })
]
}
@@ -329,12 +369,26 @@ fn columnar_docs_strategy() -> impl Strategy<Value = Vec<Vec<(&'static str, Colu
.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)>]) -> ColumnarReader {
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();
@@ -362,13 +416,15 @@ fn build_columnar_with_mapping(docs: &[Vec<(&'static str, ColumnValue)>]) -> Col
}
}
}
columnar_writer.serialize(num_docs, &mut buffer).unwrap();
columnar_writer
.serialize(num_docs, old_to_new_row_ids_opt, &mut buffer)
.unwrap();
ColumnarReader::open(buffer).unwrap()
}
fn build_columnar(docs: &[Vec<(&'static str, ColumnValue)>]) -> ColumnarReader {
build_columnar_with_mapping(docs)
build_columnar_with_mapping(docs, None)
}
fn assert_columnar_eq_strict(left: &ColumnarReader, right: &ColumnarReader) {
@@ -392,7 +448,6 @@ fn assert_columnar_eq(
}
}
#[track_caller]
fn assert_column_eq<T: Copy + PartialOrd + Debug + Send + Sync + 'static>(
left: &Column<T>,
right: &Column<T>,
@@ -628,6 +683,54 @@ proptest! {
}
}
// 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.
@@ -741,68 +844,24 @@ fn columnar_docs_and_remap(
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()) {
test_columnar_merge_and_remap(columnar_docs, shuffle_merge_order);
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);
}
}
fn test_columnar_merge_and_remap(
columnar_docs: Vec<Vec<Vec<(&'static str, ColumnValue)>>>,
shuffle_merge_order: Vec<RowAddr>,
) {
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_ref: 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_ref[..],
&[],
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_and_remap_bug_1() {
let columnar_docs = vec![vec![
vec![
("c1", ColumnValue::Numerical(NumericalValue::U64(0))),
("c1", ColumnValue::Numerical(NumericalValue::U64(0))),
],
vec![],
]];
let shuffle_merge_order: Vec<RowAddr> = vec![
RowAddr {
segment_ord: 0,
row_id: 1,
},
RowAddr {
segment_ord: 0,
row_id: 0,
},
];
test_columnar_merge_and_remap(columnar_docs, shuffle_merge_order);
}
#[test]
fn test_columnar_merge_empty() {
let columnar_reader_1 = build_columnar(&[]);

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-common"
version = "0.7.0"
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= "0.7", 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"] }
@@ -22,6 +22,3 @@ serde = { version = "1.0.136", features = ["derive"] }
[dev-dependencies]
proptest = "1.0.0"
rand = "0.8.4"
[features]
unstable = [] # useful for benches.

View File

@@ -1,5 +1,6 @@
use std::convert::TryInto;
use std::io::Write;
use std::{fmt, io};
use std::{fmt, io, u64};
use ownedbytes::OwnedBytes;

View File

@@ -1,3 +1,5 @@
#![allow(deprecated)]
use std::fmt;
use std::io::{Read, Write};
@@ -25,6 +27,9 @@ pub enum DateTimePrecision {
Nanoseconds,
}
#[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.
@@ -35,7 +40,7 @@ pub enum DateTimePrecision {
/// All constructors and conversions are provided as explicit
/// functions and not by implementing any `From`/`Into` traits
/// to prevent unintended usage.
#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord, Hash, Serialize, Deserialize)]
#[derive(Clone, Default, Copy, PartialEq, Eq, PartialOrd, Ord, Hash)]
pub struct DateTime {
// Timestamp in nanoseconds.
pub(crate) timestamp_nanos: i64,

View File

@@ -5,12 +5,6 @@ pub const JSON_PATH_SEGMENT_SEP: u8 = 1u8;
pub const JSON_PATH_SEGMENT_SEP_STR: &str =
unsafe { std::str::from_utf8_unchecked(&[JSON_PATH_SEGMENT_SEP]) };
/// Separates the json path and the value in
/// a JSON term binary representation.
pub const JSON_END_OF_PATH: u8 = 0u8;
pub const JSON_END_OF_PATH_STR: &str =
unsafe { std::str::from_utf8_unchecked(&[JSON_END_OF_PATH]) };
/// Create a new JsonPathWriter, that creates flattened json paths for tantivy.
#[derive(Clone, Debug, Default)]
pub struct JsonPathWriter {
@@ -20,14 +14,6 @@ pub struct JsonPathWriter {
}
impl JsonPathWriter {
pub fn with_expand_dots(expand_dots: bool) -> Self {
JsonPathWriter {
path: String::new(),
indices: Vec::new(),
expand_dots,
}
}
pub fn new() -> Self {
JsonPathWriter {
path: String::new(),
@@ -53,8 +39,8 @@ impl JsonPathWriter {
pub fn push(&mut self, segment: &str) {
let len_path = self.path.len();
self.indices.push(len_path);
if self.indices.len() > 1 {
self.path.push(JSON_PATH_SEGMENT_SEP as char);
if !self.path.is_empty() {
self.path.push_str(JSON_PATH_SEGMENT_SEP_STR);
}
self.path.push_str(segment);
if self.expand_dots {
@@ -69,12 +55,6 @@ impl JsonPathWriter {
}
}
/// Set the end of JSON path marker.
#[inline]
pub fn set_end(&mut self) {
self.path.push_str(JSON_END_OF_PATH_STR);
}
/// Remove the last segment. Does nothing if the path is empty.
#[inline]
pub fn pop(&mut self) {
@@ -111,7 +91,6 @@ mod tests {
#[test]
fn json_path_writer_test() {
let mut writer = JsonPathWriter::new();
writer.set_expand_dots(false);
writer.push("root");
assert_eq!(writer.as_str(), "root");
@@ -130,15 +109,4 @@ mod tests {
writer.push("k8s.node.id");
assert_eq!(writer.as_str(), "root\u{1}k8s\u{1}node\u{1}id");
}
#[test]
fn test_json_path_expand_dots_enabled_pop_segment() {
let mut json_writer = JsonPathWriter::with_expand_dots(true);
json_writer.push("hello");
assert_eq!(json_writer.as_str(), "hello");
json_writer.push("color.hue");
assert_eq!(json_writer.as_str(), "hello\x01color\x01hue");
json_writer.pop();
assert_eq!(json_writer.as_str(), "hello");
}
}

View File

@@ -9,12 +9,14 @@ mod byte_count;
mod datetime;
pub mod file_slice;
mod group_by;
pub mod json_path_writer;
mod json_path_writer;
mod serialize;
mod vint;
mod writer;
pub use bitset::*;
pub use byte_count::ByteCount;
#[allow(deprecated)]
pub use datetime::DatePrecision;
pub use datetime::{DateTime, DateTimePrecision};
pub use group_by::GroupByIteratorExtended;
pub use json_path_writer::JsonPathWriter;

View File

@@ -290,7 +290,8 @@ impl<'a> BinarySerializable for Cow<'a, [u8]> {
#[cfg(test)]
pub mod test {
use super::*;
use super::{VInt, *};
use crate::serialize::BinarySerializable;
pub fn fixed_size_test<O: BinarySerializable + FixedSize + Default>() {
let mut buffer = Vec::new();
O::default().serialize(&mut buffer).unwrap();

View File

@@ -151,7 +151,7 @@ pub fn read_u32_vint_no_advance(data: &[u8]) -> (u32, usize) {
(result, vlen)
}
/// Write a `u32` as a vint payload.
pub fn write_u32_vint<W: io::Write + ?Sized>(val: u32, writer: &mut W) -> io::Result<()> {
pub fn write_u32_vint<W: io::Write>(val: u32, writer: &mut W) -> io::Result<()> {
let mut buf = [0u8; 8];
let data = serialize_vint_u32(val, &mut buf);
writer.write_all(data)

Binary file not shown.

Before

Width:  |  Height:  |  Size: 30 KiB

View File

@@ -7,11 +7,6 @@
- [Other](#other)
- [Usage](#usage)
# Index Sorting has been removed!
More infos here:
https://github.com/quickwit-oss/tantivy/issues/2352
# Index Sorting
Tantivy allows you to sort the index according to a property.

View File

@@ -11,10 +11,9 @@ use columnar::Column;
// ---
// Importing tantivy...
use tantivy::collector::{Collector, SegmentCollector};
use tantivy::index::SegmentReader;
use tantivy::query::QueryParser;
use tantivy::schema::{Schema, FAST, INDEXED, TEXT};
use tantivy::{doc, Index, IndexWriter, Score};
use tantivy::{doc, Index, IndexWriter, Score, SegmentReader};
#[derive(Default)]
struct Stats {

View File

@@ -4,7 +4,7 @@
use tantivy::collector::TopDocs;
use tantivy::query::QueryParser;
use tantivy::schema::{DateOptions, Document, Schema, Value, INDEXED, STORED, STRING};
use tantivy::schema::{DateOptions, Document, OwnedValue, Schema, INDEXED, STORED, STRING};
use tantivy::{Index, IndexWriter, TantivyDocument};
fn main() -> tantivy::Result<()> {
@@ -13,7 +13,7 @@ fn main() -> tantivy::Result<()> {
let opts = DateOptions::from(INDEXED)
.set_stored()
.set_fast()
.set_precision(tantivy::schema::DateTimePrecision::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);
@@ -61,12 +61,10 @@ fn main() -> tantivy::Result<()> {
assert_eq!(count_docs.len(), 1);
for (_score, doc_address) in count_docs {
let retrieved_doc = searcher.doc::<TantivyDocument>(doc_address)?;
assert!(retrieved_doc
.get_first(occurred_at)
.unwrap()
.as_value()
.as_datetime()
.is_some(),);
assert!(matches!(
retrieved_doc.get_first(occurred_at),
Some(OwnedValue::Date(_))
));
assert_eq!(
retrieved_doc.to_json(&schema),
r#"{"event":["comment"],"occurred_at":["2022-06-22T13:00:00.22Z"]}"#

View File

@@ -51,7 +51,7 @@ fn main() -> tantivy::Result<()> {
let reader = index.reader()?;
let searcher = reader.searcher();
{
let facets = [
let facets = vec![
Facet::from("/ingredient/egg"),
Facet::from("/ingredient/oil"),
Facet::from("/ingredient/garlic"),
@@ -94,8 +94,9 @@ fn main() -> tantivy::Result<()> {
.doc::<TantivyDocument>(*doc_id)
.unwrap()
.get_first(title)
.and_then(|v| v.as_str().map(|el| el.to_string()))
.and_then(|v| v.as_str())
.unwrap()
.to_owned()
})
.collect();
assert_eq!(titles, vec!["Fried egg", "Egg rolls"]);

View File

@@ -61,7 +61,7 @@ fn main() -> tantivy::Result<()> {
debris of the winters flooding; and sycamores with mottled, white, recumbent \
limbs and branches that arch over the pool"
))?;
println!("add doc {i} from thread 1 - opstamp {opstamp}");
println!("add doc {} from thread 1 - opstamp {}", i, opstamp);
thread::sleep(Duration::from_millis(20));
}
Result::<(), TantivyError>::Ok(())
@@ -82,7 +82,7 @@ fn main() -> tantivy::Result<()> {
body => "Some great book description..."
))?
};
println!("add doc {i} from thread 2 - opstamp {opstamp}");
println!("add doc {} from thread 2 - opstamp {}", i, opstamp);
thread::sleep(Duration::from_millis(10));
}
Result::<(), TantivyError>::Ok(())

View File

@@ -7,11 +7,10 @@
// the list of documents containing a term, getting
// its term frequency, and accessing its positions.
use tantivy::postings::Postings;
// ---
// Importing tantivy...
use tantivy::schema::*;
use tantivy::{doc, DocSet, Index, IndexWriter, TERMINATED};
use tantivy::{doc, DocSet, Index, IndexWriter, Postings, TERMINATED};
fn main() -> tantivy::Result<()> {
// We first create a schema for the sake of the

View File

@@ -3,11 +3,10 @@ use std::collections::{HashMap, HashSet};
use std::sync::{Arc, RwLock, Weak};
use tantivy::collector::TopDocs;
use tantivy::index::SegmentId;
use tantivy::query::QueryParser;
use tantivy::schema::{Schema, FAST, TEXT};
use tantivy::{
doc, DocAddress, DocId, Index, IndexWriter, Opstamp, Searcher, SearcherGeneration,
doc, DocAddress, DocId, Index, IndexWriter, Opstamp, Searcher, SearcherGeneration, SegmentId,
SegmentReader, Warmer,
};

View File

@@ -1,7 +1,7 @@
[package]
authors = ["Paul Masurel <paul@quickwit.io>", "Pascal Seitz <pascal@quickwit.io>"]
name = "ownedbytes"
version = "0.7.0"
version = "0.6.0"
edition = "2021"
description = "Expose data as static slice"
license = "MIT"

View File

@@ -1,3 +1,4 @@
use std::convert::TryInto;
use std::ops::{Deref, Range};
use std::sync::Arc;
use std::{fmt, io};

View File

@@ -1,6 +1,6 @@
[package]
name = "tantivy-query-grammar"
version = "0.22.0"
version = "0.21.0"
authors = ["Paul Masurel <paul.masurel@gmail.com>"]
license = "MIT"
categories = ["database-implementations", "data-structures"]

View File

@@ -1,4 +1,3 @@
use std::borrow::Cow;
use std::iter::once;
use nom::branch::alt;
@@ -20,7 +19,7 @@ use crate::Occur;
// Note: '-' char is only forbidden at the beginning of a field name, would be clearer to add it to
// special characters.
const SPECIAL_CHARS: &[char] = &[
'+', '^', '`', ':', '{', '}', '"', '\'', '[', ']', '(', ')', '!', '\\', '*', ' ',
'+', '^', '`', ':', '{', '}', '"', '[', ']', '(', ')', '!', '\\', '*', ' ',
];
/// consume a field name followed by colon. Return the field name with escape sequence
@@ -42,92 +41,36 @@ fn field_name(inp: &str) -> IResult<&str, String> {
)(inp)
}
const ESCAPE_IN_WORD: &[char] = &['^', '`', ':', '{', '}', '"', '\'', '[', ']', '(', ')', '\\'];
fn interpret_escape(source: &str) -> String {
let mut res = String::with_capacity(source.len());
let mut in_escape = false;
let require_escape = |c: char| c.is_whitespace() || ESCAPE_IN_WORD.contains(&c) || c == '-';
for c in source.chars() {
if in_escape {
if !require_escape(c) {
// we re-add the escape sequence
res.push('\\');
}
res.push(c);
in_escape = false;
} else if c == '\\' {
in_escape = true;
} else {
res.push(c);
}
}
res
}
/// Consume a word outside of any context.
// TODO should support escape sequences
fn word(inp: &str) -> IResult<&str, Cow<str>> {
fn word(inp: &str) -> IResult<&str, &str> {
map_res(
recognize(tuple((
alt((
preceded(char('\\'), anychar),
satisfy(|c| !c.is_whitespace() && !ESCAPE_IN_WORD.contains(&c) && c != '-'),
)),
many0(alt((
preceded(char('\\'), anychar),
satisfy(|c: char| !c.is_whitespace() && !ESCAPE_IN_WORD.contains(&c)),
))),
satisfy(|c| {
!c.is_whitespace()
&& !['-', '^', '`', ':', '{', '}', '"', '[', ']', '(', ')'].contains(&c)
}),
many0(satisfy(|c: char| {
!c.is_whitespace() && ![':', '^', '{', '}', '"', '[', ']', '(', ')'].contains(&c)
})),
))),
|s| match s {
"OR" | "AND" | "NOT" | "IN" => Err(Error::new(inp, ErrorKind::Tag)),
s if s.contains('\\') => Ok(Cow::Owned(interpret_escape(s))),
s => Ok(Cow::Borrowed(s)),
_ => Ok(s),
},
)(inp)
}
fn word_infallible(
delimiter: &str,
emit_error: bool,
) -> impl Fn(&str) -> JResult<&str, Option<Cow<str>>> + '_ {
// emit error is set when receiving an unescaped `:` should emit an error
move |inp| {
map(
opt_i_err(
preceded(
multispace0,
recognize(many1(alt((
preceded(char::<&str, _>('\\'), anychar),
satisfy(|c| !c.is_whitespace() && !delimiter.contains(c)),
)))),
),
"expected word",
fn word_infallible(delimiter: &str) -> impl Fn(&str) -> JResult<&str, Option<&str>> + '_ {
|inp| {
opt_i_err(
preceded(
multispace0,
recognize(many1(satisfy(|c| {
!c.is_whitespace() && !delimiter.contains(c)
}))),
),
|(opt_s, mut errors)| match opt_s {
Some(s) => {
if emit_error
&& (s
.as_bytes()
.windows(2)
.any(|window| window[0] != b'\\' && window[1] == b':')
|| s.starts_with(':'))
{
errors.push(LenientErrorInternal {
pos: inp.len(),
message: "parsed possible invalid field as term".to_string(),
});
}
if s.contains('\\') {
(Some(Cow::Owned(interpret_escape(s))), errors)
} else {
(Some(Cow::Borrowed(s)), errors)
}
}
None => (None, errors),
},
"expected word",
)(inp)
}
}
@@ -216,7 +159,7 @@ fn simple_term_infallible(
(value((), char('\'')), simple_quotes),
),
// numbers are parsed with words in this case, as we allow string starting with a -
map(word_infallible(delimiter, true), |(text, errors)| {
map(word_infallible(delimiter), |(text, errors)| {
(text.map(|text| (Delimiter::None, text.to_string())), errors)
}),
)(inp)
@@ -275,14 +218,27 @@ fn term_or_phrase_infallible(inp: &str) -> JResult<&str, Option<UserInputLeaf>>
}
fn term_group(inp: &str) -> IResult<&str, UserInputAst> {
let occur_symbol = alt((
value(Occur::MustNot, char('-')),
value(Occur::Must, char('+')),
));
map(
tuple((
terminated(field_name, multispace0),
delimited(tuple((char('('), multispace0)), ast, char(')')),
delimited(
tuple((char('('), multispace0)),
separated_list0(multispace1, tuple((opt(occur_symbol), term_or_phrase))),
char(')'),
),
)),
|(field_name, mut ast)| {
ast.set_default_field(field_name);
ast
|(field_name, terms)| {
UserInputAst::Clause(
terms
.into_iter()
.map(|(occur, leaf)| (occur, leaf.set_field(Some(field_name.clone())).into()))
.collect(),
)
},
)(inp)
}
@@ -302,18 +258,46 @@ fn term_group_precond(inp: &str) -> IResult<&str, (), ()> {
}
fn term_group_infallible(inp: &str) -> JResult<&str, UserInputAst> {
let (inp, (field_name, _, _, _)) =
let (mut inp, (field_name, _, _, _)) =
tuple((field_name, multispace0, char('('), multispace0))(inp).expect("precondition failed");
let res = delimited_infallible(
nothing,
map(ast_infallible, |(mut ast, errors)| {
ast.set_default_field(field_name.to_string());
(ast, errors)
}),
opt_i_err(char(')'), "expected ')'"),
)(inp);
res
let mut terms = Vec::new();
let mut errs = Vec::new();
let mut first_round = true;
loop {
let mut space_error = if first_round {
first_round = false;
Vec::new()
} else {
let (rest, (_, err)) = space1_infallible(inp)?;
inp = rest;
err
};
if inp.is_empty() {
errs.push(LenientErrorInternal {
pos: inp.len(),
message: "missing )".to_string(),
});
break Ok((inp, (UserInputAst::Clause(terms), errs)));
}
if let Some(inp) = inp.strip_prefix(')') {
break Ok((inp, (UserInputAst::Clause(terms), errs)));
}
// only append missing space error if we did not reach the end of group
errs.append(&mut space_error);
// here we do the assumption term_or_phrase_infallible always consume something if the
// first byte is not `)` or ' '. If it did not, we would end up looping.
let (rest, ((occur, leaf), mut err)) =
tuple_infallible((occur_symbol, term_or_phrase_infallible))(inp)?;
errs.append(&mut err);
if let Some(leaf) = leaf {
terms.push((occur, leaf.set_field(Some(field_name.clone())).into()));
}
inp = rest;
}
}
fn exists(inp: &str) -> IResult<&str, UserInputLeaf> {
@@ -379,6 +363,15 @@ fn literal_no_group_infallible(inp: &str) -> JResult<&str, Option<UserInputAst>>
|((field_name, _, leaf), mut errors)| {
(
leaf.map(|leaf| {
if matches!(&leaf, UserInputLeaf::Literal(literal)
if literal.phrase.contains(':') && literal.delimiter == Delimiter::None)
&& field_name.is_none()
{
errors.push(LenientErrorInternal {
pos: inp.len(),
message: "parsed possible invalid field as term".to_string(),
});
}
if matches!(&leaf, UserInputLeaf::Literal(literal)
if literal.phrase == "NOT" && literal.delimiter == Delimiter::None)
&& field_name.is_none()
@@ -497,20 +490,20 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
tuple_infallible((
opt_i(anychar),
space0_infallible,
word_infallible("]}", false),
word_infallible("]}"),
space1_infallible,
opt_i_err(
terminated(tag("TO"), alt((value((), multispace1), value((), eof)))),
"missing keyword TO",
),
word_infallible("]}", false),
word_infallible("]}"),
opt_i_err(one_of("]}"), "missing range delimiter"),
)),
|(
(lower_bound_kind, _multispace0, lower, _multispace1, to, upper, upper_bound_kind),
errs,
)| {
let lower_bound = match (lower_bound_kind, lower.as_deref()) {
let lower_bound = match (lower_bound_kind, lower) {
(_, Some("*")) => UserInputBound::Unbounded,
(_, None) => UserInputBound::Unbounded,
// if it is some, TO was actually the bound (i.e. [TO TO something])
@@ -519,7 +512,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
(Some('{'), Some(bound)) => UserInputBound::Exclusive(bound.to_string()),
_ => unreachable!("precondition failed, range did not start with [ or {{"),
};
let upper_bound = match (upper_bound_kind, upper.as_deref()) {
let upper_bound = match (upper_bound_kind, upper) {
(_, Some("*")) => UserInputBound::Unbounded,
(_, None) => UserInputBound::Unbounded,
(Some(']'), Some(bound)) => UserInputBound::Inclusive(bound.to_string()),
@@ -536,7 +529,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
(
(
value((), tag(">=")),
map(word_infallible("", false), |(bound, err)| {
map(word_infallible(""), |(bound, err)| {
(
(
bound
@@ -550,7 +543,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
),
(
value((), tag("<=")),
map(word_infallible("", false), |(bound, err)| {
map(word_infallible(""), |(bound, err)| {
(
(
UserInputBound::Unbounded,
@@ -564,7 +557,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
),
(
value((), tag(">")),
map(word_infallible("", false), |(bound, err)| {
map(word_infallible(""), |(bound, err)| {
(
(
bound
@@ -578,7 +571,7 @@ fn range_infallible(inp: &str) -> JResult<&str, UserInputLeaf> {
),
(
value((), tag("<")),
map(word_infallible("", false), |(bound, err)| {
map(word_infallible(""), |(bound, err)| {
(
(
UserInputBound::Unbounded,
@@ -1205,12 +1198,6 @@ mod test {
test_parse_query_to_ast_helper("weight: <= 70", "\"weight\":{\"*\" TO \"70\"]");
test_parse_query_to_ast_helper("weight: <= 70.5", "\"weight\":{\"*\" TO \"70.5\"]");
test_parse_query_to_ast_helper(">a", "{\"a\" TO \"*\"}");
test_parse_query_to_ast_helper(">=a", "[\"a\" TO \"*\"}");
test_parse_query_to_ast_helper("<a", "{\"*\" TO \"a\"}");
test_parse_query_to_ast_helper("<=a", "{\"*\" TO \"a\"]");
test_parse_query_to_ast_helper("<=bsd", "{\"*\" TO \"bsd\"]");
}
#[test]
@@ -1481,18 +1468,8 @@ mod test {
#[test]
fn test_parse_query_term_group() {
test_parse_query_to_ast_helper(r#"field:(abc)"#, r#""field":abc"#);
test_parse_query_to_ast_helper(r#"field:(abc)"#, r#"(*"field":abc)"#);
test_parse_query_to_ast_helper(r#"field:(+a -"b c")"#, r#"(+"field":a -"field":"b c")"#);
test_parse_query_to_ast_helper(r#"field:(a AND "b c")"#, r#"(+"field":a +"field":"b c")"#);
test_parse_query_to_ast_helper(r#"field:(a OR "b c")"#, r#"(?"field":a ?"field":"b c")"#);
test_parse_query_to_ast_helper(
r#"field:(a OR (b AND c))"#,
r#"(?"field":a ?(+"field":b +"field":c))"#,
);
test_parse_query_to_ast_helper(
r#"field:(a [b TO c])"#,
r#"(*"field":a *"field":["b" TO "c"])"#,
);
test_is_parse_err(r#"field:(+a -"b c""#, r#"(+"field":a -"field":"b c")"#);
}
@@ -1644,21 +1621,5 @@ mod test {
r#"myfield:'hello\"happy\'tax'"#,
r#""myfield":'hello"happy'tax'"#,
);
// we don't process escape sequence for chars which don't require it
test_parse_query_to_ast_helper(r#"abc\*"#, r#"abc\*"#);
}
#[test]
fn test_queries_with_colons() {
test_parse_query_to_ast_helper(r#""abc:def""#, r#""abc:def""#);
test_parse_query_to_ast_helper(r#"'abc:def'"#, r#"'abc:def'"#);
test_parse_query_to_ast_helper(r#"abc\:def"#, r#"abc:def"#);
test_parse_query_to_ast_helper(r#""abc\:def""#, r#""abc:def""#);
test_parse_query_to_ast_helper(r#"'abc\:def'"#, r#"'abc:def'"#);
}
#[test]
fn test_invalid_field() {
test_is_parse_err(r#"!bc:def"#, "!bc:def");
}
}

View File

@@ -44,26 +44,6 @@ impl UserInputLeaf {
},
}
}
pub(crate) fn set_default_field(&mut self, default_field: String) {
match self {
UserInputLeaf::Literal(ref mut literal) if literal.field_name.is_none() => {
literal.field_name = Some(default_field)
}
UserInputLeaf::All => {
*self = UserInputLeaf::Exists {
field: default_field,
}
}
UserInputLeaf::Range { ref mut field, .. } if field.is_none() => {
*field = Some(default_field)
}
UserInputLeaf::Set { ref mut field, .. } if field.is_none() => {
*field = Some(default_field)
}
_ => (), // field was already set, do nothing
}
}
}
impl Debug for UserInputLeaf {
@@ -225,16 +205,6 @@ impl UserInputAst {
pub fn or(asts: Vec<UserInputAst>) -> UserInputAst {
UserInputAst::compose(Occur::Should, asts)
}
pub(crate) fn set_default_field(&mut self, field: String) {
match self {
UserInputAst::Clause(clauses) => clauses
.iter_mut()
.for_each(|(_, ast)| ast.set_default_field(field.clone())),
UserInputAst::Leaf(leaf) => leaf.set_default_field(field),
UserInputAst::Boost(ref mut ast, _) => ast.set_default_field(field),
}
}
}
impl From<UserInputLiteral> for UserInputLeaf {

View File

@@ -0,0 +1,585 @@
#[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 = ["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_top_hits_agg);
fn bench_aggregation_terms_many_with_top_hits_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": {
"top_hits": { "top_hits":
{
"sort": [
{ "score": "desc" }
],
"size": 2,
"doc_value_fields": ["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_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()
});
}
}

View File

@@ -81,11 +81,10 @@ impl AggregationLimits {
}
}
pub(crate) fn add_memory_consumed(&self, add_num_bytes: u64) -> crate::Result<()> {
let prev_value = self
.memory_consumption
.fetch_add(add_num_bytes, Ordering::Relaxed);
validate_memory_consumption(prev_value + add_num_bytes, self.memory_limit)?;
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(())
}
@@ -95,11 +94,11 @@ impl AggregationLimits {
}
fn validate_memory_consumption(
memory_consumption: u64,
memory_consumption: &AtomicU64,
memory_limit: ByteCount,
) -> Result<(), AggregationError> {
// Load the estimated memory consumed by the aggregations
let memory_consumed: ByteCount = memory_consumption.into();
let memory_consumed: ByteCount = memory_consumption.load(Ordering::Relaxed).into();
if memory_consumed > memory_limit {
return Err(AggregationError::MemoryExceeded {
limit: memory_limit,
@@ -119,11 +118,10 @@ pub struct ResourceLimitGuard {
}
impl ResourceLimitGuard {
pub(crate) fn add_memory_consumed(&self, add_num_bytes: u64) -> crate::Result<()> {
let prev_value = self
.memory_consumption
.fetch_add(add_num_bytes, Ordering::Relaxed);
validate_memory_consumption(prev_value + add_num_bytes, self.memory_limit)?;
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(())
}
}

View File

@@ -34,7 +34,7 @@ use super::bucket::{
DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
};
use super::metric::{
AverageAggregation, CountAggregation, ExtendedStatsAggregation, MaxAggregation, MinAggregation,
AverageAggregation, CountAggregation, MaxAggregation, MinAggregation,
PercentilesAggregationReq, StatsAggregation, SumAggregation, TopHitsAggregation,
};
@@ -146,11 +146,6 @@ pub enum AggregationVariants {
/// extracted values.
#[serde(rename = "stats")]
Stats(StatsAggregation),
/// Computes a collection of estended statistics (`min`, `max`, `sum`, `count`, `avg`,
/// `sum_of_squares`, `variance`, `variance_sampling`, `std_deviation`,
/// `std_deviation_sampling`) over the extracted values.
#[serde(rename = "extended_stats")]
ExtendedStats(ExtendedStatsAggregation),
/// Computes the sum of the extracted values.
#[serde(rename = "sum")]
Sum(SumAggregation),
@@ -175,7 +170,6 @@ impl AggregationVariants {
AggregationVariants::Max(max) => vec![max.field_name()],
AggregationVariants::Min(min) => vec![min.field_name()],
AggregationVariants::Stats(stats) => vec![stats.field_name()],
AggregationVariants::ExtendedStats(extended_stats) => vec![extended_stats.field_name()],
AggregationVariants::Sum(sum) => vec![sum.field_name()],
AggregationVariants::Percentiles(per) => vec![per.field_name()],
AggregationVariants::TopHits(top_hits) => top_hits.field_names(),
@@ -203,12 +197,6 @@ impl AggregationVariants {
_ => None,
}
}
pub(crate) fn as_top_hits(&self) -> Option<&TopHitsAggregation> {
match &self {
AggregationVariants::TopHits(top_hits) => Some(top_hits),
_ => None,
}
}
pub(crate) fn as_percentile(&self) -> Option<&PercentilesAggregationReq> {
match &self {

View File

@@ -11,14 +11,13 @@ use super::bucket::{
DateHistogramAggregationReq, HistogramAggregation, RangeAggregation, TermsAggregation,
};
use super::metric::{
AverageAggregation, CountAggregation, ExtendedStatsAggregation, MaxAggregation, MinAggregation,
StatsAggregation, SumAggregation,
AverageAggregation, CountAggregation, MaxAggregation, MinAggregation, StatsAggregation,
SumAggregation,
};
use super::segment_agg_result::AggregationLimits;
use super::VecWithNames;
use crate::aggregation::{f64_to_fastfield_u64, Key};
use crate::index::SegmentReader;
use crate::SegmentOrdinal;
use crate::{SegmentOrdinal, SegmentReader};
#[derive(Default)]
pub(crate) struct AggregationsWithAccessor {
@@ -171,8 +170,8 @@ impl AggregationWithAccessor {
ColumnType::Str,
ColumnType::DateTime,
ColumnType::Bool,
ColumnType::IpAddr,
// ColumnType::Bytes Unsupported
// ColumnType::IpAddr Unsupported
];
// In case the column is empty we want the shim column to match the missing type
@@ -276,10 +275,6 @@ impl AggregationWithAccessor {
field: ref field_name,
..
})
| ExtendedStats(ExtendedStatsAggregation {
field: ref field_name,
..
})
| Sum(SumAggregation {
field: ref field_name,
..
@@ -297,7 +292,7 @@ impl AggregationWithAccessor {
add_agg_with_accessor(&agg, accessor, column_type, &mut res)?;
}
TopHits(ref mut top_hits) => {
top_hits.validate_and_resolve_field_names(reader.fast_fields().columnar())?;
top_hits.validate_and_resolve(reader.fast_fields().columnar())?;
let accessors: Vec<(Column<u64>, ColumnType)> = top_hits
.field_names()
.iter()
@@ -339,8 +334,8 @@ fn get_missing_val(
}
_ => {
return Err(crate::TantivyError::InvalidArgument(format!(
"Missing value {missing:?} for field {field_name} is not supported for column \
type {column_type:?}"
"Missing value {:?} for field {} is not supported for column type {:?}",
missing, field_name, column_type
)));
}
};
@@ -407,7 +402,7 @@ fn get_dynamic_columns(
.iter()
.map(|h| h.open())
.collect::<io::Result<_>>()?;
assert!(!ff_fields.is_empty(), "field {field_name} not found");
assert!(!ff_fields.is_empty(), "field {} not found", field_name);
Ok(cols)
}

View File

@@ -8,9 +8,7 @@ use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use super::bucket::GetDocCount;
use super::metric::{
ExtendedStats, PercentilesMetricResult, SingleMetricResult, Stats, TopHitsMetricResult,
};
use super::metric::{PercentilesMetricResult, SingleMetricResult, Stats, TopHitsMetricResult};
use super::{AggregationError, Key};
use crate::TantivyError;
@@ -90,8 +88,6 @@ pub enum MetricResult {
Min(SingleMetricResult),
/// Stats metric result.
Stats(Stats),
/// ExtendedStats metric result.
ExtendedStats(Box<ExtendedStats>),
/// Sum metric result.
Sum(SingleMetricResult),
/// Percentiles metric result.
@@ -108,7 +104,6 @@ impl MetricResult {
MetricResult::Max(max) => Ok(max.value),
MetricResult::Min(min) => Ok(min.value),
MetricResult::Stats(stats) => stats.get_value(agg_property),
MetricResult::ExtendedStats(extended_stats) => extended_stats.get_value(agg_property),
MetricResult::Sum(sum) => Ok(sum.value),
MetricResult::Percentiles(_) => Err(TantivyError::AggregationError(
AggregationError::InvalidRequest("percentiles can't be used to order".to_string()),

View File

@@ -4,7 +4,6 @@ use crate::aggregation::agg_req::{Aggregation, Aggregations};
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::buf_collector::DOC_BLOCK_SIZE;
use crate::aggregation::collector::AggregationCollector;
use crate::aggregation::intermediate_agg_result::IntermediateAggregationResults;
use crate::aggregation::segment_agg_result::AggregationLimits;
use crate::aggregation::tests::{get_test_index_2_segments, get_test_index_from_values_and_terms};
use crate::aggregation::DistributedAggregationCollector;
@@ -67,22 +66,6 @@ fn test_aggregation_flushing(
}
}
},
"top_hits_test":{
"terms": {
"field": "string_id"
},
"aggs": {
"bucketsL2": {
"top_hits": {
"size": 2,
"sort": [
{ "score": "asc" }
],
"docvalue_fields": ["score"]
}
}
}
},
"histogram_test":{
"histogram": {
"field": "score",
@@ -125,16 +108,6 @@ fn test_aggregation_flushing(
let searcher = reader.searcher();
let intermediate_agg_result = searcher.search(&AllQuery, &collector).unwrap();
// Test postcard roundtrip serialization
let intermediate_agg_result_bytes = postcard::to_allocvec(&intermediate_agg_result).expect(
"Postcard Serialization failed, flatten etc. is not supported in the intermediate \
result",
);
let intermediate_agg_result: IntermediateAggregationResults =
postcard::from_bytes(&intermediate_agg_result_bytes)
.expect("Post deserialization failed");
intermediate_agg_result
.into_final_result(agg_req, &Default::default())
.unwrap()
@@ -843,38 +816,38 @@ fn test_aggregation_on_json_object_mixed_types() {
let mut index_writer: IndexWriter = index.writer_for_tests().unwrap();
// => Segment with all values numeric
index_writer
.add_document(doc!(json => json!({"mixed_type": 10.0, "mixed_price": 10.0})))
.add_document(doc!(json => json!({"mixed_type": 10.0})))
.unwrap();
index_writer.commit().unwrap();
// => Segment with all values text
index_writer
.add_document(doc!(json => json!({"mixed_type": "blue", "mixed_price": 5.0})))
.add_document(doc!(json => json!({"mixed_type": "blue"})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": "blue", "mixed_price": 5.0})))
.add_document(doc!(json => json!({"mixed_type": "blue"})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": "blue", "mixed_price": 5.0})))
.add_document(doc!(json => json!({"mixed_type": "blue"})))
.unwrap();
index_writer.commit().unwrap();
// => Segment with all boolen
index_writer
.add_document(doc!(json => json!({"mixed_type": true, "mixed_price": "no_price"})))
.add_document(doc!(json => json!({"mixed_type": true})))
.unwrap();
index_writer.commit().unwrap();
// => Segment with mixed values
index_writer
.add_document(doc!(json => json!({"mixed_type": "red", "mixed_price": 1.0})))
.add_document(doc!(json => json!({"mixed_type": "red"})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": "red", "mixed_price": 1.0})))
.add_document(doc!(json => json!({"mixed_type": "red"})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": -20.5, "mixed_price": -20.5})))
.add_document(doc!(json => json!({"mixed_type": -20.5})))
.unwrap();
index_writer
.add_document(doc!(json => json!({"mixed_type": true, "mixed_price": "no_price"})))
.add_document(doc!(json => json!({"mixed_type": true})))
.unwrap();
index_writer.commit().unwrap();
@@ -888,7 +861,7 @@ fn test_aggregation_on_json_object_mixed_types() {
"order": { "min_price": "desc" }
},
"aggs": {
"min_price": { "min": { "field": "json.mixed_price" } }
"min_price": { "min": { "field": "json.mixed_type" } }
}
},
"rangeagg": {
@@ -912,6 +885,7 @@ fn test_aggregation_on_json_object_mixed_types() {
let aggregation_results = searcher.search(&AllQuery, &aggregation_collector).unwrap();
let aggregation_res_json = serde_json::to_value(aggregation_results).unwrap();
// pretty print as json
use pretty_assertions::assert_eq;
assert_eq!(
&aggregation_res_json,
@@ -927,10 +901,10 @@ fn test_aggregation_on_json_object_mixed_types() {
"termagg": {
"buckets": [
{ "doc_count": 1, "key": 10.0, "min_price": { "value": 10.0 } },
{ "doc_count": 3, "key": "blue", "min_price": { "value": 5.0 } },
{ "doc_count": 2, "key": "red", "min_price": { "value": 1.0 } },
{ "doc_count": 1, "key": -20.5, "min_price": { "value": -20.5 } },
{ "doc_count": 2, "key": "red", "min_price": { "value": null } },
{ "doc_count": 2, "key": 1.0, "key_as_string": "true", "min_price": { "value": null } },
{ "doc_count": 3, "key": "blue", "min_price": { "value": null } },
],
"sum_other_doc_count": 0
}

View File

@@ -1,5 +1,8 @@
use std::cmp::Ordering;
use std::fmt::Display;
use columnar::ColumnType;
use itertools::Itertools;
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
use tantivy_bitpacker::minmax;
@@ -15,7 +18,7 @@ use crate::aggregation::intermediate_agg_result::{
IntermediateHistogramBucketEntry,
};
use crate::aggregation::segment_agg_result::{
build_segment_agg_collector, SegmentAggregationCollector,
build_segment_agg_collector, AggregationLimits, SegmentAggregationCollector,
};
use crate::aggregation::*;
use crate::TantivyError;
@@ -307,10 +310,7 @@ impl SegmentAggregationCollector for SegmentHistogramCollector {
.column_block_accessor
.fetch_block(docs, &bucket_agg_accessor.accessor);
for (doc, val) in bucket_agg_accessor
.column_block_accessor
.iter_docid_vals(docs, &bucket_agg_accessor.accessor)
{
for (doc, val) in bucket_agg_accessor.column_block_accessor.iter_docid_vals() {
let val = self.f64_from_fastfield_u64(val);
let bucket_pos = get_bucket_pos(val);
@@ -331,11 +331,9 @@ impl SegmentAggregationCollector for SegmentHistogramCollector {
}
let mem_delta = self.get_memory_consumption() - mem_pre;
if mem_delta > 0 {
bucket_agg_accessor
.limits
.add_memory_consumed(mem_delta as u64)?;
}
bucket_agg_accessor
.limits
.add_memory_consumed(mem_delta as u64)?;
Ok(())
}
@@ -599,11 +597,13 @@ mod tests {
use serde_json::Value;
use super::*;
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::tests::{
exec_request, exec_request_with_query, exec_request_with_query_and_memory_limit,
get_test_index_2_segments, get_test_index_from_values, get_test_index_with_num_docs,
};
use crate::aggregation::AggregationCollector;
use crate::query::AllQuery;
#[test]

View File

@@ -28,7 +28,6 @@ mod term_agg;
mod term_missing_agg;
use std::collections::HashMap;
use std::fmt;
pub use histogram::*;
pub use range::*;
@@ -73,12 +72,12 @@ impl From<&str> for OrderTarget {
}
}
impl fmt::Display for OrderTarget {
fn fmt(&self, f: &mut fmt::Formatter) -> fmt::Result {
impl ToString for OrderTarget {
fn to_string(&self) -> String {
match self {
OrderTarget::Key => f.write_str("_key"),
OrderTarget::Count => f.write_str("_count"),
OrderTarget::SubAggregation(agg) => agg.fmt(f),
OrderTarget::Key => "_key".to_string(),
OrderTarget::Count => "_count".to_string(),
OrderTarget::SubAggregation(agg) => agg.to_string(),
}
}
}

View File

@@ -1,6 +1,7 @@
use std::fmt::Debug;
use std::ops::Range;
use columnar::{ColumnType, MonotonicallyMappableToU64};
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
@@ -235,10 +236,7 @@ impl SegmentAggregationCollector for SegmentRangeCollector {
.column_block_accessor
.fetch_block(docs, &bucket_agg_accessor.accessor);
for (doc, val) in bucket_agg_accessor
.column_block_accessor
.iter_docid_vals(docs, &bucket_agg_accessor.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];
@@ -449,6 +447,7 @@ pub(crate) fn range_to_key(range: &Range<u64>, field_type: &ColumnType) -> crate
#[cfg(test)]
mod tests {
use columnar::MonotonicallyMappableToU64;
use serde_json::Value;
use super::*;
@@ -457,6 +456,7 @@ mod 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>,

View File

@@ -1,10 +1,6 @@
use std::fmt::Debug;
use std::net::Ipv6Addr;
use columnar::column_values::CompactSpaceU64Accessor;
use columnar::{
BytesColumn, ColumnType, MonotonicallyMappableToU128, MonotonicallyMappableToU64, StrColumn,
};
use columnar::{BytesColumn, ColumnType, MonotonicallyMappableToU64, StrColumn};
use rustc_hash::FxHashMap;
use serde::{Deserialize, Serialize};
@@ -109,9 +105,9 @@ pub struct TermsAggregation {
///
/// Defaults to 10 * size.
#[serde(skip_serializing_if = "Option::is_none", default)]
#[serde(alias = "shard_size")]
#[serde(alias = "segment_size")]
#[serde(alias = "split_size")]
pub segment_size: Option<u32>,
pub shard_size: Option<u32>,
/// If you set the `show_term_doc_count_error` parameter to true, the terms aggregation will
/// include doc_count_error_upper_bound, which is an upper bound to the error on the
@@ -200,7 +196,7 @@ impl TermsAggregationInternal {
pub(crate) fn from_req(req: &TermsAggregation) -> Self {
let size = req.size.unwrap_or(10);
let mut segment_size = req.segment_size.unwrap_or(size * 10);
let mut segment_size = req.shard_size.unwrap_or(size * 10);
let order = req.order.clone().unwrap_or_default();
segment_size = segment_size.max(size);
@@ -310,10 +306,7 @@ impl SegmentAggregationCollector for SegmentTermCollector {
}
// has subagg
if let Some(blueprint) = self.blueprint.as_ref() {
for (doc, term_id) in bucket_agg_accessor
.column_block_accessor
.iter_docid_vals(docs, &bucket_agg_accessor.accessor)
{
for (doc, term_id) in bucket_agg_accessor.column_block_accessor.iter_docid_vals() {
let sub_aggregations = self
.term_buckets
.sub_aggs
@@ -324,11 +317,9 @@ impl SegmentAggregationCollector for SegmentTermCollector {
}
let mem_delta = self.get_memory_consumption() - mem_pre;
if mem_delta > 0 {
bucket_agg_accessor
.limits
.add_memory_consumed(mem_delta as u64)?;
}
bucket_agg_accessor
.limits
.add_memory_consumed(mem_delta as u64)?;
Ok(())
}
@@ -357,7 +348,8 @@ impl SegmentTermCollector {
) -> crate::Result<Self> {
if field_type == ColumnType::Bytes {
return Err(TantivyError::InvalidArgument(format!(
"terms aggregation is not supported for column type {field_type:?}"
"terms aggregation is not supported for column type {:?}",
field_type
)));
}
let term_buckets = TermBuckets::default();
@@ -543,27 +535,6 @@ impl SegmentTermCollector {
let val = bool::from_u64(val);
dict.insert(IntermediateKey::Bool(val), intermediate_entry);
}
} else if self.column_type == ColumnType::IpAddr {
let compact_space_accessor = agg_with_accessor
.accessor
.values
.clone()
.downcast_arc::<CompactSpaceU64Accessor>()
.map_err(|_| {
TantivyError::AggregationError(
crate::aggregation::AggregationError::InternalError(
"Type mismatch: Could not downcast to CompactSpaceU64Accessor"
.to_string(),
),
)
})?;
for (val, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(val, doc_count)?;
let val: u128 = compact_space_accessor.compact_to_u128(val as u32);
let val = Ipv6Addr::from_u128(val);
dict.insert(IntermediateKey::IpAddr(val), intermediate_entry);
}
} else {
for (val, doc_count) in entries {
let intermediate_entry = into_intermediate_bucket_entry(val, doc_count)?;
@@ -616,9 +587,6 @@ pub(crate) fn cut_off_buckets<T: GetDocCount + Debug>(
#[cfg(test)]
mod tests {
use std::net::IpAddr;
use std::str::FromStr;
use common::DateTime;
use time::{Date, Month};
@@ -629,7 +597,7 @@ mod tests {
};
use crate::aggregation::AggregationLimits;
use crate::indexer::NoMergePolicy;
use crate::schema::{IntoIpv6Addr, Schema, FAST, STRING};
use crate::schema::{Schema, FAST, STRING};
use crate::{Index, IndexWriter};
#[test]
@@ -1211,9 +1179,9 @@ mod tests {
assert_eq!(res["my_texts"]["buckets"][0]["key"], "terma");
assert_eq!(res["my_texts"]["buckets"][0]["doc_count"], 4);
assert_eq!(res["my_texts"]["buckets"][1]["key"], "termb");
assert_eq!(res["my_texts"]["buckets"][1]["key"], "termc");
assert_eq!(res["my_texts"]["buckets"][1]["doc_count"], 0);
assert_eq!(res["my_texts"]["buckets"][2]["key"], "termc");
assert_eq!(res["my_texts"]["buckets"][2]["key"], "termb");
assert_eq!(res["my_texts"]["buckets"][2]["doc_count"], 0);
assert_eq!(res["my_texts"]["sum_other_doc_count"], 0);
assert_eq!(res["my_texts"]["doc_count_error_upper_bound"], 0);
@@ -1959,44 +1927,4 @@ mod tests {
Ok(())
}
#[test]
fn terms_aggregation_ip_addr() -> crate::Result<()> {
let mut schema_builder = Schema::builder();
let field = schema_builder.add_ip_addr_field("ip_field", FAST);
let schema = schema_builder.build();
let index = Index::create_in_ram(schema);
{
let mut writer = index.writer_with_num_threads(1, 15_000_000)?;
// IpV6 loopback
writer.add_document(doc!(field=>IpAddr::from_str("::1").unwrap().into_ipv6_addr()))?;
writer.add_document(doc!(field=>IpAddr::from_str("::1").unwrap().into_ipv6_addr()))?;
// IpV4
writer.add_document(
doc!(field=>IpAddr::from_str("127.0.0.1").unwrap().into_ipv6_addr()),
)?;
writer.commit()?;
}
let agg_req: Aggregations = serde_json::from_value(json!({
"my_bool": {
"terms": {
"field": "ip_field"
},
}
}))
.unwrap();
let res = exec_request_with_query(agg_req, &index, None)?;
// print as json
// println!("{}", serde_json::to_string_pretty(&res).unwrap());
assert_eq!(res["my_bool"]["buckets"][0]["key"], "::1");
assert_eq!(res["my_bool"]["buckets"][0]["doc_count"], 2);
assert_eq!(res["my_bool"]["buckets"][1]["key"], "127.0.0.1");
assert_eq!(res["my_bool"]["buckets"][1]["doc_count"], 1);
assert_eq!(res["my_bool"]["buckets"][2]["key"], serde_json::Value::Null);
Ok(())
}
}

View File

@@ -8,8 +8,7 @@ use super::segment_agg_result::{
};
use crate::aggregation::agg_req_with_accessor::get_aggs_with_segment_accessor_and_validate;
use crate::collector::{Collector, SegmentCollector};
use crate::index::SegmentReader;
use crate::{DocId, SegmentOrdinal, TantivyError};
use crate::{DocId, SegmentOrdinal, SegmentReader, TantivyError};
/// The default max bucket count, before the aggregation fails.
pub const DEFAULT_BUCKET_LIMIT: u32 = 65000;

View File

@@ -5,7 +5,6 @@
use std::cmp::Ordering;
use std::collections::hash_map::Entry;
use std::hash::Hash;
use std::net::Ipv6Addr;
use columnar::ColumnType;
use itertools::Itertools;
@@ -19,8 +18,8 @@ use super::bucket::{
GetDocCount, Order, OrderTarget, RangeAggregation, TermsAggregation,
};
use super::metric::{
IntermediateAverage, IntermediateCount, IntermediateExtendedStats, IntermediateMax,
IntermediateMin, IntermediateStats, IntermediateSum, PercentilesCollector, TopHitsTopNComputer,
IntermediateAverage, IntermediateCount, IntermediateMax, IntermediateMin, IntermediateStats,
IntermediateSum, PercentilesCollector, TopHitsCollector,
};
use super::segment_agg_result::AggregationLimits;
use super::{format_date, AggregationError, Key, SerializedKey};
@@ -42,8 +41,6 @@ pub struct IntermediateAggregationResults {
/// This might seem redundant with `Key`, but the point is to have a different
/// Serialize implementation.
pub enum IntermediateKey {
/// Ip Addr key
IpAddr(Ipv6Addr),
/// Bool key
Bool(bool),
/// String key
@@ -63,14 +60,6 @@ impl From<IntermediateKey> for Key {
fn from(value: IntermediateKey) -> Self {
match value {
IntermediateKey::Str(s) => Self::Str(s),
IntermediateKey::IpAddr(s) => {
// Prefer to use the IPv4 representation if possible
if let Some(ip) = s.to_ipv4_mapped() {
Self::Str(ip.to_string())
} else {
Self::Str(s.to_string())
}
}
IntermediateKey::F64(f) => Self::F64(f),
IntermediateKey::Bool(f) => Self::F64(f as u64 as f64),
}
@@ -86,7 +75,6 @@ impl std::hash::Hash for IntermediateKey {
IntermediateKey::Str(text) => text.hash(state),
IntermediateKey::F64(val) => val.to_bits().hash(state),
IntermediateKey::Bool(val) => val.hash(state),
IntermediateKey::IpAddr(val) => val.hash(state),
}
}
}
@@ -215,18 +203,15 @@ pub(crate) fn empty_from_req(req: &Aggregation) -> IntermediateAggregationResult
Stats(_) => IntermediateAggregationResult::Metric(IntermediateMetricResult::Stats(
IntermediateStats::default(),
)),
ExtendedStats(_) => IntermediateAggregationResult::Metric(
IntermediateMetricResult::ExtendedStats(IntermediateExtendedStats::default()),
),
Sum(_) => IntermediateAggregationResult::Metric(IntermediateMetricResult::Sum(
IntermediateSum::default(),
)),
Percentiles(_) => IntermediateAggregationResult::Metric(
IntermediateMetricResult::Percentiles(PercentilesCollector::default()),
),
TopHits(ref req) => IntermediateAggregationResult::Metric(
IntermediateMetricResult::TopHits(TopHitsTopNComputer::new(req)),
),
TopHits(_) => IntermediateAggregationResult::Metric(IntermediateMetricResult::TopHits(
TopHitsCollector::default(),
)),
}
}
@@ -285,12 +270,10 @@ pub enum IntermediateMetricResult {
Min(IntermediateMin),
/// Intermediate stats result.
Stats(IntermediateStats),
/// Intermediate stats result.
ExtendedStats(IntermediateExtendedStats),
/// Intermediate sum result.
Sum(IntermediateSum),
/// Intermediate top_hits result
TopHits(TopHitsTopNComputer),
TopHits(TopHitsCollector),
}
impl IntermediateMetricResult {
@@ -311,9 +294,6 @@ impl IntermediateMetricResult {
IntermediateMetricResult::Stats(intermediate_stats) => {
MetricResult::Stats(intermediate_stats.finalize())
}
IntermediateMetricResult::ExtendedStats(intermediate_stats) => {
MetricResult::ExtendedStats(intermediate_stats.finalize())
}
IntermediateMetricResult::Sum(intermediate_sum) => {
MetricResult::Sum(intermediate_sum.finalize().into())
}
@@ -322,7 +302,7 @@ impl IntermediateMetricResult {
.into_final_result(req.agg.as_percentile().expect("unexpected metric type")),
),
IntermediateMetricResult::TopHits(top_hits) => {
MetricResult::TopHits(top_hits.into_final_result())
MetricResult::TopHits(top_hits.finalize())
}
}
}
@@ -354,12 +334,6 @@ impl IntermediateMetricResult {
) => {
stats_left.merge_fruits(stats_right);
}
(
IntermediateMetricResult::ExtendedStats(extended_stats_left),
IntermediateMetricResult::ExtendedStats(extended_stats_right),
) => {
extended_stats_left.merge_fruits(extended_stats_right);
}
(IntermediateMetricResult::Sum(sum_left), IntermediateMetricResult::Sum(sum_right)) => {
sum_left.merge_fruits(sum_right);
}

File diff suppressed because it is too large Load Diff

View File

@@ -18,7 +18,6 @@
mod average;
mod count;
mod extended_stats;
mod max;
mod min;
mod percentiles;
@@ -26,11 +25,8 @@ mod stats;
mod sum;
mod top_hits;
use std::collections::HashMap;
pub use average::*;
pub use count::*;
pub use extended_stats::*;
pub use max::*;
pub use min::*;
pub use percentiles::*;
@@ -40,8 +36,6 @@ pub use stats::*;
pub use sum::*;
pub use top_hits::*;
use crate::schema::OwnedValue;
/// Single-metric aggregations use this common result structure.
///
/// Main reason to wrap it in value is to match elasticsearch output structure.
@@ -98,9 +92,8 @@ pub struct TopHitsVecEntry {
/// Search results, for queries that include field retrieval requests
/// (`docvalue_fields`).
#[serde(rename = "docvalue_fields")]
#[serde(skip_serializing_if = "HashMap::is_empty")]
pub doc_value_fields: HashMap<String, OwnedValue>,
#[serde(flatten)]
pub search_results: FieldRetrivalResult,
}
/// The top_hits metric aggregation results a list of top hits by sort criteria.

View File

@@ -1,5 +1,6 @@
use std::fmt::Debug;
use columnar::ColumnType;
use serde::{Deserialize, Serialize};
use super::*;

View File

@@ -1,5 +1,4 @@
use std::fmt::Debug;
use columnar::ColumnType;
use serde::{Deserialize, Serialize};
use super::*;
@@ -87,15 +86,13 @@ impl Stats {
#[derive(Clone, Debug, PartialEq, Serialize, Deserialize)]
pub struct IntermediateStats {
/// The number of extracted values.
pub(crate) count: u64,
count: u64,
/// The sum of the extracted values.
pub(crate) sum: f64,
/// delta for sum needed for [Kahan algorithm for summation](https://en.wikipedia.org/wiki/Kahan_summation_algorithm)
pub(crate) delta: f64,
sum: f64,
/// The min value.
pub(crate) min: f64,
min: f64,
/// The max value.
pub(crate) max: f64,
max: f64,
}
impl Default for IntermediateStats {
@@ -103,7 +100,6 @@ impl Default for IntermediateStats {
Self {
count: 0,
sum: 0.0,
delta: 0.0,
min: f64::MAX,
max: f64::MIN,
}
@@ -114,13 +110,7 @@ impl IntermediateStats {
/// Merges the other stats intermediate result into self.
pub fn merge_fruits(&mut self, other: IntermediateStats) {
self.count += other.count;
// kahan algorithm for sum
let y = other.sum - (self.delta + other.delta);
let t = self.sum + y;
self.delta = (t - self.sum) - y;
self.sum = t;
self.sum += other.sum;
self.min = self.min.min(other.min);
self.max = self.max.max(other.max);
}
@@ -152,15 +142,9 @@ impl IntermediateStats {
}
#[inline]
pub(in crate::aggregation::metric) fn collect(&mut self, value: f64) {
fn collect(&mut self, value: f64) {
self.count += 1;
// kahan algorithm for sum
let y = value - self.delta;
let t = self.sum + y;
self.delta = (t - self.sum) - y;
self.sum = t;
self.sum += value;
self.min = self.min.min(value);
self.max = self.max.max(value);
}
@@ -305,6 +289,7 @@ impl SegmentAggregationCollector for SegmentStatsCollector {
#[cfg(test)]
mod tests {
use serde_json::Value;
use crate::aggregation::agg_req::{Aggregation, Aggregations};

View File

@@ -1,9 +1,7 @@
use std::collections::HashMap;
use std::net::Ipv6Addr;
use std::fmt::Formatter;
use columnar::{Column, ColumnType, ColumnarReader, DynamicColumn};
use common::json_path_writer::JSON_PATH_SEGMENT_SEP_STR;
use common::DateTime;
use columnar::{ColumnarReader, DynamicColumn};
use regex::Regex;
use serde::ser::SerializeMap;
use serde::{Deserialize, Deserializer, Serialize, Serializer};
@@ -14,8 +12,8 @@ use crate::aggregation::intermediate_agg_result::{
IntermediateAggregationResult, IntermediateMetricResult,
};
use crate::aggregation::segment_agg_result::SegmentAggregationCollector;
use crate::aggregation::AggregationError;
use crate::collector::TopNComputer;
use crate::schema::term::JSON_PATH_SEGMENT_SEP_STR;
use crate::schema::OwnedValue;
use crate::{DocAddress, DocId, SegmentOrdinal};
@@ -94,101 +92,53 @@ pub struct TopHitsAggregation {
size: usize,
from: Option<usize>,
#[serde(flatten)]
retrieval: RetrievalFields,
}
const fn default_doc_value_fields() -> Vec<String> {
Vec::new()
}
/// Search query spec for each matched document
/// TODO: move this to a common module
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Default)]
pub struct RetrievalFields {
/// The fast fields to return for each hit.
/// This is the only variant supported for now.
/// TODO: support the {field, format} variant for custom formatting.
#[serde(rename = "docvalue_fields")]
#[serde(default)]
doc_value_fields: Vec<String>,
// Not supported
_source: Option<serde_json::Value>,
fields: Option<serde_json::Value>,
script_fields: Option<serde_json::Value>,
highlight: Option<serde_json::Value>,
explain: Option<serde_json::Value>,
version: Option<serde_json::Value>,
#[serde(default = "default_doc_value_fields")]
pub doc_value_fields: Vec<String>,
}
#[derive(Debug, Clone, PartialEq, Default)]
struct KeyOrder {
field: String,
order: Order,
/// Search query result for each matched document
/// TODO: move this to a common module
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize, Default)]
pub struct FieldRetrivalResult {
/// The fast fields returned for each hit.
#[serde(rename = "docvalue_fields")]
#[serde(skip_serializing_if = "HashMap::is_empty")]
pub doc_value_fields: HashMap<String, OwnedValue>,
}
impl Serialize for KeyOrder {
fn serialize<S: Serializer>(&self, serializer: S) -> Result<S::Ok, S::Error> {
let KeyOrder { field, order } = self;
let mut map = serializer.serialize_map(Some(1))?;
map.serialize_entry(field, order)?;
map.end()
impl RetrievalFields {
fn get_field_names(&self) -> Vec<&str> {
self.doc_value_fields.iter().map(|s| s.as_str()).collect()
}
}
impl<'de> Deserialize<'de> for KeyOrder {
fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
where D: Deserializer<'de> {
let mut key_order = <HashMap<String, Order>>::deserialize(deserializer)?.into_iter();
let (field, order) = key_order.next().ok_or(serde::de::Error::custom(
"Expected exactly one key-value pair in sort parameter of top_hits, found none",
))?;
if key_order.next().is_some() {
return Err(serde::de::Error::custom(format!(
"Expected exactly one key-value pair in sort parameter of top_hits, found \
{key_order:?}"
)));
}
Ok(Self { field, order })
}
}
// Tranform a glob (`pattern*`, for example) into a regex::Regex (`^pattern.*$`)
fn globbed_string_to_regex(glob: &str) -> Result<Regex, crate::TantivyError> {
// Replace `*` glob with `.*` regex
let sanitized = format!("^{}$", regex::escape(glob).replace(r"\*", ".*"));
Regex::new(&sanitized.replace('*', ".*")).map_err(|e| {
crate::TantivyError::SchemaError(format!("Invalid regex '{glob}' in docvalue_fields: {e}"))
})
}
fn use_doc_value_fields_err(parameter: &str) -> crate::Result<()> {
Err(crate::TantivyError::AggregationError(
AggregationError::InvalidRequest(format!(
"The `{parameter}` parameter is not supported, only `docvalue_fields` is supported in \
`top_hits` aggregation"
)),
))
}
fn unsupported_err(parameter: &str) -> crate::Result<()> {
Err(crate::TantivyError::AggregationError(
AggregationError::InvalidRequest(format!(
"The `{parameter}` parameter is not supported in the `top_hits` aggregation"
)),
))
}
impl TopHitsAggregation {
/// Validate and resolve field retrieval parameters
pub fn validate_and_resolve_field_names(
&mut self,
reader: &ColumnarReader,
) -> crate::Result<()> {
if self._source.is_some() {
use_doc_value_fields_err("_source")?;
}
if self.fields.is_some() {
use_doc_value_fields_err("fields")?;
}
if self.script_fields.is_some() {
use_doc_value_fields_err("script_fields")?;
}
if self.explain.is_some() {
unsupported_err("explain")?;
}
if self.highlight.is_some() {
unsupported_err("highlight")?;
}
if self.version.is_some() {
unsupported_err("version")?;
}
fn resolve_field_names(&mut self, reader: &ColumnarReader) -> crate::Result<()> {
// Tranform a glob (`pattern*`, for example) into a regex::Regex (`^pattern.*$`)
let globbed_string_to_regex = |glob: &str| {
// Replace `*` glob with `.*` regex
let sanitized = format!("^{}$", regex::escape(glob).replace(r"\*", ".*"));
Regex::new(&sanitized.replace('*', ".*")).map_err(|e| {
crate::TantivyError::SchemaError(format!(
"Invalid regex '{}' in docvalue_fields: {}",
glob, e
))
})
};
self.doc_value_fields = self
.doc_value_fields
.iter()
@@ -212,7 +162,8 @@ impl TopHitsAggregation {
.collect::<Vec<_>>();
assert!(
!fields.is_empty(),
"No fields matched the glob '{field}' in docvalue_fields"
"No fields matched the glob '{}' in docvalue_fields",
field
);
Ok(fields)
})
@@ -224,46 +175,33 @@ impl TopHitsAggregation {
Ok(())
}
/// Return fields accessed by the aggregator, in order.
pub fn field_names(&self) -> Vec<&str> {
self.sort
.iter()
.map(|KeyOrder { field, .. }| field.as_str())
.collect()
}
/// Return fields accessed by the aggregator's value retrieval.
pub fn value_field_names(&self) -> Vec<&str> {
self.doc_value_fields.iter().map(|s| s.as_str()).collect()
}
fn get_document_field_data(
&self,
accessors: &HashMap<String, Vec<DynamicColumn>>,
doc_id: DocId,
) -> HashMap<String, FastFieldValue> {
let doc_value_fields = self
) -> FieldRetrivalResult {
let dvf = self
.doc_value_fields
.iter()
.map(|field| {
let accessors = accessors
.get(field)
.unwrap_or_else(|| panic!("field '{field}' not found in accessors"));
.unwrap_or_else(|| panic!("field '{}' not found in accessors", field));
let values: Vec<FastFieldValue> = accessors
let values: Vec<OwnedValue> = accessors
.iter()
.flat_map(|accessor| match accessor {
DynamicColumn::U64(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::U64)
.map(OwnedValue::U64)
.collect::<Vec<_>>(),
DynamicColumn::I64(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::I64)
.map(OwnedValue::I64)
.collect::<Vec<_>>(),
DynamicColumn::F64(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::F64)
.map(OwnedValue::F64)
.collect::<Vec<_>>(),
DynamicColumn::Bytes(accessor) => accessor
.term_ords(doc_id)
@@ -275,7 +213,7 @@ impl TopHitsAggregation {
.expect("could not read term dictionary"),
"term corresponding to term_ord does not exist"
);
FastFieldValue::Bytes(buffer)
OwnedValue::Bytes(buffer)
})
.collect::<Vec<_>>(),
DynamicColumn::Str(accessor) => accessor
@@ -288,82 +226,94 @@ impl TopHitsAggregation {
.expect("could not read term dictionary"),
"term corresponding to term_ord does not exist"
);
FastFieldValue::Str(String::from_utf8(buffer).unwrap())
OwnedValue::Str(String::from_utf8(buffer).unwrap())
})
.collect::<Vec<_>>(),
DynamicColumn::Bool(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::Bool)
.map(OwnedValue::Bool)
.collect::<Vec<_>>(),
DynamicColumn::IpAddr(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::IpAddr)
.map(OwnedValue::IpAddr)
.collect::<Vec<_>>(),
DynamicColumn::DateTime(accessor) => accessor
.values_for_doc(doc_id)
.map(FastFieldValue::Date)
.map(OwnedValue::Date)
.collect::<Vec<_>>(),
})
.collect();
(field.to_owned(), FastFieldValue::Array(values))
(field.to_owned(), OwnedValue::Array(values))
})
.collect();
doc_value_fields
}
}
/// A retrieved value from a fast field.
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum FastFieldValue {
/// The str type is used for any text information.
Str(String),
/// Unsigned 64-bits Integer `u64`
U64(u64),
/// Signed 64-bits Integer `i64`
I64(i64),
/// 64-bits Float `f64`
F64(f64),
/// Bool value
Bool(bool),
/// Date/time with nanoseconds precision
Date(DateTime),
/// Arbitrarily sized byte array
Bytes(Vec<u8>),
/// IpV6 Address. Internally there is no IpV4, it needs to be converted to `Ipv6Addr`.
IpAddr(Ipv6Addr),
/// A list of values.
Array(Vec<Self>),
}
impl From<FastFieldValue> for OwnedValue {
fn from(value: FastFieldValue) -> Self {
match value {
FastFieldValue::Str(s) => OwnedValue::Str(s),
FastFieldValue::U64(u) => OwnedValue::U64(u),
FastFieldValue::I64(i) => OwnedValue::I64(i),
FastFieldValue::F64(f) => OwnedValue::F64(f),
FastFieldValue::Bool(b) => OwnedValue::Bool(b),
FastFieldValue::Date(d) => OwnedValue::Date(d),
FastFieldValue::Bytes(b) => OwnedValue::Bytes(b),
FastFieldValue::IpAddr(ip) => OwnedValue::IpAddr(ip),
FastFieldValue::Array(a) => {
OwnedValue::Array(a.into_iter().map(OwnedValue::from).collect())
}
FieldRetrivalResult {
doc_value_fields: dvf,
}
}
}
/// Holds a fast field value in its u64 representation, and the order in which it should be sorted.
#[derive(Clone, Serialize, Deserialize, Debug)]
struct DocValueAndOrder {
/// A fast field value in its u64 representation.
value: Option<u64>,
/// Sort order for the value
#[derive(Debug, Clone, PartialEq, Default)]
struct KeyOrder {
field: String,
order: Order,
}
impl Ord for DocValueAndOrder {
impl Serialize for KeyOrder {
fn serialize<S: Serializer>(&self, serializer: S) -> Result<S::Ok, S::Error> {
let KeyOrder { field, order } = self;
let mut map = serializer.serialize_map(Some(1))?;
map.serialize_entry(field, order)?;
map.end()
}
}
impl<'de> Deserialize<'de> for KeyOrder {
fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>
where D: Deserializer<'de> {
let mut k_o = <HashMap<String, Order>>::deserialize(deserializer)?.into_iter();
let (k, v) = k_o.next().ok_or(serde::de::Error::custom(
"Expected exactly one key-value pair in KeyOrder, found none",
))?;
if k_o.next().is_some() {
return Err(serde::de::Error::custom(
"Expected exactly one key-value pair in KeyOrder, found more",
));
}
Ok(Self { field: k, order: v })
}
}
impl TopHitsAggregation {
/// Validate and resolve field retrieval parameters
pub fn validate_and_resolve(&mut self, reader: &ColumnarReader) -> crate::Result<()> {
self.retrieval.resolve_field_names(reader)
}
/// Return fields accessed by the aggregator, in order.
pub fn field_names(&self) -> Vec<&str> {
self.sort
.iter()
.map(|KeyOrder { field, .. }| field.as_str())
.collect()
}
/// Return fields accessed by the aggregator's value retrieval.
pub fn value_field_names(&self) -> Vec<&str> {
self.retrieval.get_field_names()
}
}
/// Holds a single comparable doc feature, and the order in which it should be sorted.
#[derive(Clone, Serialize, Deserialize, Debug)]
struct ComparableDocFeature {
/// Stores any u64-mappable feature.
value: Option<u64>,
/// Sort order for the doc feature
order: Order,
}
impl Ord for ComparableDocFeature {
fn cmp(&self, other: &Self) -> std::cmp::Ordering {
let invert = |cmp: std::cmp::Ordering| match self.order {
Order::Asc => cmp,
@@ -379,32 +329,26 @@ impl Ord for DocValueAndOrder {
}
}
impl PartialOrd for DocValueAndOrder {
impl PartialOrd for ComparableDocFeature {
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
Some(self.cmp(other))
}
}
impl PartialEq for DocValueAndOrder {
impl PartialEq for ComparableDocFeature {
fn eq(&self, other: &Self) -> bool {
self.value.cmp(&other.value) == std::cmp::Ordering::Equal
}
}
impl Eq for DocValueAndOrder {}
impl Eq for ComparableDocFeature {}
#[derive(Clone, Serialize, Deserialize, Debug)]
struct DocSortValuesAndFields {
sorts: Vec<DocValueAndOrder>,
struct ComparableDocFeatures(Vec<ComparableDocFeature>, FieldRetrivalResult);
#[serde(rename = "docvalue_fields")]
#[serde(skip_serializing_if = "HashMap::is_empty")]
doc_value_fields: HashMap<String, FastFieldValue>,
}
impl Ord for DocSortValuesAndFields {
impl Ord for ComparableDocFeatures {
fn cmp(&self, other: &Self) -> std::cmp::Ordering {
for (self_feature, other_feature) in self.sorts.iter().zip(other.sorts.iter()) {
for (self_feature, other_feature) in self.0.iter().zip(other.0.iter()) {
let cmp = self_feature.cmp(other_feature);
if cmp != std::cmp::Ordering::Equal {
return cmp;
@@ -414,43 +358,53 @@ impl Ord for DocSortValuesAndFields {
}
}
impl PartialOrd for DocSortValuesAndFields {
impl PartialOrd for ComparableDocFeatures {
fn partial_cmp(&self, other: &Self) -> Option<std::cmp::Ordering> {
Some(self.cmp(other))
}
}
impl PartialEq for DocSortValuesAndFields {
impl PartialEq for ComparableDocFeatures {
fn eq(&self, other: &Self) -> bool {
self.cmp(other) == std::cmp::Ordering::Equal
}
}
impl Eq for DocSortValuesAndFields {}
impl Eq for ComparableDocFeatures {}
/// The TopHitsCollector used for collecting over segments and merging results.
#[derive(Clone, Serialize, Deserialize, Debug)]
pub struct TopHitsTopNComputer {
#[derive(Clone, Serialize, Deserialize)]
pub struct TopHitsCollector {
req: TopHitsAggregation,
top_n: TopNComputer<DocSortValuesAndFields, DocAddress, false>,
top_n: TopNComputer<ComparableDocFeatures, DocAddress, false>,
}
impl std::cmp::PartialEq for TopHitsTopNComputer {
impl Default for TopHitsCollector {
fn default() -> Self {
Self {
req: TopHitsAggregation::default(),
top_n: TopNComputer::new(1),
}
}
}
impl std::fmt::Debug for TopHitsCollector {
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
f.debug_struct("TopHitsCollector")
.field("req", &self.req)
.field("top_n_threshold", &self.top_n.threshold)
.finish()
}
}
impl std::cmp::PartialEq for TopHitsCollector {
fn eq(&self, _other: &Self) -> bool {
false
}
}
impl TopHitsTopNComputer {
/// Create a new TopHitsCollector
pub fn new(req: &TopHitsAggregation) -> Self {
Self {
top_n: TopNComputer::new(req.size + req.from.unwrap_or(0)),
req: req.clone(),
}
}
fn collect(&mut self, features: DocSortValuesAndFields, doc: DocAddress) {
impl TopHitsCollector {
fn collect(&mut self, features: ComparableDocFeatures, doc: DocAddress) {
self.top_n.push(features, doc);
}
@@ -462,19 +416,14 @@ impl TopHitsTopNComputer {
}
/// Finalize by converting self into the final result form
pub fn into_final_result(self) -> TopHitsMetricResult {
pub fn finalize(self) -> TopHitsMetricResult {
let mut hits: Vec<TopHitsVecEntry> = self
.top_n
.into_sorted_vec()
.into_iter()
.map(|doc| TopHitsVecEntry {
sort: doc.feature.sorts.iter().map(|f| f.value).collect(),
doc_value_fields: doc
.feature
.doc_value_fields
.into_iter()
.map(|(k, v)| (k, v.into()))
.collect(),
sort: doc.feature.0.iter().map(|f| f.value).collect(),
search_results: doc.feature.1,
})
.collect();
@@ -487,55 +436,64 @@ impl TopHitsTopNComputer {
}
}
#[derive(Clone, Debug)]
pub(crate) struct TopHitsSegmentCollector {
#[derive(Clone)]
pub(crate) struct SegmentTopHitsCollector {
segment_ordinal: SegmentOrdinal,
accessor_idx: usize,
top_n: TopNComputer<Vec<DocValueAndOrder>, DocAddress, false>,
inner_collector: TopHitsCollector,
}
impl TopHitsSegmentCollector {
impl SegmentTopHitsCollector {
pub fn from_req(
req: &TopHitsAggregation,
accessor_idx: usize,
segment_ordinal: SegmentOrdinal,
) -> Self {
Self {
top_n: TopNComputer::new(req.size + req.from.unwrap_or(0)),
inner_collector: TopHitsCollector {
req: req.clone(),
top_n: TopNComputer::new(req.size + req.from.unwrap_or(0)),
},
segment_ordinal,
accessor_idx,
}
}
fn into_top_hits_collector(
self,
value_accessors: &HashMap<String, Vec<DynamicColumn>>,
req: &TopHitsAggregation,
) -> TopHitsTopNComputer {
let mut top_hits_computer = TopHitsTopNComputer::new(req);
let top_results = self.top_n.into_vec();
}
for res in top_results {
let doc_value_fields = req.get_document_field_data(value_accessors, res.doc.doc_id);
top_hits_computer.collect(
DocSortValuesAndFields {
sorts: res.feature,
doc_value_fields,
},
res.doc,
);
}
impl std::fmt::Debug for SegmentTopHitsCollector {
fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result {
f.debug_struct("SegmentTopHitsCollector")
.field("segment_id", &self.segment_ordinal)
.field("accessor_idx", &self.accessor_idx)
.field("inner_collector", &self.inner_collector)
.finish()
}
}
top_hits_computer
impl SegmentAggregationCollector for SegmentTopHitsCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_with_accessor: &crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
results: &mut crate::aggregation::intermediate_agg_result::IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let intermediate_result = IntermediateMetricResult::TopHits(self.inner_collector);
results.push(
name,
IntermediateAggregationResult::Metric(intermediate_result),
)
}
/// TODO add a specialized variant for a single sort field
fn collect_with(
fn collect(
&mut self,
doc_id: crate::DocId,
req: &TopHitsAggregation,
accessors: &[(Column<u64>, ColumnType)],
agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
) -> crate::Result<()> {
let sorts: Vec<DocValueAndOrder> = req
let accessors = &agg_with_accessor.aggs.values[self.accessor_idx].accessors;
let value_accessors = &agg_with_accessor.aggs.values[self.accessor_idx].value_accessors;
let features: Vec<ComparableDocFeature> = self
.inner_collector
.req
.sort
.iter()
.enumerate()
@@ -547,12 +505,18 @@ impl TopHitsSegmentCollector {
.0
.values_for_doc(doc_id)
.next();
DocValueAndOrder { value, order }
ComparableDocFeature { value, order }
})
.collect();
self.top_n.push(
sorts,
let retrieval_result = self
.inner_collector
.req
.retrieval
.get_document_field_data(value_accessors, doc_id);
self.inner_collector.collect(
ComparableDocFeatures(features, retrieval_result),
DocAddress {
segment_ord: self.segment_ordinal,
doc_id,
@@ -560,62 +524,19 @@ impl TopHitsSegmentCollector {
);
Ok(())
}
}
impl SegmentAggregationCollector for TopHitsSegmentCollector {
fn add_intermediate_aggregation_result(
self: Box<Self>,
agg_with_accessor: &crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
results: &mut crate::aggregation::intermediate_agg_result::IntermediateAggregationResults,
) -> crate::Result<()> {
let name = agg_with_accessor.aggs.keys[self.accessor_idx].to_string();
let value_accessors = &agg_with_accessor.aggs.values[self.accessor_idx].value_accessors;
let tophits_req = &agg_with_accessor.aggs.values[self.accessor_idx]
.agg
.agg
.as_top_hits()
.expect("aggregation request must be of type top hits");
let intermediate_result = IntermediateMetricResult::TopHits(
self.into_top_hits_collector(value_accessors, tophits_req),
);
results.push(
name,
IntermediateAggregationResult::Metric(intermediate_result),
)
}
/// TODO: Consider a caching layer to reduce the call overhead
fn collect(
&mut self,
doc_id: crate::DocId,
agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
) -> crate::Result<()> {
let tophits_req = &agg_with_accessor.aggs.values[self.accessor_idx]
.agg
.agg
.as_top_hits()
.expect("aggregation request must be of type top hits");
let accessors = &agg_with_accessor.aggs.values[self.accessor_idx].accessors;
self.collect_with(doc_id, tophits_req, accessors)?;
Ok(())
}
fn collect_block(
&mut self,
docs: &[crate::DocId],
agg_with_accessor: &mut crate::aggregation::agg_req_with_accessor::AggregationsWithAccessor,
) -> crate::Result<()> {
let tophits_req = &agg_with_accessor.aggs.values[self.accessor_idx]
.agg
.agg
.as_top_hits()
.expect("aggregation request must be of type top hits");
let accessors = &agg_with_accessor.aggs.values[self.accessor_idx].accessors;
// TODO: Consider getting fields with the column block accessor.
// TODO: Consider getting fields with the column block accessor and refactor this.
// ---
// Would the additional complexity of getting fields with the column_block_accessor
// make sense here? Probably yes, but I want to get a first-pass review first
// before proceeding.
for doc in docs {
self.collect_with(*doc, tophits_req, accessors)?;
self.collect(*doc, agg_with_accessor)?;
}
Ok(())
}
@@ -628,7 +549,7 @@ mod tests {
use serde_json::Value;
use time::macros::datetime;
use super::{DocSortValuesAndFields, DocValueAndOrder, Order};
use super::{ComparableDocFeature, ComparableDocFeatures, Order};
use crate::aggregation::agg_req::Aggregations;
use crate::aggregation::agg_result::AggregationResults;
use crate::aggregation::bucket::tests::get_test_index_from_docs;
@@ -636,44 +557,44 @@ mod tests {
use crate::aggregation::AggregationCollector;
use crate::collector::ComparableDoc;
use crate::query::AllQuery;
use crate::schema::OwnedValue;
use crate::schema::OwnedValue as SchemaValue;
fn invert_order(cmp_feature: DocValueAndOrder) -> DocValueAndOrder {
let DocValueAndOrder { value, order } = cmp_feature;
fn invert_order(cmp_feature: ComparableDocFeature) -> ComparableDocFeature {
let ComparableDocFeature { value, order } = cmp_feature;
let order = match order {
Order::Asc => Order::Desc,
Order::Desc => Order::Asc,
};
DocValueAndOrder { value, order }
ComparableDocFeature { value, order }
}
fn collector_with_capacity(capacity: usize) -> super::TopHitsTopNComputer {
super::TopHitsTopNComputer {
fn collector_with_capacity(capacity: usize) -> super::TopHitsCollector {
super::TopHitsCollector {
top_n: super::TopNComputer::new(capacity),
req: Default::default(),
..Default::default()
}
}
fn invert_order_features(mut cmp_features: DocSortValuesAndFields) -> DocSortValuesAndFields {
cmp_features.sorts = cmp_features
.sorts
fn invert_order_features(cmp_features: ComparableDocFeatures) -> ComparableDocFeatures {
let ComparableDocFeatures(cmp_features, search_results) = cmp_features;
let cmp_features = cmp_features
.into_iter()
.map(invert_order)
.collect::<Vec<_>>();
cmp_features
ComparableDocFeatures(cmp_features, search_results)
}
#[test]
fn test_comparable_doc_feature() -> crate::Result<()> {
let small = DocValueAndOrder {
let small = ComparableDocFeature {
value: Some(1),
order: Order::Asc,
};
let big = DocValueAndOrder {
let big = ComparableDocFeature {
value: Some(2),
order: Order::Asc,
};
let none = DocValueAndOrder {
let none = ComparableDocFeature {
value: None,
order: Order::Asc,
};
@@ -695,21 +616,21 @@ mod tests {
#[test]
fn test_comparable_doc_features() -> crate::Result<()> {
let features_1 = DocSortValuesAndFields {
sorts: vec![DocValueAndOrder {
let features_1 = ComparableDocFeatures(
vec![ComparableDocFeature {
value: Some(1),
order: Order::Asc,
}],
doc_value_fields: Default::default(),
};
Default::default(),
);
let features_2 = DocSortValuesAndFields {
sorts: vec![DocValueAndOrder {
let features_2 = ComparableDocFeatures(
vec![ComparableDocFeature {
value: Some(2),
order: Order::Asc,
}],
doc_value_fields: Default::default(),
};
Default::default(),
);
assert!(features_1 < features_2);
@@ -768,39 +689,39 @@ mod tests {
segment_ord: 0,
doc_id: 0,
},
feature: DocSortValuesAndFields {
sorts: vec![DocValueAndOrder {
feature: ComparableDocFeatures(
vec![ComparableDocFeature {
value: Some(1),
order: Order::Asc,
}],
doc_value_fields: Default::default(),
},
Default::default(),
),
},
ComparableDoc {
doc: crate::DocAddress {
segment_ord: 0,
doc_id: 2,
},
feature: DocSortValuesAndFields {
sorts: vec![DocValueAndOrder {
feature: ComparableDocFeatures(
vec![ComparableDocFeature {
value: Some(3),
order: Order::Asc,
}],
doc_value_fields: Default::default(),
},
Default::default(),
),
},
ComparableDoc {
doc: crate::DocAddress {
segment_ord: 0,
doc_id: 1,
},
feature: DocSortValuesAndFields {
sorts: vec![DocValueAndOrder {
feature: ComparableDocFeatures(
vec![ComparableDocFeature {
value: Some(5),
order: Order::Asc,
}],
doc_value_fields: Default::default(),
},
Default::default(),
),
},
];
@@ -809,23 +730,23 @@ mod tests {
collector.collect(doc.feature, doc.doc);
}
let res = collector.into_final_result();
let res = collector.finalize();
assert_eq!(
res,
super::TopHitsMetricResult {
hits: vec![
super::TopHitsVecEntry {
sort: vec![docs[0].feature.sorts[0].value],
doc_value_fields: Default::default(),
sort: vec![docs[0].feature.0[0].value],
search_results: Default::default(),
},
super::TopHitsVecEntry {
sort: vec![docs[1].feature.sorts[0].value],
doc_value_fields: Default::default(),
sort: vec![docs[1].feature.0[0].value],
search_results: Default::default(),
},
super::TopHitsVecEntry {
sort: vec![docs[2].feature.sorts[0].value],
doc_value_fields: Default::default(),
sort: vec![docs[2].feature.0[0].value],
search_results: Default::default(),
},
]
}
@@ -882,7 +803,7 @@ mod tests {
{
"sort": [common::i64_to_u64(date_2017.unix_timestamp_nanos() as i64)],
"docvalue_fields": {
"date": [ OwnedValue::Date(DateTime::from_utc(date_2017)) ],
"date": [ SchemaValue::Date(DateTime::from_utc(date_2017)) ],
"text": [ "ccc" ],
"text2": [ "ddd" ],
"mixed.dyn_arr": [ 3, "4" ],
@@ -891,7 +812,7 @@ mod tests {
{
"sort": [common::i64_to_u64(date_2016.unix_timestamp_nanos() as i64)],
"docvalue_fields": {
"date": [ OwnedValue::Date(DateTime::from_utc(date_2016)) ],
"date": [ SchemaValue::Date(DateTime::from_utc(date_2016)) ],
"text": [ "aaa" ],
"text2": [ "bbb" ],
"mixed.dyn_arr": [ 6, "7" ],

View File

@@ -143,6 +143,8 @@ use std::fmt::Display;
#[cfg(test)]
mod agg_tests;
mod agg_bench;
use core::fmt;
pub use agg_limits::AggregationLimits;
@@ -158,14 +160,15 @@ use serde::de::{self, Visitor};
use serde::{Deserialize, Deserializer, Serialize};
fn parse_str_into_f64<E: de::Error>(value: &str) -> Result<f64, E> {
let parsed = value
.parse::<f64>()
.map_err(|_err| de::Error::custom(format!("Failed to parse f64 from string: {value:?}")))?;
let parsed = value.parse::<f64>().map_err(|_err| {
de::Error::custom(format!("Failed to parse f64 from string: {:?}", value))
})?;
// Check if the parsed value is NaN or infinity
if parsed.is_nan() || parsed.is_infinite() {
Err(de::Error::custom(format!(
"Value is not a valid f64 (NaN or Infinity): {value:?}"
"Value is not a valid f64 (NaN or Infinity): {:?}",
value
)))
} else {
Ok(parsed)
@@ -414,6 +417,7 @@ mod tests {
use time::OffsetDateTime;
use super::agg_req::Aggregations;
use super::segment_agg_result::AggregationLimits;
use super::*;
use crate::indexer::NoMergePolicy;
use crate::query::{AllQuery, TermQuery};

View File

@@ -11,12 +11,12 @@ use super::agg_req_with_accessor::{AggregationWithAccessor, AggregationsWithAcce
use super::bucket::{SegmentHistogramCollector, SegmentRangeCollector, SegmentTermCollector};
use super::intermediate_agg_result::IntermediateAggregationResults;
use super::metric::{
AverageAggregation, CountAggregation, ExtendedStatsAggregation, MaxAggregation, MinAggregation,
AverageAggregation, CountAggregation, MaxAggregation, MinAggregation,
SegmentPercentilesCollector, SegmentStatsCollector, SegmentStatsType, StatsAggregation,
SumAggregation,
};
use crate::aggregation::bucket::TermMissingAgg;
use crate::aggregation::metric::{SegmentExtendedStatsCollector, TopHitsSegmentCollector};
use crate::aggregation::metric::SegmentTopHitsCollector;
pub(crate) trait SegmentAggregationCollector: CollectorClone + Debug {
fn add_intermediate_aggregation_result(
@@ -148,9 +148,6 @@ pub(crate) fn build_single_agg_segment_collector(
accessor_idx,
*missing,
))),
ExtendedStats(ExtendedStatsAggregation { missing, sigma, .. }) => Ok(Box::new(
SegmentExtendedStatsCollector::from_req(req.field_type, *sigma, accessor_idx, *missing),
)),
Sum(SumAggregation { missing, .. }) => Ok(Box::new(SegmentStatsCollector::from_req(
req.field_type,
SegmentStatsType::Sum,
@@ -164,7 +161,7 @@ pub(crate) fn build_single_agg_segment_collector(
accessor_idx,
)?,
)),
TopHits(top_hits_req) => Ok(Box::new(TopHitsSegmentCollector::from_req(
TopHits(top_hits_req) => Ok(Box::new(SegmentTopHitsCollector::from_req(
top_hits_req,
accessor_idx,
req.segment_ordinal,

View File

@@ -1,7 +1,7 @@
use std::cmp::Ordering;
use std::collections::{btree_map, BTreeMap, BTreeSet, BinaryHeap};
use std::io;
use std::ops::Bound;
use std::{io, u64, usize};
use crate::collector::{Collector, SegmentCollector};
use crate::fastfield::FacetReader;
@@ -598,7 +598,7 @@ mod tests {
let mid = n % 4;
n /= 4;
let leaf = n % 5;
Facet::from(&format!("/top{top}/mid{mid}/leaf{leaf}"))
Facet::from(&format!("/top{}/mid{}/leaf{}", top, mid, leaf))
})
.collect();
for i in 0..num_facets * 10 {
@@ -737,7 +737,7 @@ mod tests {
vec![("a", 10), ("b", 100), ("c", 7), ("d", 12), ("e", 21)]
.into_iter()
.flat_map(|(c, count)| {
let facet = Facet::from(&format!("/facet/{c}"));
let facet = Facet::from(&format!("/facet/{}", c));
let doc = doc!(facet_field => facet);
iter::repeat(doc).take(count)
})
@@ -785,7 +785,7 @@ mod tests {
let docs: Vec<TantivyDocument> = vec![("b", 2), ("a", 2), ("c", 4)]
.into_iter()
.flat_map(|(c, count)| {
let facet = Facet::from(&format!("/facet/{c}"));
let facet = Facet::from(&format!("/facet/{}", c));
let doc = doc!(facet_field => facet);
iter::repeat(doc).take(count)
})

View File

@@ -160,7 +160,7 @@ mod tests {
use super::{add_vecs, HistogramCollector, HistogramComputer};
use crate::schema::{Schema, FAST};
use crate::time::{Date, Month};
use crate::{query, DateTime, Index};
use crate::{doc, query, DateTime, Index};
#[test]
fn test_add_histograms_simple() {

View File

@@ -274,10 +274,6 @@ pub trait SegmentCollector: 'static {
fn collect(&mut self, doc: DocId, score: Score);
/// The query pushes the scored document to the collector via this method.
/// This method is used when the collector does not require scoring.
///
/// See [`COLLECT_BLOCK_BUFFER_LEN`](crate::COLLECT_BLOCK_BUFFER_LEN) for the
/// buffer size passed to the collector.
fn collect_block(&mut self, docs: &[DocId]) {
for doc in docs {
self.collect(*doc, 0.0);

View File

@@ -52,16 +52,10 @@ impl<TCollector: Collector> Collector for CollectorWrapper<TCollector> {
impl SegmentCollector for Box<dyn BoxableSegmentCollector> {
type Fruit = Box<dyn Fruit>;
#[inline]
fn collect(&mut self, doc: u32, score: Score) {
self.as_mut().collect(doc, score);
}
#[inline]
fn collect_block(&mut self, docs: &[DocId]) {
self.as_mut().collect_block(docs);
}
fn harvest(self) -> Box<dyn Fruit> {
BoxableSegmentCollector::harvest_from_box(self)
}
@@ -69,11 +63,6 @@ impl SegmentCollector for Box<dyn BoxableSegmentCollector> {
pub trait BoxableSegmentCollector {
fn collect(&mut self, doc: u32, score: Score);
fn collect_block(&mut self, docs: &[DocId]) {
for &doc in docs {
self.collect(doc, 0.0);
}
}
fn harvest_from_box(self: Box<Self>) -> Box<dyn Fruit>;
}
@@ -82,14 +71,9 @@ pub struct SegmentCollectorWrapper<TSegmentCollector: SegmentCollector>(TSegment
impl<TSegmentCollector: SegmentCollector> BoxableSegmentCollector
for SegmentCollectorWrapper<TSegmentCollector>
{
#[inline]
fn collect(&mut self, doc: u32, score: Score) {
self.0.collect(doc, score);
}
#[inline]
fn collect_block(&mut self, docs: &[DocId]) {
self.0.collect_block(docs);
}
fn harvest_from_box(self: Box<Self>) -> Box<dyn Fruit> {
Box::new(self.0.harvest())

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