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1 Commits
python-v0.
...
v0.21.0
| Author | SHA1 | Date | |
|---|---|---|---|
|
6b5130cccb |
307
Cargo.lock
generated
307
Cargo.lock
generated
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"tokio",
|
||||
"tracing",
|
||||
"url",
|
||||
"walkdir",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "object_store"
|
||||
version = "0.12.2"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "7781f96d79ed0f961a7021424ab01840efbda64ae7a505aaea195efc91eaaec4"
|
||||
dependencies = [
|
||||
"async-trait",
|
||||
"bytes",
|
||||
"chrono",
|
||||
"futures",
|
||||
"http 1.3.1",
|
||||
"humantime",
|
||||
"itertools 0.14.0",
|
||||
"parking_lot",
|
||||
"percent-encoding",
|
||||
"thiserror 2.0.12",
|
||||
"tokio",
|
||||
"tracing",
|
||||
@@ -5361,18 +5396,6 @@ dependencies = [
|
||||
"indexmap 2.9.0",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "petgraph"
|
||||
version = "0.8.2"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "54acf3a685220b533e437e264e4d932cfbdc4cc7ec0cd232ed73c08d03b8a7ca"
|
||||
dependencies = [
|
||||
"fixedbitset",
|
||||
"hashbrown 0.15.4",
|
||||
"indexmap 2.9.0",
|
||||
"serde",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "phf"
|
||||
version = "0.11.3"
|
||||
@@ -5905,7 +5928,7 @@ dependencies = [
|
||||
"log",
|
||||
"multimap",
|
||||
"once_cell",
|
||||
"petgraph 0.7.1",
|
||||
"petgraph",
|
||||
"prettyplease",
|
||||
"prost",
|
||||
"prost-types",
|
||||
@@ -6247,20 +6270,6 @@ dependencies = [
|
||||
"unicase",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "random_word"
|
||||
version = "0.5.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "bcd87d2e3f99cc11e6c7fc518f09e63e194f7243b4cf30c979b0c524d04fbd90"
|
||||
dependencies = [
|
||||
"ahash",
|
||||
"brotli",
|
||||
"once_cell",
|
||||
"paste",
|
||||
"rand 0.8.5",
|
||||
"unicase",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "rangemap"
|
||||
version = "1.5.1"
|
||||
|
||||
32
Cargo.toml
32
Cargo.toml
@@ -21,14 +21,14 @@ categories = ["database-implementations"]
|
||||
rust-version = "1.78.0"
|
||||
|
||||
[workspace.dependencies]
|
||||
lance = { "version" = "=0.31.1", tag="v0.31.1-beta.2", git="https://github.com/lancedb/lance.git", features = ["dynamodb"] }
|
||||
lance-io = { "version" = "=0.31.1", tag="v0.31.1-beta.2", git="https://github.com/lancedb/lance.git" }
|
||||
lance-index = { "version" = "=0.31.1", tag="v0.31.1-beta.2", git="https://github.com/lancedb/lance.git" }
|
||||
lance-linalg = { "version" = "=0.31.1", tag="v0.31.1-beta.2", git="https://github.com/lancedb/lance.git" }
|
||||
lance-table = { "version" = "=0.31.1", tag="v0.31.1-beta.2", git="https://github.com/lancedb/lance.git" }
|
||||
lance-testing = { "version" = "=0.31.1", tag="v0.31.1-beta.2", git="https://github.com/lancedb/lance.git" }
|
||||
lance-datafusion = { "version" = "=0.31.1", tag="v0.31.1-beta.2", git="https://github.com/lancedb/lance.git" }
|
||||
lance-encoding = { "version" = "=0.31.1", tag="v0.31.1-beta.2", git="https://github.com/lancedb/lance.git" }
|
||||
lance = { "version" = "=0.30.0", "features" = ["dynamodb"] }
|
||||
lance-io = "=0.30.0"
|
||||
lance-index = "=0.30.0"
|
||||
lance-linalg = "=0.30.0"
|
||||
lance-table = "=0.30.0"
|
||||
lance-testing = "=0.30.0"
|
||||
lance-datafusion = "=0.30.0"
|
||||
lance-encoding = "=0.30.0"
|
||||
# Note that this one does not include pyarrow
|
||||
arrow = { version = "55.1", optional = false }
|
||||
arrow-array = "55.1"
|
||||
@@ -39,20 +39,20 @@ arrow-schema = "55.1"
|
||||
arrow-arith = "55.1"
|
||||
arrow-cast = "55.1"
|
||||
async-trait = "0"
|
||||
datafusion = { version = "48.0", default-features = false }
|
||||
datafusion-catalog = "48.0"
|
||||
datafusion-common = { version = "48.0", default-features = false }
|
||||
datafusion-execution = "48.0"
|
||||
datafusion-expr = "48.0"
|
||||
datafusion-physical-plan = "48.0"
|
||||
datafusion = { version = "47.0", default-features = false }
|
||||
datafusion-catalog = "47.0"
|
||||
datafusion-common = { version = "47.0", default-features = false }
|
||||
datafusion-execution = "47.0"
|
||||
datafusion-expr = "47.0"
|
||||
datafusion-physical-plan = "47.0"
|
||||
env_logger = "0.11"
|
||||
half = { "version" = "=2.6.0", default-features = false, features = [
|
||||
half = { "version" = "=2.5.0", default-features = false, features = [
|
||||
"num-traits",
|
||||
] }
|
||||
futures = "0"
|
||||
log = "0.4"
|
||||
moka = { version = "0.12", features = ["future"] }
|
||||
object_store = "0.12.0"
|
||||
object_store = "0.11.0"
|
||||
pin-project = "1.0.7"
|
||||
snafu = "0.8"
|
||||
url = "2"
|
||||
|
||||
@@ -428,7 +428,7 @@
|
||||
"\n",
|
||||
"**Why?** \n",
|
||||
"Embedding the UFO dataset and ingesting it into LanceDB takes **~2 hours on a T4 GPU**. To save time: \n",
|
||||
"- **Use the pre-prepared table with index created** (provided below) to proceed directly to **Step 7**: search. \n",
|
||||
"- **Use the pre-prepared table with index created ** (provided below) to proceed directly to step7: search. \n",
|
||||
"- **Step 5a** contains the full ingestion code for reference (run it only if necessary). \n",
|
||||
"- **Step 6** contains the details on creating the index on the multivector column"
|
||||
]
|
||||
|
||||
44
node/package-lock.json
generated
44
node/package-lock.json
generated
@@ -1,12 +1,12 @@
|
||||
{
|
||||
"name": "vectordb",
|
||||
"version": "0.21.0",
|
||||
"version": "0.20.1-beta.2",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"name": "vectordb",
|
||||
"version": "0.21.0",
|
||||
"version": "0.20.1-beta.2",
|
||||
"cpu": [
|
||||
"x64",
|
||||
"arm64"
|
||||
@@ -52,11 +52,11 @@
|
||||
"uuid": "^9.0.0"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"@lancedb/vectordb-darwin-arm64": "0.21.0",
|
||||
"@lancedb/vectordb-darwin-x64": "0.21.0",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.21.0",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.21.0",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.21.0"
|
||||
"@lancedb/vectordb-darwin-arm64": "0.20.1-beta.2",
|
||||
"@lancedb/vectordb-darwin-x64": "0.20.1-beta.2",
|
||||
"@lancedb/vectordb-linux-arm64-gnu": "0.20.1-beta.2",
|
||||
"@lancedb/vectordb-linux-x64-gnu": "0.20.1-beta.2",
|
||||
"@lancedb/vectordb-win32-x64-msvc": "0.20.1-beta.2"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@apache-arrow/ts": "^14.0.2",
|
||||
@@ -327,9 +327,9 @@
|
||||
}
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-darwin-arm64": {
|
||||
"version": "0.21.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.21.0.tgz",
|
||||
"integrity": "sha512-FTKbdYG36mvQ75tId+esyRfRjIBzryRhAp/6h51tiXy8gsq/TButuiPdqIXeonNModEjhu8wkzsGFwgjCcePow==",
|
||||
"version": "0.20.1-beta.2",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.20.1-beta.2.tgz",
|
||||
"integrity": "sha512-mqi0yI+ZwBTydaDy1FRHAUZwrWS28u6tbHTe1s4uSrmERbVI6PfmoPR+NZWWAp6ZhlseSdl/+yeI4imk11rQSw==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
@@ -339,9 +339,9 @@
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-darwin-x64": {
|
||||
"version": "0.21.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.21.0.tgz",
|
||||
"integrity": "sha512-vGaFBr2sQZWE0mudg3LGTHiRE7p2Qce2ogiE2VAf1DLAJ4MrIhgVmEttf966ausIwNCgml+5AzUntw6zC0Oyuw==",
|
||||
"version": "0.20.1-beta.2",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.20.1-beta.2.tgz",
|
||||
"integrity": "sha512-m8EYYA8JZIeNsJqQsBDUMu6r31/u7FzpjonJ4Y+CjapVl6UdvI65KUkeL2dYrFao++RuIoaiqcm3e7gRgFZpXQ==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
@@ -351,9 +351,9 @@
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-linux-arm64-gnu": {
|
||||
"version": "0.21.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.21.0.tgz",
|
||||
"integrity": "sha512-KlxqhnX4eBN6rDqrPgf/x/vLpnHK2UcIzNLpiOZzSAhooCmKmnNpfs/EXt+KRFloEQMy25AHpMpqkSPv1Q2oDA==",
|
||||
"version": "0.20.1-beta.2",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.20.1-beta.2.tgz",
|
||||
"integrity": "sha512-3Og2+bk4GlWmMO1Yg2HBfeb5zrOMLaIHD7bEqQ4+6yw4IckAaV+ke05H0tyyqmOVrOQ0LpvtXgD7pPztjm9r9A==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
@@ -363,9 +363,9 @@
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-linux-x64-gnu": {
|
||||
"version": "0.21.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.21.0.tgz",
|
||||
"integrity": "sha512-t7dkFV6kga3rqXR1rH460GdpSVuY0tw7CIc0KqsIIkBcXzUPA1n0QDoazdwPQ1MXzG/+F5WWCTp3dYWx2vP0Lw==",
|
||||
"version": "0.20.1-beta.2",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.20.1-beta.2.tgz",
|
||||
"integrity": "sha512-mwTQyA/FBoU/FkPuvCNBZG3y83gBN+iYoejehBH2HBkLUIcmlsDgSRZ1OQ+f9ijj12EMBCA11tBUPA9zhHzyrw==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
@@ -375,9 +375,9 @@
|
||||
]
|
||||
},
|
||||
"node_modules/@lancedb/vectordb-win32-x64-msvc": {
|
||||
"version": "0.21.0",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.21.0.tgz",
|
||||
"integrity": "sha512-yovkW61RECBTsu0S527BX1uW0jCAZK9MAsJTknXmDjp78figx4/AyI5ajT63u/Uo4EKoheeNiiLdyU4v+A9YVw==",
|
||||
"version": "0.20.1-beta.2",
|
||||
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.20.1-beta.2.tgz",
|
||||
"integrity": "sha512-VkjNpqhK3l3uHLLPmox+HrmKPMaZgV+qsGQWx0nfseGnSOEmXAWZWQFe0APVCQ9y0xTypQB0oH7eSOPZv2t4WQ==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
|
||||
@@ -368,9 +368,9 @@ describe("merge insert", () => {
|
||||
{ a: 4, b: "z" },
|
||||
];
|
||||
|
||||
const result = (await table.toArrow()).toArray().sort((a, b) => a.a - b.a);
|
||||
|
||||
expect(result.map((row) => ({ ...row }))).toEqual(expected);
|
||||
expect(
|
||||
JSON.parse(JSON.stringify((await table.toArrow()).toArray())),
|
||||
).toEqual(expected);
|
||||
});
|
||||
test("conditional update", async () => {
|
||||
const newData = [
|
||||
|
||||
4
nodejs/package-lock.json
generated
4
nodejs/package-lock.json
generated
@@ -1,12 +1,12 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.21.0",
|
||||
"version": "0.20.1-beta.2",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.21.0",
|
||||
"version": "0.20.1-beta.2",
|
||||
"cpu": [
|
||||
"x64",
|
||||
"arm64"
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
[tool.bumpversion]
|
||||
current_version = "0.24.1-beta.0"
|
||||
current_version = "0.24.0"
|
||||
parse = """(?x)
|
||||
(?P<major>0|[1-9]\\d*)\\.
|
||||
(?P<minor>0|[1-9]\\d*)\\.
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
[package]
|
||||
name = "lancedb-python"
|
||||
version = "0.24.1-beta.0"
|
||||
version = "0.24.0"
|
||||
edition.workspace = true
|
||||
description = "Python bindings for LanceDB"
|
||||
license.workspace = true
|
||||
|
||||
@@ -85,7 +85,7 @@ embeddings = [
|
||||
"boto3>=1.28.57",
|
||||
"awscli>=1.29.57",
|
||||
"botocore>=1.31.57",
|
||||
"ollama>=0.3.0",
|
||||
"ollama",
|
||||
"ibm-watsonx-ai>=1.1.2",
|
||||
]
|
||||
azure = ["adlfs>=2024.2.0"]
|
||||
|
||||
@@ -2,15 +2,14 @@
|
||||
# SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
from functools import cached_property
|
||||
from typing import TYPE_CHECKING, List, Optional, Sequence, Union
|
||||
|
||||
import numpy as np
|
||||
from typing import TYPE_CHECKING, List, Optional, Union
|
||||
|
||||
from ..util import attempt_import_or_raise
|
||||
from .base import TextEmbeddingFunction
|
||||
from .registry import register
|
||||
|
||||
if TYPE_CHECKING:
|
||||
import numpy as np
|
||||
import ollama
|
||||
|
||||
|
||||
@@ -29,21 +28,23 @@ class OllamaEmbeddings(TextEmbeddingFunction):
|
||||
keep_alive: Optional[Union[float, str]] = None
|
||||
ollama_client_kwargs: Optional[dict] = {}
|
||||
|
||||
def ndims(self) -> int:
|
||||
def ndims(self):
|
||||
return len(self.generate_embeddings(["foo"])[0])
|
||||
|
||||
def _compute_embedding(self, text: Sequence[str]) -> Sequence[Sequence[float]]:
|
||||
response = self._ollama_client.embed(
|
||||
model=self.name,
|
||||
input=text,
|
||||
options=self.options,
|
||||
keep_alive=self.keep_alive,
|
||||
def _compute_embedding(self, text) -> Union["np.array", None]:
|
||||
return (
|
||||
self._ollama_client.embeddings(
|
||||
model=self.name,
|
||||
prompt=text,
|
||||
options=self.options,
|
||||
keep_alive=self.keep_alive,
|
||||
)["embedding"]
|
||||
or None
|
||||
)
|
||||
return response.embeddings
|
||||
|
||||
def generate_embeddings(
|
||||
self, texts: Union[List[str], np.ndarray]
|
||||
) -> list[Union[np.array, None]]:
|
||||
self, texts: Union[List[str], "np.ndarray"]
|
||||
) -> list[Union["np.array", None]]:
|
||||
"""
|
||||
Get the embeddings for the given texts
|
||||
|
||||
@@ -53,8 +54,8 @@ class OllamaEmbeddings(TextEmbeddingFunction):
|
||||
The texts to embed
|
||||
"""
|
||||
# TODO retry, rate limit, token limit
|
||||
embeddings = self._compute_embedding(texts)
|
||||
return list(embeddings)
|
||||
embeddings = [self._compute_embedding(text) for text in texts]
|
||||
return embeddings
|
||||
|
||||
@cached_property
|
||||
def _ollama_client(self) -> "ollama.Client":
|
||||
|
||||
@@ -3042,21 +3042,15 @@ class AsyncHybridQuery(AsyncQueryBase, AsyncVectorQueryBase):
|
||||
>>> asyncio.run(doctest_example()) # doctest: +ELLIPSIS, +NORMALIZE_WHITESPACE
|
||||
Vector Search Plan:
|
||||
ProjectionExec: expr=[vector@0 as vector, text@3 as text, _distance@2 as _distance]
|
||||
Take: columns="vector, _rowid, _distance, (text)"
|
||||
CoalesceBatchesExec: target_batch_size=1024
|
||||
GlobalLimitExec: skip=0, fetch=10
|
||||
FilterExec: _distance@2 IS NOT NULL
|
||||
SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], preserve_partitioning=[false]
|
||||
KNNVectorDistance: metric=l2
|
||||
LanceScan: uri=..., projection=[vector], row_id=true, row_addr=false, ordered=false
|
||||
<BLANKLINE>
|
||||
Take: columns="vector, _rowid, _distance, (text)"
|
||||
CoalesceBatchesExec: target_batch_size=1024
|
||||
GlobalLimitExec: skip=0, fetch=10
|
||||
FilterExec: _distance@2 IS NOT NULL
|
||||
SortExec: TopK(fetch=10), expr=[_distance@2 ASC NULLS LAST], preserve_partitioning=[false]
|
||||
KNNVectorDistance: metric=l2
|
||||
LanceScan: uri=..., projection=[vector], row_id=true, row_addr=false, ordered=false
|
||||
FTS Search Plan:
|
||||
ProjectionExec: expr=[vector@2 as vector, text@3 as text, _score@1 as _score]
|
||||
Take: columns="_rowid, _score, (vector), (text)"
|
||||
CoalesceBatchesExec: target_batch_size=1024
|
||||
GlobalLimitExec: skip=0, fetch=10
|
||||
MatchQuery: query=hello
|
||||
<BLANKLINE>
|
||||
LanceScan: uri=..., projection=[vector, text], row_id=false, row_addr=false, ordered=true
|
||||
|
||||
Parameters
|
||||
----------
|
||||
|
||||
@@ -775,82 +775,6 @@ async def test_explain_plan_async(table_async: AsyncTable):
|
||||
assert "KNN" in plan
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_explain_plan_fts(table_async: AsyncTable):
|
||||
"""Test explain plan for FTS queries"""
|
||||
# Create FTS index
|
||||
from lancedb.index import FTS
|
||||
|
||||
await table_async.create_index("text", config=FTS())
|
||||
|
||||
# Test pure FTS query
|
||||
query = await table_async.search("dog", query_type="fts", fts_columns="text")
|
||||
plan = await query.explain_plan()
|
||||
# Should show FTS details (issue #2465 is now fixed)
|
||||
assert "MatchQuery: query=dog" in plan
|
||||
assert "GlobalLimitExec" in plan # Default limit
|
||||
|
||||
# Test FTS query with limit
|
||||
query_with_limit = await table_async.search(
|
||||
"dog", query_type="fts", fts_columns="text"
|
||||
)
|
||||
plan_with_limit = await query_with_limit.limit(1).explain_plan()
|
||||
assert "MatchQuery: query=dog" in plan_with_limit
|
||||
assert "GlobalLimitExec: skip=0, fetch=1" in plan_with_limit
|
||||
|
||||
# Test FTS query with offset and limit
|
||||
query_with_offset = await table_async.search(
|
||||
"dog", query_type="fts", fts_columns="text"
|
||||
)
|
||||
plan_with_offset = await query_with_offset.offset(1).limit(1).explain_plan()
|
||||
assert "MatchQuery: query=dog" in plan_with_offset
|
||||
assert "GlobalLimitExec: skip=1, fetch=1" in plan_with_offset
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_explain_plan_vector_with_limit_offset(table_async: AsyncTable):
|
||||
"""Test explain plan for vector queries with limit and offset"""
|
||||
# Test vector query with limit
|
||||
plan_with_limit = await (
|
||||
table_async.query().nearest_to(pa.array([1, 2])).limit(1).explain_plan()
|
||||
)
|
||||
assert "KNN" in plan_with_limit
|
||||
assert "GlobalLimitExec: skip=0, fetch=1" in plan_with_limit
|
||||
|
||||
# Test vector query with offset and limit
|
||||
plan_with_offset = await (
|
||||
table_async.query()
|
||||
.nearest_to(pa.array([1, 2]))
|
||||
.offset(1)
|
||||
.limit(1)
|
||||
.explain_plan()
|
||||
)
|
||||
assert "KNN" in plan_with_offset
|
||||
assert "GlobalLimitExec: skip=1, fetch=1" in plan_with_offset
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_explain_plan_with_filters(table_async: AsyncTable):
|
||||
"""Test explain plan for queries with filters"""
|
||||
# Test vector query with filter
|
||||
plan_with_filter = await (
|
||||
table_async.query().nearest_to(pa.array([1, 2])).where("id = 1").explain_plan()
|
||||
)
|
||||
assert "KNN" in plan_with_filter
|
||||
assert "FilterExec" in plan_with_filter
|
||||
|
||||
# Test FTS query with filter
|
||||
from lancedb.index import FTS
|
||||
|
||||
await table_async.create_index("text", config=FTS())
|
||||
query_fts_filter = await table_async.search(
|
||||
"dog", query_type="fts", fts_columns="text"
|
||||
)
|
||||
plan_fts_filter = await query_fts_filter.where("id = 1").explain_plan()
|
||||
assert "MatchQuery: query=dog" in plan_fts_filter
|
||||
assert "FilterExec: id@" in plan_fts_filter # Should show filter details
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_query_camelcase_async(tmp_path):
|
||||
db = await lancedb.connect_async(tmp_path)
|
||||
|
||||
@@ -52,7 +52,7 @@ impl FromPyObject<'_> for PyLanceDB<FtsQuery> {
|
||||
let operator = ob.getattr("operator")?.extract::<String>()?;
|
||||
let prefix_length = ob.getattr("prefix_length")?.extract()?;
|
||||
|
||||
Ok(Self(
|
||||
Ok(PyLanceDB(
|
||||
MatchQuery::new(query)
|
||||
.with_column(Some(column))
|
||||
.with_boost(boost)
|
||||
@@ -70,7 +70,7 @@ impl FromPyObject<'_> for PyLanceDB<FtsQuery> {
|
||||
let column = ob.getattr("column")?.extract()?;
|
||||
let slop = ob.getattr("slop")?.extract()?;
|
||||
|
||||
Ok(Self(
|
||||
Ok(PyLanceDB(
|
||||
PhraseQuery::new(query)
|
||||
.with_column(Some(column))
|
||||
.with_slop(slop)
|
||||
@@ -78,10 +78,10 @@ impl FromPyObject<'_> for PyLanceDB<FtsQuery> {
|
||||
))
|
||||
}
|
||||
"BoostQuery" => {
|
||||
let positive: Self = ob.getattr("positive")?.extract()?;
|
||||
let negative: Self = ob.getattr("negative")?.extract()?;
|
||||
let positive: PyLanceDB<FtsQuery> = ob.getattr("positive")?.extract()?;
|
||||
let negative: PyLanceDB<FtsQuery> = ob.getattr("negative")?.extract()?;
|
||||
let negative_boost = ob.getattr("negative_boost")?.extract()?;
|
||||
Ok(Self(
|
||||
Ok(PyLanceDB(
|
||||
BoostQuery::new(positive.0, negative.0, negative_boost).into(),
|
||||
))
|
||||
}
|
||||
@@ -103,17 +103,18 @@ impl FromPyObject<'_> for PyLanceDB<FtsQuery> {
|
||||
let op = Operator::try_from(operator.as_str())
|
||||
.map_err(|e| PyValueError::new_err(format!("Invalid operator: {}", e)))?;
|
||||
|
||||
Ok(Self(q.with_operator(op).into()))
|
||||
Ok(PyLanceDB(q.with_operator(op).into()))
|
||||
}
|
||||
"BooleanQuery" => {
|
||||
let queries: Vec<(String, Self)> = ob.getattr("queries")?.extract()?;
|
||||
let queries: Vec<(String, PyLanceDB<FtsQuery>)> =
|
||||
ob.getattr("queries")?.extract()?;
|
||||
let mut sub_queries = Vec::with_capacity(queries.len());
|
||||
for (occur, q) in queries {
|
||||
let occur = Occur::try_from(occur.as_str())
|
||||
.map_err(|e| PyValueError::new_err(e.to_string()))?;
|
||||
sub_queries.push((occur, q.0));
|
||||
}
|
||||
Ok(Self(BooleanQuery::new(sub_queries).into()))
|
||||
Ok(PyLanceDB(BooleanQuery::new(sub_queries).into()))
|
||||
}
|
||||
name => Err(PyValueError::new_err(format!(
|
||||
"Unsupported FTS query type: {}",
|
||||
@@ -154,8 +155,8 @@ impl<'py> IntoPyObject<'py> for PyLanceDB<FtsQuery> {
|
||||
.call((query.terms, query.column.unwrap()), Some(&kwargs))
|
||||
}
|
||||
FtsQuery::Boost(query) => {
|
||||
let positive = Self(query.positive.as_ref().clone()).into_pyobject(py)?;
|
||||
let negative = Self(query.negative.as_ref().clone()).into_pyobject(py)?;
|
||||
let positive = PyLanceDB(query.positive.as_ref().clone()).into_pyobject(py)?;
|
||||
let negative = PyLanceDB(query.negative.as_ref().clone()).into_pyobject(py)?;
|
||||
let kwargs = PyDict::new(py);
|
||||
kwargs.set_item("negative_boost", query.negative_boost)?;
|
||||
namespace
|
||||
@@ -181,13 +182,13 @@ impl<'py> IntoPyObject<'py> for PyLanceDB<FtsQuery> {
|
||||
query.should.len() + query.must.len() + query.must_not.len(),
|
||||
);
|
||||
for q in query.should {
|
||||
queries.push((Occur::Should.into(), Self(q).into_pyobject(py)?));
|
||||
queries.push((Occur::Should.into(), PyLanceDB(q).into_pyobject(py)?));
|
||||
}
|
||||
for q in query.must {
|
||||
queries.push((Occur::Must.into(), Self(q).into_pyobject(py)?));
|
||||
queries.push((Occur::Must.into(), PyLanceDB(q).into_pyobject(py)?));
|
||||
}
|
||||
for q in query.must_not {
|
||||
queries.push((Occur::MustNot.into(), Self(q).into_pyobject(py)?));
|
||||
queries.push((Occur::MustNot.into(), PyLanceDB(q).into_pyobject(py)?));
|
||||
}
|
||||
|
||||
namespace
|
||||
@@ -562,10 +563,7 @@ impl FTSQuery {
|
||||
}
|
||||
|
||||
pub fn explain_plan(self_: PyRef<'_, Self>, verbose: bool) -> PyResult<Bound<'_, PyAny>> {
|
||||
let inner = self_
|
||||
.inner
|
||||
.clone()
|
||||
.full_text_search(self_.fts_query.clone());
|
||||
let inner = self_.inner.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
inner
|
||||
.explain_plan(verbose)
|
||||
@@ -575,10 +573,7 @@ impl FTSQuery {
|
||||
}
|
||||
|
||||
pub fn analyze_plan(self_: PyRef<'_, Self>) -> PyResult<Bound<'_, PyAny>> {
|
||||
let inner = self_
|
||||
.inner
|
||||
.clone()
|
||||
.full_text_search(self_.fts_query.clone());
|
||||
let inner = self_.inner.clone();
|
||||
future_into_py(self_.py(), async move {
|
||||
inner
|
||||
.analyze_plan()
|
||||
|
||||
@@ -105,7 +105,7 @@ impl ListingCatalog {
|
||||
}
|
||||
|
||||
async fn open_path(path: &str) -> Result<Self> {
|
||||
let (object_store, base_path) = ObjectStore::from_uri(path).await?;
|
||||
let (object_store, base_path) = ObjectStore::from_uri(path).await.unwrap();
|
||||
if object_store.is_local() {
|
||||
Self::try_create_dir(path).context(CreateDirSnafu { path })?;
|
||||
}
|
||||
|
||||
@@ -107,7 +107,7 @@ impl ObjectStore for MirroringObjectStore {
|
||||
self.primary.delete(location).await
|
||||
}
|
||||
|
||||
fn list(&self, prefix: Option<&Path>) -> BoxStream<'static, Result<ObjectMeta>> {
|
||||
fn list(&self, prefix: Option<&Path>) -> BoxStream<'_, Result<ObjectMeta>> {
|
||||
self.primary.list(prefix)
|
||||
}
|
||||
|
||||
|
||||
@@ -119,7 +119,7 @@ impl ObjectStore for IoTrackingStore {
|
||||
let result = self.target.get(location).await;
|
||||
if let Ok(result) = &result {
|
||||
let num_bytes = result.range.end - result.range.start;
|
||||
self.record_read(num_bytes);
|
||||
self.record_read(num_bytes as u64);
|
||||
}
|
||||
result
|
||||
}
|
||||
@@ -128,12 +128,12 @@ impl ObjectStore for IoTrackingStore {
|
||||
let result = self.target.get_opts(location, options).await;
|
||||
if let Ok(result) = &result {
|
||||
let num_bytes = result.range.end - result.range.start;
|
||||
self.record_read(num_bytes);
|
||||
self.record_read(num_bytes as u64);
|
||||
}
|
||||
result
|
||||
}
|
||||
|
||||
async fn get_range(&self, location: &Path, range: std::ops::Range<u64>) -> OSResult<Bytes> {
|
||||
async fn get_range(&self, location: &Path, range: std::ops::Range<usize>) -> OSResult<Bytes> {
|
||||
let result = self.target.get_range(location, range).await;
|
||||
if let Ok(result) = &result {
|
||||
self.record_read(result.len() as u64);
|
||||
@@ -144,7 +144,7 @@ impl ObjectStore for IoTrackingStore {
|
||||
async fn get_ranges(
|
||||
&self,
|
||||
location: &Path,
|
||||
ranges: &[std::ops::Range<u64>],
|
||||
ranges: &[std::ops::Range<usize>],
|
||||
) -> OSResult<Vec<Bytes>> {
|
||||
let result = self.target.get_ranges(location, ranges).await;
|
||||
if let Ok(result) = &result {
|
||||
@@ -170,7 +170,7 @@ impl ObjectStore for IoTrackingStore {
|
||||
self.target.delete_stream(locations)
|
||||
}
|
||||
|
||||
fn list(&self, prefix: Option<&Path>) -> BoxStream<'static, OSResult<ObjectMeta>> {
|
||||
fn list(&self, prefix: Option<&Path>) -> BoxStream<'_, OSResult<ObjectMeta>> {
|
||||
self.record_read(0);
|
||||
self.target.list(prefix)
|
||||
}
|
||||
@@ -179,7 +179,7 @@ impl ObjectStore for IoTrackingStore {
|
||||
&self,
|
||||
prefix: Option<&Path>,
|
||||
offset: &Path,
|
||||
) -> BoxStream<'static, OSResult<ObjectMeta>> {
|
||||
) -> BoxStream<'_, OSResult<ObjectMeta>> {
|
||||
self.record_read(0);
|
||||
self.target.list_with_offset(prefix, offset)
|
||||
}
|
||||
|
||||
@@ -392,18 +392,9 @@ pub mod tests {
|
||||
} else {
|
||||
expected_line.trim()
|
||||
};
|
||||
assert_eq!(
|
||||
&actual_trimmed[..expected_trimmed.len()],
|
||||
expected_trimmed,
|
||||
"\nactual:\n{physical_plan}\nexpected:\n{expected}"
|
||||
);
|
||||
assert_eq!(&actual_trimmed[..expected_trimmed.len()], expected_trimmed);
|
||||
}
|
||||
assert_eq!(
|
||||
lines_checked,
|
||||
expected.lines().count(),
|
||||
"\nlines_checked:\n{lines_checked}\nexpected:\n{}",
|
||||
expected.lines().count()
|
||||
);
|
||||
assert_eq!(lines_checked, expected.lines().count());
|
||||
}
|
||||
}
|
||||
|
||||
@@ -486,9 +477,9 @@ pub mod tests {
|
||||
TestFixture::check_plan(
|
||||
plan,
|
||||
"MetadataEraserExec
|
||||
RepartitionExec:...
|
||||
CoalesceBatchesExec:...
|
||||
FilterExec: i@0 >= 5
|
||||
RepartitionExec:...
|
||||
ProjectionExec:...
|
||||
LanceScan:...",
|
||||
)
|
||||
|
||||
@@ -129,9 +129,7 @@ impl DatasetRef {
|
||||
dataset: ref mut ds,
|
||||
..
|
||||
} => {
|
||||
if dataset.manifest().version > ds.manifest().version {
|
||||
*ds = dataset;
|
||||
}
|
||||
*ds = dataset;
|
||||
}
|
||||
_ => unreachable!("Dataset should be in latest mode at this point"),
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user