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...

9 Commits

Author SHA1 Message Date
Xuanwo
16a7e29639 Format python
Signed-off-by: Xuanwo <github@xuanwo.io>
2025-07-10 19:11:02 +08:00
Xuanwo
0e7a218d62 docs: Add examples for where in when_matched_update_all
Signed-off-by: Xuanwo <github@xuanwo.io>
2025-07-10 19:08:45 +08:00
CyrusAttoun
167fccc427 fix: change 'return' to 'raise' for unimplemented remote table function (#2484)
just noticed that we're doing a 'return' instead of a 'raise' while
trying to get remote functionality working for my project. I went ahead
and implemented tests for both of the unimplemented functions (to_pandas
and to_arrow) while I was in there.

---------

Co-authored-by: Cyrus Attoun <jattoun1@gmail.com>
2025-07-09 14:27:08 -07:00
Lance Release
2bffbcefa5 Bump version: 0.21.1-beta.0 → 0.21.1-beta.1 2025-07-09 05:54:20 +00:00
Lance Release
905552f993 Bump version: 0.24.1-beta.0 → 0.24.1-beta.1 2025-07-09 05:53:28 +00:00
BubbleCal
e4898c9313 chore: sync node package-lock (#2491)
Signed-off-by: BubbleCal <bubble-cal@outlook.com>
2025-07-09 12:34:03 +08:00
BubbleCal
cab36d94b2 feat: support to specify num_partitions and num_bits (#2488) 2025-07-09 11:36:09 +08:00
Weston Pace
b64252d4fd chore: don't require exact version of half (#2489)
I can't find any reason for pinning this dependency and the fact that it
is pinned can be kind of annoying to use downstream (e.g. datafusion
currently requires >= 2.6).
2025-07-08 08:36:04 -07:00
Lance Release
6fc006072c Bump version: 0.21.0 → 0.21.1-beta.0 2025-07-07 21:01:30 +00:00
27 changed files with 232 additions and 150 deletions

View File

@@ -1,5 +1,5 @@
[tool.bumpversion]
current_version = "0.21.0"
current_version = "0.21.1-beta.1"
parse = """(?x)
(?P<major>0|[1-9]\\d*)\\.
(?P<minor>0|[1-9]\\d*)\\.

8
Cargo.lock generated
View File

@@ -4314,7 +4314,7 @@ dependencies = [
[[package]]
name = "lancedb"
version = "0.21.0"
version = "0.21.1-beta.1"
dependencies = [
"arrow",
"arrow-array",
@@ -4401,7 +4401,7 @@ dependencies = [
[[package]]
name = "lancedb-node"
version = "0.21.0"
version = "0.21.1-beta.1"
dependencies = [
"arrow-array",
"arrow-ipc",
@@ -4426,7 +4426,7 @@ dependencies = [
[[package]]
name = "lancedb-nodejs"
version = "0.21.0"
version = "0.21.1-beta.1"
dependencies = [
"arrow-array",
"arrow-ipc",
@@ -4446,7 +4446,7 @@ dependencies = [
[[package]]
name = "lancedb-python"
version = "0.24.0"
version = "0.24.1-beta.1"
dependencies = [
"arrow",
"env_logger",

View File

@@ -46,7 +46,7 @@ datafusion-execution = "48.0"
datafusion-expr = "48.0"
datafusion-physical-plan = "48.0"
env_logger = "0.11"
half = { "version" = "=2.6.0", default-features = false, features = [
half = { "version" = "2.6.0", default-features = false, features = [
"num-traits",
] }
futures = "0"

View File

@@ -71,6 +71,45 @@ with merge insert, enable both `when_matched_update_all()` and
If a column is nullable, it can be omitted from input data and it will be
considered `null`. Columns can also be provided in any order.
### Conditional Updates
You can add a `where` clause to `when_matched_update_all()` to only update rows
that meet certain conditions. When using the `where` parameter, you must prefix
column names with either `source.` (for the new data) or `target.` (for the
existing data) to specify which table you're referencing.
=== "Python"
```python
# Only update rows where the target's status is 'active'
table.merge_insert("id")
.when_matched_update_all(where="target.status = 'active'")
.when_not_matched_insert_all()
.execute(new_data)
# Only update if the new price is higher than the existing price
table.merge_insert("product_id")
.when_matched_update_all(where="source.price > target.price")
.when_not_matched_insert_all()
.execute(new_data)
```
=== "Typescript"
```typescript
// Only update rows where the target's status is 'active'
await table.mergeInsert("id")
.whenMatchedUpdateAll({ where: "target.status = 'active'" })
.whenNotMatchedInsertAll()
.execute(newData);
// Only update if the new price is higher than the existing price
await table.mergeInsert("product_id")
.whenMatchedUpdateAll({ where: "source.price > target.price" })
.whenNotMatchedInsertAll()
.execute(newData);
```
## Insert-if-not-exists
To avoid inserting duplicate rows, you can use the insert-if-not-exists command.

View File

@@ -8,7 +8,7 @@
<parent>
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.21.0-final.0</version>
<version>0.21.1-beta.1</version>
<relativePath>../pom.xml</relativePath>
</parent>

View File

@@ -6,7 +6,7 @@
<groupId>com.lancedb</groupId>
<artifactId>lancedb-parent</artifactId>
<version>0.21.0-final.0</version>
<version>0.21.1-beta.1</version>
<packaging>pom</packaging>
<name>LanceDB Parent</name>

74
node/package-lock.json generated
View File

@@ -1,12 +1,12 @@
{
"name": "vectordb",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "vectordb",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"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": "0.21.1-beta.1",
"@lancedb/vectordb-darwin-x64": "0.21.1-beta.1",
"@lancedb/vectordb-linux-arm64-gnu": "0.21.1-beta.1",
"@lancedb/vectordb-linux-x64-gnu": "0.21.1-beta.1",
"@lancedb/vectordb-win32-x64-msvc": "0.21.1-beta.1"
},
"peerDependencies": {
"@apache-arrow/ts": "^14.0.2",
@@ -326,66 +326,6 @@
"@jridgewell/sourcemap-codec": "^1.4.10"
}
},
"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==",
"cpu": [
"arm64"
],
"optional": true,
"os": [
"darwin"
]
},
"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==",
"cpu": [
"x64"
],
"optional": true,
"os": [
"darwin"
]
},
"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==",
"cpu": [
"arm64"
],
"optional": true,
"os": [
"linux"
]
},
"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==",
"cpu": [
"x64"
],
"optional": true,
"os": [
"linux"
]
},
"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==",
"cpu": [
"x64"
],
"optional": true,
"os": [
"win32"
]
},
"node_modules/@neon-rs/cli": {
"version": "0.0.160",
"resolved": "https://registry.npmjs.org/@neon-rs/cli/-/cli-0.0.160.tgz",

View File

@@ -1,6 +1,6 @@
{
"name": "vectordb",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"description": " Serverless, low-latency vector database for AI applications",
"private": false,
"main": "dist/index.js",
@@ -89,10 +89,10 @@
}
},
"optionalDependencies": {
"@lancedb/vectordb-darwin-x64": "0.21.0",
"@lancedb/vectordb-darwin-arm64": "0.21.0",
"@lancedb/vectordb-linux-x64-gnu": "0.21.0",
"@lancedb/vectordb-linux-arm64-gnu": "0.21.0",
"@lancedb/vectordb-win32-x64-msvc": "0.21.0"
"@lancedb/vectordb-darwin-x64": "0.21.1-beta.1",
"@lancedb/vectordb-darwin-arm64": "0.21.1-beta.1",
"@lancedb/vectordb-linux-x64-gnu": "0.21.1-beta.1",
"@lancedb/vectordb-linux-arm64-gnu": "0.21.1-beta.1",
"@lancedb/vectordb-win32-x64-msvc": "0.21.1-beta.1"
}
}

View File

@@ -1,7 +1,7 @@
[package]
name = "lancedb-nodejs"
edition.workspace = true
version = "0.21.0"
version = "0.21.1-beta.1"
license.workspace = true
description.workspace = true
repository.workspace = true

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-darwin-arm64",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"os": ["darwin"],
"cpu": ["arm64"],
"main": "lancedb.darwin-arm64.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-darwin-x64",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"os": ["darwin"],
"cpu": ["x64"],
"main": "lancedb.darwin-x64.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-gnu",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-gnu.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-arm64-musl",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"os": ["linux"],
"cpu": ["arm64"],
"main": "lancedb.linux-arm64-musl.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-gnu",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-gnu.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-linux-x64-musl",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"os": ["linux"],
"cpu": ["x64"],
"main": "lancedb.linux-x64-musl.node",

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-arm64-msvc",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"os": [
"win32"
],

View File

@@ -1,6 +1,6 @@
{
"name": "@lancedb/lancedb-win32-x64-msvc",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"os": ["win32"],
"cpu": ["x64"],
"main": "lancedb.win32-x64-msvc.node",

View File

@@ -1,12 +1,12 @@
{
"name": "@lancedb/lancedb",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"lockfileVersion": 3,
"requires": true,
"packages": {
"": {
"name": "@lancedb/lancedb",
"version": "0.21.0",
"version": "0.21.1-beta.1",
"cpu": [
"x64",
"arm64"

View File

@@ -11,7 +11,7 @@
"ann"
],
"private": false,
"version": "0.21.0",
"version": "0.21.1-beta.1",
"main": "dist/index.js",
"exports": {
".": "./dist/index.js",

View File

@@ -1,5 +1,5 @@
[tool.bumpversion]
current_version = "0.24.1-beta.0"
current_version = "0.24.1-beta.1"
parse = """(?x)
(?P<major>0|[1-9]\\d*)\\.
(?P<minor>0|[1-9]\\d*)\\.

View File

@@ -1,6 +1,6 @@
[package]
name = "lancedb-python"
version = "0.24.1-beta.0"
version = "0.24.1-beta.1"
edition.workspace = true
description = "Python bindings for LanceDB"
license.workspace = true

View File

@@ -45,6 +45,16 @@ class LanceMergeInsertBuilder(object):
If there are multiple matches then the behavior is undefined.
Currently this causes multiple copies of the row to be created
but that behavior is subject to change.
Parameters
----------
where : Optional[str], default None
A SQL filter expression to apply to matched rows. The filter must
specify whether you are referencing the source table (new data) or
the target table (existing data) by prefixing column names with
"source." or "target." respectively.
Example: "target.status = 'active'" or "source.price > target.price"
"""
self._when_matched_update_all = True
self._when_matched_update_all_condition = where

View File

@@ -18,7 +18,7 @@ from lancedb._lancedb import (
UpdateResult,
)
from lancedb.embeddings.base import EmbeddingFunctionConfig
from lancedb.index import FTS, BTree, Bitmap, HnswPq, HnswSq, IvfFlat, IvfPq, LabelList
from lancedb.index import FTS, BTree, Bitmap, HnswSq, IvfFlat, IvfPq, LabelList
from lancedb.remote.db import LOOP
import pyarrow as pa
@@ -89,7 +89,7 @@ class RemoteTable(Table):
def to_pandas(self):
"""to_pandas() is not yet supported on LanceDB cloud."""
return NotImplementedError("to_pandas() is not yet supported on LanceDB cloud.")
raise NotImplementedError("to_pandas() is not yet supported on LanceDB cloud.")
def checkout(self, version: Union[int, str]):
return LOOP.run(self._table.checkout(version))
@@ -186,6 +186,8 @@ class RemoteTable(Table):
accelerator: Optional[str] = None,
index_type="vector",
wait_timeout: Optional[timedelta] = None,
*,
num_bits: int = 8,
):
"""Create an index on the table.
Currently, the only parameters that matter are
@@ -220,11 +222,6 @@ class RemoteTable(Table):
>>> table.create_index("l2", "vector") # doctest: +SKIP
"""
if num_partitions is not None:
logging.warning(
"num_partitions is not supported on LanceDB cloud."
"This parameter will be tuned automatically."
)
if num_sub_vectors is not None:
logging.warning(
"num_sub_vectors is not supported on LanceDB cloud."
@@ -244,13 +241,21 @@ class RemoteTable(Table):
index_type = index_type.upper()
if index_type == "VECTOR" or index_type == "IVF_PQ":
config = IvfPq(distance_type=metric)
config = IvfPq(
distance_type=metric,
num_partitions=num_partitions,
num_sub_vectors=num_sub_vectors,
num_bits=num_bits,
)
elif index_type == "IVF_HNSW_PQ":
config = HnswPq(distance_type=metric)
raise ValueError(
"IVF_HNSW_PQ is not supported on LanceDB cloud."
"Please use IVF_HNSW_SQ instead."
)
elif index_type == "IVF_HNSW_SQ":
config = HnswSq(distance_type=metric)
config = HnswSq(distance_type=metric, num_partitions=num_partitions)
elif index_type == "IVF_FLAT":
config = IvfFlat(distance_type=metric)
config = IvfFlat(distance_type=metric, num_partitions=num_partitions)
else:
raise ValueError(
f"Unknown vector index type: {index_type}. Valid options are"

View File

@@ -210,6 +210,25 @@ async def test_retry_error():
assert cause.status_code == 429
def test_table_unimplemented_functions():
def handler(request):
if request.path == "/v1/table/test/create/?mode=create":
request.send_response(200)
request.send_header("Content-Type", "application/json")
request.end_headers()
request.wfile.write(b"{}")
else:
request.send_response(404)
request.end_headers()
with mock_lancedb_connection(handler) as db:
table = db.create_table("test", [{"id": 1}])
with pytest.raises(NotImplementedError):
table.to_arrow()
with pytest.raises(NotImplementedError):
table.to_pandas()
def test_table_add_in_threadpool():
def handler(request):
if request.path == "/v1/table/test/insert/":

View File

@@ -1,6 +1,6 @@
[package]
name = "lancedb-node"
version = "0.21.0"
version = "0.21.1-beta.1"
description = "Serverless, low-latency vector database for AI applications"
license.workspace = true
edition.workspace = true

View File

@@ -1,6 +1,6 @@
[package]
name = "lancedb"
version = "0.21.0"
version = "0.21.1-beta.1"
edition.workspace = true
description = "LanceDB: A serverless, low-latency vector database for AI applications"
license.workspace = true

View File

@@ -57,6 +57,8 @@ use crate::{
};
const REQUEST_TIMEOUT_HEADER: HeaderName = HeaderName::from_static("x-request-timeout-ms");
const METRIC_TYPE_KEY: &str = "metric_type";
const INDEX_TYPE_KEY: &str = "index_type";
pub struct RemoteTags<'a, S: HttpSend = Sender> {
inner: &'a RemoteTable<S>,
@@ -997,23 +999,53 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
"column": column
});
let (index_type, distance_type) = match index.index {
match index.index {
// TODO: Should we pass the actual index parameters? SaaS does not
// yet support them.
Index::IvfFlat(index) => ("IVF_FLAT", Some(index.distance_type)),
Index::IvfPq(index) => ("IVF_PQ", Some(index.distance_type)),
Index::IvfHnswSq(index) => ("IVF_HNSW_SQ", Some(index.distance_type)),
Index::BTree(_) => ("BTREE", None),
Index::Bitmap(_) => ("BITMAP", None),
Index::LabelList(_) => ("LABEL_LIST", None),
Index::IvfFlat(index) => {
body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_FLAT".to_string());
body[METRIC_TYPE_KEY] =
serde_json::Value::String(index.distance_type.to_string().to_lowercase());
if let Some(num_partitions) = index.num_partitions {
body["num_partitions"] = serde_json::Value::Number(num_partitions.into());
}
}
Index::IvfPq(index) => {
body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_PQ".to_string());
body[METRIC_TYPE_KEY] =
serde_json::Value::String(index.distance_type.to_string().to_lowercase());
if let Some(num_partitions) = index.num_partitions {
body["num_partitions"] = serde_json::Value::Number(num_partitions.into());
}
if let Some(num_bits) = index.num_bits {
body["num_bits"] = serde_json::Value::Number(num_bits.into());
}
}
Index::IvfHnswSq(index) => {
body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_HNSW_SQ".to_string());
body[METRIC_TYPE_KEY] =
serde_json::Value::String(index.distance_type.to_string().to_lowercase());
if let Some(num_partitions) = index.num_partitions {
body["num_partitions"] = serde_json::Value::Number(num_partitions.into());
}
}
Index::BTree(_) => {
body[INDEX_TYPE_KEY] = serde_json::Value::String("BTREE".to_string());
}
Index::Bitmap(_) => {
body[INDEX_TYPE_KEY] = serde_json::Value::String("BITMAP".to_string());
}
Index::LabelList(_) => {
body[INDEX_TYPE_KEY] = serde_json::Value::String("LABEL_LIST".to_string());
}
Index::FTS(fts) => {
body[INDEX_TYPE_KEY] = serde_json::Value::String("FTS".to_string());
let params = serde_json::to_value(&fts).map_err(|e| Error::InvalidInput {
message: format!("failed to serialize FTS index params {:?}", e),
})?;
for (key, value) in params.as_object().unwrap() {
body[key] = value.clone();
}
("FTS", None)
}
Index::Auto => {
let schema = self.schema().await?;
@@ -1023,9 +1055,11 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
message: format!("Column {} not found in schema", column),
})?;
if supported_vector_data_type(field.data_type()) {
("IVF_PQ", Some(DistanceType::L2))
body[INDEX_TYPE_KEY] = serde_json::Value::String("IVF_PQ".to_string());
body[METRIC_TYPE_KEY] =
serde_json::Value::String(DistanceType::L2.to_string().to_lowercase());
} else if supported_btree_data_type(field.data_type()) {
("BTREE", None)
body[INDEX_TYPE_KEY] = serde_json::Value::String("BTREE".to_string());
} else {
return Err(Error::NotSupported {
message: format!(
@@ -1042,12 +1076,6 @@ impl<S: HttpSend> BaseTable for RemoteTable<S> {
})
}
};
body["index_type"] = serde_json::Value::String(index_type.into());
if let Some(distance_type) = distance_type {
// Phalanx expects this to be lowercase right now.
body["metric_type"] =
serde_json::Value::String(distance_type.to_string().to_lowercase());
}
let request = request.json(&body);
@@ -1429,11 +1457,12 @@ mod tests {
use chrono::{DateTime, Utc};
use futures::{future::BoxFuture, StreamExt, TryFutureExt};
use lance_index::scalar::inverted::query::MatchQuery;
use lance_index::scalar::FullTextSearchQuery;
use lance_index::scalar::{FullTextSearchQuery, InvertedIndexParams};
use reqwest::Body;
use rstest::rstest;
use serde_json::json;
use crate::index::vector::IvfFlatIndexBuilder;
use crate::index::vector::{IvfFlatIndexBuilder, IvfHnswSqIndexBuilder};
use crate::remote::db::DEFAULT_SERVER_VERSION;
use crate::remote::JSON_CONTENT_TYPE;
use crate::{
@@ -2433,29 +2462,79 @@ mod tests {
let cases = [
(
"IVF_FLAT",
Some("hamming"),
json!({
"metric_type": "hamming",
}),
Index::IvfFlat(IvfFlatIndexBuilder::default().distance_type(DistanceType::Hamming)),
),
("IVF_PQ", Some("l2"), Index::IvfPq(Default::default())),
(
"IVF_FLAT",
json!({
"metric_type": "hamming",
"num_partitions": 128,
}),
Index::IvfFlat(
IvfFlatIndexBuilder::default()
.distance_type(DistanceType::Hamming)
.num_partitions(128),
),
),
(
"IVF_PQ",
Some("cosine"),
Index::IvfPq(IvfPqIndexBuilder::default().distance_type(DistanceType::Cosine)),
json!({
"metric_type": "l2",
}),
Index::IvfPq(Default::default()),
),
(
"IVF_PQ",
json!({
"metric_type": "cosine",
"num_partitions": 128,
"num_bits": 4,
}),
Index::IvfPq(
IvfPqIndexBuilder::default()
.distance_type(DistanceType::Cosine)
.num_partitions(128)
.num_bits(4),
),
),
(
"IVF_HNSW_SQ",
Some("l2"),
json!({
"metric_type": "l2",
}),
Index::IvfHnswSq(Default::default()),
),
(
"IVF_HNSW_SQ",
json!({
"metric_type": "l2",
"num_partitions": 128,
}),
Index::IvfHnswSq(
IvfHnswSqIndexBuilder::default()
.distance_type(DistanceType::L2)
.num_partitions(128),
),
),
// HNSW_PQ isn't yet supported on SaaS
("BTREE", None, Index::BTree(Default::default())),
("BITMAP", None, Index::Bitmap(Default::default())),
("LABEL_LIST", None, Index::LabelList(Default::default())),
("FTS", None, Index::FTS(Default::default())),
("BTREE", json!({}), Index::BTree(Default::default())),
("BITMAP", json!({}), Index::Bitmap(Default::default())),
(
"LABEL_LIST",
json!({}),
Index::LabelList(Default::default()),
),
(
"FTS",
serde_json::to_value(InvertedIndexParams::default()).unwrap(),
Index::FTS(Default::default()),
),
];
for (index_type, distance_type, index) in cases {
let params = index.clone();
for (index_type, expected_body, index) in cases {
let table = Table::new_with_handler("my_table", move |request| {
assert_eq!(request.method(), "POST");
assert_eq!(request.url().path(), "/v1/table/my_table/create_index/");
@@ -2465,19 +2544,9 @@ mod tests {
);
let body = request.body().unwrap().as_bytes().unwrap();
let body: serde_json::Value = serde_json::from_slice(body).unwrap();
let mut expected_body = serde_json::json!({
"column": "a",
"index_type": index_type,
});
if let Some(distance_type) = distance_type {
expected_body["metric_type"] = distance_type.to_lowercase().into();
}
if let Index::FTS(fts) = &params {
let params = serde_json::to_value(fts).unwrap();
for (key, value) in params.as_object().unwrap() {
expected_body[key] = value.clone();
}
}
let mut expected_body = expected_body.clone();
expected_body["column"] = "a".into();
expected_body[INDEX_TYPE_KEY] = index_type.into();
assert_eq!(body, expected_body);