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2 Commits

Author SHA1 Message Date
qzhu
8e25e0c7f0 reformatted 2023-12-07 12:08:05 -08:00
qzhu
5f989e86d2 SaaS python SDK doc 2023-12-07 12:01:03 -08:00
79 changed files with 702 additions and 3429 deletions

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@@ -1,5 +1,5 @@
[bumpversion]
current_version = 0.4.1
current_version = 0.3.9
commit = True
message = Bump version: {current_version} → {new_version}
tag = True

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@@ -1,33 +0,0 @@
name: Bug Report - Node / Typescript
description: File a bug report
title: "bug(node): "
labels: [bug, typescript]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this bug report!
- type: input
id: version
attributes:
label: LanceDB version
description: What version of LanceDB are you using? `npm list | grep vectordb`.
placeholder: v0.3.2
validations:
required: false
- type: textarea
id: what-happened
attributes:
label: What happened?
description: Also tell us, what did you expect to happen?
validations:
required: true
- type: textarea
id: reproduction
attributes:
label: Are there known steps to reproduce?
description: |
Let us know how to reproduce the bug and we may be able to fix it more
quickly. This is not required, but it is helpful.
validations:
required: false

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@@ -1,33 +0,0 @@
name: Bug Report - Python
description: File a bug report
title: "bug(python): "
labels: [bug, python]
body:
- type: markdown
attributes:
value: |
Thanks for taking the time to fill out this bug report!
- type: input
id: version
attributes:
label: LanceDB version
description: What version of LanceDB are you using? `python -c "import lancedb; print(lancedb.__version__)"`.
placeholder: v0.3.2
validations:
required: false
- type: textarea
id: what-happened
attributes:
label: What happened?
description: Also tell us, what did you expect to happen?
validations:
required: true
- type: textarea
id: reproduction
attributes:
label: Are there known steps to reproduce?
description: |
Let us know how to reproduce the bug and we may be able to fix it more
quickly. This is not required, but it is helpful.
validations:
required: false

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@@ -1,5 +0,0 @@
blank_issues_enabled: true
contact_links:
- name: Discord Community Support
url: https://discord.com/invite/zMM32dvNtd
about: Please ask and answer questions here.

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@@ -1,23 +0,0 @@
name: 'Documentation improvement'
description: Report an issue with the documentation.
labels: [documentation]
body:
- type: textarea
id: description
attributes:
label: Description
description: >
Describe the issue with the documentation and how it can be fixed or improved.
validations:
required: true
- type: input
id: link
attributes:
label: Link
description: >
Provide a link to the existing documentation, if applicable.
placeholder: ex. https://lancedb.github.io/lancedb/guides/tables/...
validations:
required: false

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@@ -1,31 +0,0 @@
name: Feature suggestion
description: Suggestion a new feature for LanceDB
title: "Feature: "
labels: [enhancement]
body:
- type: markdown
attributes:
value: |
Share a new idea for a feature or improvement. Be sure to search existing
issues first to avoid duplicates.
- type: dropdown
id: sdk
attributes:
label: SDK
description: Which SDK are you using? This helps us prioritize.
options:
- Python
- Node
- Rust
default: 0
validations:
required: false
- type: textarea
id: description
attributes:
label: Description
description: |
Describe the feature and why it would be useful. If applicable, consider
providing a code example of what it might be like to use the feature.
validations:
required: true

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@@ -38,17 +38,13 @@ jobs:
node/vectordb-*.tgz
node-macos:
strategy:
matrix:
config:
- arch: x86_64-apple-darwin
runner: macos-13
- arch: aarch64-apple-darwin
# xlarge is implicitly arm64.
runner: macos-13-xlarge
runs-on: ${{ matrix.config.runner }}
runs-on: macos-13
# Only runs on tags that matches the make-release action
if: startsWith(github.ref, 'refs/tags/v')
strategy:
fail-fast: false
matrix:
target: [x86_64-apple-darwin, aarch64-apple-darwin]
steps:
- name: Checkout
uses: actions/checkout@v3
@@ -58,8 +54,11 @@ jobs:
run: |
cd node
npm ci
- name: Install rustup target
if: ${{ matrix.target == 'aarch64-apple-darwin' }}
run: rustup target add aarch64-apple-darwin
- name: Build MacOS native node modules
run: bash ci/build_macos_artifacts.sh ${{ matrix.config.arch }}
run: bash ci/build_macos_artifacts.sh ${{ matrix.target }}
- name: Upload Darwin Artifacts
uses: actions/upload-artifact@v3
with:
@@ -67,7 +66,6 @@ jobs:
path: |
node/dist/lancedb-vectordb-darwin*.tgz
node-linux:
name: node-linux (${{ matrix.config.arch}}-unknown-linux-gnu
runs-on: ${{ matrix.config.runner }}

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@@ -44,19 +44,12 @@ jobs:
run: pytest -m "not slow" -x -v --durations=30 tests
- name: doctest
run: pytest --doctest-modules lancedb
platform:
name: "Platform: ${{ matrix.config.name }}"
mac:
timeout-minutes: 30
strategy:
matrix:
config:
- name: x86 Mac
runner: macos-13
- name: Arm Mac
runner: macos-13-xlarge
- name: x86 Windows
runner: windows-latest
runs-on: "${{ matrix.config.runner }}"
mac-runner: [ "macos-13", "macos-13-xlarge" ]
runs-on: "${{ matrix.mac-runner }}"
defaults:
run:
shell: bash
@@ -98,7 +91,11 @@ jobs:
pip install "pydantic<2"
pip install -e .[tests]
pip install tantivy@git+https://github.com/quickwit-oss/tantivy-py#164adc87e1a033117001cf70e38c82a53014d985
pip install pytest pytest-mock
pip install pytest pytest-mock black isort
- name: Black
run: black --check --diff --no-color --quiet .
- name: isort
run: isort --check --diff --quiet .
- name: Run tests
run: pytest -m "not slow" -x -v --durations=30 tests
- name: doctest

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@@ -24,29 +24,6 @@ env:
RUST_BACKTRACE: "1"
jobs:
lint:
timeout-minutes: 30
runs-on: ubuntu-22.04
defaults:
run:
shell: bash
working-directory: rust
steps:
- uses: actions/checkout@v3
with:
fetch-depth: 0
lfs: true
- uses: Swatinem/rust-cache@v2
with:
workspaces: rust
- name: Install dependencies
run: |
sudo apt update
sudo apt install -y protobuf-compiler libssl-dev
- name: Run format
run: cargo fmt --all -- --check
- name: Run clippy
run: cargo clippy --all --all-features -- -D warnings
linux:
timeout-minutes: 30
runs-on: ubuntu-22.04

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@@ -5,24 +5,24 @@ exclude = ["python"]
resolver = "2"
[workspace.dependencies]
lance = { "version" = "=0.9.1", "features" = ["dynamodb"] }
lance-index = { "version" = "=0.9.1" }
lance-linalg = { "version" = "=0.9.1" }
lance-testing = { "version" = "=0.9.1" }
lance = { "version" = "=0.8.17", "features" = ["dynamodb"] }
lance-index = { "version" = "=0.8.17" }
lance-linalg = { "version" = "=0.8.17" }
lance-testing = { "version" = "=0.8.17" }
# Note that this one does not include pyarrow
arrow = { version = "49.0.0", optional = false }
arrow-array = "49.0"
arrow-data = "49.0"
arrow-ipc = "49.0"
arrow-ord = "49.0"
arrow-schema = "49.0"
arrow-arith = "49.0"
arrow-cast = "49.0"
arrow = { version = "47.0.0", optional = false }
arrow-array = "47.0"
arrow-data = "47.0"
arrow-ipc = "47.0"
arrow-ord = "47.0"
arrow-schema = "47.0"
arrow-arith = "47.0"
arrow-cast = "47.0"
chrono = "0.4.23"
half = { "version" = "=2.3.1", default-features = false, features = [
"num-traits",
] }
log = "0.4"
object_store = "0.8.0"
object_store = "0.7.1"
snafu = "0.7.4"
url = "2"

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@@ -5,11 +5,10 @@
**Developer-friendly, serverless vector database for AI applications**
<a href='https://github.com/lancedb/vectordb-recipes/tree/main' target="_blank"><img alt='LanceDB' src='https://img.shields.io/badge/VectorDB_Recipes-100000?style=for-the-badge&logo=LanceDB&logoColor=white&labelColor=645cfb&color=645cfb'/></a>
<a href='https://lancedb.github.io/lancedb/' target="_blank"><img alt='lancdb' src='https://img.shields.io/badge/DOCS-100000?style=for-the-badge&logo=lancdb&logoColor=white&labelColor=645cfb&color=645cfb'/></a>
[![Medium](https://img.shields.io/badge/Medium-12100E?style=for-the-badge&logo=medium&logoColor=white)](https://blog.lancedb.com/)
[![Discord](https://img.shields.io/badge/Discord-%235865F2.svg?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/zMM32dvNtd)
[![Twitter](https://img.shields.io/badge/Twitter-%231DA1F2.svg?style=for-the-badge&logo=Twitter&logoColor=white)](https://twitter.com/lancedb)
<a href="https://lancedb.github.io/lancedb/">Documentation</a>
<a href="https://blog.lancedb.com/">Blog</a>
<a href="https://discord.gg/zMM32dvNtd">Discord</a>
<a href="https://twitter.com/lancedb">Twitter</a>
</p>

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@@ -80,6 +80,7 @@ nav:
- Ingest Embedding Functions: embeddings/embedding_functions.md
- Available Functions: embeddings/default_embedding_functions.md
- Create Custom Embedding Functions: embeddings/api.md
- Example - Calculate CLIP Embeddings with Roboflow Inference: examples/image_embeddings_roboflow.md
- Example - Multi-lingual semantic search: notebooks/multi_lingual_example.ipynb
- Example - MultiModal CLIP Embeddings: notebooks/DisappearingEmbeddingFunction.ipynb
- 🔍 Python full-text search: fts.md
@@ -98,7 +99,6 @@ nav:
- YouTube Transcript Search: notebooks/youtube_transcript_search.ipynb
- Documentation QA Bot using LangChain: notebooks/code_qa_bot.ipynb
- Multimodal search using CLIP: notebooks/multimodal_search.ipynb
- Example - Calculate CLIP Embeddings with Roboflow Inference: examples/image_embeddings_roboflow.md
- Serverless QA Bot with S3 and Lambda: examples/serverless_lancedb_with_s3_and_lambda.md
- Serverless QA Bot with Modal: examples/serverless_qa_bot_with_modal_and_langchain.md
- 🌐 Javascript examples:

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@@ -2,4 +2,3 @@ mkdocs==1.4.2
mkdocs-jupyter==0.24.1
mkdocs-material==9.1.3
mkdocstrings[python]==0.20.0
pydantic

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@@ -64,26 +64,18 @@ We'll cover the basics of using LanceDB on your local machine in this section.
tbl = db.create_table("table_from_df", data=df)
```
!!! warning
If the table already exists, LanceDB will raise an error by default.
If you want to overwrite the table, you can pass in `mode="overwrite"`
to the `createTable` function.
=== "Javascript"
```javascript
const tb = await db.createTable(
"myTable",
[{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
const tb = await db.createTable("my_table",
data=[{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
```
!!! warning
If the table already exists, LanceDB will raise an error by default.
If you want to overwrite the table, you can pass in `"overwrite"`
to the `createTable` function like this: `await con.createTable(tableName, data, { writeMode: WriteMode.Overwrite })`
!!! warning
If the table already exists, LanceDB will raise an error by default.
If you want to overwrite the table, you can pass in `mode="overwrite"`
to the `createTable` function.
??? info "Under the hood, LanceDB is converting the input data into an Apache Arrow table and persisting it to disk in [Lance format](https://www.github.com/lancedb/lance)."
@@ -116,7 +108,7 @@ Once created, you can open a table using the following code:
=== "Javascript"
```javascript
const tbl = await db.openTable("myTable");
const tbl = await db.openTable("my_table");
```
If you forget the name of your table, you can always get a listing of all table names:
@@ -202,17 +194,10 @@ Use the `drop_table()` method on the database to remove a table.
db.drop_table("my_table")
```
This permanently removes the table and is not recoverable, unlike deleting rows.
By default, if the table does not exist an exception is raised. To suppress this,
you can pass in `ignore_missing=True`.
This permanently removes the table and is not recoverable, unlike deleting rows.
By default, if the table does not exist an exception is raised. To suppress this,
you can pass in `ignore_missing=True`.
=== "JavaScript"
```javascript
await db.dropTable('myTable')
```
This permanently removes the table and is not recoverable, unlike deleting rows.
If the table does not exist an exception is raised.
## What's next

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@@ -1,9 +1,9 @@
There are various Embedding functions available out of the box with LanceDB. We're working on supporting other popular embedding APIs.
There are various Embedding functions available out of the box with lancedb. We're working on supporting other popular embedding APIs.
## Text Embedding Functions
Here are the text embedding functions registered by default.
Embedding functions have an inbuilt rate limit handler wrapper for source and query embedding function calls that retry with exponential standoff.
Each `EmbeddingFunction` implementation automatically takes `max_retries` as an argument which has the default value of 7.
Embedding functions have inbuilt rate limit handler wrapper for source and query embedding function calls that retry with exponential standoff.
Each `EmbeddingFunction` implementation automatically takes `max_retries` as an argument which has the deafult value of 7.
### Sentence Transformers
Here are the parameters that you can set when registering a `sentence-transformers` object, and their default values:
@@ -69,15 +69,15 @@ print(actual.text)
```
### Instructor Embeddings
Instructor is an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e.g. classification, retrieval, clustering, text evaluation, etc.) and domains (e.g. science, finance, etc.) by simply providing the task instruction, without any finetuning.
Instructor is an instruction-finetuned text embedding model that can generate text embeddings tailored to any task (e.g., classification, retrieval, clustering, text evaluation, etc.) and domains (e.g., science, finance, etc.) by simply providing the task instruction, without any finetuning
If you want to calculate customized embeddings for specific sentences, you may follow the unified template to write instructions:
Represent the `domain` `text_type` for `task_objective`:
* `domain` is optional, and it specifies the domain of the text, e.g. science, finance, medicine, etc.
* `text_type` is required, and it specifies the encoding unit, e.g. sentence, document, paragraph, etc.
* `task_objective` is optional, and it specifies the objective of embedding, e.g. retrieve a document, classify the sentence, etc.
* `domain` is optional, and it specifies the domain of the text, e.g., science, finance, medicine, etc.
* `text_type` is required, and it specifies the encoding unit, e.g., sentence, document, paragraph, etc.
* `task_objective` is optional, and it specifies the objective of embedding, e.g., retrieve a document, classify the sentence, etc.
More information about the model can be found here - https://github.com/xlang-ai/instructor-embedding
@@ -119,10 +119,10 @@ tbl.add(texts)
```
## Multi-modal embedding functions
Multi-modal embedding functions allow you to query your table using both images and text.
Multi-modal embedding functions allow you query your table using both images and text.
### OpenClipEmbeddings
We support CLIP model embeddings using the open source alternative, open-clip which supports various customizations. It is registered as `open-clip` and supports the following customizations:
We support CLIP model embeddings using the open souce alternbative, open-clip which support various customizations. It is registered as `open-clip` and supports following customizations.
| Parameter | Type | Default Value | Description |

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@@ -1,7 +1,5 @@
<a href="https://colab.research.google.com/github/lancedb/lancedb/blob/main/docs/src/notebooks/tables_guide.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a><br/>
A Table is a collection of Records in a LanceDB Database. Tables in Lance have a schema that defines the columns and their types. These schemas can include nested columns and can evolve over time.
This guide will show how to create tables, insert data into them, and update the data. You can follow along on colab!
A Table is a collection of Records in a LanceDB Database. You can follow along on colab!
## Creating a LanceDB Table
@@ -203,8 +201,8 @@ This guide will show how to create tables, insert data into them, and update the
```javascript
data
const tb = await db.createTable("my_table",
[{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
data=[{"vector": [3.1, 4.1], "item": "foo", "price": 10.0},
{"vector": [5.9, 26.5], "item": "bar", "price": 20.0}])
```
!!! info "Note"
@@ -363,28 +361,19 @@ Use the `delete()` method on tables to delete rows from a table. To choose which
await tbl.countRows() // Returns 1
```
## Updating a Table
### Updating a Table [Experimental]
EXPERIMENTAL: Update rows in the table (not threadsafe).
This can be used to update zero to all rows depending on how many rows match the where clause. The update queries follow the form of a SQL UPDATE statement. The `where` parameter is a SQL filter that matches on the metadata columns. The `values` or `values_sql` parameters are used to provide the new values for the columns.
This can be used to update zero to all rows depending on how many rows match the where clause.
| Parameter | Type | Description |
| Parameter | Type | Description |
|---|---|---|
| `where` | `str` | The SQL where clause to use when updating rows. For example, `'x = 2'` or `'x IN (1, 2, 3)'`. The filter must not be empty, or it will error. |
| `values` | `dict` | The values to update. The keys are the column names and the values are the values to set. |
| `values_sql` | `dict` | The values to update. The keys are the column names and the values are the SQL expressions to set. For example, `{'x': 'x + 1'}` will increment the value of the `x` column by 1. |
!!! info "SQL syntax"
See [SQL filters](sql.md) for more information on the supported SQL syntax.
!!! warning "Warning"
Updating nested columns is not yet supported.
=== "Python"
API Reference: [lancedb.table.Table.update][]
```python
import lancedb
import pandas as pd
@@ -414,55 +403,6 @@ This can be used to update zero to all rows depending on how many rows match the
2 2 [10.0, 10.0]
```
=== "Javascript/Typescript"
API Reference: [vectordb.Table.update](../../javascript/interfaces/Table/#update)
```javascript
const lancedb = require("vectordb");
const db = await lancedb.connect("./.lancedb");
const data = [
{x: 1, vector: [1, 2]},
{x: 2, vector: [3, 4]},
{x: 3, vector: [5, 6]},
];
const tbl = await db.createTable("my_table", data)
await tbl.update({ where: "x = 2", values: {vector: [10, 10]} })
```
The `values` parameter is used to provide the new values for the columns as literal values. You can also use the `values_sql` / `valuesSql` parameter to provide SQL expressions for the new values. For example, you can use `values_sql="x + 1"` to increment the value of the `x` column by 1.
=== "Python"
```python
# Update the table where x = 2
table.update(valuesSql={"x": "x + 1"})
print(table.to_pandas())
```
Output
```shell
x vector
0 2 [1.0, 2.0]
1 4 [5.0, 6.0]
2 3 [10.0, 10.0]
```
=== "Javascript/Typescript"
```javascript
await tbl.update({ valuesSql: { x: "x + 1" } })
```
!!! info "Note"
When rows are updated, they are moved out of the index. The row will still show up in ANN queries, but the query will not be as fast as it would be if the row was in the index. If you update a large proportion of rows, consider rebuilding the index afterwards.
## What's Next?
Learn how to Query your tables and create indices

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@@ -11,13 +11,8 @@ npm install vectordb
```
This will download the appropriate native library for your platform. We currently
support:
* Linux (x86_64 and aarch64)
* MacOS (Intel and ARM/M1/M2)
* Windows (x86_64 only)
We do not yet support musl-based Linux (such as Alpine Linux) or aarch64 Windows.
support x86_64 Linux, aarch64 Linux, Intel MacOS, and ARM (M1/M2) MacOS. We do not
yet support Windows or musl-based Linux (such as Alpine Linux).
## Usage

View File

@@ -1,41 +0,0 @@
[vectordb](../README.md) / [Exports](../modules.md) / DefaultWriteOptions
# Class: DefaultWriteOptions
Write options when creating a Table.
## Implements
- [`WriteOptions`](../interfaces/WriteOptions.md)
## Table of contents
### Constructors
- [constructor](DefaultWriteOptions.md#constructor)
### Properties
- [writeMode](DefaultWriteOptions.md#writemode)
## Constructors
### constructor
**new DefaultWriteOptions**()
## Properties
### writeMode
**writeMode**: [`WriteMode`](../enums/WriteMode.md) = `WriteMode.Create`
A [WriteMode](../enums/WriteMode.md) to use on this operation
#### Implementation of
[WriteOptions](../interfaces/WriteOptions.md).[writeMode](../interfaces/WriteOptions.md#writemode)
#### Defined in
[index.ts:778](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L778)

View File

@@ -26,7 +26,7 @@ A connection to a LanceDB database.
### Methods
- [createTable](LocalConnection.md#createtable)
- [createTableImpl](LocalConnection.md#createtableimpl)
- [createTableArrow](LocalConnection.md#createtablearrow)
- [dropTable](LocalConnection.md#droptable)
- [openTable](LocalConnection.md#opentable)
- [tableNames](LocalConnection.md#tablenames)
@@ -46,7 +46,7 @@ A connection to a LanceDB database.
#### Defined in
[index.ts:355](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L355)
[index.ts:184](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L184)
## Properties
@@ -56,25 +56,17 @@ A connection to a LanceDB database.
#### Defined in
[index.ts:353](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L353)
[index.ts:182](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L182)
___
### \_options
`Private` `Readonly` **\_options**: () => [`ConnectionOptions`](../interfaces/ConnectionOptions.md)
#### Type declaration
▸ (): [`ConnectionOptions`](../interfaces/ConnectionOptions.md)
##### Returns
[`ConnectionOptions`](../interfaces/ConnectionOptions.md)
`Private` `Readonly` **\_options**: [`ConnectionOptions`](../interfaces/ConnectionOptions.md)
#### Defined in
[index.ts:352](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L352)
[index.ts:181](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L181)
## Accessors
@@ -92,34 +84,27 @@ ___
#### Defined in
[index.ts:360](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L360)
[index.ts:189](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L189)
## Methods
### createTable
**createTable**\<`T`\>(`name`, `data?`, `optsOrEmbedding?`, `opt?`): `Promise`\<[`Table`](../interfaces/Table.md)\<`T`\>\>
**createTable**(`name`, `data`, `mode?`): `Promise`<[`Table`](../interfaces/Table.md)<`number`[]\>\>
Creates a new Table, optionally initializing it with new data.
#### Type parameters
| Name |
| :------ |
| `T` |
Creates a new Table and initialize it with new data.
#### Parameters
| Name | Type |
| :------ | :------ |
| `name` | `string` \| [`CreateTableOptions`](../interfaces/CreateTableOptions.md)\<`T`\> |
| `data?` | `Record`\<`string`, `unknown`\>[] |
| `optsOrEmbedding?` | [`WriteOptions`](../interfaces/WriteOptions.md) \| [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)\<`T`\> |
| `opt?` | [`WriteOptions`](../interfaces/WriteOptions.md) |
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
| `data` | `Record`<`string`, `unknown`\>[] | Non-empty Array of Records to be inserted into the Table |
| `mode?` | [`WriteMode`](../enums/WriteMode.md) | The write mode to use when creating the table. |
#### Returns
`Promise`\<[`Table`](../interfaces/Table.md)\<`T`\>\>
`Promise`<[`Table`](../interfaces/Table.md)<`number`[]\>\>
#### Implementation of
@@ -127,94 +112,33 @@ Creates a new Table, optionally initializing it with new data.
#### Defined in
[index.ts:395](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L395)
[index.ts:230](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L230)
___
### createTableImpl
`Private` **createTableImpl**\<`T`\>(`«destructured»`): `Promise`\<[`Table`](../interfaces/Table.md)\<`T`\>\>
#### Type parameters
| Name |
| :------ |
| `T` |
**createTable**(`name`, `data`, `mode`): `Promise`<[`Table`](../interfaces/Table.md)<`number`[]\>\>
#### Parameters
| Name | Type |
| :------ | :------ |
| `«destructured»` | `Object` |
|  `data?` | `Table`\<`any`\> \| `Record`\<`string`, `unknown`\>[] |
|  `embeddingFunction?` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)\<`T`\> |
|  `name` | `string` |
|  `schema?` | `Schema`\<`any`\> |
|  `writeOptions?` | [`WriteOptions`](../interfaces/WriteOptions.md) |
| `name` | `string` |
| `data` | `Record`<`string`, `unknown`\>[] |
| `mode` | [`WriteMode`](../enums/WriteMode.md) |
#### Returns
`Promise`\<[`Table`](../interfaces/Table.md)\<`T`\>\>
#### Defined in
[index.ts:413](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L413)
___
### dropTable
**dropTable**(`name`): `Promise`\<`void`\>
Drop an existing table.
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table to drop. |
#### Returns
`Promise`\<`void`\>
`Promise`<[`Table`](../interfaces/Table.md)<`number`[]\>\>
#### Implementation of
[Connection](../interfaces/Connection.md).[dropTable](../interfaces/Connection.md#droptable)
Connection.createTable
#### Defined in
[index.ts:453](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L453)
[index.ts:231](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L231)
___
**createTable**<`T`\>(`name`, `data`, `mode`, `embeddings`): `Promise`<[`Table`](../interfaces/Table.md)<`T`\>\>
### openTable
**openTable**(`name`): `Promise`\<[`Table`](../interfaces/Table.md)\<`number`[]\>\>
Open a table in the database.
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
#### Returns
`Promise`\<[`Table`](../interfaces/Table.md)\<`number`[]\>\>
#### Implementation of
[Connection](../interfaces/Connection.md).[openTable](../interfaces/Connection.md#opentable)
#### Defined in
[index.ts:376](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L376)
**openTable**\<`T`\>(`name`, `embeddings`): `Promise`\<[`Table`](../interfaces/Table.md)\<`T`\>\>
Open a table in the database.
Creates a new Table and initialize it with new data.
#### Type parameters
@@ -227,21 +151,23 @@ Open a table in the database.
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
| `embeddings` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)\<`T`\> | An embedding function to use on this Table |
| `data` | `Record`<`string`, `unknown`\>[] | Non-empty Array of Records to be inserted into the Table |
| `mode` | [`WriteMode`](../enums/WriteMode.md) | The write mode to use when creating the table. |
| `embeddings` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)<`T`\> | An embedding function to use on this Table |
#### Returns
`Promise`\<[`Table`](../interfaces/Table.md)\<`T`\>\>
`Promise`<[`Table`](../interfaces/Table.md)<`T`\>\>
#### Implementation of
Connection.openTable
Connection.createTable
#### Defined in
[index.ts:384](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L384)
[index.ts:241](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L241)
**openTable**\<`T`\>(`name`, `embeddings?`): `Promise`\<[`Table`](../interfaces/Table.md)\<`T`\>\>
**createTable**<`T`\>(`name`, `data`, `mode`, `embeddings?`): `Promise`<[`Table`](../interfaces/Table.md)<`T`\>\>
#### Type parameters
@@ -254,11 +180,119 @@ Connection.openTable
| Name | Type |
| :------ | :------ |
| `name` | `string` |
| `embeddings?` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)\<`T`\> |
| `data` | `Record`<`string`, `unknown`\>[] |
| `mode` | [`WriteMode`](../enums/WriteMode.md) |
| `embeddings?` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)<`T`\> |
#### Returns
`Promise`\<[`Table`](../interfaces/Table.md)\<`T`\>\>
`Promise`<[`Table`](../interfaces/Table.md)<`T`\>\>
#### Implementation of
Connection.createTable
#### Defined in
[index.ts:242](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L242)
___
### createTableArrow
**createTableArrow**(`name`, `table`): `Promise`<[`Table`](../interfaces/Table.md)<`number`[]\>\>
#### Parameters
| Name | Type |
| :------ | :------ |
| `name` | `string` |
| `table` | `Table`<`any`\> |
#### Returns
`Promise`<[`Table`](../interfaces/Table.md)<`number`[]\>\>
#### Implementation of
[Connection](../interfaces/Connection.md).[createTableArrow](../interfaces/Connection.md#createtablearrow)
#### Defined in
[index.ts:266](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L266)
___
### dropTable
**dropTable**(`name`): `Promise`<`void`\>
Drop an existing table.
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table to drop. |
#### Returns
`Promise`<`void`\>
#### Implementation of
[Connection](../interfaces/Connection.md).[dropTable](../interfaces/Connection.md#droptable)
#### Defined in
[index.ts:276](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L276)
___
### openTable
**openTable**(`name`): `Promise`<[`Table`](../interfaces/Table.md)<`number`[]\>\>
Open a table in the database.
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
#### Returns
`Promise`<[`Table`](../interfaces/Table.md)<`number`[]\>\>
#### Implementation of
[Connection](../interfaces/Connection.md).[openTable](../interfaces/Connection.md#opentable)
#### Defined in
[index.ts:205](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L205)
**openTable**<`T`\>(`name`, `embeddings`): `Promise`<[`Table`](../interfaces/Table.md)<`T`\>\>
Open a table in the database.
#### Type parameters
| Name |
| :------ |
| `T` |
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
| `embeddings` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)<`T`\> | An embedding function to use on this Table |
#### Returns
`Promise`<[`Table`](../interfaces/Table.md)<`T`\>\>
#### Implementation of
@@ -266,19 +300,46 @@ Connection.openTable
#### Defined in
[index.ts:385](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L385)
[index.ts:212](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L212)
**openTable**<`T`\>(`name`, `embeddings?`): `Promise`<[`Table`](../interfaces/Table.md)<`T`\>\>
#### Type parameters
| Name |
| :------ |
| `T` |
#### Parameters
| Name | Type |
| :------ | :------ |
| `name` | `string` |
| `embeddings?` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)<`T`\> |
#### Returns
`Promise`<[`Table`](../interfaces/Table.md)<`T`\>\>
#### Implementation of
Connection.openTable
#### Defined in
[index.ts:213](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L213)
___
### tableNames
**tableNames**(): `Promise`\<`string`[]\>
**tableNames**(): `Promise`<`string`[]\>
Get the names of all tables in the database.
#### Returns
`Promise`\<`string`[]\>
`Promise`<`string`[]\>
#### Implementation of
@@ -286,4 +347,4 @@ Get the names of all tables in the database.
#### Defined in
[index.ts:367](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L367)
[index.ts:196](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L196)

View File

@@ -1,6 +1,6 @@
[vectordb](../README.md) / [Exports](../modules.md) / LocalTable
# Class: LocalTable\<T\>
# Class: LocalTable<T\>
A LanceDB Table is the collection of Records. Each Record has one or more vector fields.
@@ -12,7 +12,7 @@ A LanceDB Table is the collection of Records. Each Record has one or more vector
## Implements
- [`Table`](../interfaces/Table.md)\<`T`\>
- [`Table`](../interfaces/Table.md)<`T`\>
## Table of contents
@@ -26,7 +26,6 @@ A LanceDB Table is the collection of Records. Each Record has one or more vector
- [\_name](LocalTable.md#_name)
- [\_options](LocalTable.md#_options)
- [\_tbl](LocalTable.md#_tbl)
- [where](LocalTable.md#where)
### Accessors
@@ -35,23 +34,17 @@ A LanceDB Table is the collection of Records. Each Record has one or more vector
### Methods
- [add](LocalTable.md#add)
- [cleanupOldVersions](LocalTable.md#cleanupoldversions)
- [compactFiles](LocalTable.md#compactfiles)
- [countRows](LocalTable.md#countrows)
- [createIndex](LocalTable.md#createindex)
- [delete](LocalTable.md#delete)
- [filter](LocalTable.md#filter)
- [indexStats](LocalTable.md#indexstats)
- [listIndices](LocalTable.md#listindices)
- [overwrite](LocalTable.md#overwrite)
- [search](LocalTable.md#search)
- [update](LocalTable.md#update)
## Constructors
### constructor
**new LocalTable**\<`T`\>(`tbl`, `name`, `options`)
**new LocalTable**<`T`\>(`tbl`, `name`, `options`)
#### Type parameters
@@ -69,9 +62,9 @@ A LanceDB Table is the collection of Records. Each Record has one or more vector
#### Defined in
[index.ts:464](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L464)
[index.ts:287](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L287)
**new LocalTable**\<`T`\>(`tbl`, `name`, `options`, `embeddings`)
**new LocalTable**<`T`\>(`tbl`, `name`, `options`, `embeddings`)
#### Type parameters
@@ -86,21 +79,21 @@ A LanceDB Table is the collection of Records. Each Record has one or more vector
| `tbl` | `any` | |
| `name` | `string` | |
| `options` | [`ConnectionOptions`](../interfaces/ConnectionOptions.md) | |
| `embeddings` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)\<`T`\> | An embedding function to use when interacting with this table |
| `embeddings` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)<`T`\> | An embedding function to use when interacting with this table |
#### Defined in
[index.ts:471](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L471)
[index.ts:294](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L294)
## Properties
### \_embeddings
`Private` `Optional` `Readonly` **\_embeddings**: [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)\<`T`\>
`Private` `Optional` `Readonly` **\_embeddings**: [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)<`T`\>
#### Defined in
[index.ts:461](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L461)
[index.ts:284](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L284)
___
@@ -110,61 +103,27 @@ ___
#### Defined in
[index.ts:460](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L460)
[index.ts:283](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L283)
___
### \_options
`Private` `Readonly` **\_options**: () => [`ConnectionOptions`](../interfaces/ConnectionOptions.md)
#### Type declaration
▸ (): [`ConnectionOptions`](../interfaces/ConnectionOptions.md)
##### Returns
[`ConnectionOptions`](../interfaces/ConnectionOptions.md)
`Private` `Readonly` **\_options**: [`ConnectionOptions`](../interfaces/ConnectionOptions.md)
#### Defined in
[index.ts:462](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L462)
[index.ts:285](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L285)
___
### \_tbl
`Private` **\_tbl**: `any`
`Private` `Readonly` **\_tbl**: `any`
#### Defined in
[index.ts:459](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L459)
___
### where
**where**: (`value`: `string`) => [`Query`](Query.md)\<`T`\>
#### Type declaration
▸ (`value`): [`Query`](Query.md)\<`T`\>
Creates a filter query to find all rows matching the specified criteria
##### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `value` | `string` | The filter criteria (like SQL where clause syntax) |
##### Returns
[`Query`](Query.md)\<`T`\>
#### Defined in
[index.ts:499](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L499)
[index.ts:282](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L282)
## Accessors
@@ -182,13 +141,13 @@ Creates a filter query to find all rows matching the specified criteria
#### Defined in
[index.ts:479](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L479)
[index.ts:302](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L302)
## Methods
### add
**add**(`data`): `Promise`\<`number`\>
**add**(`data`): `Promise`<`number`\>
Insert records into this Table.
@@ -196,11 +155,11 @@ Insert records into this Table.
| Name | Type | Description |
| :------ | :------ | :------ |
| `data` | `Record`\<`string`, `unknown`\>[] | Records to be inserted into the Table |
| `data` | `Record`<`string`, `unknown`\>[] | Records to be inserted into the Table |
#### Returns
`Promise`\<`number`\>
`Promise`<`number`\>
The number of rows added to the table
@@ -210,69 +169,19 @@ The number of rows added to the table
#### Defined in
[index.ts:507](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L507)
___
### cleanupOldVersions
**cleanupOldVersions**(`olderThan?`, `deleteUnverified?`): `Promise`\<[`CleanupStats`](../interfaces/CleanupStats.md)\>
Clean up old versions of the table, freeing disk space.
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `olderThan?` | `number` | The minimum age in minutes of the versions to delete. If not provided, defaults to two weeks. |
| `deleteUnverified?` | `boolean` | Because they may be part of an in-progress transaction, uncommitted files newer than 7 days old are not deleted by default. This means that failed transactions can leave around data that takes up disk space for up to 7 days. You can override this safety mechanism by setting this option to `true`, only if you promise there are no in progress writes while you run this operation. Failure to uphold this promise can lead to corrupted tables. |
#### Returns
`Promise`\<[`CleanupStats`](../interfaces/CleanupStats.md)\>
#### Defined in
[index.ts:596](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L596)
___
### compactFiles
**compactFiles**(`options?`): `Promise`\<[`CompactionMetrics`](../interfaces/CompactionMetrics.md)\>
Run the compaction process on the table.
This can be run after making several small appends to optimize the table
for faster reads.
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `options?` | [`CompactionOptions`](../interfaces/CompactionOptions.md) | Advanced options configuring compaction. In most cases, you can omit this arguments, as the default options are sensible for most tables. |
#### Returns
`Promise`\<[`CompactionMetrics`](../interfaces/CompactionMetrics.md)\>
Metrics about the compaction operation.
#### Defined in
[index.ts:615](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L615)
[index.ts:320](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L320)
___
### countRows
**countRows**(): `Promise`\<`number`\>
**countRows**(): `Promise`<`number`\>
Returns the number of rows in this table.
#### Returns
`Promise`\<`number`\>
`Promise`<`number`\>
#### Implementation of
@@ -280,16 +189,20 @@ Returns the number of rows in this table.
#### Defined in
[index.ts:543](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L543)
[index.ts:362](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L362)
___
### createIndex
**createIndex**(`indexParams`): `Promise`\<`any`\>
**createIndex**(`indexParams`): `Promise`<`any`\>
Create an ANN index on this Table vector index.
**`See`**
VectorIndexParams.
#### Parameters
| Name | Type | Description |
@@ -298,11 +211,7 @@ Create an ANN index on this Table vector index.
#### Returns
`Promise`\<`any`\>
**`See`**
VectorIndexParams.
`Promise`<`any`\>
#### Implementation of
@@ -310,13 +219,13 @@ VectorIndexParams.
#### Defined in
[index.ts:536](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L536)
[index.ts:355](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L355)
___
### delete
**delete**(`filter`): `Promise`\<`void`\>
**delete**(`filter`): `Promise`<`void`\>
Delete rows from this table.
@@ -328,7 +237,7 @@ Delete rows from this table.
#### Returns
`Promise`\<`void`\>
`Promise`<`void`\>
#### Implementation of
@@ -336,81 +245,13 @@ Delete rows from this table.
#### Defined in
[index.ts:552](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L552)
___
### filter
**filter**(`value`): [`Query`](Query.md)\<`T`\>
Creates a filter query to find all rows matching the specified criteria
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `value` | `string` | The filter criteria (like SQL where clause syntax) |
#### Returns
[`Query`](Query.md)\<`T`\>
#### Defined in
[index.ts:495](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L495)
___
### indexStats
**indexStats**(`indexUuid`): `Promise`\<[`IndexStats`](../interfaces/IndexStats.md)\>
Get statistics about an index.
#### Parameters
| Name | Type |
| :------ | :------ |
| `indexUuid` | `string` |
#### Returns
`Promise`\<[`IndexStats`](../interfaces/IndexStats.md)\>
#### Implementation of
[Table](../interfaces/Table.md).[indexStats](../interfaces/Table.md#indexstats)
#### Defined in
[index.ts:628](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L628)
___
### listIndices
**listIndices**(): `Promise`\<[`VectorIndex`](../interfaces/VectorIndex.md)[]\>
List the indicies on this table.
#### Returns
`Promise`\<[`VectorIndex`](../interfaces/VectorIndex.md)[]\>
#### Implementation of
[Table](../interfaces/Table.md).[listIndices](../interfaces/Table.md#listindices)
#### Defined in
[index.ts:624](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L624)
[index.ts:371](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L371)
___
### overwrite
**overwrite**(`data`): `Promise`\<`number`\>
**overwrite**(`data`): `Promise`<`number`\>
Insert records into this Table, replacing its contents.
@@ -418,11 +259,11 @@ Insert records into this Table, replacing its contents.
| Name | Type | Description |
| :------ | :------ | :------ |
| `data` | `Record`\<`string`, `unknown`\>[] | Records to be inserted into the Table |
| `data` | `Record`<`string`, `unknown`\>[] | Records to be inserted into the Table |
#### Returns
`Promise`\<`number`\>
`Promise`<`number`\>
The number of rows added to the table
@@ -432,13 +273,13 @@ The number of rows added to the table
#### Defined in
[index.ts:522](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L522)
[index.ts:338](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L338)
___
### search
**search**(`query`): [`Query`](Query.md)\<`T`\>
**search**(`query`): [`Query`](Query.md)<`T`\>
Creates a search query to find the nearest neighbors of the given search term
@@ -450,7 +291,7 @@ Creates a search query to find the nearest neighbors of the given search term
#### Returns
[`Query`](Query.md)\<`T`\>
[`Query`](Query.md)<`T`\>
#### Implementation of
@@ -458,30 +299,4 @@ Creates a search query to find the nearest neighbors of the given search term
#### Defined in
[index.ts:487](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L487)
___
### update
**update**(`args`): `Promise`\<`void`\>
Update rows in this table.
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `args` | [`UpdateArgs`](../interfaces/UpdateArgs.md) \| [`UpdateSqlArgs`](../interfaces/UpdateSqlArgs.md) | see [UpdateArgs](../interfaces/UpdateArgs.md) and [UpdateSqlArgs](../interfaces/UpdateSqlArgs.md) for more details |
#### Returns
`Promise`\<`void`\>
#### Implementation of
[Table](../interfaces/Table.md).[update](../interfaces/Table.md#update)
#### Defined in
[index.ts:563](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L563)
[index.ts:310](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L310)

View File

@@ -6,7 +6,7 @@ An embedding function that automatically creates vector representation for a giv
## Implements
- [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)\<`string`\>
- [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)<`string`\>
## Table of contents
@@ -40,7 +40,7 @@ An embedding function that automatically creates vector representation for a giv
#### Defined in
[embedding/openai.ts:21](https://github.com/lancedb/lancedb/blob/7856a94/node/src/embedding/openai.ts#L21)
[embedding/openai.ts:21](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/embedding/openai.ts#L21)
## Properties
@@ -50,7 +50,7 @@ An embedding function that automatically creates vector representation for a giv
#### Defined in
[embedding/openai.ts:19](https://github.com/lancedb/lancedb/blob/7856a94/node/src/embedding/openai.ts#L19)
[embedding/openai.ts:19](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/embedding/openai.ts#L19)
___
@@ -60,7 +60,7 @@ ___
#### Defined in
[embedding/openai.ts:18](https://github.com/lancedb/lancedb/blob/7856a94/node/src/embedding/openai.ts#L18)
[embedding/openai.ts:18](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/embedding/openai.ts#L18)
___
@@ -76,13 +76,13 @@ The name of the column that will be used as input for the Embedding Function.
#### Defined in
[embedding/openai.ts:50](https://github.com/lancedb/lancedb/blob/7856a94/node/src/embedding/openai.ts#L50)
[embedding/openai.ts:50](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/embedding/openai.ts#L50)
## Methods
### embed
**embed**(`data`): `Promise`\<`number`[][]\>
**embed**(`data`): `Promise`<`number`[][]\>
Creates a vector representation for the given values.
@@ -94,7 +94,7 @@ Creates a vector representation for the given values.
#### Returns
`Promise`\<`number`[][]\>
`Promise`<`number`[][]\>
#### Implementation of
@@ -102,4 +102,4 @@ Creates a vector representation for the given values.
#### Defined in
[embedding/openai.ts:38](https://github.com/lancedb/lancedb/blob/7856a94/node/src/embedding/openai.ts#L38)
[embedding/openai.ts:38](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/embedding/openai.ts#L38)

View File

@@ -1,6 +1,6 @@
[vectordb](../README.md) / [Exports](../modules.md) / Query
# Class: Query\<T\>
# Class: Query<T\>
A builder for nearest neighbor queries for LanceDB.
@@ -23,7 +23,6 @@ A builder for nearest neighbor queries for LanceDB.
- [\_limit](Query.md#_limit)
- [\_metricType](Query.md#_metrictype)
- [\_nprobes](Query.md#_nprobes)
- [\_prefilter](Query.md#_prefilter)
- [\_query](Query.md#_query)
- [\_queryVector](Query.md#_queryvector)
- [\_refineFactor](Query.md#_refinefactor)
@@ -35,11 +34,9 @@ A builder for nearest neighbor queries for LanceDB.
- [execute](Query.md#execute)
- [filter](Query.md#filter)
- [isElectron](Query.md#iselectron)
- [limit](Query.md#limit)
- [metricType](Query.md#metrictype)
- [nprobes](Query.md#nprobes)
- [prefilter](Query.md#prefilter)
- [refineFactor](Query.md#refinefactor)
- [select](Query.md#select)
@@ -47,7 +44,7 @@ A builder for nearest neighbor queries for LanceDB.
### constructor
**new Query**\<`T`\>(`query?`, `tbl?`, `embeddings?`)
**new Query**<`T`\>(`tbl`, `query`, `embeddings?`)
#### Type parameters
@@ -59,23 +56,23 @@ A builder for nearest neighbor queries for LanceDB.
| Name | Type |
| :------ | :------ |
| `query?` | `T` |
| `tbl?` | `any` |
| `embeddings?` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)\<`T`\> |
| `tbl` | `any` |
| `query` | `T` |
| `embeddings?` | [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)<`T`\> |
#### Defined in
[query.ts:38](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L38)
[index.ts:448](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L448)
## Properties
### \_embeddings
`Protected` `Optional` `Readonly` **\_embeddings**: [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)\<`T`\>
`Private` `Optional` `Readonly` **\_embeddings**: [`EmbeddingFunction`](../interfaces/EmbeddingFunction.md)<`T`\>
#### Defined in
[query.ts:36](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L36)
[index.ts:446](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L446)
___
@@ -85,17 +82,17 @@ ___
#### Defined in
[query.ts:33](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L33)
[index.ts:444](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L444)
___
### \_limit
`Private` `Optional` **\_limit**: `number`
`Private` **\_limit**: `number`
#### Defined in
[query.ts:29](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L29)
[index.ts:440](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L440)
___
@@ -105,7 +102,7 @@ ___
#### Defined in
[query.ts:34](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L34)
[index.ts:445](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L445)
___
@@ -115,27 +112,17 @@ ___
#### Defined in
[query.ts:31](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L31)
___
### \_prefilter
`Private` **\_prefilter**: `boolean`
#### Defined in
[query.ts:35](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L35)
[index.ts:442](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L442)
___
### \_query
`Private` `Optional` `Readonly` **\_query**: `T`
`Private` `Readonly` **\_query**: `T`
#### Defined in
[query.ts:26](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L26)
[index.ts:438](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L438)
___
@@ -145,7 +132,7 @@ ___
#### Defined in
[query.ts:28](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L28)
[index.ts:439](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L439)
___
@@ -155,7 +142,7 @@ ___
#### Defined in
[query.ts:30](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L30)
[index.ts:441](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L441)
___
@@ -165,27 +152,27 @@ ___
#### Defined in
[query.ts:32](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L32)
[index.ts:443](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L443)
___
### \_tbl
`Private` `Optional` `Readonly` **\_tbl**: `any`
`Private` `Readonly` **\_tbl**: `any`
#### Defined in
[query.ts:27](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L27)
[index.ts:437](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L437)
___
### where
**where**: (`value`: `string`) => [`Query`](Query.md)\<`T`\>
**where**: (`value`: `string`) => [`Query`](Query.md)<`T`\>
#### Type declaration
▸ (`value`): [`Query`](Query.md)\<`T`\>
▸ (`value`): [`Query`](Query.md)<`T`\>
A filter statement to be applied to this query.
@@ -197,17 +184,17 @@ A filter statement to be applied to this query.
##### Returns
[`Query`](Query.md)\<`T`\>
[`Query`](Query.md)<`T`\>
#### Defined in
[query.ts:87](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L87)
[index.ts:496](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L496)
## Methods
### execute
**execute**\<`T`\>(): `Promise`\<`T`[]\>
**execute**<`T`\>(): `Promise`<`T`[]\>
Execute the query and return the results as an Array of Objects
@@ -215,21 +202,21 @@ Execute the query and return the results as an Array of Objects
| Name | Type |
| :------ | :------ |
| `T` | `Record`\<`string`, `unknown`\> |
| `T` | `Record`<`string`, `unknown`\> |
#### Returns
`Promise`\<`T`[]\>
`Promise`<`T`[]\>
#### Defined in
[query.ts:115](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L115)
[index.ts:519](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L519)
___
### filter
**filter**(`value`): [`Query`](Query.md)\<`T`\>
**filter**(`value`): [`Query`](Query.md)<`T`\>
A filter statement to be applied to this query.
@@ -241,31 +228,17 @@ A filter statement to be applied to this query.
#### Returns
[`Query`](Query.md)\<`T`\>
[`Query`](Query.md)<`T`\>
#### Defined in
[query.ts:82](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L82)
___
### isElectron
`Private` **isElectron**(): `boolean`
#### Returns
`boolean`
#### Defined in
[query.ts:142](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L142)
[index.ts:491](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L491)
___
### limit
**limit**(`value`): [`Query`](Query.md)\<`T`\>
**limit**(`value`): [`Query`](Query.md)<`T`\>
Sets the number of results that will be returned
@@ -277,20 +250,24 @@ Sets the number of results that will be returned
#### Returns
[`Query`](Query.md)\<`T`\>
[`Query`](Query.md)<`T`\>
#### Defined in
[query.ts:55](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L55)
[index.ts:464](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L464)
___
### metricType
**metricType**(`value`): [`Query`](Query.md)\<`T`\>
**metricType**(`value`): [`Query`](Query.md)<`T`\>
The MetricType used for this Query.
**`See`**
MetricType for the different options
#### Parameters
| Name | Type | Description |
@@ -299,21 +276,17 @@ The MetricType used for this Query.
#### Returns
[`Query`](Query.md)\<`T`\>
**`See`**
MetricType for the different options
[`Query`](Query.md)<`T`\>
#### Defined in
[query.ts:102](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L102)
[index.ts:511](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L511)
___
### nprobes
**nprobes**(`value`): [`Query`](Query.md)\<`T`\>
**nprobes**(`value`): [`Query`](Query.md)<`T`\>
The number of probes used. A higher number makes search more accurate but also slower.
@@ -325,37 +298,17 @@ The number of probes used. A higher number makes search more accurate but also s
#### Returns
[`Query`](Query.md)\<`T`\>
[`Query`](Query.md)<`T`\>
#### Defined in
[query.ts:73](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L73)
___
### prefilter
**prefilter**(`value`): [`Query`](Query.md)\<`T`\>
#### Parameters
| Name | Type |
| :------ | :------ |
| `value` | `boolean` |
#### Returns
[`Query`](Query.md)\<`T`\>
#### Defined in
[query.ts:107](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L107)
[index.ts:482](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L482)
___
### refineFactor
**refineFactor**(`value`): [`Query`](Query.md)\<`T`\>
**refineFactor**(`value`): [`Query`](Query.md)<`T`\>
Refine the results by reading extra elements and re-ranking them in memory.
@@ -367,17 +320,17 @@ Refine the results by reading extra elements and re-ranking them in memory.
#### Returns
[`Query`](Query.md)\<`T`\>
[`Query`](Query.md)<`T`\>
#### Defined in
[query.ts:64](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L64)
[index.ts:473](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L473)
___
### select
**select**(`value`): [`Query`](Query.md)\<`T`\>
**select**(`value`): [`Query`](Query.md)<`T`\>
Return only the specified columns.
@@ -389,8 +342,8 @@ Return only the specified columns.
#### Returns
[`Query`](Query.md)\<`T`\>
[`Query`](Query.md)<`T`\>
#### Defined in
[query.ts:93](https://github.com/lancedb/lancedb/blob/7856a94/node/src/query.ts#L93)
[index.ts:502](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L502)

View File

@@ -22,7 +22,7 @@ Cosine distance
#### Defined in
[index.ts:798](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L798)
[index.ts:567](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L567)
___
@@ -34,7 +34,7 @@ Dot product
#### Defined in
[index.ts:803](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L803)
[index.ts:572](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L572)
___
@@ -46,4 +46,4 @@ Euclidean distance
#### Defined in
[index.ts:793](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L793)
[index.ts:562](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L562)

View File

@@ -22,7 +22,7 @@ Append new data to the table.
#### Defined in
[index.ts:766](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L766)
[index.ts:552](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L552)
___
@@ -34,7 +34,7 @@ Create a new [Table](../interfaces/Table.md).
#### Defined in
[index.ts:762](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L762)
[index.ts:548](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L548)
___
@@ -46,4 +46,4 @@ Overwrite the existing [Table](../interfaces/Table.md) if presented.
#### Defined in
[index.ts:764](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L764)
[index.ts:550](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L550)

View File

@@ -18,7 +18,7 @@
#### Defined in
[index.ts:34](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L34)
[index.ts:31](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L31)
___
@@ -28,7 +28,7 @@ ___
#### Defined in
[index.ts:36](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L36)
[index.ts:33](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L33)
___
@@ -38,4 +38,4 @@ ___
#### Defined in
[index.ts:38](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L38)
[index.ts:35](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L35)

View File

@@ -1,34 +0,0 @@
[vectordb](../README.md) / [Exports](../modules.md) / CleanupStats
# Interface: CleanupStats
## Table of contents
### Properties
- [bytesRemoved](CleanupStats.md#bytesremoved)
- [oldVersions](CleanupStats.md#oldversions)
## Properties
### bytesRemoved
**bytesRemoved**: `number`
The number of bytes removed from disk.
#### Defined in
[index.ts:637](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L637)
___
### oldVersions
**oldVersions**: `number`
The number of old table versions removed.
#### Defined in
[index.ts:641](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L641)

View File

@@ -1,62 +0,0 @@
[vectordb](../README.md) / [Exports](../modules.md) / CompactionMetrics
# Interface: CompactionMetrics
## Table of contents
### Properties
- [filesAdded](CompactionMetrics.md#filesadded)
- [filesRemoved](CompactionMetrics.md#filesremoved)
- [fragmentsAdded](CompactionMetrics.md#fragmentsadded)
- [fragmentsRemoved](CompactionMetrics.md#fragmentsremoved)
## Properties
### filesAdded
**filesAdded**: `number`
The number of files added. This is typically equal to the number of
fragments added.
#### Defined in
[index.ts:692](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L692)
___
### filesRemoved
**filesRemoved**: `number`
The number of files that were removed. Each fragment may have more than one
file.
#### Defined in
[index.ts:687](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L687)
___
### fragmentsAdded
**fragmentsAdded**: `number`
The number of new fragments that were created.
#### Defined in
[index.ts:682](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L682)
___
### fragmentsRemoved
**fragmentsRemoved**: `number`
The number of fragments that were removed.
#### Defined in
[index.ts:678](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L678)

View File

@@ -1,80 +0,0 @@
[vectordb](../README.md) / [Exports](../modules.md) / CompactionOptions
# Interface: CompactionOptions
## Table of contents
### Properties
- [materializeDeletions](CompactionOptions.md#materializedeletions)
- [materializeDeletionsThreshold](CompactionOptions.md#materializedeletionsthreshold)
- [maxRowsPerGroup](CompactionOptions.md#maxrowspergroup)
- [numThreads](CompactionOptions.md#numthreads)
- [targetRowsPerFragment](CompactionOptions.md#targetrowsperfragment)
## Properties
### materializeDeletions
`Optional` **materializeDeletions**: `boolean`
If true, fragments that have rows that are deleted may be compacted to
remove the deleted rows. This can improve the performance of queries.
Default is true.
#### Defined in
[index.ts:660](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L660)
___
### materializeDeletionsThreshold
`Optional` **materializeDeletionsThreshold**: `number`
A number between 0 and 1, representing the proportion of rows that must be
marked deleted before a fragment is a candidate for compaction to remove
the deleted rows. Default is 10%.
#### Defined in
[index.ts:666](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L666)
___
### maxRowsPerGroup
`Optional` **maxRowsPerGroup**: `number`
The maximum number of rows per group. Defaults to 1024.
#### Defined in
[index.ts:654](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L654)
___
### numThreads
`Optional` **numThreads**: `number`
The number of threads to use for compaction. If not provided, defaults to
the number of cores on the machine.
#### Defined in
[index.ts:671](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L671)
___
### targetRowsPerFragment
`Optional` **targetRowsPerFragment**: `number`
The number of rows per fragment to target. Fragments that have fewer rows
will be compacted into adjacent fragments to produce larger fragments.
Defaults to 1024 * 1024.
#### Defined in
[index.ts:650](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L650)

View File

@@ -19,6 +19,7 @@ Connection could be local against filesystem or remote against a server.
### Methods
- [createTable](Connection.md#createtable)
- [createTableArrow](Connection.md#createtablearrow)
- [dropTable](Connection.md#droptable)
- [openTable](Connection.md#opentable)
- [tableNames](Connection.md#tablenames)
@@ -31,15 +32,15 @@ Connection could be local against filesystem or remote against a server.
#### Defined in
[index.ts:125](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L125)
[index.ts:70](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L70)
## Methods
### createTable
**createTable**\<`T`\>(`«destructured»`): `Promise`\<[`Table`](Table.md)\<`T`\>\>
**createTable**<`T`\>(`name`, `data`, `mode?`, `embeddings?`): `Promise`<[`Table`](Table.md)<`T`\>\>
Creates a new Table, optionally initializing it with new data.
Creates a new Table and initialize it with new data.
#### Type parameters
@@ -49,115 +50,47 @@ Creates a new Table, optionally initializing it with new data.
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
| `data` | `Record`<`string`, `unknown`\>[] | Non-empty Array of Records to be inserted into the table |
| `mode?` | [`WriteMode`](../enums/WriteMode.md) | The write mode to use when creating the table. |
| `embeddings?` | [`EmbeddingFunction`](EmbeddingFunction.md)<`T`\> | An embedding function to use on this table |
#### Returns
`Promise`<[`Table`](Table.md)<`T`\>\>
#### Defined in
[index.ts:90](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L90)
___
### createTableArrow
**createTableArrow**(`name`, `table`): `Promise`<[`Table`](Table.md)<`number`[]\>\>
#### Parameters
| Name | Type |
| :------ | :------ |
| `«destructured»` | [`CreateTableOptions`](CreateTableOptions.md)\<`T`\> |
| `name` | `string` |
| `table` | `Table`<`any`\> |
#### Returns
`Promise`\<[`Table`](Table.md)\<`T`\>\>
`Promise`<[`Table`](Table.md)<`number`[]\>\>
#### Defined in
[index.ts:146](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L146)
**createTable**(`name`, `data`): `Promise`\<[`Table`](Table.md)\<`number`[]\>\>
Creates a new Table and initialize it with new data.
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
| `data` | `Record`\<`string`, `unknown`\>[] | Non-empty Array of Records to be inserted into the table |
#### Returns
`Promise`\<[`Table`](Table.md)\<`number`[]\>\>
#### Defined in
[index.ts:154](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L154)
**createTable**(`name`, `data`, `options`): `Promise`\<[`Table`](Table.md)\<`number`[]\>\>
Creates a new Table and initialize it with new data.
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
| `data` | `Record`\<`string`, `unknown`\>[] | Non-empty Array of Records to be inserted into the table |
| `options` | [`WriteOptions`](WriteOptions.md) | The write options to use when creating the table. |
#### Returns
`Promise`\<[`Table`](Table.md)\<`number`[]\>\>
#### Defined in
[index.ts:163](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L163)
**createTable**\<`T`\>(`name`, `data`, `embeddings`): `Promise`\<[`Table`](Table.md)\<`T`\>\>
Creates a new Table and initialize it with new data.
#### Type parameters
| Name |
| :------ |
| `T` |
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
| `data` | `Record`\<`string`, `unknown`\>[] | Non-empty Array of Records to be inserted into the table |
| `embeddings` | [`EmbeddingFunction`](EmbeddingFunction.md)\<`T`\> | An embedding function to use on this table |
#### Returns
`Promise`\<[`Table`](Table.md)\<`T`\>\>
#### Defined in
[index.ts:172](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L172)
**createTable**\<`T`\>(`name`, `data`, `embeddings`, `options`): `Promise`\<[`Table`](Table.md)\<`T`\>\>
Creates a new Table and initialize it with new data.
#### Type parameters
| Name |
| :------ |
| `T` |
#### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
| `data` | `Record`\<`string`, `unknown`\>[] | Non-empty Array of Records to be inserted into the table |
| `embeddings` | [`EmbeddingFunction`](EmbeddingFunction.md)\<`T`\> | An embedding function to use on this table |
| `options` | [`WriteOptions`](WriteOptions.md) | The write options to use when creating the table. |
#### Returns
`Promise`\<[`Table`](Table.md)\<`T`\>\>
#### Defined in
[index.ts:181](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L181)
[index.ts:92](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L92)
___
### dropTable
**dropTable**(`name`): `Promise`\<`void`\>
**dropTable**(`name`): `Promise`<`void`\>
Drop an existing table.
@@ -169,17 +102,17 @@ Drop an existing table.
#### Returns
`Promise`\<`void`\>
`Promise`<`void`\>
#### Defined in
[index.ts:187](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L187)
[index.ts:98](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L98)
___
### openTable
**openTable**\<`T`\>(`name`, `embeddings?`): `Promise`\<[`Table`](Table.md)\<`T`\>\>
**openTable**<`T`\>(`name`, `embeddings?`): `Promise`<[`Table`](Table.md)<`T`\>\>
Open a table in the database.
@@ -194,26 +127,26 @@ Open a table in the database.
| Name | Type | Description |
| :------ | :------ | :------ |
| `name` | `string` | The name of the table. |
| `embeddings?` | [`EmbeddingFunction`](EmbeddingFunction.md)\<`T`\> | An embedding function to use on this table |
| `embeddings?` | [`EmbeddingFunction`](EmbeddingFunction.md)<`T`\> | An embedding function to use on this table |
#### Returns
`Promise`\<[`Table`](Table.md)\<`T`\>\>
`Promise`<[`Table`](Table.md)<`T`\>\>
#### Defined in
[index.ts:135](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L135)
[index.ts:80](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L80)
___
### tableNames
**tableNames**(): `Promise`\<`string`[]\>
**tableNames**(): `Promise`<`string`[]\>
#### Returns
`Promise`\<`string`[]\>
`Promise`<`string`[]\>
#### Defined in
[index.ts:127](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L127)
[index.ts:72](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L72)

View File

@@ -6,62 +6,18 @@
### Properties
- [apiKey](ConnectionOptions.md#apikey)
- [awsCredentials](ConnectionOptions.md#awscredentials)
- [awsRegion](ConnectionOptions.md#awsregion)
- [hostOverride](ConnectionOptions.md#hostoverride)
- [region](ConnectionOptions.md#region)
- [uri](ConnectionOptions.md#uri)
## Properties
### apiKey
`Optional` **apiKey**: `string`
#### Defined in
[index.ts:49](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L49)
___
### awsCredentials
`Optional` **awsCredentials**: [`AwsCredentials`](AwsCredentials.md)
#### Defined in
[index.ts:44](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L44)
___
### awsRegion
`Optional` **awsRegion**: `string`
#### Defined in
[index.ts:46](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L46)
___
### hostOverride
`Optional` **hostOverride**: `string`
#### Defined in
[index.ts:54](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L54)
___
### region
`Optional` **region**: `string`
#### Defined in
[index.ts:51](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L51)
[index.ts:40](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L40)
___
@@ -71,4 +27,4 @@ ___
#### Defined in
[index.ts:42](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L42)
[index.ts:39](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L39)

View File

@@ -1,69 +0,0 @@
[vectordb](../README.md) / [Exports](../modules.md) / CreateTableOptions
# Interface: CreateTableOptions\<T\>
## Type parameters
| Name |
| :------ |
| `T` |
## Table of contents
### Properties
- [data](CreateTableOptions.md#data)
- [embeddingFunction](CreateTableOptions.md#embeddingfunction)
- [name](CreateTableOptions.md#name)
- [schema](CreateTableOptions.md#schema)
- [writeOptions](CreateTableOptions.md#writeoptions)
## Properties
### data
`Optional` **data**: `Table`\<`any`\> \| `Record`\<`string`, `unknown`\>[]
#### Defined in
[index.ts:79](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L79)
___
### embeddingFunction
`Optional` **embeddingFunction**: [`EmbeddingFunction`](EmbeddingFunction.md)\<`T`\>
#### Defined in
[index.ts:85](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L85)
___
### name
**name**: `string`
#### Defined in
[index.ts:76](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L76)
___
### schema
`Optional` **schema**: `Schema`\<`any`\>
#### Defined in
[index.ts:82](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L82)
___
### writeOptions
`Optional` **writeOptions**: [`WriteOptions`](WriteOptions.md)
#### Defined in
[index.ts:88](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L88)

View File

@@ -1,6 +1,6 @@
[vectordb](../README.md) / [Exports](../modules.md) / EmbeddingFunction
# Interface: EmbeddingFunction\<T\>
# Interface: EmbeddingFunction<T\>
An embedding function that automatically creates vector representation for a given column.
@@ -25,11 +25,11 @@ An embedding function that automatically creates vector representation for a giv
### embed
**embed**: (`data`: `T`[]) => `Promise`\<`number`[][]\>
**embed**: (`data`: `T`[]) => `Promise`<`number`[][]\>
#### Type declaration
▸ (`data`): `Promise`\<`number`[][]\>
▸ (`data`): `Promise`<`number`[][]\>
Creates a vector representation for the given values.
@@ -41,11 +41,11 @@ Creates a vector representation for the given values.
##### Returns
`Promise`\<`number`[][]\>
`Promise`<`number`[][]\>
#### Defined in
[embedding/embedding_function.ts:27](https://github.com/lancedb/lancedb/blob/7856a94/node/src/embedding/embedding_function.ts#L27)
[embedding/embedding_function.ts:27](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/embedding/embedding_function.ts#L27)
___
@@ -57,4 +57,4 @@ The name of the column that will be used as input for the Embedding Function.
#### Defined in
[embedding/embedding_function.ts:22](https://github.com/lancedb/lancedb/blob/7856a94/node/src/embedding/embedding_function.ts#L22)
[embedding/embedding_function.ts:22](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/embedding/embedding_function.ts#L22)

View File

@@ -1,30 +0,0 @@
[vectordb](../README.md) / [Exports](../modules.md) / IndexStats
# Interface: IndexStats
## Table of contents
### Properties
- [numIndexedRows](IndexStats.md#numindexedrows)
- [numUnindexedRows](IndexStats.md#numunindexedrows)
## Properties
### numIndexedRows
**numIndexedRows**: ``null`` \| `number`
#### Defined in
[index.ts:344](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L344)
___
### numUnindexedRows
• **numUnindexedRows**: ``null`` \| `number`
#### Defined in
[index.ts:345](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L345)

View File

@@ -7,7 +7,6 @@
### Properties
- [column](IvfPQIndexConfig.md#column)
- [index\_cache\_size](IvfPQIndexConfig.md#index_cache_size)
- [index\_name](IvfPQIndexConfig.md#index_name)
- [max\_iters](IvfPQIndexConfig.md#max_iters)
- [max\_opq\_iters](IvfPQIndexConfig.md#max_opq_iters)
@@ -29,19 +28,7 @@ The column to be indexed
#### Defined in
[index.ts:701](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L701)
___
### index\_cache\_size
`Optional` **index\_cache\_size**: `number`
Cache size of the index
#### Defined in
[index.ts:750](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L750)
[index.ts:382](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L382)
___
@@ -53,7 +40,7 @@ A unique name for the index
#### Defined in
[index.ts:706](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L706)
[index.ts:387](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L387)
___
@@ -65,7 +52,7 @@ The max number of iterations for kmeans training.
#### Defined in
[index.ts:721](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L721)
[index.ts:402](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L402)
___
@@ -77,7 +64,7 @@ Max number of iterations to train OPQ, if `use_opq` is true.
#### Defined in
[index.ts:740](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L740)
[index.ts:421](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L421)
___
@@ -89,7 +76,7 @@ Metric type, L2 or Cosine
#### Defined in
[index.ts:711](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L711)
[index.ts:392](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L392)
___
@@ -101,7 +88,7 @@ The number of bits to present one PQ centroid.
#### Defined in
[index.ts:735](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L735)
[index.ts:416](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L416)
___
@@ -113,7 +100,7 @@ The number of partitions this index
#### Defined in
[index.ts:716](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L716)
[index.ts:397](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L397)
___
@@ -125,7 +112,7 @@ Number of subvectors to build PQ code
#### Defined in
[index.ts:731](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L731)
[index.ts:412](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L412)
___
@@ -137,7 +124,7 @@ Replace an existing index with the same name if it exists.
#### Defined in
[index.ts:745](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L745)
[index.ts:426](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L426)
___
@@ -147,7 +134,7 @@ ___
#### Defined in
[index.ts:752](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L752)
[index.ts:428](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L428)
___
@@ -159,4 +146,4 @@ Train as optimized product quantization.
#### Defined in
[index.ts:726](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L726)
[index.ts:407](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L407)

View File

@@ -1,6 +1,6 @@
[vectordb](../README.md) / [Exports](../modules.md) / Table
# Interface: Table\<T\>
# Interface: Table<T\>
A LanceDB Table is the collection of Records. Each Record has one or more vector fields.
@@ -22,22 +22,19 @@ A LanceDB Table is the collection of Records. Each Record has one or more vector
- [countRows](Table.md#countrows)
- [createIndex](Table.md#createindex)
- [delete](Table.md#delete)
- [indexStats](Table.md#indexstats)
- [listIndices](Table.md#listindices)
- [name](Table.md#name)
- [overwrite](Table.md#overwrite)
- [search](Table.md#search)
- [update](Table.md#update)
## Properties
### add
**add**: (`data`: `Record`\<`string`, `unknown`\>[]) => `Promise`\<`number`\>
**add**: (`data`: `Record`<`string`, `unknown`\>[]) => `Promise`<`number`\>
#### Type declaration
▸ (`data`): `Promise`\<`number`\>
▸ (`data`): `Promise`<`number`\>
Insert records into this Table.
@@ -45,50 +42,54 @@ Insert records into this Table.
| Name | Type | Description |
| :------ | :------ | :------ |
| `data` | `Record`\<`string`, `unknown`\>[] | Records to be inserted into the Table |
| `data` | `Record`<`string`, `unknown`\>[] | Records to be inserted into the Table |
##### Returns
`Promise`\<`number`\>
`Promise`<`number`\>
The number of rows added to the table
#### Defined in
[index.ts:209](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L209)
[index.ts:120](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L120)
___
### countRows
**countRows**: () => `Promise`\<`number`\>
**countRows**: () => `Promise`<`number`\>
#### Type declaration
▸ (): `Promise`\<`number`\>
▸ (): `Promise`<`number`\>
Returns the number of rows in this table.
##### Returns
`Promise`\<`number`\>
`Promise`<`number`\>
#### Defined in
[index.ts:229](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L229)
[index.ts:140](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L140)
___
### createIndex
**createIndex**: (`indexParams`: [`IvfPQIndexConfig`](IvfPQIndexConfig.md)) => `Promise`\<`any`\>
**createIndex**: (`indexParams`: [`IvfPQIndexConfig`](IvfPQIndexConfig.md)) => `Promise`<`any`\>
#### Type declaration
▸ (`indexParams`): `Promise`\<`any`\>
▸ (`indexParams`): `Promise`<`any`\>
Create an ANN index on this Table vector index.
**`See`**
VectorIndexParams.
##### Parameters
| Name | Type | Description |
@@ -97,41 +98,27 @@ Create an ANN index on this Table vector index.
##### Returns
`Promise`\<`any`\>
**`See`**
VectorIndexParams.
`Promise`<`any`\>
#### Defined in
[index.ts:224](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L224)
[index.ts:135](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L135)
___
### delete
**delete**: (`filter`: `string`) => `Promise`\<`void`\>
**delete**: (`filter`: `string`) => `Promise`<`void`\>
#### Type declaration
▸ (`filter`): `Promise`\<`void`\>
▸ (`filter`): `Promise`<`void`\>
Delete rows from this table.
This can be used to delete a single row, many rows, all rows, or
sometimes no rows (if your predicate matches nothing).
##### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `filter` | `string` | A filter in the same format used by a sql WHERE clause. The filter must not be empty. |
##### Returns
`Promise`\<`void`\>
**`Examples`**
```ts
@@ -155,55 +142,19 @@ await tbl.delete(`id IN (${to_remove.join(",")})`)
await tbl.countRows() // Returns 1
```
#### Defined in
[index.ts:263](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L263)
___
### indexStats
**indexStats**: (`indexUuid`: `string`) => `Promise`\<[`IndexStats`](IndexStats.md)\>
#### Type declaration
▸ (`indexUuid`): `Promise`\<[`IndexStats`](IndexStats.md)\>
Get statistics about an index.
##### Parameters
| Name | Type |
| :------ | :------ |
| `indexUuid` | `string` |
| Name | Type | Description |
| :------ | :------ | :------ |
| `filter` | `string` | A filter in the same format used by a sql WHERE clause. The filter must not be empty. |
##### Returns
`Promise`\<[`IndexStats`](IndexStats.md)\>
`Promise`<`void`\>
#### Defined in
[index.ts:306](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L306)
___
### listIndices
**listIndices**: () => `Promise`\<[`VectorIndex`](VectorIndex.md)[]\>
#### Type declaration
▸ (): `Promise`\<[`VectorIndex`](VectorIndex.md)[]\>
List the indicies on this table.
##### Returns
`Promise`\<[`VectorIndex`](VectorIndex.md)[]\>
#### Defined in
[index.ts:301](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L301)
[index.ts:174](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L174)
___
@@ -213,17 +164,17 @@ ___
#### Defined in
[index.ts:195](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L195)
[index.ts:106](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L106)
___
### overwrite
**overwrite**: (`data`: `Record`\<`string`, `unknown`\>[]) => `Promise`\<`number`\>
**overwrite**: (`data`: `Record`<`string`, `unknown`\>[]) => `Promise`<`number`\>
#### Type declaration
▸ (`data`): `Promise`\<`number`\>
▸ (`data`): `Promise`<`number`\>
Insert records into this Table, replacing its contents.
@@ -231,27 +182,27 @@ Insert records into this Table, replacing its contents.
| Name | Type | Description |
| :------ | :------ | :------ |
| `data` | `Record`\<`string`, `unknown`\>[] | Records to be inserted into the Table |
| `data` | `Record`<`string`, `unknown`\>[] | Records to be inserted into the Table |
##### Returns
`Promise`\<`number`\>
`Promise`<`number`\>
The number of rows added to the table
#### Defined in
[index.ts:217](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L217)
[index.ts:128](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L128)
___
### search
**search**: (`query`: `T`) => [`Query`](../classes/Query.md)\<`T`\>
**search**: (`query`: `T`) => [`Query`](../classes/Query.md)<`T`\>
#### Type declaration
▸ (`query`): [`Query`](../classes/Query.md)\<`T`\>
▸ (`query`): [`Query`](../classes/Query.md)<`T`\>
Creates a search query to find the nearest neighbors of the given search term
@@ -263,59 +214,8 @@ Creates a search query to find the nearest neighbors of the given search term
##### Returns
[`Query`](../classes/Query.md)\<`T`\>
[`Query`](../classes/Query.md)<`T`\>
#### Defined in
[index.ts:201](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L201)
___
### update
**update**: (`args`: [`UpdateArgs`](UpdateArgs.md) \| [`UpdateSqlArgs`](UpdateSqlArgs.md)) => `Promise`\<`void`\>
#### Type declaration
▸ (`args`): `Promise`\<`void`\>
Update rows in this table.
This can be used to update a single row, many rows, all rows, or
sometimes no rows (if your predicate matches nothing).
##### Parameters
| Name | Type | Description |
| :------ | :------ | :------ |
| `args` | [`UpdateArgs`](UpdateArgs.md) \| [`UpdateSqlArgs`](UpdateSqlArgs.md) | see [UpdateArgs](UpdateArgs.md) and [UpdateSqlArgs](UpdateSqlArgs.md) for more details |
##### Returns
`Promise`\<`void`\>
**`Examples`**
```ts
const con = await lancedb.connect("./.lancedb")
const data = [
{id: 1, vector: [3, 3], name: 'Ye'},
{id: 2, vector: [4, 4], name: 'Mike'},
];
const tbl = await con.createTable("my_table", data)
await tbl.update({
filter: "id = 2",
updates: { vector: [2, 2], name: "Michael" },
})
let results = await tbl.search([1, 1]).execute();
// Returns [
// {id: 2, vector: [2, 2], name: 'Michael'}
// {id: 1, vector: [3, 3], name: 'Ye'}
// ]
```
#### Defined in
[index.ts:296](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L296)
[index.ts:112](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L112)

View File

@@ -1,36 +0,0 @@
[vectordb](../README.md) / [Exports](../modules.md) / UpdateArgs
# Interface: UpdateArgs
## Table of contents
### Properties
- [values](UpdateArgs.md#values)
- [where](UpdateArgs.md#where)
## Properties
### values
**values**: `Record`\<`string`, `Literal`\>
A key-value map of updates. The keys are the column names, and the values are the
new values to set
#### Defined in
[index.ts:320](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L320)
___
### where
`Optional` **where**: `string`
A filter in the same format used by a sql WHERE clause. The filter may be empty,
in which case all rows will be updated.
#### Defined in
[index.ts:314](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L314)

View File

@@ -1,36 +0,0 @@
[vectordb](../README.md) / [Exports](../modules.md) / UpdateSqlArgs
# Interface: UpdateSqlArgs
## Table of contents
### Properties
- [valuesSql](UpdateSqlArgs.md#valuessql)
- [where](UpdateSqlArgs.md#where)
## Properties
### valuesSql
**valuesSql**: `Record`\<`string`, `string`\>
A key-value map of updates. The keys are the column names, and the values are the
new values to set as SQL expressions.
#### Defined in
[index.ts:334](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L334)
___
### where
`Optional` **where**: `string`
A filter in the same format used by a sql WHERE clause. The filter may be empty,
in which case all rows will be updated.
#### Defined in
[index.ts:328](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L328)

View File

@@ -1,41 +0,0 @@
[vectordb](../README.md) / [Exports](../modules.md) / VectorIndex
# Interface: VectorIndex
## Table of contents
### Properties
- [columns](VectorIndex.md#columns)
- [name](VectorIndex.md#name)
- [uuid](VectorIndex.md#uuid)
## Properties
### columns
**columns**: `string`[]
#### Defined in
[index.ts:338](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L338)
___
### name
**name**: `string`
#### Defined in
[index.ts:339](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L339)
___
### uuid
**uuid**: `string`
#### Defined in
[index.ts:340](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L340)

View File

@@ -1,27 +0,0 @@
[vectordb](../README.md) / [Exports](../modules.md) / WriteOptions
# Interface: WriteOptions
Write options when creating a Table.
## Implemented by
- [`DefaultWriteOptions`](../classes/DefaultWriteOptions.md)
## Table of contents
### Properties
- [writeMode](WriteOptions.md#writemode)
## Properties
### writeMode
`Optional` **writeMode**: [`WriteMode`](../enums/WriteMode.md)
A [WriteMode](../enums/WriteMode.md) to use on this operation
#### Defined in
[index.ts:774](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L774)

View File

@@ -11,7 +11,6 @@
### Classes
- [DefaultWriteOptions](classes/DefaultWriteOptions.md)
- [LocalConnection](classes/LocalConnection.md)
- [LocalTable](classes/LocalTable.md)
- [OpenAIEmbeddingFunction](classes/OpenAIEmbeddingFunction.md)
@@ -20,20 +19,11 @@
### Interfaces
- [AwsCredentials](interfaces/AwsCredentials.md)
- [CleanupStats](interfaces/CleanupStats.md)
- [CompactionMetrics](interfaces/CompactionMetrics.md)
- [CompactionOptions](interfaces/CompactionOptions.md)
- [Connection](interfaces/Connection.md)
- [ConnectionOptions](interfaces/ConnectionOptions.md)
- [CreateTableOptions](interfaces/CreateTableOptions.md)
- [EmbeddingFunction](interfaces/EmbeddingFunction.md)
- [IndexStats](interfaces/IndexStats.md)
- [IvfPQIndexConfig](interfaces/IvfPQIndexConfig.md)
- [Table](interfaces/Table.md)
- [UpdateArgs](interfaces/UpdateArgs.md)
- [UpdateSqlArgs](interfaces/UpdateSqlArgs.md)
- [VectorIndex](interfaces/VectorIndex.md)
- [WriteOptions](interfaces/WriteOptions.md)
### Type Aliases
@@ -42,7 +32,6 @@
### Functions
- [connect](modules.md#connect)
- [isWriteOptions](modules.md#iswriteoptions)
## Type Aliases
@@ -52,13 +41,13 @@
#### Defined in
[index.ts:755](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L755)
[index.ts:431](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L431)
## Functions
### connect
**connect**(`uri`): `Promise`\<[`Connection`](interfaces/Connection.md)\>
**connect**(`uri`): `Promise`<[`Connection`](interfaces/Connection.md)\>
Connect to a LanceDB instance at the given URI
@@ -70,44 +59,24 @@ Connect to a LanceDB instance at the given URI
#### Returns
`Promise`\<[`Connection`](interfaces/Connection.md)\>
`Promise`<[`Connection`](interfaces/Connection.md)\>
#### Defined in
[index.ts:95](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L95)
[index.ts:47](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L47)
**connect**(`opts`): `Promise`\<[`Connection`](interfaces/Connection.md)\>
**connect**(`opts`): `Promise`<[`Connection`](interfaces/Connection.md)\>
#### Parameters
| Name | Type |
| :------ | :------ |
| `opts` | `Partial`\<[`ConnectionOptions`](interfaces/ConnectionOptions.md)\> |
| `opts` | `Partial`<[`ConnectionOptions`](interfaces/ConnectionOptions.md)\> |
#### Returns
`Promise`\<[`Connection`](interfaces/Connection.md)\>
`Promise`<[`Connection`](interfaces/Connection.md)\>
#### Defined in
[index.ts:96](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L96)
___
### isWriteOptions
**isWriteOptions**(`value`): value is WriteOptions
#### Parameters
| Name | Type |
| :------ | :------ |
| `value` | `any` |
#### Returns
value is WriteOptions
#### Defined in
[index.ts:781](https://github.com/lancedb/lancedb/blob/7856a94/node/src/index.ts#L781)
[index.ts:48](https://github.com/lancedb/lancedb/blob/b1eeb90/node/src/index.ts#L48)

View File

@@ -119,100 +119,3 @@ This is why it is often called **Approximate Nearest Neighbors (ANN)** search, w
always returns 100% recall.
See [ANN Index](ann_indexes.md) for more details.
### Output formats
LanceDB returns results in many different formats commonly used in python.
Let's create a LanceDB table with a nested schema:
```python
from datetime import datetime
import lancedb
from lancedb.pydantic import LanceModel, Vector
import numpy as np
from pydantic import BaseModel
uri = "data/sample-lancedb-nested"
class Metadata(BaseModel):
source: str
timestamp: datetime
class Document(BaseModel):
content: str
meta: Metadata
class LanceSchema(LanceModel):
id: str
vector: Vector(1536)
payload: Document
# Let's add 100 sample rows to our dataset
data = [LanceSchema(
id=f"id{i}",
vector=np.random.randn(1536),
payload=Document(
content=f"document{i}", meta=Metadata(source=f"source{i%10}", timestamp=datetime.now())
),
) for i in range(100)]
tbl = db.create_table("documents", data=data)
```
#### As a pyarrow table
Using `to_arrow()` we can get the results back as a pyarrow Table.
This result table has the same columns as the LanceDB table, with
the addition of an `_distance` column for vector search or a `score`
column for full text search.
```python
tbl.search(np.random.randn(1536)).to_arrow()
```
#### As a pandas dataframe
You can also get the results as a pandas dataframe.
```python
tbl.search(np.random.randn(1536)).to_pandas()
```
While other formats like Arrow/Pydantic/Python dicts have a natural
way to handle nested schemas, pandas can only store nested data as a
python dict column, which makes it difficult to support nested references.
So for convenience, you can also tell LanceDB to flatten a nested schema
when creating the pandas dataframe.
```python
tbl.search(np.random.randn(1536)).to_pandas(flatten=True)
```
If your table has a deeply nested struct, you can control how many levels
of nesting to flatten by passing in a positive integer.
```python
tbl.search(np.random.randn(1536)).to_pandas(flatten=1)
```
#### As a list of python dicts
You can of course return results as a list of python dicts.
```python
tbl.search(np.random.randn(1536)).to_list()
```
#### As a list of pydantic models
We can add data using pydantic models, and we can certainly
retrieve results as pydantic models
```python
tbl.search(np.random.randn(1536)).to_pydantic(LanceSchema)
```
Note that in this case the extra `_distance` field is discarded since
it's not part of the LanceSchema.

View File

@@ -1,7 +1,7 @@
# SQL filters
LanceDB embraces the utilization of standard SQL expressions as predicates for hybrid
filters. It can be used during hybrid vector search, update, and deletion operations.
filters. It can be used during hybrid vector search and deletion operations.
Currently, Lance supports a growing list of expressions.
@@ -22,7 +22,7 @@ import numpy as np
uri = "data/sample-lancedb"
db = lancedb.connect(uri)
data = [{"vector": row, "item": f"item {i}", "id": i}
data = [{"vector": row, "item": f"item {i}"}
for i, row in enumerate(np.random.random((10_000, 2)).astype('int'))]
tbl = db.create_table("my_vectors", data=data)
@@ -35,25 +35,33 @@ const db = await vectordb.connect('data/sample-lancedb')
let data = []
for (let i = 0; i < 10_000; i++) {
data.push({vector: Array(1536).fill(i), id: i, item: `item ${i}`, strId: `${i}`})
data.push({vector: Array(1536).fill(i), id: `${i}`, content: "", longId: `${i}`},)
}
const tbl = await db.createTable('myVectors', data)
const tbl = await db.createTable('my_vectors', data)
```
-->
=== "Python"
```python
tbl.search([100, 102]) \
.where("(item IN ('item 0', 'item 2')) AND (id > 10)") \
.to_arrow()
```
.where("""(
(label IN [10, 20])
AND
(note.email IS NOT NULL)
) OR NOT note.created
""")
```
=== "Javascript"
```javascript
await tbl.search(Array(1536).fill(0))
.where("(item IN ('item 0', 'item 2')) AND (id > 10)")
.execute()
tbl.search([100, 102])
.where(`(
(label IN [10, 20])
AND
(note.email IS NOT NULL)
) OR NOT note.created
`)
```
@@ -110,22 +118,3 @@ The mapping from SQL types to Arrow types is:
[^1]: See precision mapping in previous table.
## Filtering without Vector Search
You can also filter your data without search.
=== "Python"
```python
tbl.search().where("id=10").limit(10).to_arrow()
```
=== "JavaScript"
```javascript
await tbl.where('id=10').limit(10).execute()
```
!!! warning
If your table is large, this could potentially return a very large
amount of data. Please be sure to use a `limit` clause unless
you're sure you want to return the whole result set.

View File

@@ -9,13 +9,8 @@ npm install vectordb
```
This will download the appropriate native library for your platform. We currently
support:
* Linux (x86_64 and aarch64)
* MacOS (Intel and ARM/M1/M2)
* Windows (x86_64 only)
We do not yet support musl-based Linux (such as Alpine Linux) or aarch64 Windows.
support x86_64 Linux, aarch64 Linux, Intel MacOS, and ARM (M1/M2) MacOS. We do not
yet support musl-based Linux (such as Alpine Linux).
## Usage

80
node/package-lock.json generated
View File

@@ -1,12 +1,12 @@
{
"name": "vectordb",
"version": "0.4.0",
"version": "0.3.9",
"lockfileVersion": 2,
"requires": true,
"packages": {
"": {
"name": "vectordb",
"version": "0.4.0",
"version": "0.3.9",
"cpu": [
"x64",
"arm64"
@@ -53,11 +53,11 @@
"uuid": "^9.0.0"
},
"optionalDependencies": {
"@lancedb/vectordb-darwin-arm64": "0.4.0",
"@lancedb/vectordb-darwin-x64": "0.4.0",
"@lancedb/vectordb-linux-arm64-gnu": "0.4.0",
"@lancedb/vectordb-linux-x64-gnu": "0.4.0",
"@lancedb/vectordb-win32-x64-msvc": "0.4.0"
"@lancedb/vectordb-darwin-arm64": "0.3.9",
"@lancedb/vectordb-darwin-x64": "0.3.9",
"@lancedb/vectordb-linux-arm64-gnu": "0.3.9",
"@lancedb/vectordb-linux-x64-gnu": "0.3.9",
"@lancedb/vectordb-win32-x64-msvc": "0.3.9"
}
},
"node_modules/@apache-arrow/ts": {
@@ -316,22 +316,10 @@
"@jridgewell/sourcemap-codec": "^1.4.10"
}
},
"node_modules/@lancedb/vectordb-darwin-arm64": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.4.0.tgz",
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"cpu": [
"arm64"
],
"optional": true,
"os": [
"darwin"
]
},
"node_modules/@lancedb/vectordb-darwin-x64": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.4.0.tgz",
"integrity": "sha512-ig0gV5ol1sFe2lb1HOatK0rizyj9I91WbnH79i7OdUl3nAQIcWm70CnxrPLtx0DS2NTGh2kFJbYCWcaUlu6YfA==",
"version": "0.3.9",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.3.9.tgz",
"integrity": "sha512-4xXQoPheyIl1P5kRoKmZtaAHFrYdL9pw5yq+r6ewIx0TCemN4LSvzSUTqM5nZl3QPU8FeL0CGD8Gt2gMU0HQ2A==",
"cpu": [
"x64"
],
@@ -341,9 +329,9 @@
]
},
"node_modules/@lancedb/vectordb-linux-arm64-gnu": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.4.0.tgz",
"integrity": "sha512-gMXIDT2kriAPDwWIRKXdaTCNdOeFGEok1S9Y30AOruHXddW1vCIo4JNJIYbBqHnwAeI4wI3ae6GRCFaf1UxO3g==",
"version": "0.3.9",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.3.9.tgz",
"integrity": "sha512-WIxCZKnLeSlz0PGURtKSX6hJ4CYE2o5P+IFmmuWOWB1uNapQu6zOpea6rNxcRFHUA0IJdO02lVxVfn2hDX4SMg==",
"cpu": [
"arm64"
],
@@ -353,9 +341,9 @@
]
},
"node_modules/@lancedb/vectordb-linux-x64-gnu": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.4.0.tgz",
"integrity": "sha512-ZQ3lDrDSz1IKdx/mS9Lz08agFO+OD5oSFrrcFNCoT1+H93eS1mCLdmCoEARu3jKbx0tMs38l5J9yXZ2QmJye3w==",
"version": "0.3.9",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.3.9.tgz",
"integrity": "sha512-bQbcV9adKzYbJLNzDjk9OYsMnT2IjmieLfb4IQ1hj5IUoWfbg80Bd0+gZUnrmrhG6fe56TIriFZYQR9i7TSE9Q==",
"cpu": [
"x64"
],
@@ -365,9 +353,9 @@
]
},
"node_modules/@lancedb/vectordb-win32-x64-msvc": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.4.0.tgz",
"integrity": "sha512-toNcNwBRE1sdsSf5hr7W8QiqZ33csc/knVEek4CyvYkZHJGh4Z6WI+DJUIASo5wzUez4TX7qUPpRPL9HuaPMCg==",
"version": "0.3.9",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.3.9.tgz",
"integrity": "sha512-7EXI7P1QvAfgJNPWWBMDOkoJ696gSBAClcyEJNYg0JV21jVFZRwJVI3bZXflesWduFi/mTuzPkFFA68us1u19A==",
"cpu": [
"x64"
],
@@ -4868,34 +4856,28 @@
"@jridgewell/sourcemap-codec": "^1.4.10"
}
},
"@lancedb/vectordb-darwin-arm64": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-arm64/-/vectordb-darwin-arm64-0.4.0.tgz",
"integrity": "sha512-cP6zGtBWXEcJHCI4uLNIP5ILtRvexvwmL8Uri1dnHG8dT8g12Ykug3BHO6Wt6wp/xASd2jJRIF/VAJsN9IeP1A==",
"optional": true
},
"@lancedb/vectordb-darwin-x64": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.4.0.tgz",
"integrity": "sha512-ig0gV5ol1sFe2lb1HOatK0rizyj9I91WbnH79i7OdUl3nAQIcWm70CnxrPLtx0DS2NTGh2kFJbYCWcaUlu6YfA==",
"version": "0.3.9",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-darwin-x64/-/vectordb-darwin-x64-0.3.9.tgz",
"integrity": "sha512-4xXQoPheyIl1P5kRoKmZtaAHFrYdL9pw5yq+r6ewIx0TCemN4LSvzSUTqM5nZl3QPU8FeL0CGD8Gt2gMU0HQ2A==",
"optional": true
},
"@lancedb/vectordb-linux-arm64-gnu": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.4.0.tgz",
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"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-arm64-gnu/-/vectordb-linux-arm64-gnu-0.3.9.tgz",
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"optional": true
},
"@lancedb/vectordb-linux-x64-gnu": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-linux-x64-gnu/-/vectordb-linux-x64-gnu-0.4.0.tgz",
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"optional": true
},
"@lancedb/vectordb-win32-x64-msvc": {
"version": "0.4.0",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.4.0.tgz",
"integrity": "sha512-toNcNwBRE1sdsSf5hr7W8QiqZ33csc/knVEek4CyvYkZHJGh4Z6WI+DJUIASo5wzUez4TX7qUPpRPL9HuaPMCg==",
"version": "0.3.9",
"resolved": "https://registry.npmjs.org/@lancedb/vectordb-win32-x64-msvc/-/vectordb-win32-x64-msvc-0.3.9.tgz",
"integrity": "sha512-7EXI7P1QvAfgJNPWWBMDOkoJ696gSBAClcyEJNYg0JV21jVFZRwJVI3bZXflesWduFi/mTuzPkFFA68us1u19A==",
"optional": true
},
"@neon-rs/cli": {

View File

@@ -1,6 +1,6 @@
{
"name": "vectordb",
"version": "0.4.1",
"version": "0.3.9",
"description": " Serverless, low-latency vector database for AI applications",
"main": "dist/index.js",
"types": "dist/index.d.ts",
@@ -81,10 +81,10 @@
}
},
"optionalDependencies": {
"@lancedb/vectordb-darwin-arm64": "0.4.1",
"@lancedb/vectordb-darwin-x64": "0.4.1",
"@lancedb/vectordb-linux-arm64-gnu": "0.4.1",
"@lancedb/vectordb-linux-x64-gnu": "0.4.1",
"@lancedb/vectordb-win32-x64-msvc": "0.4.1"
"@lancedb/vectordb-darwin-arm64": "0.3.9",
"@lancedb/vectordb-darwin-x64": "0.3.9",
"@lancedb/vectordb-linux-arm64-gnu": "0.3.9",
"@lancedb/vectordb-linux-x64-gnu": "0.3.9",
"@lancedb/vectordb-win32-x64-msvc": "0.3.9"
}
}

View File

@@ -21,10 +21,9 @@ import type { EmbeddingFunction } from './embedding/embedding_function'
import { RemoteConnection } from './remote'
import { Query } from './query'
import { isEmbeddingFunction } from './embedding/embedding_function'
import { type Literal, toSQL } from './util'
// eslint-disable-next-line @typescript-eslint/no-var-requires
const { databaseNew, databaseTableNames, databaseOpenTable, databaseDropTable, tableCreate, tableAdd, tableCreateScalarIndex, tableCreateVectorIndex, tableCountRows, tableDelete, tableUpdate, tableCleanupOldVersions, tableCompactFiles, tableListIndices, tableIndexStats } = require('../native.js')
const { databaseNew, databaseTableNames, databaseOpenTable, databaseDropTable, tableCreate, tableAdd, tableCreateVectorIndex, tableCountRows, tableDelete, tableCleanupOldVersions, tableCompactFiles, tableListIndices, tableIndexStats } = require('../native.js')
export { Query }
export type { EmbeddingFunction }
@@ -223,56 +222,6 @@ export interface Table<T = number[]> {
*/
createIndex: (indexParams: VectorIndexParams) => Promise<any>
/**
* Create a scalar index on this Table for the given column
*
* @param column The column to index
* @param replace If false, fail if an index already exists on the column
*
* Scalar indices, like vector indices, can be used to speed up scans. A scalar
* index can speed up scans that contain filter expressions on the indexed column.
* For example, the following scan will be faster if the column `my_col` has
* a scalar index:
*
* ```ts
* const con = await lancedb.connect('./.lancedb');
* const table = await con.openTable('images');
* const results = await table.where('my_col = 7').execute();
* ```
*
* Scalar indices can also speed up scans containing a vector search and a
* prefilter:
*
* ```ts
* const con = await lancedb.connect('././lancedb');
* const table = await con.openTable('images');
* const results = await table.search([1.0, 2.0]).where('my_col != 7').prefilter(true);
* ```
*
* Scalar indices can only speed up scans for basic filters using
* equality, comparison, range (e.g. `my_col BETWEEN 0 AND 100`), and set
* membership (e.g. `my_col IN (0, 1, 2)`)
*
* Scalar indices can be used if the filter contains multiple indexed columns and
* the filter criteria are AND'd or OR'd together
* (e.g. `my_col < 0 AND other_col> 100`)
*
* Scalar indices may be used if the filter contains non-indexed columns but,
* depending on the structure of the filter, they may not be usable. For example,
* if the column `not_indexed` does not have a scalar index then the filter
* `my_col = 0 OR not_indexed = 1` will not be able to use any scalar index on
* `my_col`.
*
* @examples
*
* ```ts
* const con = await lancedb.connect('././lancedb')
* const table = await con.openTable('images')
* await table.createScalarIndex('my_col')
* ```
*/
createScalarIndex: (column: string, replace: boolean) => Promise<void>
/**
* Returns the number of rows in this table.
*/
@@ -312,39 +261,6 @@ export interface Table<T = number[]> {
*/
delete: (filter: string) => Promise<void>
/**
* Update rows in this table.
*
* This can be used to update a single row, many rows, all rows, or
* sometimes no rows (if your predicate matches nothing).
*
* @param args see {@link UpdateArgs} and {@link UpdateSqlArgs} for more details
*
* @examples
*
* ```ts
* const con = await lancedb.connect("./.lancedb")
* const data = [
* {id: 1, vector: [3, 3], name: 'Ye'},
* {id: 2, vector: [4, 4], name: 'Mike'},
* ];
* const tbl = await con.createTable("my_table", data)
*
* await tbl.update({
* where: "id = 2",
* values: { vector: [2, 2], name: "Michael" },
* })
*
* let results = await tbl.search([1, 1]).execute();
* // Returns [
* // {id: 2, vector: [2, 2], name: 'Michael'}
* // {id: 1, vector: [3, 3], name: 'Ye'}
* // ]
* ```
*
*/
update: (args: UpdateArgs | UpdateSqlArgs) => Promise<void>
/**
* List the indicies on this table.
*/
@@ -356,34 +272,6 @@ export interface Table<T = number[]> {
indexStats: (indexUuid: string) => Promise<IndexStats>
}
export interface UpdateArgs {
/**
* A filter in the same format used by a sql WHERE clause. The filter may be empty,
* in which case all rows will be updated.
*/
where?: string
/**
* A key-value map of updates. The keys are the column names, and the values are the
* new values to set
*/
values: Record<string, Literal>
}
export interface UpdateSqlArgs {
/**
* A filter in the same format used by a sql WHERE clause. The filter may be empty,
* in which case all rows will be updated.
*/
where?: string
/**
* A key-value map of updates. The keys are the column names, and the values are the
* new values to set as SQL expressions.
*/
valuesSql: Record<string, string>
}
export interface VectorIndex {
columns: string[]
name: string
@@ -538,16 +426,6 @@ export class LocalTable<T = number[]> implements Table<T> {
return new Query(query, this._tbl, this._embeddings)
}
/**
* Creates a filter query to find all rows matching the specified criteria
* @param value The filter criteria (like SQL where clause syntax)
*/
filter (value: string): Query<T> {
return new Query(undefined, this._tbl, this._embeddings).filter(value)
}
where = this.filter
/**
* Insert records into this Table.
*
@@ -587,10 +465,6 @@ export class LocalTable<T = number[]> implements Table<T> {
return tableCreateVectorIndex.call(this._tbl, indexParams).then((newTable: any) => { this._tbl = newTable })
}
async createScalarIndex (column: string, replace: boolean): Promise<void> {
return tableCreateScalarIndex.call(this._tbl, column, replace)
}
/**
* Returns the number of rows in this table.
*/
@@ -607,31 +481,6 @@ export class LocalTable<T = number[]> implements Table<T> {
return tableDelete.call(this._tbl, filter).then((newTable: any) => { this._tbl = newTable })
}
/**
* Update rows in this table.
*
* @param args see {@link UpdateArgs} and {@link UpdateSqlArgs} for more details
*
* @returns
*/
async update (args: UpdateArgs | UpdateSqlArgs): Promise<void> {
let filter: string | null
let updates: Record<string, string>
if ('valuesSql' in args) {
filter = args.where ?? null
updates = args.valuesSql
} else {
filter = args.where ?? null
updates = {}
for (const [key, value] of Object.entries(args.values)) {
updates[key] = toSQL(value)
}
}
return tableUpdate.call(this._tbl, filter, updates).then((newTable: any) => { this._tbl = newTable })
}
/**
* Clean up old versions of the table, freeing disk space.
*
@@ -798,11 +647,6 @@ export interface IvfPQIndexConfig {
*/
replace?: boolean
/**
* Cache size of the index
*/
index_cache_size?: number
type: 'ivf_pq'
}

View File

@@ -23,10 +23,10 @@ const { tableSearch } = require('../native.js')
* A builder for nearest neighbor queries for LanceDB.
*/
export class Query<T = number[]> {
private readonly _query?: T
private readonly _query: T
private readonly _tbl?: any
private _queryVector?: number[]
private _limit?: number
private _limit: number
private _refineFactor?: number
private _nprobes: number
private _select?: string[]
@@ -35,10 +35,10 @@ export class Query<T = number[]> {
private _prefilter: boolean
protected readonly _embeddings?: EmbeddingFunction<T>
constructor (query?: T, tbl?: any, embeddings?: EmbeddingFunction<T>) {
constructor (query: T, tbl?: any, embeddings?: EmbeddingFunction<T>) {
this._tbl = tbl
this._query = query
this._limit = undefined
this._limit = 10
this._nprobes = 20
this._refineFactor = undefined
this._select = undefined
@@ -113,12 +113,10 @@ export class Query<T = number[]> {
* Execute the query and return the results as an Array of Objects
*/
async execute<T = Record<string, unknown>> (): Promise<T[]> {
if (this._query !== undefined) {
if (this._embeddings !== undefined) {
this._queryVector = (await this._embeddings.embed([this._query]))[0]
} else {
this._queryVector = this._query as number[]
}
if (this._embeddings !== undefined) {
this._queryVector = (await this._embeddings.embed([this._query]))[0]
} else {
this._queryVector = this._query as number[]
}
const isElectron = this.isElectron()

View File

@@ -16,8 +16,7 @@ import {
type EmbeddingFunction, type Table, type VectorIndexParams, type Connection,
type ConnectionOptions, type CreateTableOptions, type VectorIndex,
type WriteOptions,
type IndexStats,
type UpdateArgs, type UpdateSqlArgs
type IndexStats
} from '../index'
import { Query } from '../query'
@@ -25,7 +24,6 @@ import { Vector, Table as ArrowTable } from 'apache-arrow'
import { HttpLancedbClient } from './client'
import { isEmbeddingFunction } from '../embedding/embedding_function'
import { createEmptyTable, fromRecordsToStreamBuffer, fromTableToStreamBuffer } from '../arrow'
import { toSQL } from '../util'
/**
* Remote connection.
@@ -57,8 +55,8 @@ export class RemoteConnection implements Connection {
return 'db://' + this._client.uri
}
async tableNames (pageToken: string = '', limit: number = 10): Promise<string[]> {
const response = await this._client.get('/v1/table/', { limit, page_token: pageToken })
async tableNames (): Promise<string[]> {
const response = await this._client.get('/v1/table/')
return response.data.tables
}
@@ -195,17 +193,6 @@ export class RemoteTable<T = number[]> implements Table<T> {
return this._name
}
get schema (): Promise<any> {
return this._client.post(`/v1/table/${this._name}/describe/`).then(res => {
if (res.status !== 200) {
throw new Error(`Server Error, status: ${res.status}, ` +
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
`message: ${res.statusText}: ${res.data}`)
}
return res.data?.schema
})
}
search (query: T): Query<T> {
return new RemoteQuery(query, this._client, this._name)//, this._embeddings_new)
}
@@ -246,44 +233,7 @@ export class RemoteTable<T = number[]> implements Table<T> {
return data.length
}
async createIndex (indexParams: VectorIndexParams): Promise<void> {
const unsupportedParams = [
'index_name',
'num_partitions',
'max_iters',
'use_opq',
'num_sub_vectors',
'num_bits',
'max_opq_iters',
'replace'
]
for (const param of unsupportedParams) {
// eslint-disable-next-line @typescript-eslint/strict-boolean-expressions
if (indexParams[param as keyof VectorIndexParams]) {
throw new Error(`${param} is not supported for remote connections`)
}
}
const column = indexParams.column ?? 'vector'
const indexType = 'vector' // only vector index is supported for remote connections
const metricType = indexParams.metric_type ?? 'L2'
const indexCacheSize = indexParams ?? null
const data = {
column,
index_type: indexType,
metric_type: metricType,
index_cache_size: indexCacheSize
}
const res = await this._client.post(`/v1/table/${this._name}/create_index/`, data)
if (res.status !== 200) {
throw new Error(`Server Error, status: ${res.status}, ` +
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
`message: ${res.statusText}: ${res.data}`)
}
}
async createScalarIndex (column: string, replace: boolean): Promise<void> {
async createIndex (indexParams: VectorIndexParams): Promise<any> {
throw new Error('Not implemented')
}
@@ -296,26 +246,6 @@ export class RemoteTable<T = number[]> implements Table<T> {
await this._client.post(`/v1/table/${this._name}/delete/`, { predicate: filter })
}
async update (args: UpdateArgs | UpdateSqlArgs): Promise<void> {
let filter: string | null
let updates: Record<string, string>
if ('valuesSql' in args) {
filter = args.where ?? null
updates = args.valuesSql
} else {
filter = args.where ?? null
updates = {}
for (const [key, value] of Object.entries(args.values)) {
updates[key] = toSQL(value)
}
}
await this._client.post(`/v1/table/${this._name}/update/`, {
predicate: filter,
updates: Object.entries(updates).map(([key, value]) => [key, value])
})
}
async listIndices (): Promise<VectorIndex[]> {
const results = await this._client.post(`/v1/table/${this._name}/index/list/`)
return results.data.indexes?.map((index: any) => ({

View File

@@ -78,31 +78,12 @@ describe('LanceDB client', function () {
})
it('limits # of results', async function () {
const uri = await createTestDB(2, 100)
const uri = await createTestDB()
const con = await lancedb.connect(uri)
const table = await con.openTable('vectors')
let results = await table.search([0.1, 0.3]).limit(1).execute()
const results = await table.search([0.1, 0.3]).limit(1).execute()
assert.equal(results.length, 1)
assert.equal(results[0].id, 1)
// there is a default limit if unspecified
results = await table.search([0.1, 0.3]).execute()
assert.equal(results.length, 10)
})
it('uses a filter / where clause without vector search', async function () {
// eslint-disable-next-line @typescript-eslint/explicit-function-return-type
const assertResults = (results: Array<Record<string, unknown>>) => {
assert.equal(results.length, 50)
}
const uri = await createTestDB(2, 100)
const con = await lancedb.connect(uri)
const table = (await con.openTable('vectors')) as LocalTable
let results = await table.filter('id % 2 = 0').execute()
assertResults(results)
results = await table.where('id % 2 = 0').execute()
assertResults(results)
})
it('uses a filter / where clause', async function () {
@@ -135,17 +116,6 @@ describe('LanceDB client', function () {
assert.isTrue(results.length === 10)
})
it('should allow creation and use of scalar indices', async function () {
const uri = await createTestDB(16, 300)
const con = await lancedb.connect(uri)
const table = await con.openTable('vectors')
await table.createScalarIndex('id', true)
// Prefiltering should still work the same
const results = await table.search(new Array(16).fill(0.1)).limit(10).filter('id >= 10').prefilter(true).execute()
assert.isTrue(results.length === 10)
})
it('select only a subset of columns', async function () {
const uri = await createTestDB()
const con = await lancedb.connect(uri)
@@ -290,46 +260,6 @@ describe('LanceDB client', function () {
assert.equal(await table.countRows(), 2)
})
it('can update records in the table', async function () {
const uri = await createTestDB()
const con = await lancedb.connect(uri)
const table = await con.openTable('vectors')
assert.equal(await table.countRows(), 2)
await table.update({ where: 'price = 10', valuesSql: { price: '100' } })
const results = await table.search([0.1, 0.2]).execute()
assert.equal(results[0].price, 100)
assert.equal(results[1].price, 11)
})
it('can update the records using a literal value', async function () {
const uri = await createTestDB()
const con = await lancedb.connect(uri)
const table = await con.openTable('vectors')
assert.equal(await table.countRows(), 2)
await table.update({ where: 'price = 10', values: { price: 100 } })
const results = await table.search([0.1, 0.2]).execute()
assert.equal(results[0].price, 100)
assert.equal(results[1].price, 11)
})
it('can update every record in the table', async function () {
const uri = await createTestDB()
const con = await lancedb.connect(uri)
const table = await con.openTable('vectors')
assert.equal(await table.countRows(), 2)
await table.update({ valuesSql: { price: '100' } })
const results = await table.search([0.1, 0.2]).execute()
assert.equal(results[0].price, 100)
assert.equal(results[1].price, 100)
})
it('can delete records from a table', async function () {
const uri = await createTestDB()
const con = await lancedb.connect(uri)
@@ -612,7 +542,7 @@ describe('Compact and cleanup', function () {
// should have no effect, but this validates the arguments are parsed.
await table.compactFiles({
targetRowsPerFragment: 102410,
targetRowsPerFragment: 1024 * 10,
maxRowsPerGroup: 1024,
materializeDeletions: true,
materializeDeletionsThreshold: 0.5,

View File

@@ -1,45 +0,0 @@
// Copyright 2023 LanceDB Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
import { toSQL } from '../util'
import * as chai from 'chai'
const expect = chai.expect
describe('toSQL', function () {
it('should turn string to SQL expression', function () {
expect(toSQL('foo')).to.equal("'foo'")
})
it('should turn number to SQL expression', function () {
expect(toSQL(123)).to.equal('123')
})
it('should turn boolean to SQL expression', function () {
expect(toSQL(true)).to.equal('TRUE')
})
it('should turn null to SQL expression', function () {
expect(toSQL(null)).to.equal('NULL')
})
it('should turn Date to SQL expression', function () {
const date = new Date('05 October 2011 14:48 UTC')
expect(toSQL(date)).to.equal("'2011-10-05T14:48:00.000Z'")
})
it('should turn array to SQL expression', function () {
expect(toSQL(['foo', 'bar', true, 1])).to.equal("['foo', 'bar', TRUE, 1]")
})
})

View File

@@ -1,44 +0,0 @@
// Copyright 2023 LanceDB Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
export type Literal = string | number | boolean | null | Date | Literal[]
export function toSQL (value: Literal): string {
if (typeof value === 'string') {
return `'${value}'`
}
if (typeof value === 'number') {
return value.toString()
}
if (typeof value === 'boolean') {
return value ? 'TRUE' : 'FALSE'
}
if (value === null) {
return 'NULL'
}
if (value instanceof Date) {
return `'${value.toISOString()}'`
}
if (Array.isArray(value)) {
return `[${value.map(toSQL).join(', ')}]`
}
// eslint-disable-next-line @typescript-eslint/restrict-template-expressions
throw new Error(`Unsupported value type: ${typeof value} value: (${value})`)
}

View File

@@ -1,5 +1,5 @@
[bumpversion]
current_version = 0.4.1
current_version = 0.3.4
commit = True
message = [python] Bump version: {current_version} → {new_version}
tag = True

View File

@@ -23,7 +23,7 @@ from overrides import EnforceOverrides, override
from pyarrow import fs
from .table import LanceTable, Table
from .util import fs_from_uri, get_uri_location, get_uri_scheme, join_uri
from .util import fs_from_uri, get_uri_location, get_uri_scheme
if TYPE_CHECKING:
from .common import DATA, URI
@@ -288,13 +288,14 @@ class LanceDBConnection(DBConnection):
A list of table names.
"""
try:
filesystem = fs_from_uri(self.uri)[0]
filesystem, path = fs_from_uri(self.uri)
except pa.ArrowInvalid:
raise NotImplementedError("Unsupported scheme: " + self.uri)
try:
loc = get_uri_location(self.uri)
paths = filesystem.get_file_info(fs.FileSelector(loc))
paths = filesystem.get_file_info(
fs.FileSelector(get_uri_location(self.uri))
)
except FileNotFoundError:
# It is ok if the file does not exist since it will be created
paths = []
@@ -372,7 +373,7 @@ class LanceDBConnection(DBConnection):
"""
try:
filesystem, path = fs_from_uri(self.uri)
table_path = join_uri(path, name + ".lance")
table_path = os.path.join(path, name + ".lance")
filesystem.delete_dir(table_path)
except FileNotFoundError:
if not ignore_missing:

View File

@@ -75,14 +75,8 @@ def populate_index(index: tantivy.Index, table: LanceTable, fields: List[str]) -
The number of rows indexed
"""
# first check the fields exist and are string or large string type
nested = []
for name in fields:
try:
f = table.schema.field(name) # raises KeyError if not found
except KeyError:
f = resolve_path(table.schema, name)
nested.append(name)
f = table.schema.field(name) # raises KeyError if not found
if not pa.types.is_string(f.type) and not pa.types.is_large_string(f.type):
raise TypeError(f"Field {name} is not a string type")
@@ -91,16 +85,7 @@ def populate_index(index: tantivy.Index, table: LanceTable, fields: List[str]) -
# write data into index
dataset = table.to_lance()
row_id = 0
max_nested_level = 0
if len(nested) > 0:
max_nested_level = max([len(name.split(".")) for name in nested])
for b in dataset.to_batches(columns=fields):
if max_nested_level > 0:
b = pa.Table.from_batches([b])
for _ in range(max_nested_level - 1):
b = b.flatten()
for i in range(b.num_rows):
doc = tantivy.Document()
doc.add_integer("doc_id", row_id)
@@ -113,30 +98,6 @@ def populate_index(index: tantivy.Index, table: LanceTable, fields: List[str]) -
return row_id
def resolve_path(schema, field_name: str) -> pa.Field:
"""
Resolve a nested field path to a list of field names
Parameters
----------
field_name : str
The field name to resolve
Returns
-------
List[str]
The resolved path
"""
path = field_name.split(".")
field = schema.field(path.pop(0))
for segment in path:
if pa.types.is_struct(field.type):
field = field.type.field(segment)
else:
raise KeyError(f"field {field_name} not found in schema {schema}")
return field
def search_index(
index: tantivy.Index, query: str, limit: int = 10
) -> Tuple[Tuple[int], Tuple[float]]:

View File

@@ -348,20 +348,3 @@ def get_extras(field_info: pydantic.fields.FieldInfo, key: str) -> Any:
if PYDANTIC_VERSION.major >= 2:
return (field_info.json_schema_extra or {}).get(key)
return (field_info.field_info.extra or {}).get("json_schema_extra", {}).get(key)
if PYDANTIC_VERSION.major < 2:
def model_to_dict(model: pydantic.BaseModel) -> Dict[str, Any]:
"""
Convert a Pydantic model to a dictionary.
"""
return model.dict()
else:
def model_to_dict(model: pydantic.BaseModel) -> Dict[str, Any]:
"""
Convert a Pydantic model to a dictionary.
"""
return model.model_dump()

View File

@@ -185,40 +185,14 @@ class LanceQueryBuilder(ABC):
"""
return self.to_pandas()
def to_pandas(self, flatten: Optional[Union[int, bool]] = None) -> "pd.DataFrame":
def to_pandas(self) -> "pd.DataFrame":
"""
Execute the query and return the results as a pandas DataFrame.
In addition to the selected columns, LanceDB also returns a vector
and also the "_distance" column which is the distance between the query
vector and the returned vector.
Parameters
----------
flatten: Optional[Union[int, bool]]
If flatten is True, flatten all nested columns.
If flatten is an integer, flatten the nested columns up to the
specified depth.
If unspecified, do not flatten the nested columns.
"""
tbl = self.to_arrow()
if flatten is True:
while True:
tbl = tbl.flatten()
has_struct = False
# loop through all columns to check if there is any struct column
if any(pa.types.is_struct(col.type) for col in tbl.schema):
continue
else:
break
elif isinstance(flatten, int):
if flatten <= 0:
raise ValueError(
"Please specify a positive integer for flatten or the boolean value `True`"
)
while flatten > 0:
tbl = tbl.flatten()
flatten -= 1
return tbl.to_pandas()
return self.to_arrow().to_pandas()
@abstractmethod
def to_arrow(self) -> pa.Table:

View File

@@ -18,8 +18,6 @@ import attrs
import pyarrow as pa
from pydantic import BaseModel
from lancedb.common import VECTOR_COLUMN_NAME
__all__ = ["LanceDBClient", "VectorQuery", "VectorQueryResult"]
@@ -45,8 +43,6 @@ class VectorQuery(BaseModel):
refine_factor: Optional[int] = None
vector_column: str = VECTOR_COLUMN_NAME
@attrs.define
class VectorQueryResult:

View File

@@ -56,7 +56,7 @@ class RemoteDBConnection(DBConnection):
self._loop = asyncio.get_event_loop()
def __repr__(self) -> str:
return f"RemoteConnect(name={self.db_name})"
return f"RemoveConnect(name={self.db_name})"
@override
def table_names(
@@ -167,10 +167,10 @@ class RemoteDBConnection(DBConnection):
Can create with list of tuples or dictionaries:
>>> import lancedb
>>> db = lancedb.connect("db://...", api_key="...", region="...") # doctest: +SKIP
>>> db = lancedb.connect("db://test-project-8f45eb")
>>> data = [{"vector": [1.1, 1.2], "lat": 45.5, "long": -122.7},
... {"vector": [0.2, 1.8], "lat": 40.1, "long": -74.1}]
>>> db.create_table("my_table", data) # doctest: +SKIP
>>> db.create_table("my_table", data)
LanceTable(my_table)
You can also pass a pandas DataFrame:
@@ -181,7 +181,7 @@ class RemoteDBConnection(DBConnection):
... "lat": [45.5, 40.1],
... "long": [-122.7, -74.1]
... })
>>> db.create_table("table2", data) # doctest: +SKIP
>>> db.create_table("table2", data)
LanceTable(table2)
>>> custom_schema = pa.schema([
@@ -189,7 +189,7 @@ class RemoteDBConnection(DBConnection):
... pa.field("lat", pa.float32()),
... pa.field("long", pa.float32())
... ])
>>> db.create_table("table3", data, schema = custom_schema) # doctest: +SKIP
>>> db.create_table("table3", data, schema = custom_schema)
LanceTable(table3)
It is also possible to create an table from `[Iterable[pa.RecordBatch]]`:
@@ -211,7 +211,7 @@ class RemoteDBConnection(DBConnection):
... pa.field("item", pa.utf8()),
... pa.field("price", pa.float32()),
... ])
>>> db.create_table("table4", make_batches(), schema=schema) # doctest: +SKIP
>>> db.create_table("table4", make_batches(), schema=schema)
LanceTable(table4)
"""

View File

@@ -13,7 +13,7 @@
import uuid
from functools import cached_property
from typing import Dict, Optional, Union
from typing import Optional, Union
import pyarrow as pa
from lance import json_to_schema
@@ -22,7 +22,6 @@ from lancedb.common import DATA, VEC, VECTOR_COLUMN_NAME
from ..query import LanceVectorQueryBuilder
from ..table import Query, Table, _sanitize_data
from ..util import value_to_sql
from .arrow import to_ipc_binary
from .client import ARROW_STREAM_CONTENT_TYPE
from .db import RemoteDBConnection
@@ -64,12 +63,6 @@ class RemoteTable(Table):
"""to_pandas() is not supported on the LanceDB cloud"""
return NotImplementedError("to_pandas() is not supported on the LanceDB cloud")
def create_scalar_index(self, *args, **kwargs):
"""Creates a scalar index"""
return NotImplementedError(
"create_scalar_index() is not supported on the LanceDB cloud"
)
def create_index(
self,
metric="L2",
@@ -92,7 +85,7 @@ class RemoteTable(Table):
>>> import lancedb
>>> import uuid
>>> from lancedb.schema import vector
>>> db = lancedb.connect("db://...", api_key="...", region="...") # doctest: +SKIP
>>> conn = lancedb.connect("db://...", api_key="...", region="...")
>>> table_name = uuid.uuid4().hex
>>> schema = pa.schema(
... [
@@ -101,11 +94,11 @@ class RemoteTable(Table):
... pa.field("s", pa.string(), False),
... ]
... )
>>> table = db.create_table( # doctest: +SKIP
... table_name, # doctest: +SKIP
... schema=schema, # doctest: +SKIP
... )
>>> table.create_index("L2", "vector") # doctest: +SKIP
>>> table = conn.create_table(
>>> table_name,
>>> schema=schema,
>>> )
>>> table.create_index("L2", "vector")
"""
index_type = "vector"
@@ -180,22 +173,22 @@ class RemoteTable(Table):
Examples
--------
>>> import lancedb
>>> db = lancedb.connect("db://...", api_key="...", region="...") # doctest: +SKIP
>>> db = lancedb.connect("db://...", api_key="...", region="...")
>>> data = [
... {"original_width": 100, "caption": "bar", "vector": [0.1, 2.3, 4.5]},
... {"original_width": 2000, "caption": "foo", "vector": [0.5, 3.4, 1.3]},
... {"original_width": 3000, "caption": "test", "vector": [0.3, 6.2, 2.6]}
... ]
>>> table = db.create_table("my_table", data) # doctest: +SKIP
>>> table = db.create_table("my_table", data)
>>> query = [0.4, 1.4, 2.4]
>>> (table.search(query, vector_column_name="vector") # doctest: +SKIP
... .where("original_width > 1000", prefilter=True) # doctest: +SKIP
... .select(["caption", "original_width"]) # doctest: +SKIP
... .limit(2) # doctest: +SKIP
... .to_pandas()) # doctest: +SKIP
caption original_width vector _distance # doctest: +SKIP
0 foo 2000 [0.5, 3.4, 1.3] 5.220000 # doctest: +SKIP
1 test 3000 [0.3, 6.2, 2.6] 23.089996 # doctest: +SKIP
>>> (table.search(query, vector_column_name="vector")
... .where("original_width > 1000", prefilter=True)
... .select(["caption", "original_width"])
... .limit(2)
... .to_pandas())
caption original_width vector _distance
0 foo 2000 [0.5, 3.4, 1.3] 5.220000
1 test 3000 [0.3, 6.2, 2.6] 23.089996
Parameters
----------
@@ -253,92 +246,32 @@ class RemoteTable(Table):
... {"x": 2, "vector": [3, 4]},
... {"x": 3, "vector": [5, 6]}
... ]
>>> db = lancedb.connect("db://...", api_key="...", region="...") # doctest: +SKIP
>>> table = db.create_table("my_table", data) # doctest: +SKIP
>>> table.search([10,10]).to_pandas() # doctest: +SKIP
x vector _distance # doctest: +SKIP
0 3 [5.0, 6.0] 41.0 # doctest: +SKIP
1 2 [3.0, 4.0] 85.0 # doctest: +SKIP
2 1 [1.0, 2.0] 145.0 # doctest: +SKIP
>>> table.delete("x = 2") # doctest: +SKIP
>>> table.search([10,10]).to_pandas() # doctest: +SKIP
x vector _distance # doctest: +SKIP
0 3 [5.0, 6.0] 41.0 # doctest: +SKIP
1 1 [1.0, 2.0] 145.0 # doctest: +SKIP
>>> db = lancedb.connect("db://...", api_key="...", region="...")
>>> table = db.create_table("my_table", data)
>>> table.search([10,10]).to_pandas()
x vector _distance
0 3 [5.0, 6.0] 41.0
1 2 [3.0, 4.0] 85.0
2 1 [1.0, 2.0] 145.0
>>> table.delete("x = 2")
>>> table.search([10,10]).to_pandas()
x vector _distance
0 3 [5.0, 6.0] 41.0
1 1 [1.0, 2.0] 145.0
If you have a list of values to delete, you can combine them into a
stringified list and use the `IN` operator:
>>> to_remove = [1, 3] # doctest: +SKIP
>>> to_remove = ", ".join([str(v) for v in to_remove]) # doctest: +SKIP
>>> table.delete(f"x IN ({to_remove})") # doctest: +SKIP
>>> table.search([10,10]).to_pandas() # doctest: +SKIP
x vector _distance # doctest: +SKIP
0 2 [3.0, 4.0] 85.0 # doctest: +SKIP
>>> to_remove = [1, 3]
>>> to_remove = ", ".join([str(v) for v in to_remove])
>>> to_remove
'1, 3'
>>> table.delete(f"x IN ({to_remove})")
>>> table.search([10,10]).to_pandas()
x vector _distance
0 2 [3.0, 4.0] 85.0
"""
payload = {"predicate": predicate}
self._conn._loop.run_until_complete(
self._conn._client.post(f"/v1/table/{self._name}/delete/", data=payload)
)
def update(
self,
where: Optional[str] = None,
values: Optional[dict] = None,
*,
values_sql: Optional[Dict[str, str]] = None,
):
"""
This can be used to update zero to all rows depending on how many
rows match the where clause.
Parameters
----------
where: str, optional
The SQL where clause to use when updating rows. For example, 'x = 2'
or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
values: dict, optional
The values to update. The keys are the column names and the values
are the values to set.
values_sql: dict, optional
The values to update, expressed as SQL expression strings. These can
reference existing columns. For example, {"x": "x + 1"} will increment
the x column by 1.
Examples
--------
>>> import lancedb
>>> data = [
... {"x": 1, "vector": [1, 2]},
... {"x": 2, "vector": [3, 4]},
... {"x": 3, "vector": [5, 6]}
... ]
>>> db = lancedb.connect("db://...", api_key="...", region="...") # doctest: +SKIP
>>> table = db.create_table("my_table", data) # doctest: +SKIP
>>> table.to_pandas() # doctest: +SKIP
x vector # doctest: +SKIP
0 1 [1.0, 2.0] # doctest: +SKIP
1 2 [3.0, 4.0] # doctest: +SKIP
2 3 [5.0, 6.0] # doctest: +SKIP
>>> table.update(where="x = 2", values={"vector": [10, 10]}) # doctest: +SKIP
>>> table.to_pandas() # doctest: +SKIP
x vector # doctest: +SKIP
0 1 [1.0, 2.0] # doctest: +SKIP
1 3 [5.0, 6.0] # doctest: +SKIP
2 2 [10.0, 10.0] # doctest: +SKIP
"""
if values is not None and values_sql is not None:
raise ValueError("Only one of values or values_sql can be provided")
if values is None and values_sql is None:
raise ValueError("Either values or values_sql must be provided")
if values is not None:
updates = [[k, value_to_sql(v)] for k, v in values.items()]
else:
updates = [[k, v] for k, v in values_sql.items()]
payload = {"predicate": where, "updates": updates}
self._conn._loop.run_until_complete(
self._conn._client.post(f"/v1/table/{self._name}/update/", data=payload)
)

View File

@@ -17,21 +17,20 @@ import inspect
import os
from abc import ABC, abstractmethod
from functools import cached_property
from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Union
from typing import TYPE_CHECKING, Any, Iterable, List, Optional, Union
import lance
import numpy as np
import pyarrow as pa
import pyarrow.compute as pc
import pyarrow.fs as pa_fs
from lance import LanceDataset
from lance.vector import vec_to_table
from .common import DATA, VEC, VECTOR_COLUMN_NAME
from .embeddings import EmbeddingFunctionConfig, EmbeddingFunctionRegistry
from .pydantic import LanceModel, model_to_dict
from .pydantic import LanceModel
from .query import LanceQueryBuilder, Query
from .util import fs_from_uri, safe_import_pandas, value_to_sql, join_uri
from .util import fs_from_uri, safe_import_pandas
from .utils.events import register_event
if TYPE_CHECKING:
@@ -54,10 +53,8 @@ def _sanitize_data(
# convert to list of dict if data is a bunch of LanceModels
if isinstance(data[0], LanceModel):
schema = data[0].__class__.to_arrow_schema()
data = [model_to_dict(d) for d in data]
data = pa.Table.from_pylist(data, schema=schema)
else:
data = pa.Table.from_pylist(data)
data = [dict(d) for d in data]
data = pa.Table.from_pylist(data)
elif isinstance(data, dict):
data = vec_to_table(data)
elif pd is not None and isinstance(data, pd.DataFrame):
@@ -221,77 +218,6 @@ class Table(ABC):
"""
raise NotImplementedError
@abstractmethod
def create_scalar_index(
self,
column: str,
*,
replace: bool = True,
):
"""Create a scalar index on a column.
Scalar indices, like vector indices, can be used to speed up scans. A scalar
index can speed up scans that contain filter expressions on the indexed column.
For example, the following scan will be faster if the column ``my_col`` has
a scalar index:
.. code-block:: python
import lancedb
db = lancedb.connect("/data/lance")
img_table = db.open_table("images")
my_df = img_table.search().where("my_col = 7", prefilter=True).to_pandas()
Scalar indices can also speed up scans containing a vector search and a
prefilter:
.. code-block::python
import lancedb
db = lancedb.connect("/data/lance")
img_table = db.open_table("images")
img_table.search([1, 2, 3, 4], vector_column_name="vector")
.where("my_col != 7", prefilter=True)
.to_pandas()
Scalar indices can only speed up scans for basic filters using
equality, comparison, range (e.g. ``my_col BETWEEN 0 AND 100``), and set
membership (e.g. `my_col IN (0, 1, 2)`)
Scalar indices can be used if the filter contains multiple indexed columns and
the filter criteria are AND'd or OR'd together
(e.g. ``my_col < 0 AND other_col> 100``)
Scalar indices may be used if the filter contains non-indexed columns but,
depending on the structure of the filter, they may not be usable. For example,
if the column ``not_indexed`` does not have a scalar index then the filter
``my_col = 0 OR not_indexed = 1`` will not be able to use any scalar index on
``my_col``.
**Experimental API**
Parameters
----------
column : str
The column to be indexed. Must be a boolean, integer, float,
or string column.
replace : bool, default True
Replace the existing index if it exists.
Examples
--------
.. code-block:: python
import lance
dataset = lance.dataset("/tmp/images.lance")
dataset.create_scalar_index("category")
"""
raise NotImplementedError
@abstractmethod
def add(
self,
@@ -455,62 +381,6 @@ class Table(ABC):
"""
raise NotImplementedError
@abstractmethod
def update(
self,
where: Optional[str] = None,
values: Optional[dict] = None,
*,
values_sql: Optional[Dict[str, str]] = None,
):
"""
This can be used to update zero to all rows depending on how many
rows match the where clause. If no where clause is provided, then
all rows will be updated.
Either `values` or `values_sql` must be provided. You cannot provide
both.
Parameters
----------
where: str, optional
The SQL where clause to use when updating rows. For example, 'x = 2'
or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
values: dict, optional
The values to update. The keys are the column names and the values
are the values to set.
values_sql: dict, optional
The values to update, expressed as SQL expression strings. These can
reference existing columns. For example, {"x": "x + 1"} will increment
the x column by 1.
Examples
--------
>>> import lancedb
>>> import pandas as pd
>>> data = pd.DataFrame({"x": [1, 2, 3], "vector": [[1, 2], [3, 4], [5, 6]]})
>>> db = lancedb.connect("./.lancedb")
>>> table = db.create_table("my_table", data)
>>> table.to_pandas()
x vector
0 1 [1.0, 2.0]
1 2 [3.0, 4.0]
2 3 [5.0, 6.0]
>>> table.update(where="x = 2", values={"vector": [10, 10]})
>>> table.to_pandas()
x vector
0 1 [1.0, 2.0]
1 3 [5.0, 6.0]
2 2 [10.0, 10.0]
>>> table.update(values_sql={"x": "x + 1"})
>>> table.to_pandas()
x vector
0 2 [1.0, 2.0]
1 4 [5.0, 6.0]
2 3 [10.0, 10.0]
"""
raise NotImplementedError
class LanceTable(Table):
"""
@@ -679,7 +549,7 @@ class LanceTable(Table):
@property
def _dataset_uri(self) -> str:
return join_uri(self._conn.uri, f"{self.name}.lance")
return os.path.join(self._conn.uri, f"{self.name}.lance")
def create_index(
self,
@@ -705,12 +575,7 @@ class LanceTable(Table):
self._reset_dataset()
register_event("create_index")
def create_scalar_index(self, column: str, *, replace: bool = True):
self._dataset.create_scalar_index(column, index_type="BTREE", replace=replace)
def create_fts_index(
self, field_names: Union[str, List[str]], *, replace: bool = False
):
def create_fts_index(self, field_names: Union[str, List[str]]):
"""Create a full-text search index on the table.
Warning - this API is highly experimental and is highly likely to change
@@ -720,31 +585,17 @@ class LanceTable(Table):
----------
field_names: str or list of str
The name(s) of the field to index.
replace: bool, default False
If True, replace the existing index if it exists. Note that this is
not yet an atomic operation; the index will be temporarily
unavailable while the new index is being created.
"""
from .fts import create_index, populate_index
if isinstance(field_names, str):
field_names = [field_names]
fs, path = fs_from_uri(self._get_fts_index_path())
index_exists = fs.get_file_info(path).type != pa_fs.FileType.NotFound
if index_exists:
if not replace:
raise ValueError(
f"Index already exists. Use replace=True to overwrite."
)
fs.delete_dir(path)
index = create_index(self._get_fts_index_path(), field_names)
populate_index(index, self, field_names)
register_event("create_fts_index")
def _get_fts_index_path(self):
return join_uri(self._dataset_uri, "_indices", "tantivy")
return os.path.join(self._dataset_uri, "_indices", "tantivy")
@cached_property
def _dataset(self) -> LanceDataset:
@@ -934,7 +785,7 @@ class LanceTable(Table):
and also the "_distance" column which is the distance between the query
vector and the returned vector.
"""
register_event("search_table")
register_event("search")
return LanceQueryBuilder.create(
self, query, query_type, vector_column_name=vector_column_name
)
@@ -1055,42 +906,35 @@ class LanceTable(Table):
f"Table {name} does not exist."
f"Please first call db.create_table({name}, data)"
)
register_event("open_table")
return tbl
def delete(self, where: str):
self._dataset.delete(where)
def update(
self,
where: Optional[str] = None,
values: Optional[dict] = None,
*,
values_sql: Optional[Dict[str, str]] = None,
):
def update(self, where: str, values: dict):
"""
EXPERIMENTAL: Update rows in the table (not threadsafe).
This can be used to update zero to all rows depending on how many
rows match the where clause.
Parameters
----------
where: str, optional
where: str
The SQL where clause to use when updating rows. For example, 'x = 2'
or 'x IN (1, 2, 3)'. The filter must not be empty, or it will error.
values: dict, optional
values: dict
The values to update. The keys are the column names and the values
are the values to set.
values_sql: dict, optional
The values to update, expressed as SQL expression strings. These can
reference existing columns. For example, {"x": "x + 1"} will increment
the x column by 1.
Examples
--------
>>> import lancedb
>>> import pandas as pd
>>> data = pd.DataFrame({"x": [1, 2, 3], "vector": [[1, 2], [3, 4], [5, 6]]})
>>> data = [
... {"x": 1, "vector": [1, 2]},
... {"x": 2, "vector": [3, 4]},
... {"x": 3, "vector": [5, 6]}
... ]
>>> db = lancedb.connect("./.lancedb")
>>> table = db.create_table("my_table", data)
>>> table.to_pandas()
@@ -1106,15 +950,18 @@ class LanceTable(Table):
2 2 [10.0, 10.0]
"""
if values is not None and values_sql is not None:
raise ValueError("Only one of values or values_sql can be provided")
if values is None and values_sql is None:
raise ValueError("Either values or values_sql must be provided")
if values is not None:
values_sql = {k: value_to_sql(v) for k, v in values.items()}
self.to_lance().update(values_sql, where)
orig_data = self._dataset.to_table(filter=where).combine_chunks()
if len(orig_data) == 0:
return
for col, val in values.items():
i = orig_data.column_names.index(col)
if i < 0:
raise ValueError(f"Column {col} does not exist")
orig_data = orig_data.set_column(
i, col, pa.array([val] * len(orig_data), type=orig_data[col].type)
)
self.delete(where)
self.add(orig_data, mode="append")
self._reset_dataset()
register_event("update")

View File

@@ -12,13 +12,9 @@
# limitations under the License.
import os
from datetime import date, datetime
from functools import singledispatch
import pathlib
from typing import Tuple, Union
from typing import Tuple
from urllib.parse import urlparse
import numpy as np
import pyarrow.fs as pa_fs
@@ -63,12 +59,6 @@ def get_uri_location(uri: str) -> str:
str: Location part of the URL, without scheme
"""
parsed = urlparse(uri)
if len(parsed.scheme) == 1:
# Windows drive names are parsed as the scheme
# e.g. "c:\path" -> ParseResult(scheme="c", netloc="", path="/path", ...)
# So we add special handling here for schemes that are a single character
return uri
if not parsed.netloc:
return parsed.path
else:
@@ -91,29 +81,6 @@ def fs_from_uri(uri: str) -> Tuple[pa_fs.FileSystem, str]:
return pa_fs.FileSystem.from_uri(uri)
def join_uri(base: Union[str, pathlib.Path], *parts: str) -> str:
"""
Join a URI with multiple parts, handles both local and remote paths
Parameters
----------
base : str
The base URI
parts : str
The parts to join to the base URI, each separated by the
appropriate path separator for the URI scheme and OS
"""
if isinstance(base, pathlib.Path):
return base.joinpath(*parts)
base = str(base)
if get_uri_scheme(base) == "file":
# using pathlib for local paths make this windows compatible
# `get_uri_scheme` returns `file` for windows drive names (e.g. `c:\path`)
return str(pathlib.Path(base, *parts))
# for remote paths, just use os.path.join
return "/".join([p.rstrip("/") for p in [base, *parts]])
def safe_import_pandas():
try:
import pandas as pd
@@ -121,53 +88,3 @@ def safe_import_pandas():
return pd
except ImportError:
return None
@singledispatch
def value_to_sql(value):
raise NotImplementedError("SQL conversion is not implemented for this type")
@value_to_sql.register(str)
def _(value: str):
return f"'{value}'"
@value_to_sql.register(int)
def _(value: int):
return str(value)
@value_to_sql.register(float)
def _(value: float):
return str(value)
@value_to_sql.register(bool)
def _(value: bool):
return str(value).upper()
@value_to_sql.register(type(None))
def _(value: type(None)):
return "NULL"
@value_to_sql.register(datetime)
def _(value: datetime):
return f"'{value.isoformat()}'"
@value_to_sql.register(date)
def _(value: date):
return f"'{value.isoformat()}'"
@value_to_sql.register(list)
def _(value: list):
return "[" + ", ".join(map(value_to_sql, value)) + "]"
@value_to_sql.register(np.ndarray)
def _(value: np.ndarray):
return value_to_sql(value.tolist())

View File

@@ -64,10 +64,8 @@ class _Events:
Initializes the Events object with default values for events, rate_limit, and metadata.
"""
self.events = [] # events list
self.throttled_event_names = ["search_table"]
self.throttled_events = set()
self.max_events = 5 # max events to store in memory
self.rate_limit = 60.0 * 5 # rate limit (seconds)
self.max_events = 25 # max events to store in memory
self.rate_limit = 60.0 # rate limit (seconds)
self.time = 0.0
if is_git_dir():
@@ -114,21 +112,18 @@ class _Events:
return
if (
len(self.events) < self.max_events
): # Events list limited to self.max_events (drop any events past this)
): # Events list limited to 25 events (drop any events past this)
params.update(self.metadata)
event = {
"event": event_name,
"properties": params,
"timestamp": datetime.datetime.now(
tz=datetime.timezone.utc
).isoformat(),
"distinct_id": CONFIG["uuid"],
}
if event_name not in self.throttled_event_names:
self.events.append(event)
elif event_name not in self.throttled_events:
self.throttled_events.add(event_name)
self.events.append(event)
self.events.append(
{
"event": event_name,
"properties": params,
"timestamp": datetime.datetime.now(
tz=datetime.timezone.utc
).isoformat(),
"distinct_id": CONFIG["uuid"],
}
)
# Check rate limit
t = time.time()
@@ -140,6 +135,7 @@ class _Events:
"distinct_id": CONFIG["uuid"], # posthog needs this to accepts the event
"batch": self.events,
}
# POST equivalent to requests.post(self.url, json=data).
# threaded request is used to avoid blocking, retries are disabled, and verbose is disabled
# to avoid any possible disruption in the console.
@@ -154,7 +150,6 @@ class _Events:
# Flush & Reset
self.events = []
self.throttled_events = set()
self.time = t

View File

@@ -1,12 +1,12 @@
[project]
name = "lancedb"
version = "0.4.1"
version = "0.3.4"
dependencies = [
"deprecation",
"pylance==0.9.1",
"pylance==0.8.17",
"ratelimiter~=1.0",
"retry>=0.9.2",
"tqdm>=4.27.0",
"tqdm>=4.1.0",
"aiohttp",
"pydantic>=1.10",
"attrs>=21.3.0",

View File

@@ -43,15 +43,7 @@ def table(tmp_path) -> ldb.table.LanceTable:
for _ in range(100)
]
table = db.create_table(
"test",
data=pd.DataFrame(
{
"vector": vectors,
"text": text,
"text2": text,
"nested": [{"text": t} for t in text],
}
),
"test", data=pd.DataFrame({"vector": vectors, "text": text, "text2": text})
)
return table
@@ -83,24 +75,6 @@ def test_create_index_from_table(tmp_path, table):
assert len(df) == 10
assert "text" in df.columns
# Check whether it can be updated
table.add(
[
{
"vector": np.random.randn(128),
"text": "gorilla",
"text2": "gorilla",
"nested": {"text": "gorilla"},
}
]
)
with pytest.raises(ValueError, match="already exists"):
table.create_fts_index("text")
table.create_fts_index("text", replace=True)
assert len(table.search("gorilla").limit(1).to_pandas()) == 1
def test_create_index_multiple_columns(tmp_path, table):
table.create_fts_index(["text", "text2"])
@@ -115,9 +89,3 @@ def test_empty_rs(tmp_path, table, mocker):
mocker.patch("lancedb.fts.search_index", return_value=([], []))
df = table.search("puppy").limit(10).to_pandas()
assert len(df) == 0
def test_nested_schema(tmp_path, table):
table.create_fts_index("nested.text")
rs = table.search("puppy").limit(10).to_list()
assert len(rs) == 10

View File

@@ -12,7 +12,7 @@
# limitations under the License.
import functools
from datetime import date, datetime, timedelta
from datetime import timedelta
from pathlib import Path
from typing import List
from unittest.mock import PropertyMock, patch
@@ -22,7 +22,6 @@ import numpy as np
import pandas as pd
import pyarrow as pa
import pytest
from pydantic import BaseModel
from lancedb.conftest import MockTextEmbeddingFunction
from lancedb.db import LanceDBConnection
@@ -142,44 +141,14 @@ def test_add(db):
def test_add_pydantic_model(db):
# https://github.com/lancedb/lancedb/issues/562
class Metadata(BaseModel):
source: str
timestamp: datetime
class Document(BaseModel):
content: str
meta: Metadata
class LanceSchema(LanceModel):
id: str
vector: Vector(2)
class TestModel(LanceModel):
vector: Vector(16)
li: List[int]
payload: Document
tbl = LanceTable.create(db, "mytable", schema=LanceSchema, mode="overwrite")
assert tbl.schema == LanceSchema.to_arrow_schema()
# add works
expected = LanceSchema(
id="id",
vector=[0.0, 0.0],
li=[1, 2, 3],
payload=Document(
content="foo", meta=Metadata(source="bar", timestamp=datetime.now())
),
)
tbl.add([expected])
result = tbl.search([0.0, 0.0]).limit(1).to_pydantic(LanceSchema)[0]
assert result == expected
flattened = tbl.search([0.0, 0.0]).limit(1).to_pandas(flatten=1)
assert len(flattened.columns) == 6 # _distance is automatically added
really_flattened = tbl.search([0.0, 0.0]).limit(1).to_pandas(flatten=True)
assert len(really_flattened.columns) == 7
data = TestModel(vector=list(range(16)), li=[1, 2, 3])
table = LanceTable.create(db, "test", data=[data])
assert len(table) == 1
assert table.schema == TestModel.to_arrow_schema()
def _add(table, schema):
@@ -379,79 +348,14 @@ def test_update(db):
assert len(table) == 2
assert len(table.list_versions()) == 2
table.update(where="id=0", values={"vector": [1.1, 1.1]})
assert len(table.list_versions()) == 3
assert table.version == 3
assert len(table.list_versions()) == 4
assert table.version == 4
assert len(table) == 2
v = table.to_arrow()["vector"].combine_chunks()
v = v.values.to_numpy().reshape(2, 2)
assert np.allclose(v, np.array([[1.2, 1.9], [1.1, 1.1]]))
def test_update_types(db):
table = LanceTable.create(
db,
"my_table",
data=[
{
"id": 0,
"str": "foo",
"float": 1.1,
"timestamp": datetime(2021, 1, 1),
"date": date(2021, 1, 1),
"vector1": [1.0, 0.0],
"vector2": [1.0, 1.0],
}
],
)
# Update with SQL
table.update(
values_sql=dict(
id="1",
str="'bar'",
float="2.2",
timestamp="TIMESTAMP '2021-01-02 00:00:00'",
date="DATE '2021-01-02'",
vector1="[2.0, 2.0]",
vector2="[3.0, 3.0]",
)
)
actual = table.to_arrow().to_pylist()[0]
expected = dict(
id=1,
str="bar",
float=2.2,
timestamp=datetime(2021, 1, 2),
date=date(2021, 1, 2),
vector1=[2.0, 2.0],
vector2=[3.0, 3.0],
)
assert actual == expected
# Update with values
table.update(
values=dict(
id=2,
str="baz",
float=3.3,
timestamp=datetime(2021, 1, 3),
date=date(2021, 1, 3),
vector1=[3.0, 3.0],
vector2=np.array([4.0, 4.0]),
)
)
actual = table.to_arrow().to_pylist()[0]
expected = dict(
id=2,
str="baz",
float=3.3,
timestamp=datetime(2021, 1, 3),
date=date(2021, 1, 3),
vector1=[3.0, 3.0],
vector2=[4.0, 4.0],
)
assert actual == expected
def test_create_with_embedding_function(db):
class MyTable(LanceModel):
text: str
@@ -532,33 +436,6 @@ def test_multiple_vector_columns(db):
assert result1["text"].iloc[0] != result2["text"].iloc[0]
def test_create_scalar_index(db):
vec_array = pa.array(
[[1, 1], [2, 2], [3, 3], [4, 4], [5, 5]], pa.list_(pa.float32(), 2)
)
test_data = pa.Table.from_pydict(
{"x": ["c", "b", "a", "e", "b"], "y": [1, 2, 3, 4, 5], "vector": vec_array}
)
table = LanceTable.create(
db,
"my_table",
data=test_data,
)
table.create_scalar_index("x")
indices = table.to_lance().list_indices()
assert len(indices) == 1
scalar_index = indices[0]
assert scalar_index["type"] == "Scalar"
# Confirm that prefiltering still works with the scalar index column
results = table.search().where("x = 'c'").to_arrow()
assert results == test_data.slice(0, 1)
results = table.search([5, 5]).to_arrow()
assert results["_distance"][0].as_py() == 0
results = table.search([5, 5]).where("x != 'b'").to_arrow()
assert results["_distance"][0].as_py() > 0
def test_empty_query(db):
table = LanceTable.create(
db,

View File

@@ -11,12 +11,7 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import pathlib
import pytest
from lancedb.util import get_uri_scheme, join_uri
from lancedb.util import get_uri_scheme
def test_normalize_uri():
@@ -33,55 +28,3 @@ def test_normalize_uri():
for uri, expected_scheme in zip(uris, schemes):
parsed_scheme = get_uri_scheme(uri)
assert parsed_scheme == expected_scheme
def test_join_uri_remote():
schemes = ["s3", "az", "gs"]
for scheme in schemes:
expected = f"{scheme}://bucket/path/to/table.lance"
base_uri = f"{scheme}://bucket/path/to/"
parts = ["table.lance"]
assert join_uri(base_uri, *parts) == expected
base_uri = f"{scheme}://bucket"
parts = ["path", "to", "table.lance"]
assert join_uri(base_uri, *parts) == expected
# skip this test if on windows
@pytest.mark.skipif(os.name == "nt", reason="Windows paths are not POSIX")
def test_join_uri_posix():
for base in [
# relative path
"relative/path",
"relative/path/",
# an absolute path
"/absolute/path",
"/absolute/path/",
# a file URI
"file:///absolute/path",
"file:///absolute/path/",
]:
joined = join_uri(base, "table.lance")
assert joined == str(pathlib.Path(base) / "table.lance")
joined = join_uri(pathlib.Path(base), "table.lance")
assert joined == pathlib.Path(base) / "table.lance"
# skip this test if not on windows
@pytest.mark.skipif(os.name != "nt", reason="Windows paths are not POSIX")
def test_local_join_uri_windows():
# https://learn.microsoft.com/en-us/dotnet/standard/io/file-path-formats
for base in [
# windows relative path
"relative\\path",
"relative\\path\\",
# windows absolute path from current drive
"c:\\absolute\\path",
# relative path from root of current drive
"\\relative\\path",
]:
joined = join_uri(base, "table.lance")
assert joined == str(pathlib.Path(base) / "table.lance")
joined = join_uri(pathlib.Path(base), "table.lance")
assert joined == pathlib.Path(base) / "table.lance"

View File

@@ -1,6 +1,6 @@
[package]
name = "vectordb-node"
version = "0.4.1"
version = "0.3.9"
description = "Serverless, low-latency vector database for AI applications"
license = "Apache-2.0"
edition = "2018"

View File

@@ -23,7 +23,7 @@ pub enum Error {
#[snafu(display("column '{name}' is missing"))]
MissingColumn { name: String },
#[snafu(display("{name}: {message}"))]
OutOfRange { name: String, message: String },
RangeError { name: String, message: String },
#[snafu(display("{index_type} is not a valid index type"))]
InvalidIndexType { index_type: String },

View File

@@ -12,5 +12,4 @@
// See the License for the specific language governing permissions and
// limitations under the License.
pub mod scalar;
pub mod vector;

View File

@@ -1,43 +0,0 @@
// Copyright 2023 Lance Developers.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
use neon::{
context::{Context, FunctionContext},
result::JsResult,
types::{JsBoolean, JsBox, JsPromise, JsString},
};
use crate::{error::ResultExt, runtime, table::JsTable};
pub(crate) fn table_create_scalar_index(mut cx: FunctionContext) -> JsResult<JsPromise> {
let js_table = cx.this().downcast_or_throw::<JsBox<JsTable>, _>(&mut cx)?;
let column = cx.argument::<JsString>(0)?.value(&mut cx);
let replace = cx.argument::<JsBoolean>(1)?.value(&mut cx);
let rt = runtime(&mut cx)?;
let (deferred, promise) = cx.promise();
let channel = cx.channel();
let mut table = js_table.table.clone();
rt.spawn(async move {
let idx_result = table.create_scalar_index(&column, replace).await;
deferred.settle_with(&channel, move |mut cx| {
idx_result.or_throw(&mut cx)?;
Ok(cx.undefined())
});
});
Ok(promise)
}

View File

@@ -65,10 +65,12 @@ fn get_index_params_builder(
obj.get_opt::<JsString, _, _>(cx, "index_name")?
.map(|s| index_builder.index_name(s.value(cx)));
if let Some(metric_type) = obj.get_opt::<JsString, _, _>(cx, "metric_type")? {
let metric_type = MetricType::try_from(metric_type.value(cx).as_str()).unwrap();
index_builder.metric_type(metric_type);
}
obj.get_opt::<JsString, _, _>(cx, "metric_type")?
.map(|s| MetricType::try_from(s.value(cx).as_str()))
.map(|mt| {
let metric_type = mt.unwrap();
index_builder.metric_type(metric_type);
});
let num_partitions = obj.get_opt_usize(cx, "num_partitions")?;
let max_iters = obj.get_opt_usize(cx, "max_iters")?;
@@ -83,29 +85,23 @@ fn get_index_params_builder(
index_builder.ivf_params(ivf_params)
});
if let Some(use_opq) = obj.get_opt::<JsBoolean, _, _>(cx, "use_opq")? {
pq_params.use_opq = use_opq.value(cx);
}
obj.get_opt::<JsBoolean, _, _>(cx, "use_opq")?
.map(|s| pq_params.use_opq = s.value(cx));
if let Some(num_sub_vectors) = obj.get_opt_usize(cx, "num_sub_vectors")? {
pq_params.num_sub_vectors = num_sub_vectors;
}
obj.get_opt_usize(cx, "num_sub_vectors")?
.map(|s| pq_params.num_sub_vectors = s);
if let Some(num_bits) = obj.get_opt_usize(cx, "num_bits")? {
pq_params.num_bits = num_bits;
}
obj.get_opt_usize(cx, "num_bits")?
.map(|s| pq_params.num_bits = s);
if let Some(max_iters) = obj.get_opt_usize(cx, "max_iters")? {
pq_params.max_iters = max_iters;
}
obj.get_opt_usize(cx, "max_iters")?
.map(|s| pq_params.max_iters = s);
if let Some(max_opq_iters) = obj.get_opt_usize(cx, "max_opq_iters")? {
pq_params.max_opq_iters = max_opq_iters;
}
obj.get_opt_usize(cx, "max_opq_iters")?
.map(|s| pq_params.max_opq_iters = s);
if let Some(replace) = obj.get_opt::<JsBoolean, _, _>(cx, "replace")? {
index_builder.replace(replace.value(cx));
}
obj.get_opt::<JsBoolean, _, _>(cx, "replace")?
.map(|s| index_builder.replace(s.value(cx)));
Ok(index_builder)
}

View File

@@ -237,15 +237,10 @@ fn main(mut cx: ModuleContext) -> NeonResult<()> {
cx.export_function("tableAdd", JsTable::js_add)?;
cx.export_function("tableCountRows", JsTable::js_count_rows)?;
cx.export_function("tableDelete", JsTable::js_delete)?;
cx.export_function("tableUpdate", JsTable::js_update)?;
cx.export_function("tableCleanupOldVersions", JsTable::js_cleanup)?;
cx.export_function("tableCompactFiles", JsTable::js_compact)?;
cx.export_function("tableListIndices", JsTable::js_list_indices)?;
cx.export_function("tableIndexStats", JsTable::js_index_stats)?;
cx.export_function(
"tableCreateScalarIndex",
index::scalar::table_create_scalar_index,
)?;
cx.export_function(
"tableCreateVectorIndex",
index::vector::table_create_vector_index,

View File

@@ -47,15 +47,15 @@ fn f64_to_u32_safe(n: f64, key: &str) -> Result<u32> {
use conv::*;
n.approx_as::<u32>().map_err(|e| match e {
FloatError::NegOverflow(_) => Error::OutOfRange {
FloatError::NegOverflow(_) => Error::RangeError {
name: key.into(),
message: "must be > 0".to_string(),
},
FloatError::PosOverflow(_) => Error::OutOfRange {
FloatError::PosOverflow(_) => Error::RangeError {
name: key.into(),
message: format!("must be < {}", u32::MAX),
},
FloatError::NotANumber(_) => Error::OutOfRange {
FloatError::NotANumber(_) => Error::RangeError {
name: key.into(),
message: "not a valid number".to_string(),
},
@@ -66,15 +66,15 @@ fn f64_to_usize_safe(n: f64, key: &str) -> Result<usize> {
use conv::*;
n.approx_as::<usize>().map_err(|e| match e {
FloatError::NegOverflow(_) => Error::OutOfRange {
FloatError::NegOverflow(_) => Error::RangeError {
name: key.into(),
message: "must be > 0".to_string(),
},
FloatError::PosOverflow(_) => Error::OutOfRange {
FloatError::PosOverflow(_) => Error::RangeError {
name: key.into(),
message: format!("must be < {}", usize::MAX),
},
FloatError::NotANumber(_) => Error::OutOfRange {
FloatError::NotANumber(_) => Error::RangeError {
name: key.into(),
message: "not a valid number".to_string(),
},

View File

@@ -23,14 +23,8 @@ impl JsQuery {
let query_obj = cx.argument::<JsObject>(0)?;
let limit = query_obj
.get_opt::<JsNumber, _, _>(&mut cx, "_limit")?
.map(|value| {
let limit = value.value(&mut cx);
if limit <= 0.0 {
panic!("Limit must be a positive integer");
}
limit as u64
});
.get::<JsNumber, _, _>(&mut cx, "_limit")?
.value(&mut cx);
let select = query_obj
.get_opt::<JsArray, _, _>(&mut cx, "_select")?
.map(|arr| {
@@ -54,9 +48,7 @@ impl JsQuery {
.map(|s| s.value(&mut cx))
.map(|s| MetricType::try_from(s.as_str()).unwrap());
let prefilter = query_obj
.get::<JsBoolean, _, _>(&mut cx, "_prefilter")?
.value(&mut cx);
let prefilter = query_obj.get::<JsBoolean, _, _>(&mut cx, "_prefilter")?.value(&mut cx);
let is_electron = cx
.argument::<JsBoolean>(1)
@@ -67,23 +59,20 @@ impl JsQuery {
let (deferred, promise) = cx.promise();
let channel = cx.channel();
let query_vector = query_obj.get_opt::<JsArray, _, _>(&mut cx, "_queryVector")?;
let query_vector = query_obj.get::<JsArray, _, _>(&mut cx, "_queryVector")?;
let query = convert::js_array_to_vec(query_vector.deref(), &mut cx);
let table = js_table.table.clone();
let query = query_vector.map(|q| convert::js_array_to_vec(q.deref(), &mut cx));
rt.spawn(async move {
let mut builder = table
.search(query.map(Float32Array::from))
let builder = table
.search(Float32Array::from(query))
.limit(limit as usize)
.refine_factor(refine_factor)
.nprobes(nprobes)
.filter(filter)
.metric_type(metric_type)
.select(select)
.prefilter(prefilter);
if let Some(limit) = limit {
builder = builder.limit(limit as usize);
};
let record_batch_stream = builder.execute();
let results = record_batch_stream
.and_then(|stream| {

View File

@@ -45,7 +45,7 @@ impl JsTable {
let table_name = cx.argument::<JsString>(0)?.value(&mut cx);
let buffer = cx.argument::<JsBuffer>(1)?;
let (batches, schema) =
arrow_buffer_to_record_batch(buffer.as_slice(&cx)).or_throw(&mut cx)?;
arrow_buffer_to_record_batch(buffer.as_slice(&mut cx)).or_throw(&mut cx)?;
// Write mode
let mode = match cx.argument::<JsString>(2)?.value(&mut cx).as_str() {
@@ -93,7 +93,7 @@ impl JsTable {
let buffer = cx.argument::<JsBuffer>(0)?;
let write_mode = cx.argument::<JsString>(1)?.value(&mut cx);
let (batches, schema) =
arrow_buffer_to_record_batch(buffer.as_slice(&cx)).or_throw(&mut cx)?;
arrow_buffer_to_record_batch(buffer.as_slice(&mut cx)).or_throw(&mut cx)?;
let rt = runtime(&mut cx)?;
let channel = cx.channel();
let mut table = js_table.table.clone();
@@ -165,69 +165,6 @@ impl JsTable {
Ok(promise)
}
pub(crate) fn js_update(mut cx: FunctionContext) -> JsResult<JsPromise> {
let js_table = cx.this().downcast_or_throw::<JsBox<JsTable>, _>(&mut cx)?;
let mut table = js_table.table.clone();
let rt = runtime(&mut cx)?;
let (deferred, promise) = cx.promise();
let channel = cx.channel();
// create a vector of updates from the passed map
let updates_arg = cx.argument::<JsObject>(1)?;
let properties = updates_arg.get_own_property_names(&mut cx)?;
let mut updates: Vec<(String, String)> =
Vec::with_capacity(properties.len(&mut cx) as usize);
let len_properties = properties.len(&mut cx);
for i in 0..len_properties {
let property = properties
.get_value(&mut cx, i)?
.downcast_or_throw::<JsString, _>(&mut cx)?;
let value = updates_arg
.get_value(&mut cx, property)?
.downcast_or_throw::<JsString, _>(&mut cx)?;
let property = property.value(&mut cx);
let value = value.value(&mut cx);
updates.push((property, value));
}
// get the filter/predicate if the user passed one
let predicate = cx.argument_opt(0);
let predicate = predicate.unwrap().downcast::<JsString, _>(&mut cx);
let predicate = match predicate {
Ok(_) => {
let val = predicate.map(|s| s.value(&mut cx)).unwrap();
Some(val)
}
Err(_) => {
// if the predicate is not string, check it's null otherwise an invalid
// type was passed
cx.argument::<JsNull>(0)?;
None
}
};
rt.spawn(async move {
let updates_arg = updates
.iter()
.map(|(k, v)| (k.as_str(), v.as_str()))
.collect::<Vec<_>>();
let predicate = predicate.as_deref();
let update_result = table.update(predicate, updates_arg).await;
deferred.settle_with(&channel, move |mut cx| {
update_result.or_throw(&mut cx)?;
Ok(cx.boxed(JsTable::from(table)))
})
});
Ok(promise)
}
pub(crate) fn js_cleanup(mut cx: FunctionContext) -> JsResult<JsPromise> {
let js_table = cx.this().downcast_or_throw::<JsBox<JsTable>, _>(&mut cx)?;
let rt = runtime(&mut cx)?;

View File

@@ -1,6 +1,6 @@
[package]
name = "vectordb"
version = "0.4.1"
version = "0.3.9"
edition = "2021"
description = "LanceDB: A serverless, low-latency vector database for AI applications"
license = "Apache-2.0"

View File

@@ -26,7 +26,7 @@ use futures::{stream::BoxStream, FutureExt, StreamExt};
use lance::io::object_store::WrappingObjectStore;
use object_store::{
path::Path, Error, GetOptions, GetResult, ListResult, MultipartId, ObjectMeta, ObjectStore,
PutOptions, PutResult, Result,
Result,
};
use async_trait::async_trait;
@@ -72,28 +72,13 @@ impl PrimaryOnly for Path {
/// Note: this object store does not mirror writes to *.manifest files
#[async_trait]
impl ObjectStore for MirroringObjectStore {
async fn put(&self, location: &Path, bytes: Bytes) -> Result<PutResult> {
async fn put(&self, location: &Path, bytes: Bytes) -> Result<()> {
if location.primary_only() {
self.primary.put(location, bytes).await
} else {
self.secondary.put(location, bytes.clone()).await?;
self.primary.put(location, bytes).await
}
}
async fn put_opts(
&self,
location: &Path,
bytes: Bytes,
options: PutOptions,
) -> Result<PutResult> {
if location.primary_only() {
self.primary.put_opts(location, bytes, options).await
} else {
self.secondary
.put_opts(location, bytes.clone(), options.clone())
.await?;
self.primary.put_opts(location, bytes, options).await
self.primary.put(location, bytes).await?;
Ok(())
}
}
@@ -144,8 +129,8 @@ impl ObjectStore for MirroringObjectStore {
self.primary.delete(location).await
}
fn list(&self, prefix: Option<&Path>) -> BoxStream<'_, Result<ObjectMeta>> {
self.primary.list(prefix)
async fn list(&self, prefix: Option<&Path>) -> Result<BoxStream<'_, Result<ObjectMeta>>> {
self.primary.list(prefix).await
}
async fn list_with_delimiter(&self, prefix: Option<&Path>) -> Result<ListResult> {
@@ -374,9 +359,7 @@ mod test {
assert_eq!(t.count_rows().await.unwrap(), 100);
let q = t
.search(Some(PrimitiveArray::from_iter_values(vec![
0.1, 0.1, 0.1, 0.1,
])))
.search(PrimitiveArray::from_iter_values(vec![0.1, 0.1, 0.1, 0.1]))
.limit(10)
.execute()
.await

View File

@@ -24,9 +24,8 @@ use crate::error::Result;
/// A builder for nearest neighbor queries for LanceDB.
pub struct Query {
pub dataset: Arc<Dataset>,
pub query_vector: Option<Float32Array>,
pub column: String,
pub limit: Option<usize>,
pub query_vector: Float32Array,
pub limit: usize,
pub filter: Option<String>,
pub select: Option<Vec<String>>,
pub nprobes: usize,
@@ -47,12 +46,11 @@ impl Query {
/// # Returns
///
/// * A [Query] object.
pub(crate) fn new(dataset: Arc<Dataset>, vector: Option<Float32Array>) -> Self {
pub(crate) fn new(dataset: Arc<Dataset>, vector: Float32Array) -> Self {
Query {
dataset,
query_vector: vector,
column: crate::table::VECTOR_COLUMN_NAME.to_string(),
limit: None,
limit: 10,
nprobes: 20,
refine_factor: None,
metric_type: None,
@@ -71,13 +69,11 @@ impl Query {
pub async fn execute(&self) -> Result<DatasetRecordBatchStream> {
let mut scanner: Scanner = self.dataset.scan();
if let Some(query) = self.query_vector.as_ref() {
// If there is a vector query, default to limit=10 if unspecified
scanner.nearest(&self.column, query, self.limit.unwrap_or(10))?;
} else {
// If there is no vector query, it's ok to not have a limit
scanner.limit(self.limit.map(|limit| limit as i64), None)?;
}
scanner.nearest(
crate::table::VECTOR_COLUMN_NAME,
&self.query_vector,
self.limit,
)?;
scanner.nprobs(self.nprobes);
scanner.use_index(self.use_index);
scanner.prefilter(self.prefilter);
@@ -89,23 +85,13 @@ impl Query {
Ok(scanner.try_into_stream().await?)
}
/// Set the column to query
///
/// # Arguments
///
/// * `column` - The column name
pub fn column(mut self, column: &str) -> Query {
self.column = column.into();
self
}
/// Set the maximum number of results to return.
///
/// # Arguments
///
/// * `limit` - The maximum number of results to return.
pub fn limit(mut self, limit: usize) -> Query {
self.limit = Some(limit);
self.limit = limit;
self
}
@@ -115,7 +101,7 @@ impl Query {
///
/// * `vector` - The vector that will be used for search.
pub fn query_vector(mut self, query_vector: Float32Array) -> Query {
self.query_vector = Some(query_vector);
self.query_vector = query_vector;
self
}
@@ -188,10 +174,7 @@ mod tests {
use std::sync::Arc;
use super::*;
use arrow_array::{
cast::AsArray, Float32Array, Int32Array, RecordBatch, RecordBatchIterator,
RecordBatchReader,
};
use arrow_array::{Float32Array, RecordBatch, RecordBatchIterator, RecordBatchReader};
use arrow_schema::{DataType, Field as ArrowField, Schema as ArrowSchema};
use futures::StreamExt;
use lance::dataset::Dataset;
@@ -204,7 +187,7 @@ mod tests {
let batches = make_test_batches();
let ds = Dataset::write(batches, "memory://foo", None).await.unwrap();
let vector = Some(Float32Array::from_iter_values([0.1, 0.2]));
let vector = Float32Array::from_iter_values([0.1, 0.2]);
let query = Query::new(Arc::new(ds), vector.clone());
assert_eq!(query.query_vector, vector);
@@ -218,8 +201,8 @@ mod tests {
.metric_type(Some(MetricType::Cosine))
.refine_factor(Some(999));
assert_eq!(query.query_vector.unwrap(), new_vector);
assert_eq!(query.limit.unwrap(), 100);
assert_eq!(query.query_vector, new_vector);
assert_eq!(query.limit, 100);
assert_eq!(query.nprobes, 1000);
assert_eq!(query.use_index, true);
assert_eq!(query.metric_type, Some(MetricType::Cosine));
@@ -231,7 +214,7 @@ mod tests {
let batches = make_non_empty_batches();
let ds = Arc::new(Dataset::write(batches, "memory://foo", None).await.unwrap());
let vector = Some(Float32Array::from_iter_values([0.1; 4]));
let vector = Float32Array::from_iter_values([0.1; 4]);
let query = Query::new(ds.clone(), vector.clone());
let result = query
@@ -261,27 +244,6 @@ mod tests {
}
}
#[tokio::test]
async fn test_execute_no_vector() {
// test that it's ok to not specify a query vector (just filter / limit)
let batches = make_non_empty_batches();
let ds = Arc::new(Dataset::write(batches, "memory://foo", None).await.unwrap());
let query = Query::new(ds.clone(), None);
let result = query
.filter(Some("id % 2 == 0".to_string()))
.execute()
.await;
let mut stream = result.expect("should have result");
// should only have one batch
while let Some(batch) = stream.next().await {
let b = batch.expect("should be Ok");
// cast arr into Int32Array
let arr: &Int32Array = b["id"].as_primitive();
assert!(arr.iter().all(|x| x.unwrap() % 2 == 0));
}
}
fn make_non_empty_batches() -> impl RecordBatchReader + Send + 'static {
let vec = Box::new(RandomVector::new().named("vector".to_string()));
let id = Box::new(IncrementingInt32::new().named("id".to_string()));

View File

@@ -14,7 +14,6 @@
use chrono::Duration;
use lance::dataset::builder::DatasetBuilder;
use lance::index::scalar::ScalarIndexParams;
use lance_index::IndexType;
use std::sync::Arc;
@@ -24,7 +23,7 @@ use lance::dataset::cleanup::RemovalStats;
use lance::dataset::optimize::{
compact_files, CompactionMetrics, CompactionOptions, IndexRemapperOptions,
};
use lance::dataset::{Dataset, UpdateBuilder, WriteParams};
use lance::dataset::{Dataset, WriteParams};
use lance::index::DatasetIndexExt;
use lance::io::object_store::WrappingObjectStore;
use std::path::Path;
@@ -263,16 +262,6 @@ impl Table {
Ok(())
}
/// Create a scalar index on the table
pub async fn create_scalar_index(&mut self, column: &str, replace: bool) -> Result<()> {
let mut dataset = self.dataset.as_ref().clone();
let params = ScalarIndexParams::default();
dataset
.create_index(&[column], IndexType::Scalar, None, &params, replace)
.await?;
Ok(())
}
pub async fn optimize_indices(&mut self) -> Result<()> {
let mut dataset = self.dataset.as_ref().clone();
@@ -319,14 +308,10 @@ impl Table {
/// # Returns
///
/// * A [Query] object.
pub fn search(&self, query_vector: Option<Float32Array>) -> Query {
pub fn search(&self, query_vector: Float32Array) -> Query {
Query::new(self.dataset.clone(), query_vector)
}
pub fn filter(&self, expr: String) -> Query {
Query::new(self.dataset.clone(), None).filter(Some(expr))
}
/// Returns the number of rows in this Table
pub async fn count_rows(&self) -> Result<usize> {
Ok(self.dataset.count_rows().await?)
@@ -353,27 +338,6 @@ impl Table {
Ok(())
}
pub async fn update(
&mut self,
predicate: Option<&str>,
updates: Vec<(&str, &str)>,
) -> Result<()> {
let mut builder = UpdateBuilder::new(self.dataset.clone());
if let Some(predicate) = predicate {
builder = builder.update_where(predicate)?;
}
for (column, value) in updates {
builder = builder.set(column, value)?;
}
let operation = builder.build()?;
let new_ds = operation.execute().await?;
self.dataset = new_ds;
Ok(())
}
/// Remove old versions of the dataset from disk.
///
/// # Arguments
@@ -449,14 +413,11 @@ mod tests {
use std::sync::Arc;
use arrow_array::{
Array, BooleanArray, Date32Array, FixedSizeListArray, Float32Array, Float64Array,
Int32Array, Int64Array, LargeStringArray, RecordBatch, RecordBatchIterator,
RecordBatchReader, StringArray, TimestampMillisecondArray, TimestampNanosecondArray,
UInt32Array,
Array, FixedSizeListArray, Float32Array, Int32Array, RecordBatch, RecordBatchIterator,
RecordBatchReader,
};
use arrow_data::ArrayDataBuilder;
use arrow_schema::{DataType, Field, Schema, TimeUnit};
use futures::TryStreamExt;
use arrow_schema::{DataType, Field, Schema};
use lance::dataset::{Dataset, WriteMode};
use lance::index::vector::pq::PQBuildParams;
use lance::io::object_store::{ObjectStoreParams, WrappingObjectStore};
@@ -579,272 +540,6 @@ mod tests {
assert_eq!(table.name, "test");
}
#[tokio::test]
async fn test_update_with_predicate() {
let tmp_dir = tempdir().unwrap();
let dataset_path = tmp_dir.path().join("test.lance");
let uri = dataset_path.to_str().unwrap();
let schema = Arc::new(Schema::new(vec![
Field::new("id", DataType::Int32, false),
Field::new("name", DataType::Utf8, false),
]));
let record_batch_iter = RecordBatchIterator::new(
vec![RecordBatch::try_new(
schema.clone(),
vec![
Arc::new(Int32Array::from_iter_values(0..10)),
Arc::new(StringArray::from_iter_values(vec![
"a", "b", "c", "d", "e", "f", "g", "h", "i", "j",
])),
],
)
.unwrap()]
.into_iter()
.map(Ok),
schema.clone(),
);
Dataset::write(record_batch_iter, uri, None).await.unwrap();
let mut table = Table::open(uri).await.unwrap();
table
.update(Some("id > 5"), vec![("name", "'foo'")])
.await
.unwrap();
let ds_after = Dataset::open(uri).await.unwrap();
let mut batches = ds_after
.scan()
.project(&["id", "name"])
.unwrap()
.try_into_stream()
.await
.unwrap()
.try_collect::<Vec<_>>()
.await
.unwrap();
while let Some(batch) = batches.pop() {
let ids = batch
.column(0)
.as_any()
.downcast_ref::<Int32Array>()
.unwrap()
.iter()
.collect::<Vec<_>>();
let names = batch
.column(1)
.as_any()
.downcast_ref::<StringArray>()
.unwrap()
.iter()
.collect::<Vec<_>>();
for (i, name) in names.iter().enumerate() {
let id = ids[i].unwrap();
let name = name.unwrap();
if id > 5 {
assert_eq!(name, "foo");
} else {
assert_eq!(name, &format!("{}", (b'a' + id as u8) as char));
}
}
}
}
#[tokio::test]
async fn test_update_all_types() {
let tmp_dir = tempdir().unwrap();
let dataset_path = tmp_dir.path().join("test.lance");
let uri = dataset_path.to_str().unwrap();
let schema = Arc::new(Schema::new(vec![
Field::new("int32", DataType::Int32, false),
Field::new("int64", DataType::Int64, false),
Field::new("uint32", DataType::UInt32, false),
Field::new("string", DataType::Utf8, false),
Field::new("large_string", DataType::LargeUtf8, false),
Field::new("float32", DataType::Float32, false),
Field::new("float64", DataType::Float64, false),
Field::new("bool", DataType::Boolean, false),
Field::new("date32", DataType::Date32, false),
Field::new(
"timestamp_ns",
DataType::Timestamp(TimeUnit::Nanosecond, None),
false,
),
Field::new(
"timestamp_ms",
DataType::Timestamp(TimeUnit::Millisecond, None),
false,
),
Field::new(
"vec_f32",
DataType::FixedSizeList(Arc::new(Field::new("item", DataType::Float32, true)), 2),
false,
),
Field::new(
"vec_f64",
DataType::FixedSizeList(Arc::new(Field::new("item", DataType::Float64, true)), 2),
false,
),
]));
let record_batch_iter = RecordBatchIterator::new(
vec![RecordBatch::try_new(
schema.clone(),
vec![
Arc::new(Int32Array::from_iter_values(0..10)),
Arc::new(Int64Array::from_iter_values(0..10)),
Arc::new(UInt32Array::from_iter_values(0..10)),
Arc::new(StringArray::from_iter_values(vec![
"a", "b", "c", "d", "e", "f", "g", "h", "i", "j",
])),
Arc::new(LargeStringArray::from_iter_values(vec![
"a", "b", "c", "d", "e", "f", "g", "h", "i", "j",
])),
Arc::new(Float32Array::from_iter_values(
(0..10).into_iter().map(|i| i as f32),
)),
Arc::new(Float64Array::from_iter_values(
(0..10).into_iter().map(|i| i as f64),
)),
Arc::new(Into::<BooleanArray>::into(vec![
true, false, true, false, true, false, true, false, true, false,
])),
Arc::new(Date32Array::from_iter_values(0..10)),
Arc::new(TimestampNanosecondArray::from_iter_values(0..10)),
Arc::new(TimestampMillisecondArray::from_iter_values(0..10)),
Arc::new(
create_fixed_size_list(
Float32Array::from_iter_values((0..20).into_iter().map(|i| i as f32)),
2,
)
.unwrap(),
),
Arc::new(
create_fixed_size_list(
Float64Array::from_iter_values((0..20).into_iter().map(|i| i as f64)),
2,
)
.unwrap(),
),
],
)
.unwrap()]
.into_iter()
.map(Ok),
schema.clone(),
);
Dataset::write(record_batch_iter, uri, None).await.unwrap();
let mut table = Table::open(uri).await.unwrap();
// check it can do update for each type
let updates: Vec<(&str, &str)> = vec![
("string", "'foo'"),
("large_string", "'large_foo'"),
("int32", "1"),
("int64", "1"),
("uint32", "1"),
("float32", "1.0"),
("float64", "1.0"),
("bool", "true"),
("date32", "1"),
("timestamp_ns", "1"),
("timestamp_ms", "1"),
("vec_f32", "[1.0, 1.0]"),
("vec_f64", "[1.0, 1.0]"),
];
// for (column, value) in test_cases {
table.update(None, updates).await.unwrap();
let ds_after = Dataset::open(uri).await.unwrap();
let mut batches = ds_after
.scan()
.project(&[
"string",
"large_string",
"int32",
"int64",
"uint32",
"float32",
"float64",
"bool",
"date32",
"timestamp_ns",
"timestamp_ms",
"vec_f32",
"vec_f64",
])
.unwrap()
.try_into_stream()
.await
.unwrap()
.try_collect::<Vec<_>>()
.await
.unwrap();
let batch = batches.pop().unwrap();
macro_rules! assert_column {
($column:expr, $array_type:ty, $expected:expr) => {
let array = $column
.as_any()
.downcast_ref::<$array_type>()
.unwrap()
.iter()
.collect::<Vec<_>>();
for v in array {
assert_eq!(v, Some($expected));
}
};
}
assert_column!(batch.column(0), StringArray, "foo");
assert_column!(batch.column(1), LargeStringArray, "large_foo");
assert_column!(batch.column(2), Int32Array, 1);
assert_column!(batch.column(3), Int64Array, 1);
assert_column!(batch.column(4), UInt32Array, 1);
assert_column!(batch.column(5), Float32Array, 1.0);
assert_column!(batch.column(6), Float64Array, 1.0);
assert_column!(batch.column(7), BooleanArray, true);
assert_column!(batch.column(8), Date32Array, 1);
assert_column!(batch.column(9), TimestampNanosecondArray, 1);
assert_column!(batch.column(10), TimestampMillisecondArray, 1);
let array = batch
.column(11)
.as_any()
.downcast_ref::<FixedSizeListArray>()
.unwrap()
.iter()
.collect::<Vec<_>>();
for v in array {
let v = v.unwrap();
let f32array = v.as_any().downcast_ref::<Float32Array>().unwrap();
for v in f32array {
assert_eq!(v, Some(1.0));
}
}
let array = batch
.column(12)
.as_any()
.downcast_ref::<FixedSizeListArray>()
.unwrap()
.iter()
.collect::<Vec<_>>();
for v in array {
let v = v.unwrap();
let f64array = v.as_any().downcast_ref::<Float64Array>().unwrap();
for v in f64array {
assert_eq!(v, Some(1.0));
}
}
}
#[tokio::test]
async fn test_search() {
let tmp_dir = tempdir().unwrap();
@@ -859,8 +554,8 @@ mod tests {
let table = Table::open(uri).await.unwrap();
let vector = Float32Array::from_iter_values([0.1, 0.2]);
let query = table.search(Some(vector.clone()));
assert_eq!(vector, query.query_vector.unwrap());
let query = table.search(vector.clone());
assert_eq!(vector, query.query_vector);
}
#[derive(Default, Debug)]