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https://github.com/lancedb/lancedb.git
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feat(node): Create empty tables / Arrow Tables (#399)
- Supports creating an empty table as long as an Arrow Schema is provided - Supports creating a table from an Arrow Table (can be passed as data) - Simplified some Arrow code in the TS/FFI side - removed createTableArrow method, it was never documented / tested.
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@@ -13,18 +13,19 @@
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// limitations under the License.
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import {
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Field,
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Field, type FixedSizeListBuilder,
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Float32,
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List, type ListBuilder,
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makeBuilder,
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RecordBatchFileWriter,
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Table, Utf8,
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Utf8,
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type Vector,
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vectorFromArray
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FixedSizeList,
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vectorFromArray, type Schema, Table as ArrowTable
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} from 'apache-arrow'
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import { type EmbeddingFunction } from './index'
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export async function convertToTable<T> (data: Array<Record<string, unknown>>, embeddings?: EmbeddingFunction<T>): Promise<Table> {
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// Converts an Array of records into an Arrow Table, optionally applying an embeddings function to it.
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export async function convertToTable<T> (data: Array<Record<string, unknown>>, embeddings?: EmbeddingFunction<T>): Promise<ArrowTable> {
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if (data.length === 0) {
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throw new Error('At least one record needs to be provided')
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}
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@@ -34,8 +35,8 @@ export async function convertToTable<T> (data: Array<Record<string, unknown>>, e
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for (const columnsKey of columns) {
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if (columnsKey === 'vector') {
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const listBuilder = newVectorListBuilder()
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const vectorSize = (data[0].vector as any[]).length
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const listBuilder = newVectorBuilder(vectorSize)
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for (const datum of data) {
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if ((datum[columnsKey] as any[]).length !== vectorSize) {
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throw new Error(`Invalid vector size, expected ${vectorSize}`)
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@@ -52,9 +53,7 @@ export async function convertToTable<T> (data: Array<Record<string, unknown>>, e
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if (columnsKey === embeddings?.sourceColumn) {
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const vectors = await embeddings.embed(values as T[])
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const listBuilder = newVectorListBuilder()
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vectors.map(v => listBuilder.append(v))
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records.vector = listBuilder.finish().toVector()
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records.vector = vectorFromArray(vectors, newVectorType(vectors[0].length))
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}
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if (typeof values[0] === 'string') {
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@@ -66,20 +65,47 @@ export async function convertToTable<T> (data: Array<Record<string, unknown>>, e
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}
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}
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return new Table(records)
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return new ArrowTable(records)
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}
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// Creates a new Arrow ListBuilder that stores a Vector column
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function newVectorListBuilder (): ListBuilder<Float32, any> {
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const children = new Field<Float32>('item', new Float32())
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const list = new List(children)
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function newVectorBuilder (dim: number): FixedSizeListBuilder<Float32> {
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return makeBuilder({
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type: list
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type: newVectorType(dim)
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})
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}
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// Creates the Arrow Type for a Vector column with dimension `dim`
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function newVectorType (dim: number): FixedSizeList<Float32> {
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const children = new Field<Float32>('item', new Float32())
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return new FixedSizeList(dim, children)
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}
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// Converts an Array of records into Arrow IPC format
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export async function fromRecordsToBuffer<T> (data: Array<Record<string, unknown>>, embeddings?: EmbeddingFunction<T>): Promise<Buffer> {
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const table = await convertToTable(data, embeddings)
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const writer = RecordBatchFileWriter.writeAll(table)
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return Buffer.from(await writer.toUint8Array())
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}
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// Converts an Arrow Table into Arrow IPC format
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export async function fromTableToBuffer<T> (table: ArrowTable, embeddings?: EmbeddingFunction<T>): Promise<Buffer> {
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if (embeddings !== undefined) {
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const source = table.getChild(embeddings.sourceColumn)
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if (source === null) {
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throw new Error(`The embedding source column ${embeddings.sourceColumn} was not found in the Arrow Table`)
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}
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const vectors = await embeddings.embed(source.toArray() as T[])
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const column = vectorFromArray(vectors, newVectorType(vectors[0].length))
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table = table.assign(new ArrowTable({ vector: column }))
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}
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const writer = RecordBatchFileWriter.writeAll(table)
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return Buffer.from(await writer.toUint8Array())
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}
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// Creates an empty Arrow Table
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export function createEmptyTable (schema: Schema): ArrowTable {
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return new ArrowTable(schema)
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}
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