mirror of
https://github.com/lancedb/lancedb.git
synced 2026-09-11 15:52:17 +00:00
Merge origin/main into gatekeeper/fix-1289-1
# Conflicts: # nodejs/lancedb/arrow.ts # nodejs/lancedb/embedding/registry.ts
This commit is contained in:
+5
-5
@@ -1,7 +1,7 @@
|
||||
[package]
|
||||
name = "lancedb-nodejs"
|
||||
edition.workspace = true
|
||||
version = "0.37.1-beta.0"
|
||||
version = "0.38.0-beta.3"
|
||||
publish = false
|
||||
license.workspace = true
|
||||
description.workspace = true
|
||||
@@ -16,12 +16,12 @@ crate-type = ["cdylib"]
|
||||
async-trait.workspace = true
|
||||
arrow-ipc.workspace = true
|
||||
arrow-array.workspace = true
|
||||
arrow-buffer = "58.0.0"
|
||||
arrow-buffer.workspace = true
|
||||
half.workspace = true
|
||||
arrow-schema.workspace = true
|
||||
env_logger.workspace = true
|
||||
futures.workspace = true
|
||||
lancedb = { path = "../rust/lancedb", default-features = false }
|
||||
lancedb.workspace = true
|
||||
lance-namespace.workspace = true
|
||||
napi = { version = "3.8.3", default-features = false, features = [
|
||||
"napi9",
|
||||
@@ -29,8 +29,8 @@ napi = { version = "3.8.3", default-features = false, features = [
|
||||
"chrono_date",
|
||||
"serde-json",
|
||||
] }
|
||||
chrono = { version = "0.4", default-features = false, features = ["clock"] }
|
||||
serde_json = "1"
|
||||
chrono.workspace = true
|
||||
serde_json.workspace = true
|
||||
napi-derive = "3.5.2"
|
||||
# Prevent dynamic linking of lzma, which comes from datafusion
|
||||
lzma-sys = { version = "0.1", features = ["static"] }
|
||||
|
||||
@@ -6,7 +6,9 @@ import * as arrow17 from "apache-arrow-17";
|
||||
import * as arrow18 from "apache-arrow-18";
|
||||
|
||||
import {
|
||||
Vector as CurrentVector,
|
||||
convertToTable,
|
||||
tableFromIPC as currentTableFromIPC,
|
||||
fromBufferToRecordBatch,
|
||||
fromDataToBuffer,
|
||||
fromRecordBatchToBuffer,
|
||||
@@ -19,6 +21,7 @@ import {
|
||||
FunctionOptions,
|
||||
} from "../lancedb/embedding/embedding_function";
|
||||
import { EmbeddingFunctionConfig } from "../lancedb/embedding/registry";
|
||||
import { sanitizeTable } from "../lancedb/sanitize";
|
||||
|
||||
// biome-ignore lint/suspicious/noExplicitAny: skip
|
||||
function sampleRecords(): Array<Record<string, any>> {
|
||||
@@ -64,7 +67,11 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
|
||||
tableFromIPC,
|
||||
DataType,
|
||||
Dictionary,
|
||||
RecordBatch: ArrowRecordBatch,
|
||||
Table: ArrowTable,
|
||||
Uint8: ArrowUint8,
|
||||
makeData: arrowMakeData,
|
||||
vectorFromArray,
|
||||
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
|
||||
} = <any>arrow;
|
||||
type Schema = ApacheArrow["Schema"];
|
||||
@@ -166,6 +173,36 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
|
||||
}
|
||||
|
||||
describe("The function makeArrowTable", function () {
|
||||
it("accepts snake_case embedding metadata like camelCase", function () {
|
||||
const spellings = [
|
||||
// biome-ignore lint/style/useNamingConvention: the Python wire spelling
|
||||
{ source_column: "text", vector_column: "vector" },
|
||||
{ sourceColumn: "text", vectorColumn: "vector" },
|
||||
];
|
||||
for (const columns of spellings) {
|
||||
const schema = new Schema(
|
||||
[
|
||||
new Field("text", new Utf8(), false),
|
||||
new Field(
|
||||
"vector",
|
||||
new FixedSizeList(3, new Field("item", new Float32(), true)),
|
||||
false,
|
||||
),
|
||||
],
|
||||
new Map([
|
||||
[
|
||||
"embedding_functions",
|
||||
JSON.stringify([{ name: "mock", model: {}, ...columns }]),
|
||||
],
|
||||
]),
|
||||
);
|
||||
// The vector field is non-nullable and absent from the data; only a
|
||||
// recognized embedding config makes that acceptable.
|
||||
const table = makeArrowTable([{ text: "hello" }], { schema });
|
||||
expect(table.numRows).toBe(1);
|
||||
}
|
||||
});
|
||||
|
||||
it("will use data types from a provided schema instead of inference", async function () {
|
||||
const schema = new Schema([
|
||||
new Field("a", new Int32(), false),
|
||||
@@ -1054,6 +1091,114 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
|
||||
});
|
||||
|
||||
describe("when using two versions of arrow", function () {
|
||||
it("preserves a dictionary shared by multiple fields", async function () {
|
||||
const values = ["alpha", "beta", "alpha"];
|
||||
const dictionaryVector = vectorFromArray(values);
|
||||
const batch = new ArrowRecordBatch({
|
||||
first: dictionaryVector.data[0],
|
||||
second: dictionaryVector.data[0],
|
||||
});
|
||||
const table = new ArrowTable([batch]);
|
||||
|
||||
const sanitized = sanitizeTable(table);
|
||||
expect([...sanitized.getChild("first")!]).toEqual(values);
|
||||
expect([...sanitized.getChild("second")!]).toEqual(values);
|
||||
const firstType = sanitized.schema.fields[0].type as {
|
||||
dictionary: unknown;
|
||||
};
|
||||
const secondType = sanitized.schema.fields[1].type as {
|
||||
dictionary: unknown;
|
||||
};
|
||||
expect(secondType.dictionary).toBe(firstType.dictionary);
|
||||
expect(sanitized.batches[0].data.children[1].dictionary).toBe(
|
||||
sanitized.batches[0].data.children[0].dictionary,
|
||||
);
|
||||
|
||||
const buf = await fromDataToBuffer(table);
|
||||
const actual = currentTableFromIPC(buf);
|
||||
expect([...actual.getChild("first")!]).toEqual(values);
|
||||
expect([...actual.getChild("second")!]).toEqual(values);
|
||||
});
|
||||
|
||||
it("preserves shared dictionary data from another Arrow version", async function () {
|
||||
const values = ["alpha", "beta", "alpha"];
|
||||
const dictionaryVector = vectorFromArray(values);
|
||||
const firstBatch = new ArrowRecordBatch({
|
||||
label: dictionaryVector.slice(0, 2).data[0],
|
||||
});
|
||||
const secondBatch = new ArrowRecordBatch({
|
||||
label: dictionaryVector.slice(2).data[0],
|
||||
});
|
||||
const table = new ArrowTable([firstBatch, secondBatch]);
|
||||
|
||||
const sanitized = sanitizeTable(table);
|
||||
expect([...sanitized.getChild("label")!]).toEqual(values);
|
||||
|
||||
const dictionaries = sanitized.batches.map(
|
||||
(batch) => batch.data.children[0].dictionary,
|
||||
);
|
||||
expect(dictionaries[0]).toBeInstanceOf(CurrentVector);
|
||||
expect(dictionaries[1]).toBe(dictionaries[0]);
|
||||
|
||||
const buf = await fromDataToBuffer(table);
|
||||
const actual = currentTableFromIPC(buf);
|
||||
expect([...actual.getChild("label")!]).toEqual(values);
|
||||
});
|
||||
|
||||
it("preserves shared chunks in growing dictionaries", async function () {
|
||||
const type = new Dictionary(new Utf8(), new Int32(), 42, false);
|
||||
const firstDictionary = vectorFromArray(["alpha", "beta"], new Utf8());
|
||||
const secondDictionary = firstDictionary.concat(
|
||||
vectorFromArray(["gamma"], new Utf8()),
|
||||
);
|
||||
const firstData = arrowMakeData({
|
||||
type,
|
||||
data: Int32Array.from([0, 1]),
|
||||
dictionary: firstDictionary,
|
||||
});
|
||||
const secondData = arrowMakeData({
|
||||
type,
|
||||
data: Int32Array.from([2]),
|
||||
dictionary: secondDictionary,
|
||||
});
|
||||
const table = new ArrowTable([
|
||||
new ArrowRecordBatch({ label: firstData }),
|
||||
new ArrowRecordBatch({ label: secondData }),
|
||||
]);
|
||||
|
||||
const sanitized = sanitizeTable(table);
|
||||
const expected = ["alpha", "beta", "gamma"];
|
||||
expect([...sanitized.getChild("label")!]).toEqual(expected);
|
||||
const firstLocalDictionary =
|
||||
sanitized.batches[0].data.children[0].dictionary!;
|
||||
const secondLocalDictionary =
|
||||
sanitized.batches[1].data.children[0].dictionary!;
|
||||
expect(secondLocalDictionary.data[0]).toBe(
|
||||
firstLocalDictionary.data[0],
|
||||
);
|
||||
|
||||
const buf = await fromTableToBuffer(sanitized);
|
||||
const actual = currentTableFromIPC(buf);
|
||||
expect([...actual.getChild("label")!]).toEqual(expected);
|
||||
});
|
||||
|
||||
it("can serialize list data from another Arrow version", async function () {
|
||||
const values = [["anime", "action"], [], null];
|
||||
const vector = vectorFromArray(
|
||||
values,
|
||||
new List(new Field("item", new Utf8(), true)),
|
||||
);
|
||||
const table = new ArrowTable({ tags: vector });
|
||||
|
||||
const buf = await fromDataToBuffer(table);
|
||||
const actual = currentTableFromIPC(buf);
|
||||
const actualTags = actual.getChild("tags");
|
||||
|
||||
expect(actualTags?.get(0)?.toJSON()).toEqual(values[0]);
|
||||
expect(actualTags?.get(1)?.toJSON()).toEqual(values[1]);
|
||||
expect(actualTags?.get(2)).toBeNull();
|
||||
});
|
||||
|
||||
it("can still import data", async function () {
|
||||
const schema = new arrow15.Schema([
|
||||
new arrow15.Field("id", new arrow15.Int32()),
|
||||
|
||||
@@ -89,6 +89,16 @@ describe("given a connection", () => {
|
||||
await db.createTable("test4", [{ id: 1 }, { id: 2 }]);
|
||||
});
|
||||
|
||||
it("should return a completed job when dropping a local table", async () => {
|
||||
await db.createTable("async-drop", [{ id: 1 }]);
|
||||
|
||||
const job = await db.dropTableAsync("async-drop");
|
||||
expect(job.id).toBeNull();
|
||||
await expect(job.status()).resolves.toBe("finished");
|
||||
await job.wait();
|
||||
await expect(db.tableNames()).resolves.toEqual([]);
|
||||
});
|
||||
|
||||
it("should fail if creating table twice, unless overwrite is true", async () => {
|
||||
let tbl = await db.createTable("test", [{ id: 1 }, { id: 2 }]);
|
||||
await expect(tbl.countRows()).resolves.toBe(2);
|
||||
|
||||
@@ -106,6 +106,77 @@ describe.each([arrow15, arrow16, arrow17, arrow18])("Registry", (arrow) => {
|
||||
'Embedding function with alias "mock-embedding" already exists',
|
||||
);
|
||||
});
|
||||
test("parseFunctions keeps entries sharing a function name", async () => {
|
||||
class MockEmbeddingFunction extends EmbeddingFunction<string> {
|
||||
ndims() {
|
||||
return 3;
|
||||
}
|
||||
embeddingDataType() {
|
||||
return new arrow.Float32() as apiArrow.Float;
|
||||
}
|
||||
async computeSourceEmbeddings(data: string[]) {
|
||||
return data.map(() => [1, 2, 3]);
|
||||
}
|
||||
}
|
||||
register("mock-embedding")(MockEmbeddingFunction);
|
||||
const parsed = await getRegistry().parseFunctions(
|
||||
new Map([
|
||||
[
|
||||
"embedding_functions",
|
||||
JSON.stringify([
|
||||
{
|
||||
name: "mock-embedding",
|
||||
sourceColumn: "text",
|
||||
vectorColumn: "vector_a",
|
||||
model: {},
|
||||
},
|
||||
{
|
||||
name: "mock-embedding",
|
||||
sourceColumn: "text",
|
||||
vectorColumn: "vector_b",
|
||||
model: {},
|
||||
},
|
||||
]),
|
||||
],
|
||||
]),
|
||||
);
|
||||
expect([...parsed.values()].map((f) => f.vectorColumn)).toEqual([
|
||||
"vector_a",
|
||||
"vector_b",
|
||||
]);
|
||||
|
||||
// The Python bindings write snake_case keys.
|
||||
const snake = await getRegistry().parseFunctions(
|
||||
new Map([
|
||||
[
|
||||
"embedding_functions",
|
||||
JSON.stringify([
|
||||
{
|
||||
name: "mock-embedding",
|
||||
// biome-ignore lint/style/useNamingConvention: the Python wire spelling
|
||||
source_column: "text",
|
||||
// biome-ignore lint/style/useNamingConvention: the Python wire spelling
|
||||
vector_column: "vector_a",
|
||||
model: {},
|
||||
},
|
||||
{
|
||||
name: "mock-embedding",
|
||||
// biome-ignore lint/style/useNamingConvention: the Python wire spelling
|
||||
source_column: "text",
|
||||
// biome-ignore lint/style/useNamingConvention: the Python wire spelling
|
||||
vector_column: "vector_b",
|
||||
model: {},
|
||||
},
|
||||
]),
|
||||
],
|
||||
]),
|
||||
);
|
||||
expect([...snake.keys()]).toEqual(["vector_a", "vector_b"]);
|
||||
expect([...snake.values()].map((f) => f.sourceColumn)).toEqual([
|
||||
"text",
|
||||
"text",
|
||||
]);
|
||||
});
|
||||
test("schema should contain correct metadata", async () => {
|
||||
class MockEmbeddingFunction extends EmbeddingFunction<string> {
|
||||
constructor(args: FunctionOptions = {}) {
|
||||
|
||||
@@ -277,8 +277,16 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
|
||||
},
|
||||
numIndices: 0,
|
||||
numRows: 3,
|
||||
totalBytes: 44,
|
||||
// Full on-disk size of the two data files, footers and metadata included.
|
||||
totalBytes: 684,
|
||||
});
|
||||
|
||||
// Index files count toward totalBytes too (only deletion files and
|
||||
// manifests are excluded).
|
||||
await table.createIndex("id", { config: Index.btree() });
|
||||
const statsWithIndex = await table.stats();
|
||||
expect(statsWithIndex.numIndices).toBe(1);
|
||||
expect(statsWithIndex.totalBytes).toBeGreaterThan(684);
|
||||
});
|
||||
|
||||
it("should overwrite data if asked", async () => {
|
||||
@@ -3332,3 +3340,120 @@ describe("LSM merge insert", () => {
|
||||
await expect(table.query().useLsm(true).toArray()).rejects.toThrow();
|
||||
});
|
||||
});
|
||||
|
||||
describe("LSM convergence and stats", () => {
|
||||
let tmpDir: tmp.DirResult;
|
||||
|
||||
beforeEach(() => {
|
||||
tmpDir = tmp.dirSync({ unsafeCleanup: true });
|
||||
});
|
||||
afterEach(() => tmpDir.removeCallback());
|
||||
|
||||
async function lsmTable(conn: Connection): Promise<Table> {
|
||||
const table = await conn.createEmptyTable(
|
||||
"t",
|
||||
new arrow.Schema([new arrow.Field("id", new arrow.Utf8(), false)]),
|
||||
);
|
||||
await table.setUnenforcedPrimaryKey("id");
|
||||
await table.setLsmWriteSpec({ specType: "unsharded" });
|
||||
return table;
|
||||
}
|
||||
|
||||
// These four route through the server that owns the MemWAL, so a local table
|
||||
// rejects them rather than answering. What is asserted here is that the
|
||||
// bindings reach the core at all; the behavior against a real endpoint is
|
||||
// covered by the mocked endpoint tests in rust/lancedb/src/remote/table.rs.
|
||||
it("rejects flushLsm on a local table", async () => {
|
||||
const conn = await connect(tmpDir.name);
|
||||
const table = await lsmTable(conn);
|
||||
|
||||
await expect(table.flushLsm()).rejects.toThrow(/not supported/i);
|
||||
});
|
||||
|
||||
it("rejects compactLsm on a local table", async () => {
|
||||
const conn = await connect(tmpDir.name);
|
||||
const table = await lsmTable(conn);
|
||||
|
||||
await expect(table.compactLsm()).rejects.toThrow(/not supported/i);
|
||||
});
|
||||
|
||||
it("rejects getLsmStats on a local table", async () => {
|
||||
const conn = await connect(tmpDir.name);
|
||||
const table = await lsmTable(conn);
|
||||
|
||||
await expect(table.getLsmStats()).rejects.toThrow(/not supported/i);
|
||||
await expect(table.getLsmStats(true)).rejects.toThrow(/not supported/i);
|
||||
});
|
||||
|
||||
it("rejects checkpointLsm on a local table", async () => {
|
||||
const conn = await connect(tmpDir.name);
|
||||
const table = await lsmTable(conn);
|
||||
|
||||
// checkpointLsm seals first, so it surfaces flushLsm's rejection.
|
||||
await expect(table.checkpointLsm()).rejects.toThrow(/not supported/i);
|
||||
});
|
||||
});
|
||||
|
||||
describe("computed columns", () => {
|
||||
let tmpDir: tmp.DirResult;
|
||||
beforeEach(() => {
|
||||
tmpDir = tmp.dirSync({ unsafeCleanup: true });
|
||||
});
|
||||
afterEach(() => tmpDir.removeCallback());
|
||||
|
||||
it("declares a column and fills it on refresh", async () => {
|
||||
const db = await connect(tmpDir.name);
|
||||
const table = await db.createTable("computed", [{ x: 1 }, { x: 2 }]);
|
||||
|
||||
await table.addColumns({
|
||||
computed: [{ name: "doubled", valueSql: "x * 2" }],
|
||||
});
|
||||
let rows = await table.query().toArray();
|
||||
expect(rows.map((r) => r.doubled)).toEqual([null, null]);
|
||||
|
||||
const result = await table.refreshColumn("doubled");
|
||||
expect(result.rowsFilled).toBe(2);
|
||||
|
||||
rows = await table.query().toArray();
|
||||
expect(rows.map((r) => r.doubled).sort()).toEqual([2, 4]);
|
||||
});
|
||||
|
||||
it("returns a job handle from refreshColumnAsync", async () => {
|
||||
const db = await connect(tmpDir.name);
|
||||
const table = await db.createTable("computed_job", [{ x: 1 }, { x: 2 }]);
|
||||
|
||||
await table.addColumns({
|
||||
computed: [{ name: "doubled", valueSql: "x * 2" }],
|
||||
});
|
||||
|
||||
const job = await table.refreshColumnAsync("doubled");
|
||||
expect(job.id).toBeNull();
|
||||
await job.wait();
|
||||
expect(await job.status()).toBe("finished");
|
||||
|
||||
const rows = await table.query().toArray();
|
||||
expect(rows.map((r) => r.doubled).sort()).toEqual([2, 4]);
|
||||
|
||||
// Bad input rejects at the call, not through the job.
|
||||
await expect(table.refreshColumnAsync("x")).rejects.toThrow(
|
||||
"not a computed column",
|
||||
);
|
||||
});
|
||||
|
||||
it("fills rows added since the last refresh", async () => {
|
||||
const db = await connect(tmpDir.name);
|
||||
const table = await db.createTable("computed_append", [{ x: 1 }]);
|
||||
|
||||
await table.addColumns({
|
||||
computed: [{ name: "doubled", valueSql: "x * 2" }],
|
||||
});
|
||||
await table.refreshColumn("doubled");
|
||||
await table.add([{ x: 5 }]);
|
||||
|
||||
const result = await table.refreshColumn("doubled");
|
||||
expect(result.rowsFilled).toBe(1);
|
||||
|
||||
const rows = await table.query().toArray();
|
||||
expect(rows.map((r) => r.doubled).sort()).toEqual([10, 2]);
|
||||
});
|
||||
});
|
||||
|
||||
+10
-10
@@ -48,8 +48,11 @@ import {
|
||||
} from "apache-arrow";
|
||||
import { Buffers } from "apache-arrow/data";
|
||||
import { type EmbeddingFunction } from "./embedding/embedding_function";
|
||||
import { parseEmbeddingFunctionMetadata } from "./embedding/metadata";
|
||||
import { EmbeddingFunctionConfig, getRegistry } from "./embedding/registry";
|
||||
import {
|
||||
EmbeddingFunctionConfig,
|
||||
getRegistry,
|
||||
parseEmbeddingMetadata,
|
||||
} from "./embedding/registry";
|
||||
import {
|
||||
sanitizeField,
|
||||
sanitizeSchema,
|
||||
@@ -934,7 +937,7 @@ async function applyEmbeddingsFromMetadata(
|
||||
|
||||
for (const functionEntry of functions.values()) {
|
||||
const sourceColumn = columns[functionEntry.sourceColumn];
|
||||
const destColumn = functionEntry.vectorColumn ?? "vector";
|
||||
const destColumn = functionEntry.vectorColumn;
|
||||
if (sourceColumn === undefined) {
|
||||
throw new Error(
|
||||
`Cannot apply embedding function because the source column '${functionEntry.sourceColumn}' was not present in the data`,
|
||||
@@ -1386,13 +1389,10 @@ function validateSchemaEmbeddings(
|
||||
|
||||
// Check schema metadata for embedding functions
|
||||
if (schema.metadata.has("embedding_functions")) {
|
||||
const embeddings = parseEmbeddingFunctionMetadata(schema.metadata);
|
||||
if (
|
||||
embeddings.find(
|
||||
(embedding) =>
|
||||
(embedding.vectorColumn ?? "vector") === field.name,
|
||||
)
|
||||
) {
|
||||
const entries = parseEmbeddingMetadata(
|
||||
schema.metadata.get("embedding_functions")!,
|
||||
);
|
||||
if (entries.some((f) => f.vectorColumn === field.name)) {
|
||||
hasEmbeddingFunction = true;
|
||||
}
|
||||
}
|
||||
|
||||
@@ -327,6 +327,14 @@ export abstract class Connection {
|
||||
*/
|
||||
abstract dropTable(name: string, namespacePath?: string[]): Promise<void>;
|
||||
|
||||
/**
|
||||
* Start dropping a table and return its cleanup job.
|
||||
*
|
||||
* The table may become unavailable before its data files are removed. Wait
|
||||
* on the returned job to know when cleanup has finished.
|
||||
*/
|
||||
abstract dropTableAsync(name: string, namespacePath?: string[]): Promise<Job>;
|
||||
|
||||
/**
|
||||
* Drop all tables in the database.
|
||||
* @param {string[]} namespacePath The namespace path to drop tables from (defaults to root namespace).
|
||||
@@ -705,6 +713,10 @@ export class LocalConnection extends Connection {
|
||||
return this.inner.dropTable(name, namespacePath ?? []);
|
||||
}
|
||||
|
||||
async dropTableAsync(name: string, namespacePath?: string[]): Promise<Job> {
|
||||
return this.inner.dropTableAsync(name, namespacePath ?? []);
|
||||
}
|
||||
|
||||
async dropAllTables(namespacePath?: string[]): Promise<void> {
|
||||
return this.inner.dropAllTables(namespacePath ?? []);
|
||||
}
|
||||
|
||||
@@ -1,50 +0,0 @@
|
||||
// SPDX-License-Identifier: Apache-2.0
|
||||
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
|
||||
|
||||
import type { EmbeddingFunction } from "./embedding_function";
|
||||
|
||||
interface SerializedEmbeddingFunction {
|
||||
name: string;
|
||||
model: EmbeddingFunction["TOptions"];
|
||||
sourceColumn?: string;
|
||||
vectorColumn?: string;
|
||||
[key: string]: unknown;
|
||||
}
|
||||
|
||||
export interface EmbeddingFunctionMetadata {
|
||||
name: string;
|
||||
model: EmbeddingFunction["TOptions"];
|
||||
sourceColumn: string;
|
||||
vectorColumn?: string;
|
||||
}
|
||||
|
||||
export function parseEmbeddingFunctionMetadata(
|
||||
metadata: Map<string, string>,
|
||||
): EmbeddingFunctionMetadata[] {
|
||||
const serialized = metadata.get("embedding_functions");
|
||||
if (serialized === undefined) {
|
||||
return [];
|
||||
}
|
||||
|
||||
return (JSON.parse(serialized) as SerializedEmbeddingFunction[]).map(
|
||||
(functionMetadata) => {
|
||||
const sourceColumn =
|
||||
functionMetadata.sourceColumn ??
|
||||
(functionMetadata["source_column"] as string | undefined);
|
||||
if (sourceColumn === undefined) {
|
||||
throw new Error(
|
||||
"Embedding function metadata is missing a source column",
|
||||
);
|
||||
}
|
||||
|
||||
return {
|
||||
name: functionMetadata.name,
|
||||
model: functionMetadata.model,
|
||||
sourceColumn,
|
||||
vectorColumn:
|
||||
functionMetadata.vectorColumn ??
|
||||
(functionMetadata["vector_column"] as string | undefined),
|
||||
};
|
||||
},
|
||||
);
|
||||
}
|
||||
@@ -5,7 +5,6 @@ import {
|
||||
type EmbeddingFunction,
|
||||
type EmbeddingFunctionConstructor,
|
||||
} from "./embedding_function";
|
||||
import { parseEmbeddingFunctionMetadata } from "./metadata";
|
||||
import "reflect-metadata";
|
||||
|
||||
export type CreateReturnType<T> = T extends { init: () => Promise<void> }
|
||||
@@ -105,31 +104,29 @@ export class EmbeddingFunctionRegistry {
|
||||
async parseFunctions(
|
||||
this: EmbeddingFunctionRegistry,
|
||||
metadata: Map<string, string>,
|
||||
): Promise<Map<string, EmbeddingFunctionConfig>> {
|
||||
const functions = parseEmbeddingFunctionMetadata(metadata);
|
||||
if (functions.length === 0) {
|
||||
): Promise<Map<string, ResolvedEmbeddingFunctionConfig>> {
|
||||
if (!metadata.has("embedding_functions")) {
|
||||
return new Map();
|
||||
} else {
|
||||
const items: [string, EmbeddingFunctionConfig][] = await Promise.all(
|
||||
functions.map(async (f) => {
|
||||
const fn = this.get(f.name);
|
||||
if (!fn) {
|
||||
throw new Error(`Function "${f.name}" not found in registry`);
|
||||
}
|
||||
const func = await this.get(f.name)!.create(f.model);
|
||||
return [
|
||||
f.vectorColumn ?? "vector",
|
||||
{
|
||||
sourceColumn: f.sourceColumn,
|
||||
vectorColumn: f.vectorColumn,
|
||||
function: func,
|
||||
},
|
||||
];
|
||||
}),
|
||||
);
|
||||
|
||||
return new Map(items);
|
||||
}
|
||||
const entries = parseEmbeddingMetadata(
|
||||
metadata.get("embedding_functions")!,
|
||||
);
|
||||
const items = await Promise.all(
|
||||
entries.map(async (f): Promise<ResolvedEmbeddingFunctionConfig> => {
|
||||
const fn = this.get(f.name);
|
||||
if (!fn) {
|
||||
throw new Error(`Function "${f.name}" not found in registry`);
|
||||
}
|
||||
const func = await fn.create(f.model);
|
||||
return {
|
||||
sourceColumn: f.sourceColumn,
|
||||
vectorColumn: f.vectorColumn,
|
||||
function: func,
|
||||
};
|
||||
}),
|
||||
);
|
||||
// Keyed by output column: one function may serve several columns.
|
||||
return new Map(items.map((config) => [config.vectorColumn, config]));
|
||||
}
|
||||
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
|
||||
functionToMetadata(conf: EmbeddingFunctionConfig): Record<string, any> {
|
||||
@@ -209,3 +206,52 @@ export interface EmbeddingFunctionConfig {
|
||||
vectorColumn?: string;
|
||||
function: EmbeddingFunction;
|
||||
}
|
||||
|
||||
/** An [EmbeddingFunctionConfig] read back from table metadata, where the
|
||||
* vector column is always recorded. */
|
||||
export type ResolvedEmbeddingFunctionConfig = EmbeddingFunctionConfig & {
|
||||
vectorColumn: string;
|
||||
};
|
||||
|
||||
/** One entry of the `embedding_functions` schema metadata, with the column
|
||||
* keys normalized across the bindings' spellings. */
|
||||
export type EmbeddingMetadataEntry = {
|
||||
name: string;
|
||||
sourceColumn: string;
|
||||
vectorColumn: string;
|
||||
model: EmbeddingFunction["TOptions"];
|
||||
};
|
||||
|
||||
/** The single parser for `embedding_functions` schema metadata: every reader
|
||||
* goes through here, so the wire contract cannot fork between them. */
|
||||
export function parseEmbeddingMetadata(json: string): EmbeddingMetadataEntry[] {
|
||||
// The wire format, honestly: the Python bindings write snake_case keys.
|
||||
type Raw = {
|
||||
name: string;
|
||||
sourceColumn?: string;
|
||||
// biome-ignore lint/style/useNamingConvention: the Python wire spelling
|
||||
source_column?: string;
|
||||
vectorColumn?: string;
|
||||
// biome-ignore lint/style/useNamingConvention: the Python wire spelling
|
||||
vector_column?: string;
|
||||
model: EmbeddingFunction["TOptions"];
|
||||
};
|
||||
const entries = <Raw[]>JSON.parse(json);
|
||||
const seen = new Set<string>();
|
||||
return entries.map((f) => {
|
||||
const sourceColumn = f.sourceColumn ?? f.source_column;
|
||||
const vectorColumn = f.vectorColumn ?? f.vector_column;
|
||||
if (sourceColumn === undefined || vectorColumn === undefined) {
|
||||
throw new Error(
|
||||
`Embedding function "${f.name}" metadata names no source or vector column`,
|
||||
);
|
||||
}
|
||||
if (seen.has(vectorColumn)) {
|
||||
throw new Error(
|
||||
`Multiple embedding configs claim vector column "${vectorColumn}"`,
|
||||
);
|
||||
}
|
||||
seen.add(vectorColumn);
|
||||
return { name: f.name, sourceColumn, vectorColumn, model: f.model };
|
||||
});
|
||||
}
|
||||
|
||||
@@ -50,6 +50,7 @@ export {
|
||||
MergeResult,
|
||||
AddResult,
|
||||
AddColumnsResult,
|
||||
RefreshColumnResult,
|
||||
AlterColumnsResult,
|
||||
UpdateFieldMetadataResult,
|
||||
DeleteResult,
|
||||
@@ -146,6 +147,10 @@ export {
|
||||
FtsToken,
|
||||
TokenizeTableOptions,
|
||||
LsmWriteSpec,
|
||||
LsmStats,
|
||||
BucketStats,
|
||||
GenerationStats,
|
||||
MemtableStats,
|
||||
ColumnAlteration,
|
||||
FieldMetadataUpdate,
|
||||
} from "./table";
|
||||
|
||||
+174
-29
@@ -9,7 +9,7 @@
|
||||
// comes from the exact same library instance. This is not always the case
|
||||
// and so we must sanitize the input to ensure that it is compatible.
|
||||
|
||||
import { BufferType, Data } from "apache-arrow";
|
||||
import { BufferType, Data, Vector } from "apache-arrow";
|
||||
import type { IntBitWidth, TKeys, TimeBitWidth } from "apache-arrow/type";
|
||||
import {
|
||||
Binary,
|
||||
@@ -74,6 +74,20 @@ import {
|
||||
Utf8,
|
||||
} from "./arrow";
|
||||
|
||||
type SanitizationContext = {
|
||||
types: WeakMap<object, DataType>;
|
||||
vectors: WeakMap<object, Vector>;
|
||||
data: WeakMap<object, Data<DataType>>;
|
||||
};
|
||||
|
||||
function createSanitizationContext(): SanitizationContext {
|
||||
return {
|
||||
types: new WeakMap(),
|
||||
vectors: new WeakMap(),
|
||||
data: new WeakMap(),
|
||||
};
|
||||
}
|
||||
|
||||
export function sanitizeMetadata(
|
||||
metadataLike?: unknown,
|
||||
): Map<string, string> | undefined {
|
||||
@@ -186,6 +200,13 @@ export function sanitizeInterval(typeLike: object) {
|
||||
}
|
||||
|
||||
export function sanitizeList(typeLike: object) {
|
||||
return sanitizeListWithContext(typeLike, createSanitizationContext());
|
||||
}
|
||||
|
||||
function sanitizeListWithContext(
|
||||
typeLike: object,
|
||||
context: SanitizationContext,
|
||||
) {
|
||||
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
|
||||
throw Error(
|
||||
"Expected a List type to have an array-like `children` property",
|
||||
@@ -194,19 +215,35 @@ export function sanitizeList(typeLike: object) {
|
||||
if (typeLike.children.length !== 1) {
|
||||
throw Error("Expected a List type to have exactly one child");
|
||||
}
|
||||
return new List(sanitizeField(typeLike.children[0]));
|
||||
return new List(sanitizeFieldWithContext(typeLike.children[0], context));
|
||||
}
|
||||
|
||||
export function sanitizeStruct(typeLike: object) {
|
||||
return sanitizeStructWithContext(typeLike, createSanitizationContext());
|
||||
}
|
||||
|
||||
function sanitizeStructWithContext(
|
||||
typeLike: object,
|
||||
context: SanitizationContext,
|
||||
) {
|
||||
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
|
||||
throw Error(
|
||||
"Expected a Struct type to have an array-like `children` property",
|
||||
);
|
||||
}
|
||||
return new Struct(typeLike.children.map((child) => sanitizeField(child)));
|
||||
return new Struct(
|
||||
typeLike.children.map((child) => sanitizeFieldWithContext(child, context)),
|
||||
);
|
||||
}
|
||||
|
||||
export function sanitizeUnion(typeLike: object) {
|
||||
return sanitizeUnionWithContext(typeLike, createSanitizationContext());
|
||||
}
|
||||
|
||||
function sanitizeUnionWithContext(
|
||||
typeLike: object,
|
||||
context: SanitizationContext,
|
||||
) {
|
||||
if (
|
||||
!("typeIds" in typeLike) ||
|
||||
!("mode" in typeLike) ||
|
||||
@@ -226,7 +263,7 @@ export function sanitizeUnion(typeLike: object) {
|
||||
typeLike.mode,
|
||||
// biome-ignore lint/suspicious/noExplicitAny: skip
|
||||
typeLike.typeIds as any,
|
||||
typeLike.children.map((child) => sanitizeField(child)),
|
||||
typeLike.children.map((child) => sanitizeFieldWithContext(child, context)),
|
||||
);
|
||||
}
|
||||
|
||||
@@ -234,6 +271,19 @@ export function sanitizeTypedUnion(
|
||||
typeLike: object,
|
||||
// eslint-disable-next-line @typescript-eslint/naming-convention
|
||||
UnionType: typeof DenseUnion | typeof SparseUnion,
|
||||
) {
|
||||
return sanitizeTypedUnionWithContext(
|
||||
typeLike,
|
||||
UnionType,
|
||||
createSanitizationContext(),
|
||||
);
|
||||
}
|
||||
|
||||
function sanitizeTypedUnionWithContext(
|
||||
typeLike: object,
|
||||
// eslint-disable-next-line @typescript-eslint/naming-convention
|
||||
UnionType: typeof DenseUnion | typeof SparseUnion,
|
||||
context: SanitizationContext,
|
||||
) {
|
||||
if (!("typeIds" in typeLike)) {
|
||||
throw Error(
|
||||
@@ -248,7 +298,7 @@ export function sanitizeTypedUnion(
|
||||
|
||||
return new UnionType(
|
||||
typeLike.typeIds as Int32Array | number[],
|
||||
typeLike.children.map((child) => sanitizeField(child)),
|
||||
typeLike.children.map((child) => sanitizeFieldWithContext(child, context)),
|
||||
);
|
||||
}
|
||||
|
||||
@@ -262,6 +312,16 @@ export function sanitizeFixedSizeBinary(typeLike: object) {
|
||||
}
|
||||
|
||||
export function sanitizeFixedSizeList(typeLike: object) {
|
||||
return sanitizeFixedSizeListWithContext(
|
||||
typeLike,
|
||||
createSanitizationContext(),
|
||||
);
|
||||
}
|
||||
|
||||
function sanitizeFixedSizeListWithContext(
|
||||
typeLike: object,
|
||||
context: SanitizationContext,
|
||||
) {
|
||||
if (!("listSize" in typeLike) || typeof typeLike.listSize !== "number") {
|
||||
throw Error("Expected a FixedSizeList type to have a `listSize` property");
|
||||
}
|
||||
@@ -275,11 +335,18 @@ export function sanitizeFixedSizeList(typeLike: object) {
|
||||
}
|
||||
return new FixedSizeList(
|
||||
typeLike.listSize,
|
||||
sanitizeField(typeLike.children[0]),
|
||||
sanitizeFieldWithContext(typeLike.children[0], context),
|
||||
);
|
||||
}
|
||||
|
||||
export function sanitizeMap(typeLike: object) {
|
||||
return sanitizeMapWithContext(typeLike, createSanitizationContext());
|
||||
}
|
||||
|
||||
function sanitizeMapWithContext(
|
||||
typeLike: object,
|
||||
context: SanitizationContext,
|
||||
) {
|
||||
if (!("children" in typeLike) || !Array.isArray(typeLike.children)) {
|
||||
throw Error(
|
||||
"Expected a Map type to have an array-like `children` property",
|
||||
@@ -292,7 +359,10 @@ export function sanitizeMap(typeLike: object) {
|
||||
throw Error("Expected a Map type to have exactly one child");
|
||||
}
|
||||
|
||||
return new Map_(sanitizeField(typeLike.children[0]), typeLike.keysSorted);
|
||||
return new Map_(
|
||||
sanitizeFieldWithContext(typeLike.children[0], context),
|
||||
typeLike.keysSorted,
|
||||
);
|
||||
}
|
||||
|
||||
export function sanitizeDuration(typeLike: object) {
|
||||
@@ -303,6 +373,13 @@ export function sanitizeDuration(typeLike: object) {
|
||||
}
|
||||
|
||||
export function sanitizeDictionary(typeLike: object) {
|
||||
return sanitizeDictionaryWithContext(typeLike, createSanitizationContext());
|
||||
}
|
||||
|
||||
function sanitizeDictionaryWithContext(
|
||||
typeLike: object,
|
||||
context: SanitizationContext,
|
||||
) {
|
||||
if (!("id" in typeLike) || typeof typeLike.id !== "number") {
|
||||
throw Error("Expected a Dictionary type to have an `id` property");
|
||||
}
|
||||
@@ -316,8 +393,8 @@ export function sanitizeDictionary(typeLike: object) {
|
||||
throw Error("Expected a Dictionary type to have an `isOrdered` property");
|
||||
}
|
||||
return new Dictionary(
|
||||
sanitizeType(typeLike.dictionary),
|
||||
sanitizeType(typeLike.indices) as TKeys,
|
||||
sanitizeTypeWithContext(typeLike.dictionary, context),
|
||||
sanitizeTypeWithContext(typeLike.indices, context) as TKeys,
|
||||
typeLike.id,
|
||||
typeLike.isOrdered,
|
||||
);
|
||||
@@ -325,12 +402,23 @@ export function sanitizeDictionary(typeLike: object) {
|
||||
|
||||
// biome-ignore lint/suspicious/noExplicitAny: skip
|
||||
export function sanitizeType(typeLike: unknown): DataType<any> {
|
||||
return sanitizeTypeWithContext(typeLike, createSanitizationContext());
|
||||
}
|
||||
|
||||
function sanitizeTypeWithContext(
|
||||
typeLike: unknown,
|
||||
context: SanitizationContext,
|
||||
): DataType {
|
||||
if (typeof typeLike === "string") {
|
||||
return dataTypeFromName(typeLike);
|
||||
}
|
||||
if (typeof typeLike !== "object" || typeLike === null) {
|
||||
throw Error("Expected a Type but object was null/undefined");
|
||||
}
|
||||
const cached = context.types.get(typeLike);
|
||||
if (cached !== undefined) {
|
||||
return cached;
|
||||
}
|
||||
if (
|
||||
!("typeId" in typeLike) ||
|
||||
!(
|
||||
@@ -349,6 +437,16 @@ export function sanitizeType(typeLike: unknown): DataType<any> {
|
||||
throw Error("Type's typeId property was not a function or number");
|
||||
}
|
||||
|
||||
const type = sanitizeTypeById(typeLike, typeId, context);
|
||||
context.types.set(typeLike, type);
|
||||
return type;
|
||||
}
|
||||
|
||||
function sanitizeTypeById(
|
||||
typeLike: object,
|
||||
typeId: Type,
|
||||
context: SanitizationContext,
|
||||
): DataType {
|
||||
switch (typeId) {
|
||||
case Type.NONE:
|
||||
throw Error("Received a Type with a typeId of NONE");
|
||||
@@ -375,21 +473,21 @@ export function sanitizeType(typeLike: unknown): DataType<any> {
|
||||
case Type.Interval:
|
||||
return sanitizeInterval(typeLike);
|
||||
case Type.List:
|
||||
return sanitizeList(typeLike);
|
||||
return sanitizeListWithContext(typeLike, context);
|
||||
case Type.Struct:
|
||||
return sanitizeStruct(typeLike);
|
||||
return sanitizeStructWithContext(typeLike, context);
|
||||
case Type.Union:
|
||||
return sanitizeUnion(typeLike);
|
||||
return sanitizeUnionWithContext(typeLike, context);
|
||||
case Type.FixedSizeBinary:
|
||||
return sanitizeFixedSizeBinary(typeLike);
|
||||
case Type.FixedSizeList:
|
||||
return sanitizeFixedSizeList(typeLike);
|
||||
return sanitizeFixedSizeListWithContext(typeLike, context);
|
||||
case Type.Map:
|
||||
return sanitizeMap(typeLike);
|
||||
return sanitizeMapWithContext(typeLike, context);
|
||||
case Type.Duration:
|
||||
return sanitizeDuration(typeLike);
|
||||
case Type.Dictionary:
|
||||
return sanitizeDictionary(typeLike);
|
||||
return sanitizeDictionaryWithContext(typeLike, context);
|
||||
case Type.Int8:
|
||||
return new Int8();
|
||||
case Type.Int16:
|
||||
@@ -433,9 +531,9 @@ export function sanitizeType(typeLike: unknown): DataType<any> {
|
||||
case Type.TimestampSecond:
|
||||
return sanitizeTypedTimestamp(typeLike, TimestampSecond);
|
||||
case Type.DenseUnion:
|
||||
return sanitizeTypedUnion(typeLike, DenseUnion);
|
||||
return sanitizeTypedUnionWithContext(typeLike, DenseUnion, context);
|
||||
case Type.SparseUnion:
|
||||
return sanitizeTypedUnion(typeLike, SparseUnion);
|
||||
return sanitizeTypedUnionWithContext(typeLike, SparseUnion, context);
|
||||
case Type.IntervalDayTime:
|
||||
return new IntervalDayTime();
|
||||
case Type.IntervalYearMonth:
|
||||
@@ -454,6 +552,13 @@ export function sanitizeType(typeLike: unknown): DataType<any> {
|
||||
}
|
||||
|
||||
export function sanitizeField(fieldLike: unknown): Field {
|
||||
return sanitizeFieldWithContext(fieldLike, createSanitizationContext());
|
||||
}
|
||||
|
||||
function sanitizeFieldWithContext(
|
||||
fieldLike: unknown,
|
||||
context: SanitizationContext,
|
||||
): Field {
|
||||
if (fieldLike instanceof Field) {
|
||||
return fieldLike;
|
||||
}
|
||||
@@ -471,7 +576,7 @@ export function sanitizeField(fieldLike: unknown): Field {
|
||||
}
|
||||
let type: DataType;
|
||||
try {
|
||||
type = sanitizeType(fieldLike.type);
|
||||
type = sanitizeTypeWithContext(fieldLike.type, context);
|
||||
} catch (error: unknown) {
|
||||
throw Error(
|
||||
`Unable to sanitize type for field: ${fieldLike.name} due to error: ${error}`,
|
||||
@@ -501,6 +606,13 @@ export function sanitizeField(fieldLike: unknown): Field {
|
||||
* than lancedb is using.
|
||||
*/
|
||||
export function sanitizeSchema(schemaLike: SchemaLike): Schema {
|
||||
return sanitizeSchemaWithContext(schemaLike, createSanitizationContext());
|
||||
}
|
||||
|
||||
function sanitizeSchemaWithContext(
|
||||
schemaLike: SchemaLike,
|
||||
context: SanitizationContext,
|
||||
): Schema {
|
||||
if (schemaLike instanceof Schema) {
|
||||
return schemaLike;
|
||||
}
|
||||
@@ -522,7 +634,7 @@ export function sanitizeSchema(schemaLike: SchemaLike): Schema {
|
||||
);
|
||||
}
|
||||
const sanitizedFields = schemaLike.fields.map((field) =>
|
||||
sanitizeField(field),
|
||||
sanitizeFieldWithContext(field, context),
|
||||
);
|
||||
return new Schema(sanitizedFields, metadata);
|
||||
}
|
||||
@@ -544,13 +656,18 @@ export function sanitizeTable(tableLike: TableLike): Table {
|
||||
"The table passed in does not appear to be a table (no 'columns' property)",
|
||||
);
|
||||
}
|
||||
const schema = sanitizeSchema(tableLike.schema);
|
||||
|
||||
const batches = tableLike.batches.map(sanitizeRecordBatch);
|
||||
const context = createSanitizationContext();
|
||||
const schema = sanitizeSchemaWithContext(tableLike.schema, context);
|
||||
const batches = tableLike.batches.map((batch) =>
|
||||
sanitizeRecordBatch(batch, context),
|
||||
);
|
||||
return new Table(schema, batches);
|
||||
}
|
||||
|
||||
function sanitizeRecordBatch(batchLike: RecordBatchLike): RecordBatch {
|
||||
function sanitizeRecordBatch(
|
||||
batchLike: RecordBatchLike,
|
||||
context: SanitizationContext,
|
||||
): RecordBatch {
|
||||
if (batchLike instanceof RecordBatch) {
|
||||
return batchLike;
|
||||
}
|
||||
@@ -567,19 +684,43 @@ function sanitizeRecordBatch(batchLike: RecordBatchLike): RecordBatch {
|
||||
"The record batch passed in does not appear to be a record batch (no 'data' property)",
|
||||
);
|
||||
}
|
||||
const schema = sanitizeSchema(batchLike.schema);
|
||||
const data = sanitizeData(batchLike.data);
|
||||
const schema = sanitizeSchemaWithContext(batchLike.schema, context);
|
||||
const data = sanitizeData(batchLike.data, context) as Data<Struct>;
|
||||
return new RecordBatch(schema, data);
|
||||
}
|
||||
|
||||
type DictionaryVectorLike = {
|
||||
data: readonly DataLike[];
|
||||
};
|
||||
|
||||
type DictionaryDataLike = DataLike & {
|
||||
dictionary?: DictionaryVectorLike;
|
||||
};
|
||||
|
||||
function sanitizeData(
|
||||
dataLike: DataLike,
|
||||
// biome-ignore lint/suspicious/noExplicitAny: <explanation>
|
||||
): import("apache-arrow").Data<Struct<any>> {
|
||||
context: SanitizationContext,
|
||||
): Data<DataType> {
|
||||
if (dataLike instanceof Data) {
|
||||
return dataLike;
|
||||
}
|
||||
return new Data(
|
||||
dataLike.type,
|
||||
const cachedData = context.data.get(dataLike);
|
||||
if (cachedData !== undefined) {
|
||||
return cachedData;
|
||||
}
|
||||
const dictionaryLike = (dataLike as DictionaryDataLike).dictionary;
|
||||
let dictionary: Vector | undefined;
|
||||
if (dictionaryLike !== undefined) {
|
||||
dictionary = context.vectors.get(dictionaryLike);
|
||||
if (dictionary === undefined) {
|
||||
dictionary = new Vector(
|
||||
dictionaryLike.data.map((data) => sanitizeData(data, context)),
|
||||
);
|
||||
context.vectors.set(dictionaryLike, dictionary);
|
||||
}
|
||||
}
|
||||
const data = new Data(
|
||||
sanitizeTypeWithContext(dataLike.type, context),
|
||||
dataLike.offset,
|
||||
dataLike.length,
|
||||
dataLike.nullCount,
|
||||
@@ -589,7 +730,11 @@ function sanitizeData(
|
||||
[BufferType.VALIDITY]: dataLike.nullBitmap,
|
||||
[BufferType.TYPE]: dataLike.typeIds,
|
||||
},
|
||||
dataLike.children.map((child) => sanitizeData(child, context)),
|
||||
dictionary,
|
||||
);
|
||||
context.data.set(dataLike, data);
|
||||
return data;
|
||||
}
|
||||
|
||||
const constructorsByTypeName = {
|
||||
|
||||
+174
-6
@@ -31,8 +31,10 @@ import {
|
||||
IndexConfig,
|
||||
IndexStatistics,
|
||||
Job,
|
||||
LsmStats,
|
||||
Branches as NativeBranches,
|
||||
OptimizeStats,
|
||||
RefreshColumnResult,
|
||||
TableStatistics,
|
||||
Tags,
|
||||
UpdateFieldMetadataResult,
|
||||
@@ -49,6 +51,12 @@ import {
|
||||
import { sanitizeType } from "./sanitize";
|
||||
import { IntoSql, toSQL } from "./util";
|
||||
export { IndexConfig } from "./native";
|
||||
export {
|
||||
BucketStats,
|
||||
GenerationStats,
|
||||
LsmStats,
|
||||
MemtableStats,
|
||||
} from "./native";
|
||||
|
||||
/**
|
||||
* Progress snapshot for a write operation, delivered to the `progress`
|
||||
@@ -197,7 +205,11 @@ export interface LsmWriteSpec {
|
||||
column?: string;
|
||||
/** Bucket variant: the number of buckets, in `[1, 1024]`. */
|
||||
numBuckets?: number;
|
||||
/** Names of indexes the MemWAL should keep up to date during writes. */
|
||||
/**
|
||||
* Indexes the MemWAL keeps up to date. Omit to maintain every supported
|
||||
* index, resolved on install — a snapshot, so indexes created later are not
|
||||
* maintained. Pass `[]` for none.
|
||||
*/
|
||||
maintainedIndexes?: string[];
|
||||
/** Default `ShardWriter` configuration recorded in the MemWAL index. */
|
||||
writerConfigDefaults?: Record<string, string>;
|
||||
@@ -521,18 +533,75 @@ export abstract class Table {
|
||||
abstract vectorSearch(vector: IntoVector | MultiVector): VectorQuery;
|
||||
/**
|
||||
* Add new columns with defined values.
|
||||
*
|
||||
* The `{ computed }` form stores the expression rather than evaluating it
|
||||
* now: the column is committed with no values, and rows get them from
|
||||
* {@link Table#refreshColumn}. Declaring one therefore costs the same on a
|
||||
* large table as on an empty one.
|
||||
*
|
||||
* A refresh does not revisit rows it has already filled, so mutating an
|
||||
* input leaves the value computed at fill time; recomputing means dropping
|
||||
* the column and declaring it again. While a declaration reads a column,
|
||||
* that column cannot be renamed, retyped or dropped.
|
||||
*
|
||||
* On LanceDB Cloud and Enterprise the expression is planned by the
|
||||
* server, and the refresh runs as a server job -- see
|
||||
* {@link Table#refreshColumnAsync}.
|
||||
* @param {AddColumnsSql[] | Field | Field[] | Schema} newColumnTransforms Either:
|
||||
* - An array of objects with column names and SQL expressions to calculate values
|
||||
* - A single Arrow Field defining one column with its data type (column will be initialized with null values)
|
||||
* - An array of Arrow Fields defining columns with their data types (columns will be initialized with null values)
|
||||
* - An Arrow Schema defining columns with their data types (columns will be initialized with null values)
|
||||
* - `{ computed }`, declaring columns defined by a SQL expression whose type and inputs are derived from it
|
||||
* @returns {Promise<AddColumnsResult>} A promise that resolves to an object
|
||||
* containing the new version number of the table after adding the columns.
|
||||
* @example
|
||||
* ```ts
|
||||
* await table.addColumns({ computed: [{ name: "doubled", valueSql: "x * 2" }] });
|
||||
* const { rowsFilled } = await table.refreshColumn("doubled");
|
||||
* ```
|
||||
*/
|
||||
abstract addColumns(
|
||||
newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
|
||||
newColumnTransforms:
|
||||
| AddColumnsSql[]
|
||||
| Field
|
||||
| Field[]
|
||||
| Schema
|
||||
| { computed: AddColumnsSql[] },
|
||||
): Promise<AddColumnsResult>;
|
||||
|
||||
/**
|
||||
* Fill the rows of a computed column that hold no value yet.
|
||||
*
|
||||
* Rows appended since the last refresh are filled by the next one; rows
|
||||
* already filled are left as they are, so the call is idempotent and does
|
||||
* not observe a mutated input. Local tables only: a remote refresh runs
|
||||
* as a server job, through {@link Table#refreshColumnAsync}.
|
||||
* @param {string} column The name of the computed column to fill.
|
||||
* @returns {Promise<RefreshColumnResult>} A promise that resolves to the
|
||||
* number of rows filled and the new version number of the table.
|
||||
*/
|
||||
abstract refreshColumn(column: string): Promise<RefreshColumnResult>;
|
||||
|
||||
/**
|
||||
* Like {@link Table#refreshColumn}, but returns a handle to the refresh
|
||||
* job instead of blocking until it completes.
|
||||
*
|
||||
* The job may already be complete when returned; callers must not assume
|
||||
* the column is filled until {@link Job.wait} resolves. Invalid input --
|
||||
* an unknown column, or one that is not computed -- rejects here rather
|
||||
* than failing the job. On local tables the job runs in-process; on
|
||||
* LanceDB Cloud and Enterprise it is the server's backfill job.
|
||||
* @param {string} column The name of the computed column to fill.
|
||||
* @example
|
||||
* ```ts
|
||||
* const job = await table.refreshColumnAsync("doubled");
|
||||
* await job.wait();
|
||||
* console.log(await job.status()); // "finished"
|
||||
* ```
|
||||
*/
|
||||
abstract refreshColumnAsync(column: string): Promise<Job>;
|
||||
|
||||
/**
|
||||
* Alter the name or nullability of columns.
|
||||
* @param {ColumnAlteration[]} columnAlterations One or more alterations to
|
||||
@@ -595,6 +664,11 @@ export abstract class Table {
|
||||
* All variants require the table to have an unenforced primary key
|
||||
* ({@link Table#setUnenforcedPrimaryKey}); bucket sharding additionally
|
||||
* requires it to be the single column being bucketed.
|
||||
*
|
||||
* Omitting `maintainedIndexes` maintains every index on the table, resolved
|
||||
* here, failing if one cannot be maintained — name them to install anyway.
|
||||
* Naming them pins an exact set, and a still-building index is rejected
|
||||
* rather than quietly omitted.
|
||||
* @param {LsmWriteSpec} spec The sharding spec to install.
|
||||
* @returns {Promise<void>}
|
||||
* @example
|
||||
@@ -622,9 +696,10 @@ export abstract class Table {
|
||||
*
|
||||
* Resolves to `undefined` when the MemWAL LSM write path is not enabled (no
|
||||
* spec has been set, or it was removed with {@link Table#unsetLsmWriteSpec}).
|
||||
* The returned spec — including its `maintainedIndexes` and
|
||||
* `writerConfigDefaults` — mirrors what was passed to
|
||||
* {@link Table#setLsmWriteSpec}.
|
||||
* The returned spec mirrors what was passed to
|
||||
* {@link Table#setLsmWriteSpec}, except that `maintainedIndexes` always
|
||||
* reports the concrete list resolved when the spec was set — `undefined`
|
||||
* never round-trips.
|
||||
* @returns {Promise<LsmWriteSpec | undefined>}
|
||||
*/
|
||||
abstract getLsmWriteSpec(): Promise<LsmWriteSpec | undefined>;
|
||||
@@ -638,6 +713,59 @@ export abstract class Table {
|
||||
* @returns {Promise<void>}
|
||||
*/
|
||||
abstract closeLsmWriters(): Promise<void>;
|
||||
/**
|
||||
* Seal every bucket's active memtable into a new L0 generation.
|
||||
*
|
||||
* Returns once the seal is committed. Sealing an empty memtable is a no-op,
|
||||
* so this is safe to call repeatedly.
|
||||
* @returns {Promise<void>}
|
||||
*/
|
||||
abstract flushLsm(): Promise<void>;
|
||||
/**
|
||||
* Trigger a background L0 → base compaction pass per bucket.
|
||||
*
|
||||
* Returns once the passes are *dispatched*, not once they finish — watch
|
||||
* {@link Table#getLsmStats} for progress, or use
|
||||
* {@link Table#checkpointLsm} to wait for convergence.
|
||||
* @returns {Promise<void>}
|
||||
*/
|
||||
abstract compactLsm(): Promise<void>;
|
||||
/**
|
||||
* Converge this table's LSM write path into its base table.
|
||||
*
|
||||
* Seals once, then triggers compaction and polls until the L0 that existed
|
||||
* at the start is gone. The target set is fixed at the start, so
|
||||
* generations created *during* the checkpoint are ignored — that is what
|
||||
* lets it terminate under write load, and what makes it best-effort: it
|
||||
* converges the fresh tier as of some instant. Idempotent, abandonable at
|
||||
* any point, and safe to run on a cadence.
|
||||
*
|
||||
* There is no liveness bound — the compactor pool is shared across tables,
|
||||
* so a checkpoint queued behind unrelated work looks exactly like one that
|
||||
* is merging. The caller owns the deadline.
|
||||
* @returns {Promise<void>}
|
||||
* @example
|
||||
* ```ts
|
||||
* const before = await table.getLsmStats();
|
||||
* await table.checkpointLsm();
|
||||
* const after = await table.getLsmStats();
|
||||
* ```
|
||||
*/
|
||||
abstract checkpointLsm(): Promise<void>;
|
||||
/**
|
||||
* Read live per-bucket LSM state.
|
||||
*
|
||||
* Answers "how far behind is my fresh tier", "which bucket is hot", and
|
||||
* "why is my fresh-tier vector search brute-force". Mutates no table state.
|
||||
*
|
||||
* Resolves to `undefined` only when the LSM write path is not enabled.
|
||||
* @param {boolean} includeGenerationRows Also count rows per L0 generation.
|
||||
* Off by default because each count opens an uncached Lance dataset.
|
||||
* @returns {Promise<LsmStats | undefined>}
|
||||
*/
|
||||
abstract getLsmStats(
|
||||
includeGenerationRows?: boolean,
|
||||
): Promise<LsmStats | undefined>;
|
||||
/** Retrieve the version of the table */
|
||||
|
||||
abstract version(): Promise<number>;
|
||||
@@ -1078,8 +1206,22 @@ export class LocalTable extends Table {
|
||||
// TODO: Support BatchUDF
|
||||
|
||||
async addColumns(
|
||||
newColumnTransforms: AddColumnsSql[] | Field | Field[] | Schema,
|
||||
newColumnTransforms:
|
||||
| AddColumnsSql[]
|
||||
| Field
|
||||
| Field[]
|
||||
| Schema
|
||||
| { computed: AddColumnsSql[] },
|
||||
): Promise<AddColumnsResult> {
|
||||
// Columns defined by an expression are declared, not materialized here.
|
||||
if (
|
||||
typeof newColumnTransforms === "object" &&
|
||||
!Array.isArray(newColumnTransforms) &&
|
||||
"computed" in newColumnTransforms
|
||||
) {
|
||||
return await this.inner.addComputedColumns(newColumnTransforms.computed);
|
||||
}
|
||||
|
||||
// Handle single Field -> convert to array of Fields
|
||||
if (newColumnTransforms instanceof Field) {
|
||||
newColumnTransforms = [newColumnTransforms];
|
||||
@@ -1114,6 +1256,14 @@ export class LocalTable extends Table {
|
||||
throw new Error("Invalid input type for addColumns");
|
||||
}
|
||||
|
||||
async refreshColumn(column: string): Promise<RefreshColumnResult> {
|
||||
return await this.inner.refreshColumn(column);
|
||||
}
|
||||
|
||||
async refreshColumnAsync(column: string): Promise<Job> {
|
||||
return await this.inner.refreshColumnAsync(column);
|
||||
}
|
||||
|
||||
async alterColumns(
|
||||
columnAlterations: ColumnAlteration[],
|
||||
): Promise<AlterColumnsResult> {
|
||||
@@ -1176,6 +1326,24 @@ export class LocalTable extends Table {
|
||||
return await this.inner.closeLsmWriters();
|
||||
}
|
||||
|
||||
async flushLsm(): Promise<void> {
|
||||
return await this.inner.flushLsm();
|
||||
}
|
||||
|
||||
async compactLsm(): Promise<void> {
|
||||
return await this.inner.compactLsm();
|
||||
}
|
||||
|
||||
async checkpointLsm(): Promise<void> {
|
||||
return await this.inner.checkpointLsm();
|
||||
}
|
||||
|
||||
async getLsmStats(
|
||||
includeGenerationRows: boolean = false,
|
||||
): Promise<LsmStats | undefined> {
|
||||
return (await this.inner.getLsmStats(includeGenerationRows)) ?? undefined;
|
||||
}
|
||||
|
||||
async version(): Promise<number> {
|
||||
return await this.inner.version();
|
||||
}
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-darwin-arm64",
|
||||
"version": "0.37.1-beta.0",
|
||||
"version": "0.38.0-beta.3",
|
||||
"os": ["darwin"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.darwin-arm64.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-arm64-gnu",
|
||||
"version": "0.37.1-beta.0",
|
||||
"version": "0.38.0-beta.3",
|
||||
"os": ["linux"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.linux-arm64-gnu.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-arm64-musl",
|
||||
"version": "0.37.1-beta.0",
|
||||
"version": "0.38.0-beta.3",
|
||||
"os": ["linux"],
|
||||
"cpu": ["arm64"],
|
||||
"main": "lancedb.linux-arm64-musl.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-x64-gnu",
|
||||
"version": "0.37.1-beta.0",
|
||||
"version": "0.38.0-beta.3",
|
||||
"os": ["linux"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.linux-x64-gnu.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-linux-x64-musl",
|
||||
"version": "0.37.1-beta.0",
|
||||
"version": "0.38.0-beta.3",
|
||||
"os": ["linux"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.linux-x64-musl.node",
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-arm64-msvc",
|
||||
"version": "0.37.1-beta.0",
|
||||
"version": "0.38.0-beta.3",
|
||||
"os": [
|
||||
"win32"
|
||||
],
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb-win32-x64-msvc",
|
||||
"version": "0.37.1-beta.0",
|
||||
"version": "0.38.0-beta.3",
|
||||
"os": ["win32"],
|
||||
"cpu": ["x64"],
|
||||
"main": "lancedb.win32-x64-msvc.node",
|
||||
|
||||
Generated
+2
-2
@@ -1,12 +1,12 @@
|
||||
{
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.37.1-beta.0",
|
||||
"version": "0.38.0-beta.3",
|
||||
"lockfileVersion": 3,
|
||||
"requires": true,
|
||||
"packages": {
|
||||
"": {
|
||||
"name": "@lancedb/lancedb",
|
||||
"version": "0.37.1-beta.0",
|
||||
"version": "0.38.0-beta.3",
|
||||
"cpu": [
|
||||
"x64",
|
||||
"arm64"
|
||||
|
||||
+1
-1
@@ -11,7 +11,7 @@
|
||||
"ann"
|
||||
],
|
||||
"private": false,
|
||||
"version": "0.37.1-beta.0",
|
||||
"version": "0.38.0-beta.3",
|
||||
"main": "dist/index.js",
|
||||
"exports": {
|
||||
".": "./dist/index.js",
|
||||
|
||||
@@ -334,6 +334,22 @@ impl Connection {
|
||||
.default_error()
|
||||
}
|
||||
|
||||
/// Start dropping a table and return its cleanup job.
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn drop_table_async(
|
||||
&self,
|
||||
name: String,
|
||||
namespace_path: Option<Vec<String>>,
|
||||
) -> napi::Result<crate::job::Job> {
|
||||
let ns = namespace_path.unwrap_or_default();
|
||||
let job = self
|
||||
.get_inner()?
|
||||
.drop_table_async(&name, &ns)
|
||||
.await
|
||||
.default_error()?;
|
||||
Ok(crate::job::Job::new(job))
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn drop_all_tables(&self, namespace_path: Option<Vec<String>>) -> napi::Result<()> {
|
||||
let ns = namespace_path.unwrap_or_default();
|
||||
|
||||
+210
-7
@@ -347,6 +347,40 @@ impl Table {
|
||||
Ok(res.into())
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn add_computed_columns(
|
||||
&self,
|
||||
columns: Vec<AddColumnsSql>,
|
||||
) -> napi::Result<AddColumnsResult> {
|
||||
let table = self.inner_ref()?;
|
||||
let mut builder = table.add_columns();
|
||||
for column in columns {
|
||||
builder = builder.computed(column.name, column.value_sql);
|
||||
}
|
||||
let res = builder.execute().await.default_error()?;
|
||||
Ok(res.into())
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn refresh_column(&self, column: String) -> napi::Result<RefreshColumnResult> {
|
||||
let res = self
|
||||
.inner_ref()?
|
||||
.refresh_column(column)
|
||||
.await
|
||||
.default_error()?;
|
||||
Ok(res.into())
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn refresh_column_async(&self, column: String) -> napi::Result<crate::job::Job> {
|
||||
let job = self
|
||||
.inner_ref()?
|
||||
.refresh_column_async(column)
|
||||
.await
|
||||
.default_error()?;
|
||||
Ok(crate::job::Job::new(job))
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn add_columns_with_schema(
|
||||
&self,
|
||||
@@ -463,6 +497,34 @@ impl Table {
|
||||
self.inner_ref()?.close_lsm_writers().await.default_error()
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn flush_lsm(&self) -> napi::Result<()> {
|
||||
self.inner_ref()?.flush_lsm().await.default_error()
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn compact_lsm(&self) -> napi::Result<()> {
|
||||
self.inner_ref()?.compact_lsm().await.default_error()
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn checkpoint_lsm(&self) -> napi::Result<()> {
|
||||
self.inner_ref()?.checkpoint_lsm().await.default_error()
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn get_lsm_stats(
|
||||
&self,
|
||||
include_generation_rows: bool,
|
||||
) -> napi::Result<Option<LsmStats>> {
|
||||
let stats = self
|
||||
.inner_ref()?
|
||||
.get_lsm_stats(include_generation_rows)
|
||||
.await
|
||||
.default_error()?;
|
||||
Ok(stats.map(LsmStats::from))
|
||||
}
|
||||
|
||||
#[napi(catch_unwind)]
|
||||
pub async fn version(&self) -> napi::Result<i64> {
|
||||
self.inner_ref()?
|
||||
@@ -772,7 +834,8 @@ pub struct LsmWriteSpec {
|
||||
pub column: Option<String>,
|
||||
/// Bucket variant: the number of buckets, in `[1, 1024]`.
|
||||
pub num_buckets: Option<u32>,
|
||||
/// Names of indexes the MemWAL should keep up to date during writes.
|
||||
/// Indexes the MemWAL keeps up to date. Omitted resolves every
|
||||
/// maintainable index on install; an empty array means none.
|
||||
pub maintained_indexes: Option<Vec<String>>,
|
||||
/// Default `ShardWriter` configuration recorded in the MemWAL index.
|
||||
pub writer_config_defaults: Option<HashMap<String, String>>,
|
||||
@@ -782,7 +845,6 @@ impl TryFrom<LsmWriteSpec> for lancedb::table::LsmWriteSpec {
|
||||
type Error = napi::Error;
|
||||
|
||||
fn try_from(value: LsmWriteSpec) -> napi::Result<Self> {
|
||||
let maintained = value.maintained_indexes.unwrap_or_default();
|
||||
let writer_config_defaults = value.writer_config_defaults.unwrap_or_default();
|
||||
let spec = match value.spec_type.as_str() {
|
||||
"bucket" => {
|
||||
@@ -809,7 +871,7 @@ impl TryFrom<LsmWriteSpec> for lancedb::table::LsmWriteSpec {
|
||||
}
|
||||
};
|
||||
Ok(spec
|
||||
.with_maintained_indexes(maintained)
|
||||
.with_maintained_indexes(value.maintained_indexes)
|
||||
.with_writer_config_defaults(writer_config_defaults))
|
||||
}
|
||||
}
|
||||
@@ -827,7 +889,7 @@ impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
|
||||
spec_type: "bucket".to_string(),
|
||||
column: Some(column),
|
||||
num_buckets: Some(num_buckets),
|
||||
maintained_indexes: Some(maintained_indexes),
|
||||
maintained_indexes,
|
||||
writer_config_defaults: Some(writer_config_defaults),
|
||||
},
|
||||
Native::Identity {
|
||||
@@ -838,7 +900,7 @@ impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
|
||||
spec_type: "identity".to_string(),
|
||||
column: Some(column),
|
||||
num_buckets: None,
|
||||
maintained_indexes: Some(maintained_indexes),
|
||||
maintained_indexes,
|
||||
writer_config_defaults: Some(writer_config_defaults),
|
||||
},
|
||||
Native::Unsharded {
|
||||
@@ -848,13 +910,136 @@ impl From<lancedb::table::LsmWriteSpec> for LsmWriteSpec {
|
||||
spec_type: "unsharded".to_string(),
|
||||
column: None,
|
||||
num_buckets: None,
|
||||
maintained_indexes: Some(maintained_indexes),
|
||||
maintained_indexes,
|
||||
writer_config_defaults: Some(writer_config_defaults),
|
||||
},
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// One flushed L0 generation.
|
||||
#[napi(object)]
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct GenerationStats {
|
||||
/// The generation number. Increases as memtables are sealed into L0.
|
||||
pub generation: i64,
|
||||
/// On-disk size of the generation.
|
||||
pub bytes: i64,
|
||||
/// Present only when `includeGenerationRows` was requested. Off by default
|
||||
/// because each count opens an uncached Lance dataset.
|
||||
pub rows: Option<i64>,
|
||||
}
|
||||
|
||||
impl From<lancedb::table::GenerationStats> for GenerationStats {
|
||||
fn from(g: lancedb::table::GenerationStats) -> Self {
|
||||
Self {
|
||||
generation: g.generation as i64,
|
||||
bytes: g.bytes as i64,
|
||||
rows: g.rows.map(|r| r as i64),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// One in-memory memtable.
|
||||
#[napi(object)]
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct MemtableStats {
|
||||
/// The generation this memtable will become once sealed.
|
||||
pub generation: i64,
|
||||
/// Rows currently buffered.
|
||||
pub rows: i64,
|
||||
/// Estimated in-memory size.
|
||||
pub bytes: i64,
|
||||
/// Record batches currently buffered.
|
||||
pub batches: i64,
|
||||
/// Names of the indexes this memtable carries. An absent name is the whole
|
||||
/// answer to "why is my fresh-tier search on that column brute-force".
|
||||
pub indexes: Vec<String>,
|
||||
}
|
||||
|
||||
impl From<lancedb::table::MemtableStats> for MemtableStats {
|
||||
fn from(m: lancedb::table::MemtableStats) -> Self {
|
||||
Self {
|
||||
generation: m.generation as i64,
|
||||
rows: m.rows as i64,
|
||||
bytes: m.bytes as i64,
|
||||
batches: m.batches as i64,
|
||||
indexes: m.indexes,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Live state of one bucket. A table is N buckets on one node; flattening to a
|
||||
/// single number hides the one hot bucket that is usually why someone opened
|
||||
/// this endpoint.
|
||||
#[napi(object)]
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct BucketStats {
|
||||
/// The shard this bucket writes.
|
||||
pub shard_id: String,
|
||||
/// `"Active"` or `"Sealed"` (drop-table 2PC in flight).
|
||||
pub status: String,
|
||||
/// Epoch of the writer that currently owns the shard.
|
||||
pub writer_epoch: i64,
|
||||
/// Version of the shard manifest these numbers were read from.
|
||||
pub manifest_version: i64,
|
||||
/// The generation the active memtable will become.
|
||||
pub current_generation: i64,
|
||||
/// WAL position replay resumes from.
|
||||
pub replay_after_wal_entry_position: i64,
|
||||
/// Highest WAL position the writer has seen. The difference against
|
||||
/// `replayAfterWalEntryPosition` is the WAL lag.
|
||||
pub wal_entry_position_last_seen: i64,
|
||||
/// Flushed L0 generations not yet merged into the base table.
|
||||
pub generations: Vec<GenerationStats>,
|
||||
/// Whether a pass owns this bucket's compaction latch right now. Says *a*
|
||||
/// driver is running, not *whose*, and the latch is held from dispatch —
|
||||
/// including while the pass queues for a pod-wide compactor permit. Read it
|
||||
/// as "do not pile on", never as "mine is progressing".
|
||||
pub compacting: bool,
|
||||
/// Oldest first, active last. Absent for a `"Sealed"` bucket, whose
|
||||
/// in-memory state is torn down.
|
||||
pub memtables: Option<Vec<MemtableStats>>,
|
||||
}
|
||||
|
||||
impl From<lancedb::table::BucketStats> for BucketStats {
|
||||
fn from(b: lancedb::table::BucketStats) -> Self {
|
||||
Self {
|
||||
shard_id: b.shard_id,
|
||||
status: b.status,
|
||||
writer_epoch: b.writer_epoch as i64,
|
||||
manifest_version: b.manifest_version as i64,
|
||||
current_generation: b.current_generation as i64,
|
||||
replay_after_wal_entry_position: b.replay_after_wal_entry_position as i64,
|
||||
wal_entry_position_last_seen: b.wal_entry_position_last_seen as i64,
|
||||
generations: b.generations.into_iter().map(Into::into).collect(),
|
||||
compacting: b.compacting,
|
||||
memtables: b
|
||||
.memtables
|
||||
.map(|ms| ms.into_iter().map(Into::into).collect()),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Live per-bucket LSM state, as returned by `Table#getLsmStats`.
|
||||
///
|
||||
/// Nothing here is derived: sums and differences (total L0 bytes, WAL lag) are
|
||||
/// the caller's to compute.
|
||||
#[napi(object)]
|
||||
#[derive(Clone, Debug)]
|
||||
pub struct LsmStats {
|
||||
/// One entry per bucket backing this table.
|
||||
pub buckets: Vec<BucketStats>,
|
||||
}
|
||||
|
||||
impl From<lancedb::table::LsmStats> for LsmStats {
|
||||
fn from(stats: lancedb::table::LsmStats) -> Self {
|
||||
Self {
|
||||
buckets: stats.buckets.into_iter().map(Into::into).collect(),
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// Statistics about a compaction operation.
|
||||
#[napi(object)]
|
||||
#[derive(Clone, Debug)]
|
||||
@@ -1043,7 +1228,10 @@ impl From<lancedb::index::IndexStatistics> for IndexStatistics {
|
||||
|
||||
#[napi(object)]
|
||||
pub struct TableStatistics {
|
||||
/// The total number of bytes in the table
|
||||
/// The total size, in bytes, of the table's data files, index files, and
|
||||
/// overlay files
|
||||
///
|
||||
/// Read from the manifest, so this excludes deletion files and manifests.
|
||||
pub total_bytes: i64,
|
||||
|
||||
/// The number of rows in the table
|
||||
@@ -1193,6 +1381,21 @@ pub struct AddColumnsResult {
|
||||
pub version: i64,
|
||||
}
|
||||
|
||||
#[napi(object)]
|
||||
pub struct RefreshColumnResult {
|
||||
pub rows_filled: i64,
|
||||
pub version: i64,
|
||||
}
|
||||
|
||||
impl From<lancedb::table::RefreshColumnResult> for RefreshColumnResult {
|
||||
fn from(value: lancedb::table::RefreshColumnResult) -> Self {
|
||||
Self {
|
||||
rows_filled: value.rows_filled as i64,
|
||||
version: value.version as i64,
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
impl From<lancedb::table::AddColumnsResult> for AddColumnsResult {
|
||||
fn from(value: lancedb::table::AddColumnsResult) -> Self {
|
||||
Self {
|
||||
|
||||
Reference in New Issue
Block a user