Files
lancedb/nodejs/lancedb/table.ts
T
lancedb-gatefixer[bot]andXuanwo 35b5d015ac fix(node): preserve embedding registration in server bundles (#3806)
## Summary

- lazily initialize built-in OpenAI and Hugging Face providers when
consumers call the public embedding registry API
- choose automatic vector versus FTS search from embedding metadata on a
fresh pinned table revision for every execution
- expose automatic string searches as an `AutoQuery` with only
operations common to both native query families
- keep the registry shared and built-in registration safe across
duplicated module graphs

## Root cause

Nitro treats dependency modules as side-effect-free and removes the bare
OpenAI provider import from its generated route. Registration therefore
never runs, so `getRegistry().get("openai")` remains undefined even when
the registry itself is shared globally. Bundlers may also duplicate the
provider and registry module graphs.

The public embedding entry point now initializes built-in providers only
when `getRegistry()` is explicitly called, keeping initialization on a
live path that Nitro retains. Each terminal automatic-search execution
pins the exact table revision visible at dispatch, reads embedding
metadata and computes an embedding from that snapshot, replays the
builder operations, and constructs and executes the selected native
query against the same snapshot. Pinned native snapshots execute locally
when namespace pushdown cannot carry their revision, while remote
snapshots are seeded directly from one version-and-schema response. The
public `AutoQuery` builder exposes only the operations shared by FTS and
vector search, so runtime class narrowing cannot expose invalid
vector-only methods. Repeated built-in registration replaces stale
constructors from duplicated module graphs while public `register()`
retains its duplicate-alias error.

## Validation

- `cargo fmt --all`
- `cargo check --quiet --features remote --tests --examples`
- `cargo clippy --quiet --features remote --tests --examples`
- `pnpm build`
- `pnpm lint`
- `pnpm run docs`
- `pnpm test --runInBand` (783 passed, 5 skipped)
- serial examples suite with a local OpenAI mock (11 passed), including
`sentence-transformers.test.ts`
- packaged Nitro 2.13.4 server route using the reported imports returned
`{"registered":true}`
- fresh-process FTS fixture initialized both public built-ins and
confirmed automatic string search still returned the indexed row
- schema-consistency regressions cover read-consistency refresh,
checkout, checkoutLatest, restore, runtime class narrowing, concurrent
overwrite during embedding computation, and reused automatic-search
builders
- focused regressions confirm pinned native snapshots bypass unversioned
namespace pushdown and remote snapshots use one describe request

Fixes #2429

<!-- lance-gatekeeper-fix:v1 agent=2adf0f21b8bfb634606ed8897a849e30
generation=1 -->

---------

Co-authored-by: Gatefixer <313497061+lancedb-gatefixer[bot]@users.noreply.github.com>
Co-authored-by: Xuanwo <github@xuanwo.io>
2026-08-26 04:17:32 +08:00

1714 lines
56 KiB
TypeScript

// SPDX-License-Identifier: Apache-2.0
// SPDX-FileCopyrightText: Copyright The LanceDB Authors
import {
Table as ArrowTable,
Data,
DataType,
Field,
IntoVector,
MultiVector,
Schema,
dataTypeToJson,
fromDataToBuffer,
fromTableToBuffer,
isMultiVector,
makeEmptyTable,
tableFromIPC,
} from "./arrow";
import { EmbeddingFunctionConfig, getRegistry } from "./embedding/registry";
import { IndexOptions } from "./indices";
import { MergeInsertBuilder } from "./merge";
import {
AddColumnsResult,
AddColumnsSql,
AddResult,
AlterColumnsResult,
BranchContents,
DeleteResult,
DropColumnsResult,
IndexConfig,
IndexStatistics,
Job,
LsmStats,
Branches as NativeBranches,
OptimizeStats,
RefreshColumnResult,
RefreshMaterializedViewResult,
TableStatistics,
Tags,
UpdateFieldMetadataResult,
UpdateResult,
Table as _NativeTable,
} from "./native";
import {
AutoQuery,
FullTextQuery,
Query,
TakeQuery,
VectorQuery,
instanceOfFullTextQuery,
} from "./query";
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`
* callback passed to {@link Table.add}.
*/
export interface WriteProgress {
/** Number of rows written so far. */
outputRows: number;
/** Number of bytes written so far. */
outputBytes: number;
/**
* Total rows expected, when the input source reports it.
*
* Always set on the final callback (the one with `done: true`), falling
* back to the actual number of rows written when the source could not
* report a row count up front.
*/
totalRows?: number;
/** Wall-clock seconds since the write started. */
elapsedSeconds: number;
/** Number of parallel write tasks currently in flight. */
activeTasks: number;
/** Total number of parallel write tasks (the write parallelism). */
totalTasks: number;
/** `true` for the final callback; `false` otherwise. */
done: boolean;
}
/**
* Options for adding data to a table.
*/
export interface AddDataOptions {
/**
* If "append" (the default) then the new data will be added to the table
*
* If "overwrite" then the new data will replace the existing data in the table.
*/
mode: "append" | "overwrite";
/**
* Optional callback invoked periodically with write progress.
*
* The callback is fired once per batch written and once more with
* `done: true` when the write completes. Calls are dispatched
* asynchronously to the JS event loop and never block the write — a slow
* callback will queue events rather than back-pressure the writer.
*
* Errors thrown from the callback are logged with `console.warn` and
* swallowed — they do not abort the write.
*
* @example
* ```ts
* await table.add(data, {
* progress: (p) => {
* console.log(`${p.outputRows}/${p.totalRows ?? "?"} rows`);
* },
* });
* ```
*/
progress: (progress: WriteProgress) => void;
}
export interface UpdateOptions {
/**
* A filter that limits the scope of the update.
*
* This should be an SQL filter expression.
*
* Only rows that satisfy the expression will be updated.
*
* For example, this could be 'my_col == 0' to replace all instances
* of 0 in a column with some other default value.
*/
where: string;
}
export interface OptimizeOptions {
/**
* If set then all versions older than the given date
* be removed. The current version will never be removed.
* The default is 7 days
* @example
* // Delete all versions older than 1 day
* const olderThan = new Date();
* olderThan.setDate(olderThan.getDate() - 1));
* tbl.optimize({cleanupOlderThan: olderThan});
*
* // Delete all versions except the current version
* tbl.optimize({cleanupOlderThan: new Date()});
*/
cleanupOlderThan: Date;
/**
* Because they may be part of an in-progress transaction, files newer than
* 7 days old are not deleted by default. If you are sure that there are no
* in-progress transactions, then you can set this to true to delete all
* files older than `cleanupOlderThan`.
*
* **WARNING**: This should only be set to true if you can guarantee that
* no other process is currently working on this dataset. Otherwise the
* dataset could be put into a corrupted state.
*/
deleteUnverified: boolean;
}
export interface Version {
version: number;
timestamp: Date;
metadata: Record<string, string>;
}
/** Token produced by the tokenizer configured on a full-text search index. */
export interface FtsToken {
/** Token text after tokenizer filters have been applied. */
text: string;
/** Token position used by full-text query matching. */
position: number;
}
export type TokenizeTableOptions =
| {
/** FTS-indexed column whose tokenizer should be used. */
column: string;
indexName?: never;
}
| {
/** Name of the FTS index whose tokenizer should be used. */
indexName: string;
column?: never;
};
/**
* Specification selecting Lance's MemWAL LSM-style write path for
* `mergeInsert`.
*
* `specType` is `"bucket"`, `"identity"`, or `"unsharded"`. For `"bucket"`,
* `column` and `numBuckets` are required; for `"identity"`, `column` is
* required and must be a deterministic function of the unenforced primary
* key (every row with a given primary key must always produce the same
* `column` value, or upserts of that key can land in different shards and a
* stale version can win).
*/
export interface LsmWriteSpec {
/** One of `"bucket"`, `"identity"`, or `"unsharded"`. */
specType: "bucket" | "identity" | "unsharded";
/** Bucket and identity variants: the sharding column. */
column?: string;
/** Bucket variant: the number of buckets, in `[1, 1024]`. */
numBuckets?: number;
/**
* 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>;
}
/**
* A Table is a collection of Records in a LanceDB Database.
*
* A Table object is expected to be long lived and reused for multiple operations.
* Table objects will cache a certain amount of index data in memory. This cache
* will be freed when the Table is garbage collected. To eagerly free the cache you
* can call the `close` method. Once the Table is closed, it cannot be used for any
* further operations.
*
* Tables are created using the methods {@link Connection#createTable}
* and {@link Connection#createEmptyTable}. Existing tables are opened
* using {@link Connection#openTable}.
*
* Closing a table is optional. It not closed, it will be closed when it is garbage
* collected.
*
* @hideconstructor
*/
export abstract class Table {
[Symbol.for("nodejs.util.inspect.custom")](): string {
return this.display();
}
/** Returns the name of the table */
abstract get name(): string;
/** Return true if the table has not been closed */
abstract isOpen(): boolean;
/**
* Close the table, releasing any underlying resources.
*
* It is safe to call this method multiple times.
*
* Any attempt to use the table after it is closed will result in an error.
*/
abstract close(): void;
/** Return a brief description of the table */
abstract display(): string;
/** Get the schema of the table. */
abstract schema(): Promise<Schema>;
/**
* Insert records into this Table.
* @param {Data} data Records to be inserted into the Table
* @returns {Promise<AddResult>} A promise that resolves to an object
* containing the new version number of the table
*/
abstract add(
data: Data,
options?: Partial<AddDataOptions>,
): Promise<AddResult>;
/**
* Update existing records in the Table
* @param opts.values The values to update. The keys are the column names and the values
* are the values to set.
* @returns {Promise<UpdateResult>} A promise that resolves to an object containing
* the number of rows updated and the new version number
* @example
* ```ts
* table.update({where:"x = 2", values:{"vector": [10, 10]}})
* ```
*/
abstract update(
opts: {
values: Map<string, IntoSql> | Record<string, IntoSql>;
} & Partial<UpdateOptions>,
): Promise<UpdateResult>;
/**
* Update existing records in the Table
* @param opts.valuesSql The values to update. The keys are the column names and the values
* are the values to set. The values are SQL expressions.
* @returns {Promise<UpdateResult>} A promise that resolves to an object containing
* the number of rows updated and the new version number
* @example
* ```ts
* table.update({where:"x = 2", valuesSql:{"x": "x + 1"}})
* ```
*/
abstract update(
opts: {
valuesSql: Map<string, string> | Record<string, string>;
} & Partial<UpdateOptions>,
): Promise<UpdateResult>;
/**
* Update existing records in the Table
*
* An update operation can be used to adjust existing values. Use the
* returned builder to specify which columns to update. The new value
* can be a literal value (e.g. replacing nulls with some default value)
* or an expression applied to the old value (e.g. incrementing a value)
*
* An optional condition can be specified (e.g. "only update if the old
* value is 0")
*
* Note: if your condition is something like "some_id_column == 7" and
* you are updating many rows (with different ids) then you will get
* better performance with a single [`merge_insert`] call instead of
* repeatedly calilng this method.
* @param {Map<string, string> | Record<string, string>} updates - the
* columns to update
* @returns {Promise<UpdateResult>} A promise that resolves to an object
* containing the number of rows updated and the new version number
*
* Keys in the map should specify the name of the column to update.
* Values in the map provide the new value of the column. These can
* be SQL literal strings (e.g. "7" or "'foo'") or they can be expressions
* based on the row being updated (e.g. "my_col + 1")
* @param {Partial<UpdateOptions>} options - additional options to control
* the update behavior
*/
abstract update(
updates: Map<string, string> | Record<string, string>,
options?: Partial<UpdateOptions>,
): Promise<UpdateResult>;
/** Count the total number of rows in the dataset. */
abstract countRows(filter?: string): Promise<number>;
/**
* Delete the rows that satisfy the predicate.
* @returns {Promise<DeleteResult>} A promise that resolves to an object
* containing the new version number of the table
*/
abstract delete(predicate: string): Promise<DeleteResult>;
/**
* Create an index to speed up queries.
*
* Indices can be created on vector columns or scalar columns.
* Indices on vector columns will speed up vector searches.
* Indices on scalar columns will speed up filtering (in both
* vector and non-vector searches)
*
* We currently don't support custom named indexes.
* The index name will always be `${column}_idx`.
*
* @example
* // If the column has a vector (fixed size list) data type then
* // an IvfPq vector index will be created.
* const table = await conn.openTable("my_table");
* await table.createIndex("vector");
* @example
* // For advanced control over vector index creation you can specify
* // the index type and options.
* const table = await conn.openTable("my_table");
* await table.createIndex("vector", {
* config: lancedb.Index.ivfPq({
* numPartitions: 128,
* numSubVectors: 16,
* }),
* });
* @example
* // Or create a Scalar index
* await table.createIndex("my_float_col");
*/
abstract createIndex(
column: string,
options?: Partial<IndexOptions>,
): Promise<void>;
/**
* Create an index, returning a handle to the indexing job.
*
* The job may already be complete when returned; callers must not assume
* the index exists until {@link Job.wait} resolves.
*/
abstract createIndexAsync(
column: string,
options?: Partial<IndexOptions>,
): Promise<Job>;
/**
* Drop an index from the table.
*
* @param name The name of the index.
*
* This does not delete the index from disk, it just removes it from the table.
* To delete the index, run {@link Table#optimize} after dropping the index.
*
* Use {@link Table.listIndices} to find the names of the indices.
*/
abstract dropIndex(name: string): Promise<void>;
/**
* Prewarm an index in the table.
*
* @param name The name of the index.
*
* This will load the index into memory. This may reduce the cold-start time for
* future queries. If the index does not fit in the cache then this call may be
* wasteful.
*/
abstract prewarmIndex(name: string): Promise<void>;
/**
* Prewarm one or more columns of data in the table.
*
* @param columns The columns to prewarm. If undefined, all columns are prewarmed.
*
* This will load the column data into the page cache so that future queries that
* read those columns avoid the initial cold-start latency. This call initiates
* prewarming and returns once the request is accepted; the warming itself may
* continue in the background. Calling it on already-prewarmed columns is a
* no-op on the server.
*
* Prewarming is generally useful for columns used in filters or projections.
* Large columns (e.g. high-dimensional vectors or binary data) may not be
* practical to prewarm.
*
* This feature is currently only supported on remote tables.
*/
abstract prewarmData(columns?: string[]): Promise<void>;
/**
* Waits for asynchronous indexing to complete on the table.
*
* @param indexNames The name of the indices to wait for
* @param timeoutSeconds The number of seconds to wait before timing out
*
* This will raise an error if the indices are not created and fully indexed within the timeout.
*/
abstract waitForIndex(
indexNames: string[],
timeoutSeconds: number,
): Promise<void>;
/**
* Create a {@link Query} Builder.
*
* Queries allow you to search your existing data. By default the query will
* return all the data in the table in no particular order. The builder
* returned by this method can be used to control the query using filtering,
* vector similarity, sorting, and more.
*
* Note: By default, all columns are returned. For best performance, you should
* only fetch the columns you need.
*
* When appropriate, various indices and statistics based pruning will be used to
* accelerate the query.
* @example
* // SQL-style filtering
* //
* // This query will return up to 1000 rows whose value in the `id` column
* // is greater than 5. LanceDb supports a broad set of filtering functions.
* for await (const batch of table
* .query()
* .where("id > 1")
* .select(["id"])
* .limit(20)) {
* console.log(batch);
* }
* @example
* // Vector Similarity Search
* //
* // This example will find the 10 rows whose value in the "vector" column are
* // closest to the query vector [1.0, 2.0, 3.0]. If an index has been created
* // on the "vector" column then this will perform an ANN search.
* //
* // The `refineFactor` and `nprobes` methods are used to control the recall /
* // latency tradeoff of the search.
* for await (const batch of table
* .query()
* .where("id > 1")
* .select(["id"])
* .limit(20)) {
* console.log(batch);
* }
* @example
* // Scan the full dataset
* //
* // This query will return everything in the table in no particular order.
* for await (const batch of table.query()) {
* console.log(batch);
* }
* @returns {Query} A builder that can be used to parameterize the query
*/
abstract query(): Query;
/**
* Create a query that returns a subset of the rows in the table.
* @param offsets The offsets of the rows to return.
* @returns A builder that can be used to parameterize the query.
*/
abstract takeOffsets(offsets: number[]): TakeQuery;
/**
* Create a query that returns a subset of the rows in the table.
* @param rowIds The row ids of the rows to return.
*
* Row ids returned by `withRowId()` are `bigint`, so `bigint[]` is supported.
* For convenience / backwards compatibility, `number[]` is also accepted (for
* small row ids that fit in a safe integer).
* @returns A builder that can be used to parameterize the query.
*/
abstract takeRowIds(rowIds: readonly (bigint | number)[]): TakeQuery;
/**
* Create a search query to find the nearest neighbors
* of the given query
* @param {string | IntoVector} query - the query, a vector or string
* @param {string} queryType - the type of the query, "vector", "fts", or "auto"
* @param {string | string[]} ftsColumns - the columns to search in for full text search
* for now, only one column can be searched at a time.
*
* when "auto" is used, if the query is a string and an embedding function is defined, it will be treated as a vector query
* if the query is a string and no embedding function is defined, it will be treated as a full text search query
*/
abstract search(
query: string | IntoVector | MultiVector | FullTextQuery,
queryType?: string,
ftsColumns?: string | string[],
): VectorQuery | Query | AutoQuery;
/**
* Search the table with a given query vector.
*
* This is a convenience method for preparing a vector query and
* is the same thing as calling `nearestTo` on the builder returned
* by `query`. @see {@link Query#nearestTo} for more details.
*/
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
| { 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>;
/**
* Recompute this table's contents from its materialized-view definition.
*
* Plumbing for {@link MaterializedView.refresh}, which is the way to call
* it: rejects tables that carry no view definition. Local tables only.
* @ignore
*/
abstract refreshMaterializedView(
full?: boolean,
sourceVersion?: number,
): Promise<RefreshMaterializedViewResult>;
/**
* Alter the name or nullability of columns.
* @param {ColumnAlteration[]} columnAlterations One or more alterations to
* apply to columns.
* @returns {Promise<AlterColumnsResult>} A promise that resolves to an object
* containing the new version number of the table after altering the columns.
*/
abstract alterColumns(
columnAlterations: ColumnAlteration[],
): Promise<AlterColumnsResult>;
/**
* Update per-field (column) metadata.
* @param {FieldMetadataUpdate[]} updates One or more per-field updates. Each
* update's metadata is merged into the field's existing metadata by default;
* a value of `null` deletes that key, and `replace: true` swaps the whole map.
* @returns {Promise<UpdateFieldMetadataResult>} resolves to the new table version.
*/
abstract updateFieldMetadata(
updates: FieldMetadataUpdate[],
): Promise<UpdateFieldMetadataResult>;
/**
* Drop one or more columns from the dataset
*
* This is a metadata-only operation and does not remove the data from the
* underlying storage. In order to remove the data, you must subsequently
* call ``compact_files`` to rewrite the data without the removed columns and
* then call ``cleanup_files`` to remove the old files.
* @param {string[]} columnNames The names of the columns to drop. These can
* be nested column references (e.g. "a.b.c") or top-level column names
* (e.g. "a").
* @returns {Promise<DropColumnsResult>} A promise that resolves to an object
* containing the new version number of the table after dropping the columns.
*/
abstract dropColumns(columnNames: string[]): Promise<DropColumnsResult>;
/**
* Set the unenforced primary key for this table to a single column.
*
* "Unenforced" means LanceDB does not check uniqueness on writes; the
* column is recorded in the schema as the primary key for use by features
* such as `merge_insert`. Only single-column primary keys are supported,
* and the key cannot be changed once set.
* @param {string | string[]} columns The primary key column. A one-element
* array is also accepted; passing more than one column is rejected.
* @returns {Promise<void>}
*/
abstract setUnenforcedPrimaryKey(columns: string | string[]): Promise<void>;
/**
* Install an {@link LsmWriteSpec} on this table, selecting Lance's MemWAL
* LSM-style write path for future `mergeInsert` calls.
*
* `LsmWriteSpec` chooses one of three sharding strategies via `specType`:
*
* - `"bucket"` — hash-bucket writes by the single-column unenforced primary
* key (`column` and `numBuckets` required).
* - `"identity"` — shard by the raw value of a scalar `column`.
* - `"unsharded"` — route every write to a single shard.
*
* 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
* ```ts
* await table.setUnenforcedPrimaryKey("id");
* await table.setLsmWriteSpec({
* specType: "bucket",
* column: "id",
* numBuckets: 16,
* maintainedIndexes: ["id_idx"],
* });
* ```
*/
abstract setLsmWriteSpec(spec: LsmWriteSpec): Promise<void>;
/**
* Remove the {@link LsmWriteSpec} from this table, reverting to the standard
* `mergeInsert` write path.
*
* Errors if no spec is currently set.
* @returns {Promise<void>}
*/
abstract unsetLsmWriteSpec(): Promise<void>;
/**
* Read the {@link LsmWriteSpec} currently installed on this 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 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>;
/**
* Drain and close any cached MemWAL shard writers held for this table.
*
* When an {@link LsmWriteSpec} is installed, `mergeInsert` opens MemWAL
* shard writers and caches them for reuse across calls. This closes them,
* flushing pending data; writers reopen lazily on the next `mergeInsert`.
* It is a no-op when no writers are cached.
* @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>;
/**
* Checks out a specific version of the table _This is an in-place operation._
*
* This allows viewing previous versions of the table. If you wish to
* keep writing to the dataset starting from an old version, then use
* the `restore` function.
*
* Calling this method will set the table into time-travel mode. If you
* wish to return to standard mode, call `checkoutLatest`.
* @param {number | string} version The version to checkout, could be version number or tag
* @example
* ```typescript
* import * as lancedb from "@lancedb/lancedb"
* const db = await lancedb.connect("./.lancedb");
* const table = await db.createTable("my_table", [
* { vector: [1.1, 0.9], type: "vector" },
* ]);
*
* console.log(await table.version()); // 1
* console.log(table.display());
* await table.add([{ vector: [0.5, 0.2], type: "vector" }]);
* await table.checkout(1);
* console.log(await table.version()); // 2
* ```
*/
abstract checkout(version: number | string): Promise<void>;
/**
* Checkout the latest version of the table. _This is an in-place operation._
*
* The table will be set back into standard mode, and will track the latest
* version of the table.
*/
abstract checkoutLatest(): Promise<void>;
/**
* List all the versions of the table
*/
abstract listVersions(): Promise<Version[]>;
/**
* Get a tags manager for this table.
*
* Tags allow you to label specific versions of a table with a human-readable name.
* The returned tags manager can be used to list, create, update, or delete tags.
*
* @returns {Tags} A tags manager for this table
* @example
* ```typescript
* const tagsManager = await table.tags();
* await tagsManager.create("v1", 1);
* const tags = await tagsManager.list();
* console.log(tags); // { "v1": { version: 1, manifestSize: ... } }
* ```
*/
abstract tags(): Promise<Tags>;
/**
* Get the branch manager for this table.
*
* Branches are isolated, writable lines of history forked from another
* branch (or version). Writes on a branch do not affect `main`.
*/
abstract branches(): Promise<Branches>;
/**
* The branch this table handle is scoped to, or `null` for the main branch.
*
* A handle returned by {@link Branches.create} or {@link Branches.checkout}
* reports the branch it targets; a handle opened normally reports `null`.
*/
abstract currentBranch(): string | null;
/**
* Restore the table to the currently checked out version
*
* This operation will fail if checkout has not been called previously
*
* This operation will overwrite the latest version of the table with a
* previous version. Any changes made since the checked out version will
* no longer be visible.
*
* Once the operation concludes the table will no longer be in a checked
* out state and the read_consistency_interval, if any, will apply.
*/
abstract restore(): Promise<void>;
/**
* Optimize the on-disk data and indices for better performance.
*
* Modeled after ``VACUUM`` in PostgreSQL.
*
* Optimization covers three operations:
*
* - Compaction: Merges small files into larger ones
* - Prune: Removes old versions of the dataset
* - Index: Optimizes the indices, adding new data to existing indices
*
*
* The frequency an application should call optimize is based on the frequency of
* data modifications. If data is frequently added, deleted, or updated then
* optimize should be run frequently. A good rule of thumb is to run optimize if
* you have added or modified 100,000 or more records or run more than 20 data
* modification operations.
*/
abstract optimize(options?: Partial<OptimizeOptions>): Promise<OptimizeStats>;
/** List all indices that have been created with {@link Table.createIndex} */
abstract listIndices(): Promise<IndexConfig[]>;
/**
* Tokenize a full-text search query using the tokenizer configured on an FTS index.
*
* Specify exactly one of `column` or `indexName`.
*
* Model-backed tokenizers such as `jieba/*` and `lindera/*` are rebuilt in
* the client process from index metadata. For remote tables, this means the
* same tokenizer model files must also exist locally.
*/
abstract tokenize(
query: string,
options: TokenizeTableOptions,
): Promise<FtsToken[]>;
/** Return the table as an arrow table */
abstract toArrow(): Promise<ArrowTable>;
abstract mergeInsert(on: string | string[]): MergeInsertBuilder;
/** List all the stats of a specified index
*
* @param {string} name The name of the index.
* @returns {IndexStatistics | undefined} The stats of the index. If the index does not exist, it will return undefined
*
* Use {@link Table.listIndices} to find the names of the indices.
*/
abstract indexStats(name: string): Promise<IndexStatistics | undefined>;
/** Returns table and fragment statistics
*
* @returns {TableStatistics} The table and fragment statistics
*
*/
abstract stats(): Promise<TableStatistics>;
/**
* Get the initial storage options that were passed in when opening this table.
*
* For dynamically refreshed options (e.g., credential vending), use
* {@link Table.latestStorageOptions}.
*
* Warning: This is an internal API and the return value is subject to change.
*
* @returns The storage options, or undefined if no storage options were configured.
*/
abstract initialStorageOptions(): Promise<
Record<string, string> | null | undefined
>;
/**
* Get the latest storage options, refreshing from provider if configured.
*
* This method is useful for credential vending scenarios where storage options
* may be refreshed dynamically. If no dynamic provider is configured, this
* returns the initial static options.
*
* Warning: This is an internal API and the return value is subject to change.
*
* @returns The storage options, or undefined if no storage options were configured.
*/
abstract latestStorageOptions(): Promise<
Record<string, string> | null | undefined
>;
}
export class LocalTable extends Table {
private readonly inner: _NativeTable;
constructor(inner: _NativeTable) {
super();
this.inner = inner;
}
get name(): string {
return this.inner.name;
}
isOpen(): boolean {
return this.inner.isOpen();
}
close(): void {
this.inner.close();
}
display(): string {
return this.inner.display();
}
private async getEmbeddingFunctions(
inner: _NativeTable = this.inner,
): Promise<Map<string, EmbeddingFunctionConfig>> {
const schemaBuf = await inner.schema();
const schema = tableFromIPC(schemaBuf).schema;
const registry = getRegistry();
return registry.parseFunctions(schema.metadata);
}
/** Get the schema of the table. */
async schema(): Promise<Schema> {
const schemaBuf = await this.inner.schema();
const tbl = tableFromIPC(schemaBuf);
return tbl.schema;
}
async add(data: Data, options?: Partial<AddDataOptions>): Promise<AddResult> {
const mode = options?.mode ?? "append";
const schema = await this.schema();
const buffer = await fromDataToBuffer(data, undefined, schema);
// Wrap the user callback so a thrown error doesn't surface as an
// unhandled exception (the callback fires from a napi threadsafe
// function — exceptions there crash the process).
const userProgress = options?.progress;
const progress = userProgress
? (p: WriteProgress) => {
try {
userProgress(p);
} catch (e) {
console.warn("Table.add progress callback threw:", e);
}
}
: undefined;
return await this.inner.add(buffer, mode, progress);
}
async update(
optsOrUpdates:
| (Map<string, string> | Record<string, string>)
| ({
values: Map<string, IntoSql> | Record<string, IntoSql>;
} & Partial<UpdateOptions>)
| ({
valuesSql: Map<string, string> | Record<string, string>;
} & Partial<UpdateOptions>),
options?: Partial<UpdateOptions>,
): Promise<UpdateResult> {
const isValues =
"values" in optsOrUpdates && typeof optsOrUpdates.values !== "string";
const isValuesSql =
"valuesSql" in optsOrUpdates &&
typeof optsOrUpdates.valuesSql !== "string";
const isMap = (obj: unknown): obj is Map<string, string> => {
return obj instanceof Map;
};
let predicate;
let columns: [string, string][];
switch (true) {
case isMap(optsOrUpdates):
columns = Array.from(optsOrUpdates.entries());
predicate = options?.where;
break;
case isValues && isMap(optsOrUpdates.values):
columns = Array.from(optsOrUpdates.values.entries()).map(([k, v]) => [
k,
toSQL(v),
]);
predicate = optsOrUpdates.where;
break;
case isValues && !isMap(optsOrUpdates.values):
columns = Object.entries(optsOrUpdates.values).map(([k, v]) => [
k,
toSQL(v),
]);
predicate = optsOrUpdates.where;
break;
case isValuesSql && isMap(optsOrUpdates.valuesSql):
columns = Array.from(optsOrUpdates.valuesSql.entries());
predicate = optsOrUpdates.where;
break;
case isValuesSql && !isMap(optsOrUpdates.valuesSql):
columns = Object.entries(optsOrUpdates.valuesSql).map(([k, v]) => [
k,
v,
]);
predicate = optsOrUpdates.where;
break;
default:
columns = Object.entries(optsOrUpdates as Record<string, string>);
predicate = options?.where;
}
return await this.inner.update(predicate, columns);
}
async countRows(filter?: string): Promise<number> {
return await this.inner.countRows(filter);
}
async delete(predicate: string): Promise<DeleteResult> {
return await this.inner.delete(predicate);
}
async createIndex(column: string, options?: Partial<IndexOptions>) {
// Bit of a hack to get around the fact that TS has no package-scope.
// biome-ignore lint/suspicious/noExplicitAny: skip
const nativeIndex = (options?.config as any)?.inner;
await this.inner.createIndex(
nativeIndex,
column,
options?.replace,
options?.waitTimeoutSeconds,
options?.name,
options?.train,
);
}
async createIndexAsync(
column: string,
options?: Partial<IndexOptions>,
): Promise<Job> {
// biome-ignore lint/suspicious/noExplicitAny: skip
const nativeIndex = (options?.config as any)?.inner;
return await this.inner.createIndexAsync(
nativeIndex,
column,
options?.replace,
options?.waitTimeoutSeconds,
options?.name,
options?.train,
);
}
async dropIndex(name: string): Promise<void> {
await this.inner.dropIndex(name);
}
async prewarmIndex(name: string): Promise<void> {
await this.inner.prewarmIndex(name);
}
async prewarmData(columns?: string[]): Promise<void> {
await this.inner.prewarmData(columns);
}
async waitForIndex(
indexNames: string[],
timeoutSeconds: number,
): Promise<void> {
await this.inner.waitForIndex(indexNames, timeoutSeconds);
}
takeOffsets(offsets: number[]): TakeQuery {
return new TakeQuery(this.inner.takeOffsets(offsets));
}
takeRowIds(rowIds: readonly (bigint | number)[]): TakeQuery {
const ids = rowIds.map((id) => {
if (typeof id === "bigint") {
return id;
}
if (!Number.isInteger(id)) {
throw new Error("Row id must be an integer (or bigint)");
}
if (id < 0) {
throw new Error("Row id cannot be negative");
}
if (!Number.isSafeInteger(id)) {
throw new Error("Row id is too large for number; use bigint instead");
}
return BigInt(id);
});
return new TakeQuery(this.inner.takeRowIds(ids));
}
query(): Query {
return new Query(this.inner);
}
search(
query: string | IntoVector | MultiVector | FullTextQuery,
queryType: string = "auto",
ftsColumns?: string | string[],
): VectorQuery | Query | AutoQuery {
if (typeof query !== "string" && !instanceOfFullTextQuery(query)) {
if (queryType === "fts") {
throw new Error("Cannot perform full text search on a vector query");
}
return this.vectorSearch(query);
}
// If the query is a string, we need to determine if it is a vector query or a full text search query
if (queryType === "fts") {
return this.query().fullTextSearch(query, {
columns: ftsColumns,
});
}
if (queryType === "auto" && typeof query !== "string") {
return this.query().fullTextSearch(query, {
columns: ftsColumns,
});
}
if (queryType === "auto" && typeof query === "string") {
const vector = async (snapshot: _NativeTable) => {
const functions = await this.getEmbeddingFunctions(snapshot);
// TODO: Support multiple embedding functions
const embeddingFunc: EmbeddingFunctionConfig | undefined = functions
.values()
.next().value;
if (embeddingFunc === undefined) {
return undefined;
}
return await embeddingFunc.function.computeQueryEmbeddings(query);
};
const columns =
typeof ftsColumns === "string" ? [ftsColumns] : ftsColumns;
return Query.autoSearch(
() => this.inner.checkoutCurrent(),
query,
vector,
columns,
);
}
const queryPromise = this.getEmbeddingFunctions().then(
async (functions) => {
// TODO: Support multiple embedding functions
const embeddingFunc: EmbeddingFunctionConfig | undefined = functions
.values()
.next().value;
if (!embeddingFunc) {
return Promise.reject(
new Error("No embedding functions are defined in the table"),
);
}
return await embeddingFunc.function.computeQueryEmbeddings(query);
},
);
return this.query().nearestTo(queryPromise);
}
vectorSearch(vector: IntoVector | MultiVector): VectorQuery {
if (isMultiVector(vector)) {
const query = this.query().nearestTo(vector[0]);
for (const v of vector.slice(1)) {
query.addQueryVector(v);
}
return query;
}
return this.query().nearestTo(vector);
}
// TODO: Support BatchUDF
async addColumns(
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];
}
// Handle array of Fields -> convert to Schema
if (
Array.isArray(newColumnTransforms) &&
newColumnTransforms.length > 0 &&
newColumnTransforms[0] instanceof Field
) {
const fields = newColumnTransforms as Field[];
newColumnTransforms = new Schema(fields);
}
// Handle Schema -> use schema-based approach
if (newColumnTransforms instanceof Schema) {
const schema = newColumnTransforms;
// Convert schema to buffer using Arrow IPC format
const emptyTable = makeEmptyTable(schema);
const schemaBuf = await fromTableToBuffer(emptyTable);
return await this.inner.addColumnsWithSchema(schemaBuf);
}
// Handle SQL expressions (existing functionality)
if (Array.isArray(newColumnTransforms)) {
return await this.inner.addColumns(
newColumnTransforms as AddColumnsSql[],
);
}
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 refreshMaterializedView(
full?: boolean,
sourceVersion?: number,
): Promise<RefreshMaterializedViewResult> {
return await this.inner.refreshMaterializedView(full, sourceVersion);
}
async alterColumns(
columnAlterations: ColumnAlteration[],
): Promise<AlterColumnsResult> {
const processedAlterations = columnAlterations.map((alteration) => {
if (typeof alteration.dataType === "string") {
return {
...alteration,
dataType: JSON.stringify({ type: alteration.dataType }),
};
} else if (alteration.dataType === undefined) {
return {
...alteration,
dataType: undefined,
};
} else {
const dataType = sanitizeType(alteration.dataType);
return {
...alteration,
dataType: JSON.stringify(dataTypeToJson(dataType)),
};
}
});
return await this.inner.alterColumns(processedAlterations);
}
async updateFieldMetadata(
updates: FieldMetadataUpdate[],
): Promise<UpdateFieldMetadataResult> {
return await this.inner.updateFieldMetadata(updates);
}
async dropColumns(columnNames: string[]): Promise<DropColumnsResult> {
return await this.inner.dropColumns(columnNames);
}
async setUnenforcedPrimaryKey(columns: string | string[]): Promise<void> {
const cols = typeof columns === "string" ? [columns] : columns;
return await this.inner.setUnenforcedPrimaryKey(cols);
}
async setLsmWriteSpec(spec: LsmWriteSpec): Promise<void> {
return await this.inner.setLsmWriteSpec(spec);
}
async unsetLsmWriteSpec(): Promise<void> {
return await this.inner.unsetLsmWriteSpec();
}
async getLsmWriteSpec(): Promise<LsmWriteSpec | undefined> {
// The native binding types `specType` as a plain `string`; narrow it back
// to the public union. The Rust `From` impl only ever emits one of the
// three valid values, so the cast is safe.
return ((await this.inner.getLsmWriteSpec()) ?? undefined) as
| LsmWriteSpec
| undefined;
}
async closeLsmWriters(): Promise<void> {
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();
}
async checkout(version: number | string): Promise<void> {
if (typeof version === "string") {
return this.inner.checkoutTag(version);
}
return this.inner.checkout(version);
}
async checkoutLatest(): Promise<void> {
await this.inner.checkoutLatest();
}
async listVersions(): Promise<Version[]> {
return (await this.inner.listVersions()).map((version) => ({
version: version.version,
timestamp: new Date(version.timestamp / 1000),
metadata: version.metadata,
}));
}
async restore(): Promise<void> {
await this.inner.restore();
}
async tags(): Promise<Tags> {
return await this.inner.tags();
}
async branches(): Promise<Branches> {
return new Branches(await this.inner.branches());
}
currentBranch(): string | null {
return this.inner.currentBranch() ?? null;
}
async optimize(options?: Partial<OptimizeOptions>): Promise<OptimizeStats> {
let cleanupOlderThanMs;
if (
options?.cleanupOlderThan !== undefined &&
options?.cleanupOlderThan !== null
) {
cleanupOlderThanMs =
new Date().getTime() - options.cleanupOlderThan.getTime();
}
return await this.inner.optimize(
cleanupOlderThanMs,
options?.deleteUnverified,
);
}
async listIndices(): Promise<IndexConfig[]> {
return await this.inner.listIndices();
}
async tokenize(
query: string,
options: TokenizeTableOptions,
): Promise<FtsToken[]> {
return await this.inner.tokenize(
query,
options?.column,
options?.indexName,
);
}
async toArrow(): Promise<ArrowTable> {
return await this.query().toArrow();
}
async indexStats(name: string): Promise<IndexStatistics | undefined> {
const stats = await this.inner.indexStats(name);
if (stats === null) {
return undefined;
}
return stats;
}
async stats(): Promise<TableStatistics> {
return await this.inner.stats();
}
async initialStorageOptions(): Promise<
Record<string, string> | null | undefined
> {
return await this.inner.initialStorageOptions();
}
async latestStorageOptions(): Promise<
Record<string, string> | null | undefined
> {
return await this.inner.latestStorageOptions();
}
mergeInsert(on: string | string[]): MergeInsertBuilder {
on = Array.isArray(on) ? on : [on];
return new MergeInsertBuilder(this.inner.mergeInsert(on), this.schema());
}
/**
* Check if the table uses the new manifest path scheme.
*
* This function will return true if the table uses the V2 manifest
* path scheme.
*/
async usesV2ManifestPaths(): Promise<boolean> {
return await this.inner.usesV2ManifestPaths();
}
/**
* Migrate the table to use the new manifest path scheme.
*
* This function will rename all V1 manifests to V2 manifest paths.
* These paths provide more efficient opening of datasets with many versions
* on object stores.
*
* This function is idempotent, and can be run multiple times without
* changing the state of the object store.
*
* However, it should not be run while other concurrent operations are happening.
* And it should also run until completion before resuming other operations.
*/
async migrateManifestPathsV2(): Promise<void> {
await this.inner.migrateManifestPathsV2();
}
}
/**
* A definition of a column alteration. The alteration changes the column at
* `path` to have the new name `name`, to be nullable if `nullable` is true,
* and to have the data type `data_type`. At least one of `rename` or `nullable`
* must be provided.
*/
export interface ColumnAlteration {
/**
* The path to the column to alter. This is a dot-separated path to the column.
* If it is a top-level column then it is just the name of the column. If it is
* a nested column then it is the path to the column, e.g. "a.b.c" for a column
* `c` nested inside a column `b` nested inside a column `a`.
*/
path: string;
/**
* The new name of the column. If not provided then the name will not be changed.
* This must be distinct from the names of all other columns in the table.
*/
rename?: string;
/**
* A new data type for the column. If not provided then the data type will not be changed.
* Changing data types is limited to casting to the same general type. For example, these
* changes are valid:
* * `int32` -> `int64` (integers)
* * `double` -> `float` (floats)
* * `string` -> `large_string` (strings)
* But these changes are not:
* * `int32` -> `double` (mix integers and floats)
* * `string` -> `int32` (mix strings and integers)
*/
dataType?: string | DataType;
/** Set the new nullability. Note that a nullable column cannot be made non-nullable. */
nullable?: boolean;
}
/** A per-field metadata update, addressed by dot-path. */
export interface FieldMetadataUpdate {
/**
* Dot-separated path to the field. For a top-level column this is just its
* name; for a nested field it's the path, e.g. "a.b.c".
*/
path: string;
/**
* Metadata key/value pairs. Merged into the field's existing metadata by
* default; a value of `null` deletes that key.
*/
metadata: Record<string, string | null>;
/** If true, replace the field's entire metadata map instead of merging. */
replace?: boolean;
}
/** Summary of a column in a branch diff. */
export interface BranchColumnSummary {
name: string;
dataType: string;
nullable: boolean;
}
/** A column whose definition differs between main and the branch. */
export interface BranchColumnChange {
name: string;
main: BranchColumnSummary;
branch: BranchColumnSummary;
}
/** Summary of an index in a branch diff. */
export interface BranchIndexSummary {
indexName: string;
columns: string[];
indexType?: string;
status: string;
}
/** Row-level comparison between main and the branch. */
export interface BranchRowCountSummary {
unchanged: number;
newOnBase: number;
newOnBranch: number;
staleRecompute: number;
inputsChanged: number;
deltaAvailable: boolean;
}
/** A reason why a cherry-pick cannot currently land. */
export interface CherryPickError {
code: string;
message: string;
}
/** Read-only comparison of a branch against main. */
export interface BranchDiff {
fromBranch: string;
parentVersion: number;
mainVersion: number;
branchVersion: number;
baseMoved: boolean;
rowCountMain: number;
rowCountBranch: number;
rowSummary: BranchRowCountSummary;
addedColumns: BranchColumnSummary[];
removedColumns: BranchColumnSummary[];
changedColumns: BranchColumnChange[];
addedIndexes: BranchIndexSummary[];
removedIndexes: BranchIndexSummary[];
errors: CherryPickError[];
}
/** Changes that would be, or were, promoted by a cherry-pick. */
export interface CherryPickPreview {
promotedColumns: string[];
}
/** Result of previewing or attempting a cherry-pick. */
export interface CherryPickResult {
status: "ready" | "failed" | "notImplemented" | "cherryPicked" | "unknown";
diff: BranchDiff;
preview: CherryPickPreview;
mainVersionAfter?: number;
}
/**
* Branch manager for a {@link Table}.
*
* Unlike tags, `create` and `checkout` return a new {@link Table} handle scoped
* to the branch; writes on it do not affect `main`.
*/
export class Branches {
#inner: NativeBranches;
/**
* Construct a Branches manager. Internal use only.
* @hidden
*/
constructor(inner: NativeBranches) {
this.#inner = inner;
}
/** List all branches, mapping name to branch metadata. */
async list(): Promise<Record<string, BranchContents>> {
return await this.#inner.list();
}
/**
* Create a branch and return a handle scoped to it.
*
* @param name Name of the new branch.
* @param fromRef Source branch to fork from. Defaults to `main`.
* @param fromVersion A specific version on `fromRef`. Defaults to latest.
*/
async create(
name: string,
fromRef?: string,
fromVersion?: number,
): Promise<Table> {
return new LocalTable(await this.#inner.create(name, fromRef, fromVersion));
}
/**
* Check out an existing branch and return a handle scoped to it.
*
* With `version` set, the returned handle is pinned to that version of the
* branch (a read-only, detached view); otherwise it tracks the branch's
* latest and stays writable.
*/
async checkout(name: string, version?: number): Promise<Table> {
return new LocalTable(await this.#inner.checkout(name, version));
}
/** Delete a branch. */
async delete(name: string): Promise<void> {
return await this.#inner.delete(name);
}
/** Compare a branch against main without modifying either branch. */
async diff(fromBranch: string): Promise<BranchDiff> {
return (await this.#inner.diff(fromBranch)) as unknown as BranchDiff;
}
/**
* Cherry-pick a branch onto main.
*
* Set `dryRun` to `true` to preview. A failed cherry-pick resolves
* with `status: "failed"` instead of throwing.
*
* @param fromBranch Branch to cherry-pick from.
* @param dryRun When true, only preview. Defaults to false.
*/
async cherryPick(
fromBranch: string,
dryRun: boolean = false,
): Promise<CherryPickResult> {
return (await this.#inner.cherryPick(
fromBranch,
dryRun,
)) as unknown as CherryPickResult;
}
}