feat(nodejs): add prewarmData method on Table (#3374)

### Summary
- Closes #3362 
- Adds `prewarmData(columns?: string[])` to the Node bindings, mirroring
the Rust and Python implementations

### Testing
- [x] `npm run build` (regenerates the napi `.node` module + TS
declarations)
- [x] `npm run lint`
- [x] `npm test
- [ ] live test against remote table - just waiting for my dev stack to
get created

### Documentation
- updated docs
This commit is contained in:
Brendan Clement
2026-05-12 15:29:48 -07:00
committed by GitHub
parent 650f173236
commit 011fdd5c94
4 changed files with 78 additions and 0 deletions

View File

@@ -1870,6 +1870,25 @@ describe.each([arrow15, arrow16, arrow17, arrow18])(
expect(results.length).toBe(3);
});
test("prewarmData errors on local tables", async () => {
const db = await connect(tmpDir.name);
const data = [
{ text: "alpha", vector: [0.1, 0.2, 0.3] },
{ text: "beta", vector: [0.4, 0.5, 0.6] },
];
const table = await db.createTable("prewarm_data_test", data);
// prewarmData is only supported on remote tables. We verify the call
// is wired through napi and surfaces the expected error for both
// arg shapes (undefined and string[]).
await expect(table.prewarmData()).rejects.toThrow(
"prewarm_data is currently only supported on remote tables",
);
await expect(table.prewarmData(["text"])).rejects.toThrow(
"prewarm_data is currently only supported on remote tables",
);
});
test("full text index on list", async () => {
const db = await connect(tmpDir.name);
const data = [

View File

@@ -285,6 +285,25 @@ export abstract class Table {
*/
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.
*
@@ -710,6 +729,10 @@ export class LocalTable extends Table {
await this.inner.prewarmIndex(name);
}
async prewarmData(columns?: string[]): Promise<void> {
await this.inner.prewarmData(columns);
}
async waitForIndex(
indexNames: string[],
timeoutSeconds: number,

View File

@@ -159,6 +159,14 @@ impl Table {
.default_error()
}
#[napi(catch_unwind)]
pub async fn prewarm_data(&self, columns: Option<Vec<String>>) -> napi::Result<()> {
self.inner_ref()?
.prewarm_data(columns)
.await
.default_error()
}
#[napi(catch_unwind)]
pub async fn wait_for_index(&self, index_names: Vec<String>, timeout_s: i64) -> Result<()> {
let timeout = std::time::Duration::from_secs(timeout_s.try_into().unwrap());