db125013fc
* Sets `"useCodeBlocks": true` * Adds a post-processing script `nodejs/typedoc_post_process.js` that puts the parameter description on the same line as the parameter name, like it is in our Python docs. This makes the text hierarchy clearer in those sections and also makes the sections shorter.
6.5 KiB
@lancedb/lancedb • Docs
@lancedb/lancedb / QueryBase
Class: QueryBase<NativeQueryType>
Common methods supported by all query types
Extended by
Type Parameters
• NativeQueryType extends NativeQuery | NativeVectorQuery
Implements
AsyncIterable<RecordBatch>
Constructors
new QueryBase()
protected new QueryBase<NativeQueryType>(inner): QueryBase<NativeQueryType>
Parameters
- inner:
NativeQueryType|Promise<NativeQueryType>
Returns
QueryBase<NativeQueryType>
Properties
inner
protected inner: NativeQueryType | Promise<NativeQueryType>;
Methods
[asyncIterator]()
asyncIterator: AsyncIterator<RecordBatch<any>, any, undefined>
Returns
AsyncIterator<RecordBatch<any>, any, undefined>
Implementation of
AsyncIterable.[asyncIterator]
doCall()
protected doCall(fn): void
Parameters
- fn
Returns
void
execute()
protected execute(options?): RecordBatchIterator
Execute the query and return the results as an
Parameters
- options?:
Partial<QueryExecutionOptions>
Returns
See
- AsyncIterator of
- RecordBatch.
By default, LanceDb will use many threads to calculate results and, when the result set is large, multiple batches will be processed at one time. This readahead is limited however and backpressure will be applied if this stream is consumed slowly (this constrains the maximum memory used by a single query)
explainPlan()
explainPlan(verbose): Promise<string>
Generates an explanation of the query execution plan.
Parameters
- verbose:
boolean=falseIf true, provides a more detailed explanation. Defaults to false.
Returns
Promise<string>
A Promise that resolves to a string containing the query execution plan explanation.
Example
import * as lancedb from "@lancedb/lancedb"
const db = await lancedb.connect("./.lancedb");
const table = await db.createTable("my_table", [
{ vector: [1.1, 0.9], id: "1" },
]);
const plan = await table.query().nearestTo([0.5, 0.2]).explainPlan();
fastSearch()
fastSearch(): this
Skip searching un-indexed data. This can make search faster, but will miss any data that is not yet indexed.
Use lancedb.Table#optimize to index all un-indexed data.
Returns
this
filter()
filter(predicate): this
A filter statement to be applied to this query.
Parameters
- predicate:
string
Returns
this
Alias
where
Deprecated
Use where instead
fullTextSearch()
fullTextSearch(query, options?): this
Parameters
-
query:
string -
options?:
Partial<FullTextSearchOptions>
Returns
this
limit()
limit(limit): this
Set the maximum number of results to return.
By default, a plain search has no limit. If this method is not called then every valid row from the table will be returned.
Parameters
- limit:
number
Returns
this
nativeExecute()
protected nativeExecute(options?): Promise<RecordBatchIterator>
Parameters
- options?:
Partial<QueryExecutionOptions>
Returns
Promise<RecordBatchIterator>
offset()
offset(offset): this
Parameters
- offset:
number
Returns
this
select()
select(columns): this
Return only the specified columns.
By default a query will return all columns from the table. However, this can have a very significant impact on latency. LanceDb stores data in a columnar fashion. This means we can finely tune our I/O to select exactly the columns we need.
As a best practice you should always limit queries to the columns that you need. If you pass in an array of column names then only those columns will be returned.
You can also use this method to create new "dynamic" columns based on your existing columns.
For example, you may not care about "a" or "b" but instead simply want "a + b". This is often
seen in the SELECT clause of an SQL query (e.g. SELECT a+b FROM my_table).
To create dynamic columns you can pass in a Map<string, string>. A column will be returned for each entry in the map. The key provides the name of the column. The value is an SQL string used to specify how the column is calculated.
For example, an SQL query might state SELECT a + b AS combined, c. The equivalent
input to this method would be:
Parameters
- columns:
string|string[] |Record<string,string> |Map<string,string>
Returns
this
Example
new Map([["combined", "a + b"], ["c", "c"]])
Columns will always be returned in the order given, even if that order is different than
the order used when adding the data.
Note that you can pass in a `Record<string, string>` (e.g. an object literal). This method
uses `Object.entries` which should preserve the insertion order of the object. However,
object insertion order is easy to get wrong and `Map` is more foolproof.
toArray()
toArray(options?): Promise<any[]>
Collect the results as an array of objects.
Parameters
- options?:
Partial<QueryExecutionOptions>
Returns
Promise<any[]>
toArrow()
toArrow(options?): Promise<Table<any>>
Collect the results as an Arrow
Parameters
- options?:
Partial<QueryExecutionOptions>
Returns
Promise<Table<any>>
See
ArrowTable.
where()
where(predicate): this
A filter statement to be applied to this query.
The filter should be supplied as an SQL query string. For example:
Parameters
- predicate:
string
Returns
this
Example
x > 10
y > 0 AND y < 100
x > 5 OR y = 'test'
Filtering performance can often be improved by creating a scalar index
on the filter column(s).
withRowId()
withRowId(): this
Whether to return the row id in the results.
This column can be used to match results between different queries. For example, to match results from a full text search and a vector search in order to perform hybrid search.
Returns
this