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@lancedb/lancedb / Exports / Query

Class: Query

A builder for LanceDB queries.

Hierarchy

Query

Table of contents

Constructors

Properties

Methods

Constructors

constructor

new Query(tbl): Query

Parameters

Name Type
tbl Table

Returns

Query

Overrides

QueryBase.constructor

Defined in

query.ts:329

Properties

inner

Protected inner: Query

Inherited from

QueryBase.inner

Defined in

query.ts:59

Methods

[asyncIterator]

[asyncIterator](): AsyncIterator\<RecordBatch\<any>, any, undefined>

Returns

AsyncIterator\<RecordBatch\<any>, any, undefined>

Inherited from

QueryBase.[asyncIterator]

Defined in

query.ts:154


execute

execute(): RecordBatchIterator

Execute the query and return the results as an

Returns

RecordBatchIterator

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)

Inherited from

QueryBase.execute

Defined in

query.ts:149


limit

limit(limit): Query

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

Name Type
limit number

Returns

Query

Inherited from

QueryBase.limit

Defined in

query.ts:129


nativeExecute

nativeExecute(): Promise\<RecordBatchIterator>

Returns

Promise\<RecordBatchIterator>

Inherited from

QueryBase.nativeExecute

Defined in

query.ts:134


nearestTo

nearestTo(vector): VectorQuery

Find the nearest vectors to the given query vector.

This converts the query from a plain query to a vector query.

This method will attempt to convert the input to the query vector expected by the embedding model. If the input cannot be converted then an error will be thrown.

By default, there is no embedding model, and the input should be an array-like object of numbers (something that can be used as input to Float32Array.from)

If there is only one vector column (a column whose data type is a fixed size list of floats) then the column does not need to be specified. If there is more than one vector column you must use

Parameters

Name Type
vector unknown

Returns

VectorQuery

See

If no index has been created on the vector column then a vector query will perform a distance comparison between the query vector and every vector in the database and then sort the results. This is sometimes called a "flat search"

For small databases, with a few hundred thousand vectors or less, this can be reasonably fast. In larger databases you should create a vector index on the column. If there is a vector index then an "approximate" nearest neighbor search (frequently called an ANN search) will be performed. This search is much faster, but the results will be approximate.

The query can be further parameterized using the returned builder. There are various ANN search parameters that will let you fine tune your recall accuracy vs search latency.

Vector searches always have a limit. If limit has not been called then a default limit of 10 will be used. - Query#limit

Defined in

query.ts:370


select

select(columns): Query

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. 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

Name Type
columns string[] | Record\<string, string> | Map\<string, string>

Returns

Query

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.

Inherited from

QueryBase.select

Defined in

query.ts:108


toArray

toArray(): Promise\<unknown[]>

Collect the results as an array of objects.

Returns

Promise\<unknown[]>

Inherited from

QueryBase.toArray

Defined in

query.ts:169


toArrow

toArrow(): Promise\<Table\<any>>

Collect the results as an Arrow

Returns

Promise\<Table\<any>>

See

ArrowTable.

Inherited from

QueryBase.toArrow

Defined in

query.ts:160


where

where(predicate): Query

A filter statement to be applied to this query.

The filter should be supplied as an SQL query string. For example:

Parameters

Name Type
predicate string

Returns

Query

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).

Inherited from

QueryBase.where

Defined in

query.ts:73