@lancedb/lancedb • Docs
@lancedb/lancedb / Query
Class: Query
A builder for LanceDB queries.
Extends
QueryBase<NativeQuery>
Constructors
new Query()
Parameters
- tbl:
Table
Returns
Overrides
Properties
inner
Inherited from
Methods
[asyncIterator]()
Returns
AsyncIterator<RecordBatch<any>, any, undefined>
Inherited from
doCall()
Parameters
- fn
Returns
void
Inherited from
execute()
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)
Inherited from
explainPlan()
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();
Inherited from
fastSearch()
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
Inherited from
filter()
A filter statement to be applied to this query.
Parameters
- predicate:
string
Returns
this
Alias
where
Deprecated
Use where instead
Inherited from
fullTextSearch()
Parameters
-
query:
string -
options?:
Partial<FullTextSearchOptions>
Returns
this
Inherited from
limit()
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
Inherited from
nativeExecute()
Parameters
- options?:
Partial<QueryExecutionOptions>
Returns
Promise<RecordBatchIterator>
Inherited from
nearestTo()
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
- vector:
IntoVector
Returns
See
- VectorQuery#column to specify which column you would like to compare with.
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
nearestToText()
Parameters
-
query:
string -
columns?:
string[]
Returns
offset()
Parameters
- offset:
number
Returns
this
Inherited from
select()
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
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.
Inherited from
toArray()
Collect the results as an array of objects.
Parameters
- options?:
Partial<QueryExecutionOptions>
Returns
Promise<any[]>
Inherited from
toArrow()
Collect the results as an Arrow
Parameters
- options?:
Partial<QueryExecutionOptions>
Returns
Promise<Table<any>>
See
ArrowTable.
Inherited from
where()
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).
Inherited from
withRowId()
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