Overview
In this guide, you can learn how to programmatically manage your MongoDB Search and MongoDB Vector Search indexes by using the PHP library.
The MongoDB Search feature enables you to perform full-text searches on collections hosted on MongoDB Atlas. To learn more about MongoDB Search, see the MongoDB Search Overview.
MongoDB Vector Search enables you to perform semantic searches on vector embeddings stored in MongoDB Atlas. To learn more about MongoDB Vector Search, see the MongoDB Vector Search Overview.
You can use the following methods on a MongoDB\Collection
instance
to manage your MongoDB Search and MongoDB Vector Search indexes:
MongoDB\Collection::createSearchIndex()
MongoDB\Collection::createSearchIndexes()
MongoDB\Collection::listSearchIndexes()
MongoDB\Collection::updateSearchIndex()
MongoDB\Collection::dropSearchIndex()
Note
MongoDB Search and MongoDB Vector Search Index Management is Asynchronous
The MongoDB PHP Library manages MongoDB Search and MongoDB Vector Search indexes asynchronously. The library methods described in the following sections return the server response immediately, but the changes to your Search indexes take place in the background and might not complete until some time later.
The following sections provide code examples that demonstrate how to use each of the preceding methods.
Create a Search Index
You can use the createSearchIndex()
method to create a single
MongoDB Search or MongoDB Vector Search index on a collection, or the
createSearchIndexes()
method to create multiple indexes
simultaneously.
The following code example shows how to create a single MongoDB Search index:
$searchIndexName = $collection->createSearchIndex( ['mappings' => ['dynamic' => true]], ['name' => 'mySearchIdx'], );
The following code example shows how to create a single MongoDB Vector Search index:
$vectorSearchIndexName = $collection->createSearchIndex( [ 'fields' => [[ 'type' => 'vector', 'path' => 'plot_embedding', 'numDimensions' => 1536, 'similarity' => 'dotProduct', ]], ], ['name' => 'myVSidx', 'type' => 'vectorSearch'], );
The following code example shows how to create MongoDB Search and Vector Search indexes in one call:
$indexNames = $collection->createSearchIndexes( [ [ 'name' => 'SearchIdx', 'definition' => ['mappings' => ['dynamic' => true]], ], [ 'name' => 'VSidx', 'type' => 'vectorSearch', 'definition' => [ 'fields' => [[ 'type' => 'vector', 'path' => 'plot_embedding', 'numDimensions' => 1536, 'similarity' => 'dotProduct', ]], ], ], ], );
After you create MongoDB Search or MongoDB Vector Search indexes, you can perform the corresponding query types on your documents. To learn more, see the following guides:
List Search Indexes
You can use the listSearchIndexes()
method to return an array of the
MongoDB Search and MongoDB Vector Search indexes on a collection:
foreach ($collection->listSearchIndexes() as $indexInfo) { echo json_encode($indexInfo), PHP_EOL; }
Update a Search Index
You can use the updateSearchIndex()
method to update a MongoDB Search or MongoDB Vector Search index. You can use this method to
change the name or configuration of an existing index.
The following code shows how to update a search index to use a simple
analyzer on the title
field:
$collection->updateSearchIndex( 'mySearchIdx', ['mappings' => [ 'dynamic' => false, 'fields' => [ 'title' => [ 'type' => 'string', 'analyzer' => 'lucene.simple', ], ], ]], );
Delete a Search Index
You can use the dropSearchIndex()
method to remove an MongoDB Search
or MongoDB Vector Search index from a collection.
The following code shows how to delete the MongoDB Search index named
mySearchIdx
:
$collection->dropSearchIndex('mySearchIdx');
Additional Information
To view runnable examples that demonstrate how to manage indexes, see Indexes for Query Optimization.
To view tutorials that explain how to use the MongoDB Search feature, see Get Started with MongoDB Search in the Atlas documentation.
API Documentation
To learn more about any of the methods discussed in this guide, see the following API documentation: