Create a vector index (Go)

Creates a new index for a vector column in a table in a database. You must create a vector index if you want to perform a vector search on vector embeddings stored in a column.

To create an index on a non-vector column, see Create an index (Go) instead.

The username and password used to generate the token must be tied to a role that has sufficient permissions to perform the desired operations.

Ready to write code? See the examples for this method to get started. If you are new to the Data API, check out the quickstart.

Result

Creates an index for the specified vector column.

A successful operation does not return anything.

Parameters

Use the CreateVectorIndex method, which belongs to the Table type.

Method signature
func (t *Table) CreateVectorIndex(
  ctx context.Context,
  name string,
  column string,
  opts ...options.CreateVectorIndexOption
) error
Name Type Summary

ctx

context.Context

The context for the operation.

name

string

The name of the index.

Index names for tables must follow these rules:

  • Must be unique within the keyspace

  • Can contain letters, numbers, and underscores

  • Must have a length of 1 to 100 characters

column

any

The name of the vector column on which to create the index.

To create indexes on non-vector columns, see Create an index (Go).

opts

…​options.CreateVectorIndexOption

Optional. A builder to generate options for this operation. See Methods of the CreateVectorIndexOption builder for more details.

Methods of the CreateVectorIndexOption builder
Method Summary

SetMetric(v VectorMetric)

Optional. The similarity metric to use for vector search.

Can be one of: options.MetricCosine, options.MetricDotProduct, options.MetricEuclidean.

For an example, see Create a vector index and specify the source model and similarity metric.

Default: options.MetricCosine

SetSourceModel(v string)

Optional. The model used to generate the embeddings that the indexed column stores. This enables certain vector optimizations on the index.

Can be one of: ada002, bert, cohere-v3, gecko, nv-qa-4, openai-v3-large, openai-v3-small, other.

For an example, see Create a vector index and specify the source model and similarity metric.

Default: other

SetIfNotExists(v bool)

Optional. Whether the command should silently succeed even if an index with the given name already exists in the keyspace and no new index was created.

This option only checks index names. It does not check index definitions.

Default: false

UpdateAPIOptions(v …​APIOption)

Optional. General API options for this operation, including the timeout.

Examples

The following examples demonstrate how to create a vector index.

Create a vector index with the default source model and similarity metric

If you do not specify the source model and similarity metric, the default values are used. For more information, see Parameters.

package main

import (
	"context"
	"log"

	"github.com/datastax/astra-db-go/v2/astra"
	"github.com/datastax/astra-db-go/v2/astra/options"
)

func main() {
	ctx := context.Background()

	// Get an existing table
	client := astra.NewClient(
		options.API().SetEnvironment(options.EnvironmentHCD),
	)

	database := client.Database(
		"API_ENDPOINT",
		options.API().
			SetUsernamePasswordTokenProvider(
				"USERNAME",
				"PASSWORD",
			).
			SetKeyspace("KEYSPACE_NAME"),
	)

	table := database.Table("TABLE_NAME")

	// Index a vector column
	err := table.CreateVectorIndex(
		ctx,
		"INDEX_NAME",
		"VECTOR_COLUMN_NAME",
	)
	if err != nil {
		log.Fatal(err)
	}
}

Create a vector index and specify the source model and similarity metric

When you create a vector index, you can specify the embedding source model, the similarity metric, or both.

package main

import (
	"context"
	"log"

	"github.com/datastax/astra-db-go/v2/astra"
	"github.com/datastax/astra-db-go/v2/astra/options"
)

func main() {
	ctx := context.Background()

	// Get an existing table
	client := astra.NewClient(
		options.API().SetEnvironment(options.EnvironmentHCD),
	)

	database := client.Database(
		"API_ENDPOINT",
		options.API().
			SetUsernamePasswordTokenProvider(
				"USERNAME",
				"PASSWORD",
			).
			SetKeyspace("KEYSPACE_NAME"),
	)

	table := database.Table("TABLE_NAME")

	// Index a vector column
	err := table.CreateVectorIndex(
		ctx,
		"INDEX_NAME",
		"VECTOR_COLUMN_NAME",
		options.CreateVectorIndex().
			SetMetric(options.MetricDotProduct).
			SetSourceModel("nv-qa-4"),
	)
	if err != nil {
		log.Fatal(err)
	}
}

Create an index only if the index does not exist

Use this option to silently do nothing if an index with the specified name already exists.

This option only checks index names. It doesn’t check the type or content of any existing indexes.

package main

import (
	"context"
	"log"

	"github.com/datastax/astra-db-go/v2/astra"
	"github.com/datastax/astra-db-go/v2/astra/options"
)

func main() {
	ctx := context.Background()

	// Get an existing table
	client := astra.NewClient(
		options.API().SetEnvironment(options.EnvironmentHCD),
	)

	database := client.Database(
		"API_ENDPOINT",
		options.API().
			SetUsernamePasswordTokenProvider(
				"USERNAME",
				"PASSWORD",
			).
			SetKeyspace("KEYSPACE_NAME"),
	)

	table := database.Table("TABLE_NAME")

	// Index a vector column
	err := table.CreateVectorIndex(
		ctx,
		"INDEX_NAME",
		"VECTOR_COLUMN_NAME",
		options.CreateVectorIndex().SetIfNotExists(true),
	)
	if err != nil {
		log.Fatal(err)
	}
}

Client reference

For more information, see the client reference.

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