Interface CfnIndexProps
- All Superinterfaces:
software.amazon.jsii.JsiiSerializable
- All Known Implementing Classes:
CfnIndexProps.Jsii$Proxy
CfnIndex.
Example:
// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import software.amazon.awscdk.services.s3vectors.*;
CfnIndexProps cfnIndexProps = CfnIndexProps.builder()
.dataType("dataType")
.dimension(123)
.distanceMetric("distanceMetric")
// the properties below are optional
.encryptionConfiguration(EncryptionConfigurationProperty.builder()
.kmsKeyArn("kmsKeyArn")
.sseType("sseType")
.build())
.indexName("indexName")
.metadataConfiguration(MetadataConfigurationProperty.builder()
.nonFilterableMetadataKeys(List.of("nonFilterableMetadataKeys"))
.build())
.vectorBucketArn("vectorBucketArn")
.vectorBucketName("vectorBucketName")
.build();
- See Also:
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Nested Class Summary
Nested ClassesModifier and TypeInterfaceDescriptionstatic final classA builder forCfnIndexPropsstatic final classAn implementation forCfnIndexProps -
Method Summary
Modifier and TypeMethodDescriptionstatic CfnIndexProps.Builderbuilder()The data type of the vectors to be inserted into the vector index.The dimensions of the vectors to be inserted into the vector index.The distance metric to be used for similarity search.default ObjectThe encryption configuration for a vector index.default StringThe name of the vector index to create.default ObjectThe metadata configuration for the vector index.default StringThe Amazon Resource Name (ARN) of the vector bucket that contains the vector index.default StringThe name of the vector bucket that contains the vector index.Methods inherited from interface software.amazon.jsii.JsiiSerializable
$jsii$toJson
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Method Details
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getDataType
The data type of the vectors to be inserted into the vector index.Currently, only
float32is supported, which represents 32-bit floating-point numbers.- See Also:
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getDimension
The dimensions of the vectors to be inserted into the vector index.This value must be between 1 and 4096, inclusive. All vectors stored in the index must have the same number of dimensions.
The dimension value affects the storage requirements and search performance. Higher dimensions require more storage space and may impact search latency.
- See Also:
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getDistanceMetric
The distance metric to be used for similarity search. Valid values are:.cosine- Measures the cosine of the angle between two vectors.euclidean- Measures the straight-line distance between two points in multi-dimensional space. Lower values indicate greater similarity.
- See Also:
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getEncryptionConfiguration
The encryption configuration for a vector index.By default, if you don't specify, all new vectors in the vector index will use the encryption configuration of the vector bucket.
Returns union: either
IResolvableorCfnIndex.EncryptionConfigurationProperty- See Also:
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getIndexName
The name of the vector index to create.The index name must be between 3 and 63 characters long and can contain only lowercase letters, numbers, hyphens (-), and dots (.). The index name must be unique within the vector bucket.
If you don't specify a name, AWS CloudFormation generates a unique ID and uses that ID for the index name.
If you specify a name, you can't perform updates that require replacement of this resource. You can perform updates that require no or some interruption. If you need to replace the resource, specify a new name.
- See Also:
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getMetadataConfiguration
The metadata configuration for the vector index.Returns union: either
IResolvableorCfnIndex.MetadataConfigurationProperty- See Also:
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getVectorBucketArn
The Amazon Resource Name (ARN) of the vector bucket that contains the vector index.- See Also:
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getVectorBucketName
The name of the vector bucket that contains the vector index.- See Also:
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builder
- Returns:
- a
CfnIndexProps.BuilderofCfnIndexProps
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