Class BinaryQuantizationCompression
java.lang.Object
com.azure.search.documents.indexes.models.VectorSearchCompression
com.azure.search.documents.indexes.models.BinaryQuantizationCompression
- All Implemented Interfaces:
com.azure.json.JsonSerializable<VectorSearchCompression>
Contains configuration options specific to the binary quantization compression method used during indexing and
querying.
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Constructor Summary
ConstructorsConstructorDescriptionBinaryQuantizationCompression(String compressionName) Creates an instance of BinaryQuantizationCompression class. -
Method Summary
Modifier and TypeMethodDescriptionfromJson(com.azure.json.JsonReader jsonReader) Reads an instance of BinaryQuantizationCompression from the JsonReader.getKind()Get the kind property: The name of the kind of compression method being configured for use with vector search.setDefaultOversampling(Double defaultOversampling) Set the defaultOversampling property: Default oversampling factor.setRerankWithOriginalVectors(Boolean rerankWithOriginalVectors) Set the rerankWithOriginalVectors property: If set to true, once the ordered set of results calculated using compressed vectors are obtained, they will be reranked again by recalculating the full-precision similarity scores.setRescoringOptions(RescoringOptions rescoringOptions) Set the rescoringOptions property: Contains the options for rescoring.setTruncationDimension(Integer truncationDimension) Set the truncationDimension property: The number of dimensions to truncate the vectors to.com.azure.json.JsonWritertoJson(com.azure.json.JsonWriter jsonWriter) Methods inherited from class com.azure.search.documents.indexes.models.VectorSearchCompression
getCompressionName, getDefaultOversampling, getRescoringOptions, getTruncationDimension, isRerankWithOriginalVectorsMethods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitMethods inherited from interface com.azure.json.JsonSerializable
toJson, toJson, toJsonBytes, toJsonString
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Constructor Details
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BinaryQuantizationCompression
Creates an instance of BinaryQuantizationCompression class.- Parameters:
compressionName- the compressionName value to set.
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Method Details
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getKind
Get the kind property: The name of the kind of compression method being configured for use with vector search.- Overrides:
getKindin classVectorSearchCompression- Returns:
- the kind value.
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setRerankWithOriginalVectors
public BinaryQuantizationCompression setRerankWithOriginalVectors(Boolean rerankWithOriginalVectors) Set the rerankWithOriginalVectors property: If set to true, once the ordered set of results calculated using compressed vectors are obtained, they will be reranked again by recalculating the full-precision similarity scores. This will improve recall at the expense of latency.- Overrides:
setRerankWithOriginalVectorsin classVectorSearchCompression- Parameters:
rerankWithOriginalVectors- the rerankWithOriginalVectors value to set.- Returns:
- the VectorSearchCompression object itself.
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setDefaultOversampling
Set the defaultOversampling property: Default oversampling factor. Oversampling will internally request more documents (specified by this multiplier) in the initial search. This increases the set of results that will be reranked using recomputed similarity scores from full-precision vectors. Minimum value is 1, meaning no oversampling (1x). This parameter can only be set when rerankWithOriginalVectors is true. Higher values improve recall at the expense of latency.- Overrides:
setDefaultOversamplingin classVectorSearchCompression- Parameters:
defaultOversampling- the defaultOversampling value to set.- Returns:
- the VectorSearchCompression object itself.
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setRescoringOptions
Set the rescoringOptions property: Contains the options for rescoring.- Overrides:
setRescoringOptionsin classVectorSearchCompression- Parameters:
rescoringOptions- the rescoringOptions value to set.- Returns:
- the VectorSearchCompression object itself.
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setTruncationDimension
Set the truncationDimension property: The number of dimensions to truncate the vectors to. Truncating the vectors reduces the size of the vectors and the amount of data that needs to be transferred during search. This can save storage cost and improve search performance at the expense of recall. It should be only used for embeddings trained with Matryoshka Representation Learning (MRL) such as OpenAI text-embedding-3-large (small). The default value is null, which means no truncation.- Overrides:
setTruncationDimensionin classVectorSearchCompression- Parameters:
truncationDimension- the truncationDimension value to set.- Returns:
- the VectorSearchCompression object itself.
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toJson
- Specified by:
toJsonin interfacecom.azure.json.JsonSerializable<VectorSearchCompression>- Overrides:
toJsonin classVectorSearchCompression- Throws:
IOException
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fromJson
public static BinaryQuantizationCompression fromJson(com.azure.json.JsonReader jsonReader) throws IOException Reads an instance of BinaryQuantizationCompression from the JsonReader.- Parameters:
jsonReader- The JsonReader being read.- Returns:
- An instance of BinaryQuantizationCompression if the JsonReader was pointing to an instance of it, or null if it was pointing to JSON null.
- Throws:
IllegalStateException- If the deserialized JSON object was missing any required properties.IOException- If an error occurs while reading the BinaryQuantizationCompression.
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