BinaryQuantizationCompression Class
- java.
lang. Object - com.
azure. search. documents. indexes. models. VectorSearchCompression - com.
azure. search. documents. indexes. models. BinaryQuantizationCompression
- com.
- com.
public final class BinaryQuantizationCompression
extends VectorSearchCompression
Contains configuration options specific to the binary quantization compression method used during indexing and querying.
Constructor Summary
| Constructor | Description |
|---|---|
| BinaryQuantizationCompression(String compressionName) |
Creates an instance of Binary |
Method Summary
| Modifier and Type | Method and Description |
|---|---|
|
static
Binary |
fromJson(JsonReader jsonReader)
Reads an instance of Binary |
|
Vector |
getKind()
Get the kind property: The name of the kind of compression method being configured for use with vector search. |
|
Binary |
setDefaultOversampling(Double defaultOversampling)
Set the default |
|
Binary |
setRerankWithOriginalVectors(Boolean rerankWithOriginalVectors)
Set the rerank |
|
Binary |
setRescoringOptions(RescoringOptions rescoringOptions)
Set the rescoring |
|
Binary |
setTruncationDimension(Integer truncationDimension)
Set the truncation |
|
Json |
toJson(JsonWriter jsonWriter) |
Methods inherited from VectorSearchCompression
Methods inherited from java.lang.Object
Constructor Details
BinaryQuantizationCompression
public BinaryQuantizationCompression(String compressionName)
Creates an instance of BinaryQuantizationCompression class.
Parameters:
Method Details
fromJson
public static BinaryQuantizationCompression fromJson(JsonReader jsonReader)
Reads an instance of BinaryQuantizationCompression from the JsonReader.
Parameters:
Returns:
Throws:
getKind
public VectorSearchCompressionKind getKind()
Get the kind property: The name of the kind of compression method being configured for use with vector search.
Overrides:
BinaryQuantizationCompression.getKind()Returns:
setDefaultOversampling
public BinaryQuantizationCompression setDefaultOversampling(Double defaultOversampling)
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. For use with only service version 2024-07-01. If using 2025-09-01 or later, use RescoringOptions.defaultOversampling.
Overrides:
BinaryQuantizationCompression.setDefaultOversampling(Double defaultOversampling)Parameters:
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. For use with only service version 2024-07-01. If using 2025-09-01 or later, use RescoringOptions.rescoringEnabled.
Overrides:
BinaryQuantizationCompression.setRerankWithOriginalVectors(Boolean rerankWithOriginalVectors)Parameters:
setRescoringOptions
public BinaryQuantizationCompression setRescoringOptions(RescoringOptions rescoringOptions)
Set the rescoringOptions property: Contains the options for rescoring.
Overrides:
BinaryQuantizationCompression.setRescoringOptions(RescoringOptions rescoringOptions)Parameters:
setTruncationDimension
public BinaryQuantizationCompression setTruncationDimension(Integer truncationDimension)
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:
BinaryQuantizationCompression.setTruncationDimension(Integer truncationDimension)Parameters:
toJson
public JsonWriter toJson(JsonWriter jsonWriter)
Overrides:
BinaryQuantizationCompression.toJson(JsonWriter jsonWriter)Parameters:
Throws: