VectorSearchCompression Class
- java.
lang. Object - com.
azure. search. documents. indexes. models. VectorSearchCompression
- com.
Implements
public class VectorSearchCompression
implements JsonSerializable<VectorSearchCompression>
Contains configuration options specific to the compression method used during indexing or querying.
Constructor Summary
Constructor | Description |
---|---|
VectorSearchCompression(String compressionName) |
Creates an instance of Vector |
Method Summary
Modifier and Type | Method and Description |
---|---|
static
Vector |
fromJson(JsonReader jsonReader)
Reads an instance of Vector |
String |
getCompressionName()
Get the compression |
Double |
getDefaultOversampling()
Get the default |
Vector |
getKind()
Get the kind property: The name of the kind of compression method being configured for use with vector search. |
Boolean |
isRerankWithOriginalVectors()
Get the rerank |
Vector |
setDefaultOversampling(Double defaultOversampling)
Set the default |
Vector |
setRerankWithOriginalVectors(Boolean rerankWithOriginalVectors)
Set the rerank |
Json |
toJson(JsonWriter jsonWriter) |
Methods inherited from java.lang.Object
Constructor Details
VectorSearchCompression
public VectorSearchCompression(String compressionName)
Creates an instance of VectorSearchCompression class.
Parameters:
Method Details
fromJson
public static VectorSearchCompression fromJson(JsonReader jsonReader)
Reads an instance of VectorSearchCompression from the JsonReader.
Parameters:
Returns:
Throws:
getCompressionName
public String getCompressionName()
Get the compressionName property: The name to associate with this particular configuration.
Returns:
getDefaultOversampling
public Double getDefaultOversampling()
Get 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.
Returns:
getKind
public VectorSearchCompressionKind getKind()
Get the kind property: The name of the kind of compression method being configured for use with vector search.
Returns:
isRerankWithOriginalVectors
public Boolean isRerankWithOriginalVectors()
Get 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.
Returns:
setDefaultOversampling
public VectorSearchCompression 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.
Parameters:
Returns:
setRerankWithOriginalVectors
public VectorSearchCompression 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.
Parameters:
Returns: