Package org.apache.lucene.backward_codecs.lucene95

# Class Lucene95HnswVectorsFormat

java.lang.Object
org.apache.lucene.codecs.KnnVectorsFormat
org.apache.lucene.backward_codecs.lucene95.Lucene95HnswVectorsFormat

All Implemented Interfaces:
  `NamedSPILoader.NamedSPI`

public class Lucene95HnswVectorsFormat extends KnnVectorsFormat
Lucene 9.5 vector format, which encodes numeric vector values and an optional associated graph connecting the documents having values. The graph is used to power HNSW search. The format consists of three files:

## .vec (vector data) file

For each field:

- Vector data ordered by field, document ordinal, and vector dimension. When the vectorEncoding is BYTE, each sample is stored as a single byte. When it is FLOAT32, each sample is stored as an IEEE float in little-endian byte order.
- DocIds encoded by `IndexedDISI.writeBitSet(DocIdSetIterator, IndexOutput, byte)`, note that only in sparse case
- OrdToDoc was encoded by `DirectMonotonicWriter`, note that only in sparse case

## .vex (vector index)

Stores graphs connecting the documents for each field organized as a list of nodes' neighbours as following:

- For each level:
  - For each node:
    - [vint] the number of neighbor nodes
    - array[vint] the delta encoded neighbor ordinals
- After all levels are encoded memory offsets for each node's neighbor nodes encoded by `DirectMonotonicWriter` are appended to the end of the file.

## .vem (vector metadata) file

For each field:

- [int32] field number
- [int32] vector similarity function ordinal
- [vlong] offset to this field's vectors in the .vec file
- [vlong] length of this field's vectors, in bytes
- [vlong] offset to this field's index in the .vex file
- [vlong] length of this field's index data, in bytes
- [vint] dimension of this field's vectors
- [int] the number of documents having values for this field
- [int8] if equals to -1, dense – all documents have values for a field. If equals to 0, sparse – some documents missing values.
- DocIds were encoded by `IndexedDISI.writeBitSet(DocIdSetIterator, IndexOutput, byte)`
- OrdToDoc was encoded by `DirectMonotonicWriter`, note that only in sparse case
- [vint] the maximum number of connections (neighbours) that each node can have
- [vint] number of levels in the graph
- Graph nodes by level. For each level
  - [vint] the number of nodes on this level
  - array[vint] for levels greater than 0 list of nodes on this level, stored as the level 0th delta encoded nodes' ordinals.

WARNING: This API is experimental and might change in incompatible ways in the next release.

## Field Summary

Fields
Modifier and Type
Field
Description
`static final int`
`DEFAULT_BEAM_WIDTH`
Default number of the size of the queue maintained while searching during a graph construction.
`static final int`
`DEFAULT_MAX_CONN`
Default number of maximum connections per node

### Fields inherited from class org.apache.lucene.codecs.KnnVectorsFormat

`DEFAULT_MAX_DIMENSIONS, EMPTY`

## Constructor Summary

Constructors
Constructor
Description
`Lucene95HnswVectorsFormat()`
Constructs a format using default graph construction parameters
`Lucene95HnswVectorsFormat(int maxConn, int beamWidth)`
Constructs a format using the given graph construction parameters.

## Method Summary

Modifier and Type
Method
Description
`KnnVectorsReader`
`fieldsReader(SegmentReadState state)`
`KnnVectorsWriter`
`fieldsWriter(SegmentWriteState state)`
`int`
`getMaxDimensions(String fieldName)`
`String`
`toString()`

### Methods inherited from class org.apache.lucene.codecs.KnnVectorsFormat

`availableKnnVectorsFormats, forName, getName, reloadKnnVectorsFormat`

### Methods inherited from class java.lang.Object

`clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait`

## Field Details

### DEFAULT_MAX_CONN

public static final int DEFAULT_MAX_CONN
Default number of maximum connections per node

See Also:
  - Constant Field Values

### DEFAULT_BEAM_WIDTH

public static final int DEFAULT_BEAM_WIDTH
Default number of the size of the queue maintained while searching during a graph construction.

See Also:
  - Constant Field Values

## Constructor Details

### Lucene95HnswVectorsFormat

public Lucene95HnswVectorsFormat()
Constructs a format using default graph construction parameters

### Lucene95HnswVectorsFormat

public Lucene95HnswVectorsFormat(int maxConn, int beamWidth)
Constructs a format using the given graph construction parameters.

Parameters:
  `maxConn` - the maximum number of connections to a node in the HNSW graph
  `beamWidth` - the size of the queue maintained during graph construction.

## Method Details

### fieldsWriter

public KnnVectorsWriter fieldsWriter(SegmentWriteState state) throws IOException

Specified by:
  `fieldsWriter` in class `KnnVectorsFormat`
Throws:
  `IOException`

### fieldsReader

public KnnVectorsReader fieldsReader(SegmentReadState state) throws IOException

Specified by:
  `fieldsReader` in class `KnnVectorsFormat`
Throws:
  `IOException`

### getMaxDimensions

public int getMaxDimensions(String fieldName)

Specified by:
  `getMaxDimensions` in class `KnnVectorsFormat`

### toString

public String toString()

Overrides:
  `toString` in class `Object`