idx_name

Name of the index to create.

table_name

Table on which to create the index.

idx_vector_col

Vector column on which to create the index.

A comma-separated list of column names to be covered by the index.

idx_partitioning_scheme

Partitioning scheme for IVF indexes:

• GLOBAL

• LOCAL

IVF indexes support both global and local indexes on partitioned tables. By default, these indexes are globally partitioned by centroid. You can choose to create a local IVF index, which provides a one-to-one relationship between the base table partitions or subpartitions and the index partitions.

For detailed information on these partitioning schemes, see Inverted File Flat Vector Indexes Partitioning Schemes.

idx_organization

Index organization:

• NEIGHBOR PARTITIONS

• INMEMORY NEIGHBOR GRAPH

For detailed information on these organization types, see Manage the Different Categories of Vector Indexes.

idx_distance_metric

Distance metric or mathematical function used to compute the distance between vectors:

• COSINE (default)
• MANHATTAN
• HAMMING
• JACCARD
• DOT
• EUCLIDEAN
• L2_SQUARED
• EUCLIDEAN_SQUARED

For detailed information on each of these metrics, see Vector Distance Functions and Operators.

idx_accuracy

Target accuracy at which the approximate search should be performed when running an approximate search query.

As explained in Understand Approximate Similarity Search Using Vector Indexes, you can specify non-default target accuracy values either by specifying a percentage value or by specifying internal parameters values, depending on the index type you are using.

• For an HNSW approximate search:

  In the case of an HNSW approximate search, you can specify a target accuracy percentage value to influence the number of  candidates considered to probe the search. This is automatically calculated by the algorithm. A value of 100 will tend to impose a similar result as an exact search, although the system may still use the index and will not perform an exact search. The optimizer may choose to still use an index as it may be faster to do so given the predicates in the query. Instead of specifying a target accuracy percentage value, you can specify the EFSEARCH parameter to impose a certain maximum number of candidates to be considered while probing the index. The higher that number, the higher the accuracy.

  For detailed information, see Understand Hierarchical Navigable Small World Indexes.

• For an IVF approximate search:

  In the case of an IVF approximate search, you can specify a target accuracy percentage value to influence the number of partitions used to probe the search. This is automatically calculated by the algorithm. A value of 100 will tend to impose an exact search, although the system may still use the index and will not perform an exact search. The optimizer may choose to still use an index as it may be faster to do so given the predicates in the query. Instead of specifying a target accuracy percentage value, you can specify the NEIGHBOR PARTITION PROBES parameter to impose a certain maximum number of partitions to be probed by the search. The higher that number, the higher the accuracy.

  For detailed information, see Understand Inverted File Flat Vector Indexes.

idx_parameters

Type of vector index and associated parameters.

Specify the indexing parameters in JSON format:

• For HNSW indexes:

  • type: Type of vector index to create, that is, HNSW

  • neighbors: Maximum number of connections permitted per vector in the HNSW graph

  • efConstruction: Maximum number of closest vector candidates considered at each step of the search during insertion

  For example:

  {
      "type"           : "HNSW", 
      "neighbors"      : 3, 
      "efConstruction" : 4
  }

  For detailed information on these parameters, see Hierarchical Navigable Small World Index Syntax and Parameters.

• For IVF indexes:

  • type: Type of vector index to create, that is, IVF

  • partitions: Neighbor partition or cluster in which you want to divide your vector space

  For example:

  {
      "type"       : "IVF",
      "partitions" : 5
  }

  For detailed information on these parameters, see Inverted File Flat Index Syntax and Parameters.

idx_parallel_creation

Number of parallel threads used for index construction.