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DOC-12434: DDL for GSI Indexes with a Vector field (#275)
* Add vector index syntax to EBNF
* Update script to use Railroad Diagram Generator 2.1
* Update syntax diagrams
* Update primary index functionality
* Update nav
* Update indexing overview
* Update index types
* Add ALTER VECTOR INDEX
* Add CREATE VECTOR INDEX
* Add DROP VECTOR INDEX
* Update ALTER INDEX
* Update BUILD INDEX
* Update CREATE INDEX
* Update CREATE PRIMARY INDEX
* Update DROP INDEX
* UPDATE DROP PRIMARY INDEX
* Update toc depth
* Adjusting related links
* Add composite vector index example
* Add examples to ALTER VECTOR INDEX
* Add clarification about base64 decoding
* Update CREATE INDEX examples
* DOC-12940: GSI Vector Index not supported on Windows (#406)
Copy file name to clipboardExpand all lines: modules/indexes/pages/index-replication.adoc
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@@ -40,7 +40,7 @@ This ensures:
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* _Availability_: If one Index-Service node is lost, the other continues to provide access to replicated indexes.
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* _High Performance_: If original and replica copies are available, incoming queries are load-balanced across them.
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Index-replicas can be created with the {sqlpp}`CREATE INDEX` statement.
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Index-replicas can be created with the {sqlpp}`CREATE INDEX`or `CREATE VECTOR INDEX`statement.
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Note that whenever a given number of index-replicas is specified for creation, the number must be less than the number of cluster-nodes currently running the {index-service}[Index Service].
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If it is not, the index creation fails.
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Note also that if, following creation of the maximum number of copies, the number of nodes running the Index Service decreases, Couchbase Server progressively assigns replacement index-replicas to any and all Index-Service nodes subsequently be added to the cluster, until the required number of index-replicas again exists for each replicated index.
Note that if `nodes` and `num_replica` are both specified in the `WITH` clause, the specified number of nodes must be _one greater_ than `num_replica`.
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* Specifying a number of index-replicas to be created by the Index Service whenever `CREATE INDEX` is invoked.
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* Specifying a number of index-replicas to be created by the Index Service whenever `CREATE INDEX`or `CREATE VECTOR INDEX`is invoked.
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The default is `0`.
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If the default is changed to, say, `2`, creation of a single index is henceforth accompanied by the creation of two replicas, which are automatically distributed across the nodes of the cluster running the Index Service.
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No explicit specification within the `CREATE INDEX` statement is required.
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No explicit specification within the `CREATE INDEX`or `CREATE VECTOR INDEX`statement is required.
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With credentials that provide appropriate authorization, this default can be changed by means of the `curl` command, as follows:
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@@ -83,10 +83,10 @@ curl -X POST -u 'Administrator:password' \
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-d 'numReplica=2'
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----
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Here, `numReplica` is an integer that establishes the default number of replicas that must be created whenever `CREATE INDEX` is invoked.
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Here, `numReplica` is an integer that establishes the default number of replicas that must be created whenever `CREATE INDEX`or `CREATE VECTOR INDEX`is invoked.
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Note that this call only succeeds if the cluster contains enough Index Service nodes to host each new index and its replicas: for example, if `2` is specified as the default number of replicas, the Index Service must have been established on at least 3 nodes.
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Note also that whenever explicit specification of replica-numbers is made within the `CREATE INDEX` statement, this explicit specification takes precedence over any established default.
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Note also that whenever explicit specification of replica-numbers is made within the `CREATE INDEX`or `CREATE VECTOR INDEX`statement, this explicit specification takes precedence over any established default.
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You can change index replication settings via the {index-storage-mode}[UI] or the {index-settings-via-rest}[REST API].
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For further information on using {sqlpp}, refer to {query}[Query Fundamentals].
Creating the right index -- with the right keys, in the right order, and using the right expressions -- is critical to query performance in any database system.
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This is true for Couchbase as well.
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.Examples on this Page
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****
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The examples in this topic use the travel-sample dataset which is shipped with Couchbase Server.
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For instructions on how to install the sample bucket, see {install-sample-buckets}[Sample Buckets].
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For instructions on how to install the sample bucket, see {install-sample-buckets}[].
@@ -79,7 +81,7 @@ Use the primary index for full keyspace scans (primary scans) when the query doe
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NOTE: A primary index does not index any {additional-storage-use}[transaction records] that may be stored in a keyspace.
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This means that if you are counting the number of documents in a keyspace, you may see slightly different results, depending on whether you are using a primary index or not.
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Refer to {aggregatefun}[Aggregate Functions] and {bucket-analyzer}[Viewing the Data Insights].
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See {aggregatefun}[] and {bucket-analyzer}[Viewing the Data Insights].
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.Metadata for Primary Index
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====
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----
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====
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For further details and examples, refer to {indexing-arrays}[Array Indexing].
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For further details and examples, see {indexing-arrays}[].
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[#partial-index]
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== Partial Index
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If it does, the query engine skips retrieving the whole document from the data nodes.
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This is a performance optimization to keep in mind when designing your indexes.
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For further details and examples, refer to {covering-indexes}[Covering Indexes].
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For further details and examples, see {covering-indexes}[].
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[#hyperscale-vector-index]
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== Hyperscale Vector Index
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Hyperscale vector indexes are a type of <<secondary-index>> which contain a single vector field.
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They excel at indexing huge datasets that can scale into the billions of documents.
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They're optimized for pure vector searches, offering the highest performance of any index for your AI applications.
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For further details and examples, see {hyperscale-vector-index}[].
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[#composite-vector-index]
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== Composite Vector Index
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Composite vector indexes are a type of <<composite-secondary-index>> which contain a single vector field and one or more scalar fields.
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Your AI applications can use the index's scalar fields to filter the dataset before performing a vector similarity search.
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For further details and examples, see {composite-vector-index}[].
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