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Chapter 1. Indexing Data Grid caches

Data Grid can create indexes of values in your caches to improve query performance, providing faster results than non-indexed queries. Indexing also lets you use full-text search capabilities in your queries.

Note

Data Grid uses Apache Lucene technology to index values in caches.

1.1. Configuring Data Grid to index caches

Enable indexing in your cache configuration and specify which entities Data Grid should include when creating indexes.

You should always configure Data Grid to index caches when using queries. Indexing provides a significant performance boost to your queries, allowing you to get faster insights into your data.

Procedure

Enable indexing in your cache configuration.
```
<distributed-cache>
  <indexing>
    
  </indexing>
</distributed-cache>
```
Tip
Adding an indexing element to your configuration enables indexing without the need to include the enabled=true attribute.
For remote caches adding this element also implicitly configures encoding as ProtoStream.

Specify the entities to index with the indexed-entity element.

<distributed-cache>
  <indexing>
    <indexed-entities>
      <indexed-entity>...</indexed-entity>
    </indexed-entities>
  </indexing>
</distributed-cache>

Protobuf messages

Specify the message declared in the schema as the value of the indexed-entity element, for example:

<distributed-cache>
  <indexing>
    <indexed-entities>
      <indexed-entity>org.infinispan.sample.Car</indexed-entity>
      <indexed-entity>org.infinispan.sample.Truck</indexed-entity>
    </indexed-entities>
  </indexing>
</distributed-cache>

This configuration indexes the Book message in a schema with the book_sample package name.

package book_sample;

/* @Indexed */
message Book {

    /* @Text(projectable = true) */
    optional string title = 1;

    /* @Text(projectable = true) */
    optional string description = 2;

    // no native Date type available in Protobuf
    optional int32 publicationYear = 3;

    repeated Author authors = 4;
}

message Author {
    optional string name = 1;
    optional string surname = 2;
}

Java objects

Specify the fully qualified name (FQN) of each class that includes the @Indexed annotation.

XML

<distributed-cache>
  <indexing>
    <indexed-entities>
      <indexed-entity>book_sample.Book</indexed-entity>
    </indexed-entities>
  </indexing>
</distributed-cache>

ConfigurationBuilder

import org.infinispan.configuration.cache.*;

ConfigurationBuilder config=new ConfigurationBuilder();
config.indexing().enable().storage(FILESYSTEM).path("/some/folder").addIndexedEntity(Book.class);

Additional resources

org.infinispan.configuration.cache.IndexingConfigurationBuilder

1.1.1. Index configuration

Data Grid configuration controls how indexes are stored and constructed.

Index storage

You can configure how Data Grid stores indexes:

On the host file system, which is the default and persists indexes between restarts.
In JVM heap memory, which means that indexes do not survive restarts.
You should store indexes in JVM heap memory only for small datasets.

File system

<distributed-cache>
  <indexing storage="filesystem" path="${java.io.tmpdir}/baseDir">
    <!-- Indexing configuration goes here. -->
  </indexing>
</distributed-cache>

JVM heap memory

<distributed-cache>
  <indexing storage="local-heap">
    <!-- Additional indexing configuration goes here. -->
  </indexing>
</distributed-cache>

Index path

Specifies a filesystem path for the index when storage is 'filesystem'. The value can be a relative or absolute path. Relative paths are created relative to the configured global persistent location, or to the current working directory when global state is disabled.

By default, the cache name is used as a relative path for index path.

Important

When setting a custom value, ensure that there are no conflicts between caches using the same indexed entities.

Index startup mode

When Data Grid starts caches it can perform operations to ensure the index is consistent with data in the cache. By default no indexing operation takes place when a cache starts but you can configure Data Grid to:

Clear the index when the cache starts.
- Data Grid performs the clear (purge) operation synchronously. The cache becomes available only when the purge completes.
Reindex the cache when it starts.
- Data Grid performs the reindex operation asynchronously. The reindex operation might take a longer time to complete, depending on the size of the cache.
Automatically clear or reindex the cache.
- If data is volatile and the index is persistent then Data Grid clears the cache when it starts.
- If data is persistent and the index is volatile then Data Grid reindex the cache when it starts.

Clear the index when the cache starts

<distributed-cache>
  <indexing storage="filesystem" startup-mode="purge">
    <!-- Additional indexing configuration goes here. -->
  </indexing>
</distributed-cache>

Rebuild the index when the cache starts

<distributed-cache>
  <indexing storage="local-heap" startup-mode="reindex">
    <!-- Additional indexing configuration goes here. -->
  </indexing>
</distributed-cache>

Indexing mode

indexing-mode controls how cache operations are propagated to the indexes.

auto: Data Grid immediately applies any changes to the cache to the indexes. This is the default mode.
manual: Data Grid updates indexes only when the reindex operation is explicitly invoked. Configure manual mode, for example, when you want to perform batch updates to the indexes.

Set the indexing-mode to manual:

<distributed-cache>
  <indexing indexing-mode="manual">
    <!-- Additional indexing configuration goes here. -->
  </indexing>
</distributed-cache>

Index reader

The index reader is an internal component that provides access to the indexes to perform queries. As the index content changes, Data Grid needs to refresh the reader so that search results are up to date. You can configure the refresh interval for the index reader. By default Data Grid reads the index before each query if the index changed since the last refresh.

<distributed-cache>
  <indexing storage="filesystem" path="${java.io.tmpdir}/baseDir">
    <!-- Sets an interval of one second for the index reader. -->
    <index-reader refresh-interval="1000"/>
    <!-- Additional indexing configuration goes here. -->
  </indexing>
</distributed-cache>

Index writer

The index writer is an internal component that constructs an index composed of one or more segments (sub-indexes) that can be merged over time to improve performance. Fewer segments usually means less overhead during a query because index reader operations need to take into account all segments.

Data Grid uses Apache Lucene internally and indexes entries in two tiers: memory and storage. New entries go to the memory index first and then, when a flush happens, to the configured index storage. Periodic commit operations occur that create segments from the previously flushed data and make all the index changes permanent.

Note

The index-writer configuration is optional. The defaults should work for most cases and custom configurations should only be used to tune performance.

<distributed-cache>
  <indexing storage="filesystem" path="${java.io.tmpdir}/baseDir">
    <index-writer commit-interval="2000"
                  low-level-trace="false"
                  max-buffered-entries="32"
                  queue-count="1"
                  queue-size="10000"
                  ram-buffer-size="400"
                  thread-pool-size="2">
      <index-merge calibrate-by-deletes="true"
                   factor="3"
                   max-entries="2000"
                   min-size="10"
                   max-size="20"/>
    </index-writer>
    <!-- Additional indexing configuration goes here. -->
  </indexing>
</distributed-cache>

Table 1.1. Index writer configuration attributes
Attribute	Description
`commit-interval`	Amount of time, in milliseconds, that index changes that are buffered in memory are flushed to the index storage and a commit is performed. Because operation is costly, small values should be avoided. The default is 1000 ms (1 second).
`max-buffered-entries`	Maximum number of entries that can be buffered in-memory before they are flushed to the index storage. Large values result in faster indexing but use more memory. When used in combination with the `ram-buffer-size` attribute, a flush occurs for whichever event happens first.
`ram-buffer-size`	Maximum amount of memory that can be used for buffering added entries and deletions before they are flushed to the index storage. Large values result in faster indexing but use more memory. For faster indexing performance you should set this attribute instead of `max-buffered-entries`. When used in combination with the `max-buffered-entries` attribute, a flush occurs for whichever event happens first.
`thread-pool-size`	This configuration is ignored since Infinispan 15.0. The indexing engine now uses the Infinispan thread pools.
`queue-count`	Default 4. Number of internal queues to use for each indexed type. Each queue holds a batch of modifications that is applied to the index and queues are processed in parallel. Increasing the number of queues will lead to an increase of indexing throughput, but only if the bottleneck is CPU.
`queue-size`	Default 4000. Maximum number of elements each queue can hold. Increasing the `queue-size` value increases the amount of memory that is used during indexing operations. Setting a value that is too small can lead to `CacheBackpressureFullException` or `RejectedExecutionExceptionOperationSubmitter` since index operation requests are never blocked. In this case to solve the issue increase the `queue-size` or set the `queue-count` to 1.
`low-level-trace`	Enables low-level trace information for indexing operations. Enabling this attribute substantially degrades performance. You should use this low-level tracing only as a last resource for troubleshooting.

To configure how Data Grid merges index segments, you use the index-merge sub-element.

Table 1.2. Index merge configuration attributes
Attribute	Description
`max-entries`	Maximum number of entries that an index segment can have before merging. Segments with more than this number of entries are not merged. Smaller values perform better on frequently changing indexes, larger values provide better search performance if the index does not change often.
`factor`	Number of segments that are merged at once. With smaller values, merging happens more often, which uses more resources, but the total number of segments will be lower on average, increasing search performance. Larger values (greater than 10) are best for heavy writing scenarios.
`min-size`	Minimum target size of segments, in MB, for background merges. Segments smaller than this size are merged more aggressively. Setting a value that is too large might result in expensive merge operations, even though they are less frequent.
`max-size`	Maximum size of segments, in MB, for background merges. Segments larger than this size are never merged in the background. Settings this to a lower value helps reduce memory requirements and avoids some merging operations at the cost of optimal search speed. This attribute is ignored when forcefully merging an index and `max-forced-size` applies instead.
`max-forced-size`	Maximum size of segments, in MB, for forced merges and overrides the `max-size` attribute. Set this to the same value as `max-size` or lower. However setting the value too low degrades search performance because documents are deleted.
`calibrate-by-deletes`	Whether the number of deleted entries in an index should be taken into account when counting the entries in the segment. Setting `false` will lead to more frequent merges caused by `max-entries`, but will more aggressively merge segments with many deleted documents, improving query performance.

Additional resources

Data Grid configuration schema reference

Index sharding

When you have a large amount of data, you can configure Data Grid to split index data into multiple indexes called shards. Enabling data distribution among shards improves performance. By default, sharding is disabled.

Use the shards attribute to configure the number of indexes. The number of shards must be greater then 1.

<distributed-cache>
  <indexing>
    <index-sharding shards="6" />
  </indexing>
</distributed-cache>

1.2. Data Grid native indexing annotations

When you enable indexing in caches, you configure Data Grid to create indexes. You also need to provide Data Grid with a structured representation of the entities in your caches so it can actually index them.

Overview of the Data Grid indexing annotations

@Indexed: Indicates entities, or Protobuf message types, that Data Grid indexes.

To indicate the fields that Data Grid indexes use the indexing annotations. You can use these annotations the same way for both embedded and remote queries.

@Basic: Supports any type of field. Use the @Basic annotation for numbers and short strings that don’t require any transformation or processing.
@Decimal: Use this annotation for fields that represent decimal values.
@Keyword: Use this annotation for fields that are strings and intended for exact matching. Keyword fields are not analyzed or tokenized during indexing.
@Text: Use this annotation for fields that contain textual data and are intended for full-text search capabilities. You can use the analyzer to process the text and to generate individual tokens.
@Vector: Use this annotation to mark vector fields representing embeddings, on which can be defined kNN-predicates.
@Embedded: Use this annotation to mark a field as an embedded object within the parent entity. The NESTED structure preserves the original object relationship structure while the FLATTENED structure makes the leaf fields multivalued of the parent entity. The default structure used by @Embedded is NESTED.

Each of the annotations supports a set of attributes that you can use to further describe how the entity is indexed.

Table 1.3. Data Grid annotations and supported attributes
Annotation	Supported attributes
@Basic	searchable, sortable, projectable, aggregable, indexNullAs
@Decimal	searchable, sortable, projectable, aggregable, indexNullAs, decimalScale
@Keyword	searchable, sortable, projectable, aggregable, indexNullAs, normalizer, norms
@Text	searchable, projectable, norms, analyzer, searchAnalyzer, termVector
@Vector	searchable, projectable, dimension, similarity, beamWidth, maxConnections

Using Data Grid annotations

You can provide Data Grid with indexing annotations in two ways:

Annotate your Java classes or fields directly using the Data Grid annotations.
You then generate or update your Protobuf schema, .proto files, before uploading them to Data Grid Server.
Annotate Protobuf schema directly with @Indexed and @Basic, @Keyword or @Text.
You then upload your Protobuf schema to Data Grid Server.
For example, the following schema uses the @Text annotation:
```
/**
  * @Text(projectable = true)
  */
required string street = 1;
```

1.3. Rebuilding indexes

Rebuilding an index reconstructs it from the data stored in the cache. You should rebuild indexes when you change things like the definitions of indexed types or analyzers. Likewise, you can rebuild indexes after you delete them for whatever reason.

Important

Rebuilding indexes can take a long time to complete because the process takes place for all data in the grid. While the rebuild operation is in progress, queries might also return fewer results.

Procedure

Rebuild indexes in one of the following ways:

Call the reindexCache() method to programmatically rebuild an index from a Hot Rod Java client:
```
remoteCacheManager.administration().reindexCache("MyCache");
```
Tip
For remote caches you can also rebuild indexes from Data Grid Console.
Call the index.run() method to rebuild indexes for embedded caches as follows:
```
Indexer indexer = Search.getIndexer(cache);
CompletionStage<Void> future = index.run();
```
- Check the status of reindexing operation with the reindexing attribute of the index statistics.

1.4. Updating index schema

The update index schema operation lets you add schema changes with a minimal downtime. Instead of removing previously indexed data and recreating the index schema, Data Grid adds new fields to the existing schema. Updating index schema is much faster than rebuilding the index but you can update schema only when your changes do not affect fields that were already indexed.

Important

You can update index schema only when your changes does not affect previously indexed fields. When you change index field definitions or when you delete fields, you must rebuild the index.

Procedure

Update index schema for a given cache:
- Call the updateIndexSchema() method to programmatically update the index schema from a Hot Rod Java client:
```
remoteCacheManager.administration().updateIndexSchema("MyCache");
```
  Tip
  For remote caches, you can update index schema from the Data Grid Console or using the REST API.

Additional resources

Rebuilding indexes

1.5. Non-indexed queries

Data Grid recommends indexing caches for the best performance for queries. However you can query caches that are non-indexed.

For embedded caches, you can perform non-indexed queries on Plain Old Java Objects (POJOs).
For remote caches, you must use ProtoStream encoding with the application/x-protostream media type to perform non-indexed queries.

Dieser Inhalt ist in der von Ihnen ausgewählten Sprache nicht verfügbar.

Chapter 1. Indexing Data Grid caches

1.1. Configuring Data Grid to index caches

Protobuf messages

Java objects

1.1.1. Index configuration

Index storage

Index path

Index startup mode

Indexing mode

Index reader

Index writer

Index sharding

1.2. Data Grid native indexing annotations

Overview of the Data Grid indexing annotations

Using Data Grid annotations

1.3. Rebuilding indexes

1.4. Updating index schema

1.5. Non-indexed queries

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