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.


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.


  1. Enable indexing in your cache configuration.

        <!-- Indexing configuration goes here. -->

    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.

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


Protobuf messages

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


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

    package book_sample;
    /* @Indexed */
    message Book {
        /* @Field(store = Store.YES, analyze = Analyze.YES) */
        optional string title = 1;
        /* @Field(store = Store.YES, analyze = Analyze.YES) */
        optional string description = 2;
        optional int32 publicationYear = 3; // no native Date type available in Protobuf
        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.




import org.infinispan.configuration.cache.*;

ConfigurationBuilder config=new ConfigurationBuilder();

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

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

JVM heap memory

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

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


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

  <indexing storage="filesystem" path="${}/baseDir">
    <index-writer commit-interval="2000"
      <index-merge calibrate-by-deletes="true"
    <!-- Additional indexing configuration goes here. -->

Table 1.1. Index writer configuration attributes



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).


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.


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.


Number of threads that execute write operations to the index.


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. For optimum results, do not set a value for queue-count that is larger than the value for thread-pool-size.


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 block indexing operations.


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



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.


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.


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.


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.


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.


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.

1.2. 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.

There are two annotations that control the entities and fields that Data Grid indexes:

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

Indicates fields that Data Grid indexes and has the following attributes:



Controls if Data Grid includes fields in indexes.

Index.YES or Index.NO


Allows Data Grid to store fields in indexes so you can use them for projections.

Store.YES or Store.NO


Includes fields in full-text searches.

Analyze.NO or specifies an analyzer definition

Remote caches

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

  • Annotate your Java classes directly with @ProtoDoc("@Indexed") and @ProtoDoc("@Field(…​)").
    You then generate Protobuf schema, .proto files, before uploading them to Data Grid Server.
  • Annotate Protobuf schema directly with @Indexed and @Field(…​).
    You then upload your Protobuf schema to Data Grid Server.

    For example, the following schema uses the @Field annotation:

       * @Field(analyze = Analyze.YES, store = Store.YES)
    required string street = 1;

Embedded caches

For embedded caches, you add indexing annotations to your Java classes according to how Data Grid stores your entries.

Use the @Indexed and @Field annotations, along with other Hibernate Search annotations such as @FullTextField.

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.


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.


Rebuild indexes in one of the following ways:

  • Call the reindexCache() method to programmatically rebuild an index from a Hot Rod Java client:


    For remote caches you can also rebuild indexes from Data Grid Console.

  • Call the method to rebuild indexes for embedded caches as follows:

    Indexer indexer = Search.getIndexer(cache);
    CompletionStage<Void> future =;

1.4. 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.