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Hibernate Search can take care of running the optimization process for you on a regular basis. Optimization can be triggered when the following metrics reach a certain limit:
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The number of operations applied to an index The number of transactions applied to an index
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If you set these numbers to a reasonably low value, small optimizations will be applied regularly and transparently for you. You can define these settings for all indexes or override them per index. The configuration mechanism is similar to the one you saw in section 5.1.1. A property name is composed of the following: hibernate.search. The index name or default to share these configurations for all indexes A dot (.) followed by the property suffix The two interesting suffixes are optimizer.operation_limit.max and optimizer.transaction_limit.max. When more than optimizer.operation_limit.max operations are executed on a given index (one index per entity type by default), an optimize operation is executed, and the operation and transaction counters are reset. Likewise, when optimizer.transaction_limit.max transactions are executed on a given index, an optimize operation is executed, and the operation and transaction counters are reset. Hibernate Search is smart enough to run automatic optimizations only at the end of the transaction. This is useful because an optimize operation is better done after all indexing is complete. Listing 9.13 shows a configuration where we optimize every 100 operations by default and every 30 transactions (or 100 operations, whichever comes first) for items.
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Listing 9.13 Setting transparent optimization limits
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<session-factory> ... <property name="hibernate.search.com.manning.hsia.dvdstore. model.Item.optimizer.transaction_limit.max" >30</property> <property name="hibernate.search.default. optimizer.operation_limit.max">100</property> ... </session-factory>
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Performance considerations
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You know how to trigger an optimization. Now let s see if you can configure Hibernate Search to tune the index structure.
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Tuning index structures and operations
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Hibernate Search allows you to tune its indexing performance through a set of configuration parameters that control how the underlying Lucene IndexWriter utilizes memory and disk file structures. A Lucene index is composed of mini-indexes (each of them being an atomic structure containing the necessary information). These miniindexes are called segments in Lucene. The two sets of parameters allow for different performance settings depending on the use case. During indexing operations triggered by database modifications, the following parameters are used:
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hibernate.search.<indexname>.indexwriter.transaction.merge_factor hibernate.search.<indexname>.indexwriter. transaction.max_merge_docs hibernate.search.<indexname>.indexwriter. transaction.ram_buffer_size The indexname can be replaced by default if you want to define global values. merge_factor determines how often segments are merged with each other when insertions in the Lucene index occurs. The lower the merge_factor, the fewer seg
ments are allowed at a given time and the more frequently merging happens. With small values, less RAM is used because fewer documents are kept in memory before being merged. But more file creations and merges are performed while indexing, making indexing speed slower. On the other hand, searches on unoptimized indexes are faster because fewer segments are present at a given time. With larger values, indexing is faster, but searches on unoptimized indexes are slower because of more segmented files. By default, Hibernate Search uses the Lucene default value (currently 10). max_merge_docs defines the largest number of documents allowed in a segment. When Lucene is about to add a new document to a given segment, it will create a new segment if the max_merge_docs limit is reached. This limit has priority over the merge_factor. A segment containing max_merge_docs will never be merged again. By default, Hibernate Search uses the Lucene default value (currently no limit).
While max_merge_docs can be useful for ensuring smaller merges, don t use it as a way to control memory usage; ram_buffer_size is a better way. If you happen to use both at the same time, a new segment is created as soon as one of the limits is reached.
ram_buffer_size controls the amount of memory used to buffer documents during indexing. This property is expressed in megabytes and defaults to 16. When this value is large, it takes longer for a new segment to be created, and merges happen less often. However, merge operations are slower and involve more documents.
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