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Indexing: where, how, what, and when
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Listing 5.22
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Index entities without suffering from OutOfMemoryException
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session.setFlushMode(FlushMode.MANUAL); session.setCacheMode(CacheMode.IGNORE); tx = session.beginTransaction();
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B Disable flush operations C cache operations
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//read the data from the database //Scrollable results will avoid loading too many objects in memory ScrollableResults results = session.createCriteria( Item.class ) .scroll( ScrollMode.FORWARD_ONLY );
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result set int index = 0; while( results.next() ) { Index entities index++; session.index( results.get(0) ); Apply changes to if (index % BATCH_SIZE == 0) { the index session.flushToIndexes(); session.clear(); Clear the session, } releasing memory }
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tx.commit();
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Apply the remaining index changes
Prevent Hibernate Core from doing unnecessary flush operatons. C Prevent Hibernate Core from interacting with the second-level cache. Since a lot of entities are expected to be processed, using a second-level cache would be unproductive. D Use a forward-only scroll to ensure the JDBC driver does not cache the previously processed rows. E Apply indexing to the current entity. F On every BATCH_SIZE operation, apply index changes, freeing the index queue, and clear the session to free up memory By using a forward-only scrollable result set and by clearing the session every nth operation, we ensure that memory doesn t leak. Well, almost. Remember that Hibernate Search doesn t apply the change in the index until commit; rather it keeps track of the changes and consumes memory. This defeats the whole purpose of using clear. To work around this problem, Hibernate Search lets you call flushToIndexes(). On the method call, all index changes are executed (to the backend). By releasing the index change queue and clearing the session, you ensure that the memory consumption stays under control.
NOTE
If you use Hibernate 3.0.x, flushToIndexes() isn t available. Instead, you can define a batch size that limits the number of operations queued before being applied to Lucene. Check listing 5.23 to see how this property is configured. Make sure this value equals the batch size in your loop.
Listing 5.23 Define the entity job queue batch size (Hibernate Search 3.0)
# the batch size must equal the loop size in your indexing code hibernate.search.worker.batch_size 1000
Use the same algorithm described in listing 5.22 and simply remove the call to flushToIndexes().
Indexing:when transparency is not enough
This solution is inferior and more error prone for these reasons:
Batch size in the configuration and in the code must be the same. This limit is applied to all transactions regardless of the use of the manual indexing.
This is a very good reason to upgrade to the latest version! If you follow this pattern, you ll likely ensure fast enough indexing time without risking OutOfMemoryException.
Indexing all my data is still really slow What s going on
It s hard to give numbers because they vary so much depending on these factors:
Size of the data to index Input/output disk performance Database performance Network performance Size of the index directories
Nevertheless, if you think Hibernate Search is way too slow to index your data, something is wrong. Let s explore some of the things that could go wrong:
The indexing code doesn t follow the strategy described in listing 5.22; using a scrollable result set, avoiding interaction with the second-level cache, and clearing the session on a regular basis are critical. flushToIndexes() is not called before clear(); the memory is not released. Hibernate does multiple queries when indexing an object (enable SQL logging to see what s going on behind the scene).
Remember that associations embedded in the index and associations marked as @ContainedIn must be loaded and traversed by Hibernate Search. If your initial query doesn t load these associations, Hibernate Search will hit the database to request them, and you ll essentially face the infamous n+1 queries problem. You have several possible solutions:
Write a query that loads the traversed graph in one shot. Make use of the passive fetching strategies offered by Hibernate Core (subselect and entity/collection batch size). Use both techniques.
If you re ranting about the number of associations that need to be loaded, chances are you didn t follow our advice from chapter 4. Make sure to use @IndexedEmbedded and @ContainedBy if you really need to query the association. That s okay; the next time you ll pay more attention. ;o) This is a first-aid kit for improving performance. Make sure to read section 9.1 for more information on indexing optimization.
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