How to make indexing faster

Here are some things to try to speed up the indexing speed of your 

• Be sure you really need to speed things up. 

• Make sure you are using the latest version of Lucene.

• Use a local filesystem. 

• Get faster hardware, especially a faster IO system. 

• Open a single writer and re-use it for the duration of your indexing session.

• Flush by RAM usage instead of document count.

  For Lucene <= 2.2: call writer.ramSizeInBytes() after every added doc then call flush() when it's using too much RAM. This is especially good if you have small docs or highly variable doc sizes. You need to first set maxBufferedDocs large enough to prevent the writer from flushing based on document count. However, don't set it too large otherwise you may hit LUCENE-845. Somewhere around 2-3X your "typical" flush count should be OK.

  For Lucene >= 2.3: IndexWriter can flush according to RAM usage itself. Call writer.setRAMBufferSizeMB() to set the buffer size. Be sure you don't also have any leftover calls to setMaxBufferedDocs since the writer will flush "either or" (whichever comes first).

• Use as much RAM as you can afford.

  More RAM before flushing means Lucene writes larger segments to begin with which means less merging later. Testing in LUCENE-843 found that around 48 MB is the sweet spot for that content set, but, your application could have a different sweet spot.

• Turn off compound file format.

  Call setUseCompoundFile(false). Building the compound file format takes time during indexing (7-33% in testing for LUCENE-888). However, note that doing this will greatly increase the number of file descriptors used by indexing and by searching, so you could run out of file descriptors if mergeFactor is also large.

• Re-use Document and Field instances 

  Note that you cannot re-use a single Field instance within a Document, and, you should not change a Field's value until the Document containing that Field has been added to the index. See Field for details.

• Always add fields in the same order to your Document, when using stored fields or term vectors

  Lucene's merging has an optimization whereby stored fields and term vectors can be bulk-byte-copied, but the optimization only applies if the field name -> number mapping is the same across segments. Future Lucene versions may attempt to assign the same mapping automatically (see LUCENE-1737), but until then the only way to get the same mapping is to always add the same fields in the same order to each document you index.

• Re-use a single Token instance in your analyzer 

• Use the char[] API in Token instead of the String API to represent token Text

  As of Lucene 2.3, a Token can represent its text as a slice into a char array, which saves the GC cost of new'ing and then reclaiming String instances. By re-using a single Token instance and using the char[] API you can avoid new'ing any objects for each term. See Token for details.

• Use autoCommit=false when you open your IndexWriter

  In Lucene 2.3 there are substantial optimizations for Documents that use stored fields and term vectors, to save merging of these very large index files. You should see the best gains by using autoCommit=false for a single long-running session ofIndexWriter. Note however that searchers will not see any of the changes flushed by this IndexWriter until it is closed; if that is important you should stick with autoCommit=true instead or periodically close and re-open the writer.

• Instead of indexing many small text fields, aggregate the text into a single "contents" field and index only that (you can still store the other fields).

• Increase mergeFactor, but not too much.

  Larger mergeFactors defers merging of segments until later, thus speeding up indexing because merging is a large part of indexing. However, this will slow down searching, and, you will run out of file descriptors if you make it too large. Values that are too large may even slow down indexing since merging more segments at once means much more seeking for the hard drives.

• Turn off any features you are not in fact using. 

• Use a faster analyzer.

  Sometimes analysis of a document takes alot of time. For example, StandardAnalyzer is quite time consuming, especially in Lucene version <= 2.2. If you can get by with a simpler analyzer, then try it.

• Speed up document construction. 

• Don't optimize... ever.

• Use multiple threads with one IndexWriter. 

• Index into separate indices then merge. 

• Run a Java profiler.

  If all else fails, profile your application to figure out where the time is going. I've had success with a very simple profiler called JMP. There are many others. Often you will be pleasantly surprised to find some silly, unexpected method is taking far too much time.