Awesome! Thanks for following up.
Mike
Gary Moore wrote:
Finally got back to this. The great bulk of the time is spent
parsing/tokenizing. So, using 10 threads parsing/analyzing the 4.5M
docs and feeding them to an IndexWriter took 106 minutes including a
final optimization. The index is 5.6 GB. I'm tempted to try
multiple indexing threads but my guess is it won't buy that much
since the async writer more than kept up with the thread queue.
Now, I'm even more impressed with 2.3!
-Gary
Michael McCandless wrote:
Thanks for the data point!
This is expected -- alot of work went into increasing IndexWriter's
throughput in 2.3.
Actually, I'd expect even more speedup, if indeed Lucene is the
bottleneck in your app. You could test how much time just creating/
parsing & tokenizing the docs (from whatever is holding them)
takes, to see. Also you might eke more performance out following
the suggestions here:
http://wiki.apache.org/lucene-java/ImproveIndexingSpeed
Since you've got 4 CPUs and lots of RAM you should definitely use
multiple indexing threads with a large RAM buffer.
Mike
Gary Moore wrote:
Parsing and indexing 4.5 million MARC/XML bibliographic records
was requiring ~14 hrs. using 2.2. The same job using 2.3 takes ~
5 hrs. on the same platform -- a quad processor Sun V440 w/8GB
memory. I'm using the PerFieldAnalyzerWrapper (StandardAnalyzer
and SnowballAnalyzer).
I'm impressed! Is this typical?
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