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From Paul Elschot <paul.elsc...@xs4all.nl>
Subject Re: Lucene performance bottlenecks
Date Sat, 03 Dec 2005 21:42:59 GMT
On Saturday 03 December 2005 14:09, Andrzej Bialecki wrote:
> Paul Elschot wrote:
> 
> >In somewhat more readable layout:
> > 
> >+(url:term1^4.0 anchor:term1^2.0 content:term1
> >   title:term1^1.5  host:term1^2.0)
> >+(url:term2^4.0 anchor:term2^2.0 content:term2
> >   title:term2^1.5 host:term2^2.0)
> >url:"term1 term2"~2147483647^4.0 
> >anchor:"term1 term2"~4^2.0
> >content:"term1 term2"~2147483647
> >title:"term1 term2"~2147483647^1.5
> >host:"term1 term2"~2147483647^2.0
> >
> >The first two clauses with + prefixes are required, and I would guess
> >that the 5 way disjunctions inside these clauses take most of the cpu time
> >during search.
> >  
> >
> 
> That's an interesting observation. This suggests that it could pay off 
> to glue these fields together and change this to a query on a single 
> combined field, right? I.e. to trade off space for speed.

Yes.
Querying the host field like this in a web page index can be dangerous
business. For example when term1 is "wikipedia" and term2 is "org",
the query will match at least all pages from wikipedia.org.

> 
> >The remaining clauses will be skipped to only when the two required
> >clauses are both present, so these are probably not the problem.
> >In the call tree for scoring these can be identified by the skipTo()
> >being called inside the score() method at the top level.
> >
> >This is one of the cases in which BooleanScorer2 can be faster
> >than the 1.4 BooleanScorer because the 1.4 BooleanScorer does
> >not use skipTo() for the optional clauses.
> >Could you try this by calling the static method
> >BooleanQuery.setUseScorer14(true) and repeating the test?
> >  
> >
> 
> Ok, I'll be able to do this on Monday.
> 
> >
> >>For those interested in profiler info, look here:
> >>
> >>http://www.getopt.org/lucene/20051202/
> >>    
> >>
> >
> >Thanks for making this available.
> >I had a short look and noticed that the times in the call tree are 
cumulative.
> >Would it be possible to record cpu time per method by subtracting the
> >times of the called methods?
> >  
> >
> 
> I think so, I'll check it back on Monday.
> 
> >Another interesting statistic is the actual numbers of times the methods 
get
> >called. The scorers used by BooleanScorer2 can use rather deep
> >call trees for scoring. These method calls are not free, and I would like
> >to know whether these form a bottleneck. 
> >  
> >
> 
> This statistics is available when I run with a high-detail profiling 
> (which slows down JVM considerably, like 10x). I can collect these too, 
> if it's interesting.

One measurement at a time is more than enough for me, and the slow
down does not seem to make this a good candidate to do first.

> >>From the hot spots output of the profiler info I see that the following 
methods:
> >- PhrasePositions.nextPosition
> >- SegmentTermDocs.read
> >have a larger portion of cpu time spent in the method.
> >Looking at the expanded query, seeing PhrasePositions.nextPosition
> >here is not a surprise.
> >
> >The fact that SegmentTermDocs.read shows up might explain
> >the reason why only a little heap is used:  Lucene normally leaves
> >the file buffering to the operating system, and
> >when the file buffers are read the index data is decompressed
> >mostly by the readVInt method.
> >  
> >
> 
> Yes, I understand it now. But perhaps it's time to contest this 
> approach: if there is so much heap available, does it still make sense 
> to rely so much on OS caching, if we have the space to do the caching 
> inside JVM (at least for a large portion of the index)?

You can try and use Lucene's RAMDirectory when you have enough RAM.
However, for larger indexes, It is easier to fit the index files  in RAM
(in OS buffers) than the decompressed index data (inside the JVM).

Also, caching query results by query text is probably more effective
than caching the JVM version of the searched index data.

Regards,
Paul Elschot


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