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From "Armbrust, Daniel C." <Armbrust.Dan...@mayo.edu>
Subject RE: Lucene Benchmarks and Information
Date Fri, 20 Dec 2002 18:55:10 GMT
The query's were definitely not very intelligently built.  It was a last minute thing I decided
to do for the heck of it, as my main reason for thrashing my hard drives in this exercise
was to make sure I could run the document count up significantly higher than what we are currently
up to at work.

The operator was chosen randomly, followed by a random field, followed by a random word. 
I didn't put any phrases in, as I expected the number of hits I got would be quite low (since
the documents were also randomly generated) but in retrospect, even with near 0 results, it
would probably be interesting.  Maybe I'll run a couple tonight if I get a chance.

-----Original Message-----
From: Jonathan Reichhold [mailto:reichhold@singingfish.com] 
Sent: Friday, December 20, 2002 12:24 PM
To: 'Lucene Users List'
Subject: RE: Lucene Benchmarks and Information


A question on the queries you used.  What sort of distribution of terms
did you use?  I.e. were all the queries single random words, or did you
add in multi-word queries and phrases?

I'm impressed with the results, just want to understand the testing
methodology better.

JR

-----Original Message-----
From: Armbrust, Daniel C. [mailto:Armbrust.Daniel@mayo.edu] 
Sent: Friday, December 20, 2002 8:57 AM
To: 'Lucene Users List'
Subject: Lucene Benchmarks and Information


I've been running some scalability tests on Lucene over the past couple
of weeks.  While there may be some flaws with some of my methods, I
think they will be useful for people that want an idea as to how Lucene
will scale.  If anyone has any questions about what I did, or wants
clarifications on something, I'll be happy to provide them.

I'll start by filling out the form


      Hardware Environment
    * Dedicated machine for indexing: yes
    * CPU: 1 2.53 GHz Pentium 4
    * RAM: Self-explanatory
    * Drive configuration: 100 GB 7200 RPM IDE, 80 GB 7200 RPM IDE

      Software environment
    * Java Version: java version "1.3.1"
	Java(TM) 2 Runtime Environment, Standard Edition (build 1.3.1)
	Classic VM (build 1.3.1, J2RE 1.3.1 IBM Windows 32 build
cn131-20020403 (JIT enabled: jitc))
    * OS Version: Win XP SP1
    * Location of index: Local File Systems

      Lucene indexing variables
    * Number of source documents: 43,779,000
    * Total filesize of source documents: ~350 GB -- never stored
(documents were randomly generated)
    * Average filesize of source documents: 8 KB
    * Source documents storage location: Generated while indexing, never
written to disk
    * File type of source documents: text
    * Parser(s) used, if any: None
    * Analyzer(s) used: Standard Analyzer
    * Number of fields per document: 2
    * Type of fields: text, Unstored
    * Index persistence: FSDirectory

      Figures
    * Time taken (in ms/s as an average of at least 3 indexing runs):
See notes below
    * Time taken / 1000 docs indexed: 6.5 seconds/1000, not counting
optimization time.  15 seconds/1000 when optimizing every 100,000
documents, and building an index to ~ 5 million documents.  Above 5
million documents, optimization took too much time.  See notes below.
    * Memory consumption: ~ 200 mb
   *  Index Size: 70.7 GB

      Notes
    * Notes: The documents were randomly generated on the fly as part of
the indexing process from a list of ~100,000 words, who's average length
was 7.   The documents had 3 words in the title, and 500 words in the
body.

While I was trying to build this index, the biggest limitation of Lucene
that I ran into was optimization.  Optimization kills the indexers
performance when you get between 3-5 million documents in an index.  On
my Windows XP box, I had to reoptimize every 100,000 documents to keep
from running out of file handles.  While I could build a 5 million
document index in 24 hours... I could only add about another million
over the next 24 hours due to the pain of the optimizer recopying the
entire index over and over again (about 10 GB at this point), and it
would only get worse from there.  So, to build this large of an index, I
built several ~ 5 million document indexes, and then merged them at the
end into a single index.  The second issue (though not really a problem)
was that you have to have at least double the disk space available to
build the index as you need when you are done.  I could have kept
building the index bigger, but I ran out of disk space.  

When I was done building indexes, I ran some query's against them to see
how the search performance varied with the size of the index.  Following
are my results for various size indexes.

Index Size (GB) 		MS per query
4.53				83
7.92				83
10				89
12.7				112
52.5				694
70.7				944


These numbers are an average of 3 runs of 500 randomly generated queries
being tossed at the index (single threaded) on the same hardware that
built the index.  The queries were randomly generated (about 50 % of the
queries had 0 results, 50% had 1 or more results) 

I was happy to see that these numbers make a nice linear plot
(attached).  I'm not sure what other comments to add here, other to
thank the authors of Lucene for their great design and implementation of
Lucene.

If anyone has anything else they would like me to test on this index
before I dump it... Speak up quick, I have to pull out one of the hard
drives this weekend to pass it on to its real owner.

Dan



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