The purpose of these user-submitted performance figures is to give current and potential users of Lucene a sense of how well Lucene scales. If the requirements for an upcoming project is similar to an existing benchmark, you will also have something to work with when designing the system architecture for the application.
If you've conducted performance tests with Lucene, we'd appreciate if you can submit these figures for display on this page. Post these figures to the lucene-user mailing list using this template.
Hardware Environment
Software environment
Lucene indexing variables
Figures
Notes
These benchmarks have been kindly submitted by Lucene users for reference purposes.
We make NO guarantees regarding their accuracy or validity.
We strongly recommend you conduct your own performance benchmarks before deciding on a particular hardware/software setup (and hopefully submit these figures to us).
Hardware Environment
Software environment
Lucene indexing variables
Figures
Notes
A windows client ran a random document generator which
created
documents based on some arrays of values and an excerpt
(approx 1kb)
from a text file of the bible (King James version).
These were submitted via a socket connection (open throughout
indexing process).
The index writer was not closed between index calls.
This created a 400Mb index in 23 files (after
optimization).
Query details:
Set up a threaded class to start x number of simultaneous threads to search the above created index.
Query: +Domain:sos +(+((Name:goo*^2.0 Name:plan*^2.0) (Teaser:goo* Tea ser:plan*) (Details:goo* Details:plan*)) -Cancel:y) +DisplayStartDate:[mkwsw2jk0 -mq3dj1uq0] +EndDate:[mq3dj1uq0-ntlxuggw0]
This query counted 34000 documents and I limited the returned documents to 5.
This is using Peter Halacsy's IndexSearcherCache slightly modified to be a singleton returned cached searchers for a given directory. This solved an initial problem with too many files open and running out of linux handles for them.
Threads|Avg Time per query (ms)
1 1009ms
2 2043ms
3 3087ms
4 4045ms
.. .
.. .
10 10091ms
I removed the two date range terms from the query and it made a HUGE difference in performance. With 4 threads the avg time dropped to 900ms!
Other query optimizations made little difference.
Hamish can be contacted at hamish at catalyst.net.nz.
Hardware Environment
Software environment
Lucene indexing variables
Figures
Notes
We have 10 threads reading files from the filesystem and parsing and analyzing them and the pushing them onto a queue and a single thread poping them from the queue and indexing. Note that we are indexing email messages and are storing the entire plaintext in of the message in the index. If the message contains attachment and we do not have a filter for the attachment (ie. we do not do PDFs yet), we discard the data.
Justin can be contacted at tvxh-lw4x at spamex.com.
My disclaimer is that this is a very poor "Benchmark". It was not done for raw speed, nor was the total index built in one shot. The index was created on several different machines (all with these specs, or very similar), with each machine indexing batches of 500,000 to 1 million documents per batch. Each of these small indexes was then moved to a much larger drive, where they were all merged together into a big index. This process was done manually, over the course of several months, as the sources became available.
Hardware Environment
Software environment
Lucene indexing variables
Figures
Notes
The source documents were XML. The "indexer" opened each document one at a time, ran an XSL transformation on them, and then proceeded to index the stream. The indexer optimized the index every 50,000 documents (on this run) though previously, we optimized every 300,000 documents. The performance didn't change much either way. We did no other tuning (RAM Directories, separate process to pretransform the source material, etc) to make it index faster. When all of these individual indexes were built, they were merged together into the main index. That process usually took ~ a day.
Daniel can be contacted at Armbrust.Daniel at mayo.edu.