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From Shelly_Singh <Shelly_Si...@infosys.com>
Subject RE: Scaling Lucene to 1bln docs
Date Mon, 16 Aug 2010 07:12:03 GMT
Hi,

While I could get an excellent search time on 1 bln documents in lucene; when I try to retrieve
the document, I am being faced by a problem. If the number of documents returned by lucene
is large (in my example it is 32000), then the document retrieval time is 3 seconds.

My lucene document is not big, it has 3 fields of 1-2 terms each.
From my code, I could see that most of those 3 seconds go in "reader.getDoc(docId)". 
Is there is a better way to do this.

Thanks and Regards,

Shelly Singh
Center For KNowledge Driven Information Systems, Infosys
Email: shelly_singh@infosys.com
Phone: (M) 91 992 369 7200, (VoIP)2022978622

-----Original Message-----
From: Anshum [mailto:anshumg@gmail.com] 
Sent: Wednesday, August 11, 2010 10:38 AM
To: java-user@lucene.apache.org
Subject: Re: Scaling Lucene to 1bln docs

So, you didn't really use the setRamBuffer.. ?
Any reasons for that?

--
Anshum Gupta
http://ai-cafe.blogspot.com


On Wed, Aug 11, 2010 at 10:28 AM, Shelly_Singh <Shelly_Singh@infosys.com>wrote:

> My final settings are:
> 1.      1.5 gig RAM to the jvm out of 2GB available for my desktop
> 2.      100GB disk space.
> 3.      Index creation and searching tuning factors:
>         a. mergeFactor = 10
>        b. maxFieldLength = 10
>        c. maxMergeDocs = 5000000
>         d. full optimize at end of index creation
>        e. readChunkSize = 1000000
>        f. TermInfosIndexDivisor = 10
>        g. NO sharding. Single Machine.
>
> But Pablo, my document is a single field document with the the field length
> being 2-5 words. So, u can probably reduce it by a factor of 100 directly if
> u want to compare with regular docs.
>
> -----Original Message-----
> From: Pablo Mendes [mailto:pablomendes@gmail.com]
> Sent: Tuesday, August 10, 2010 7:22 PM
> To: java-user@lucene.apache.org
> Subject: Re: Scaling Lucene to 1bln docs
>
> Shelly,
> Do you mind sharing with the list the final settings you used for your best
> results?
>
> Cheers,
> Pablo
>
> On Tue, Aug 10, 2010 at 3:49 PM, anshum.gupta@naukri.com
> <anshumg@gmail.com>wrote:
>
> > Hey Shelly,
> > If you want to get more info on lucene, I'd recommend you get a copy of
> > lucene in action 2nd Ed. It'll help you get a hang of a lot of things! :)
> >
> > --
> > Anshum
> > http://blog.anshumgupta.net
> >
> > Sent from BlackBerry®
> >
> > -----Original Message-----
> > From: Shelly_Singh <Shelly_Singh@infosys.com>
> > Date: Tue, 10 Aug 2010 19:11:11
> > To: java-user@lucene.apache.org<java-user@lucene.apache.org>
> > Reply-To: java-user@lucene.apache.org
> > Subject: RE: Scaling Lucene to 1bln docs
> >
> > Hi folks,
> >
> > Thanks for the excellent support n guidance on my very first day on this
> > mailing list...
> > At end of day, I have very optimistic results. 100bln search in less than
> > 1ms and the index creation time is not huge either ( close to 15
> minutes).
> >
> > I am now hitting the 1bln mark with roughly the same settings. But, I
> want
> > to understand Norms and TermFilters.
> >
> > Can someone explain, why or why not should one use each of these and what
> > tradeoffs does it have.
> >
> > Regards,
> > Shelly
> >
> > -----Original Message-----
> > From: Danil ŢORIN [mailto:torindan@gmail.com]
> > Sent: Tuesday, August 10, 2010 6:52 PM
> > To: java-user@lucene.apache.org
> > Subject: Re: Scaling Lucene to 1bln docs
> >
> > That won't work...if you'll have something like "A Basic Crazy
> > Document E-something F-something G-something....you get the point" it
> > will go to all shards so the whole point of shards will be
> > compromised...you'll have 26 billion documents index ;)
> >
> > Looks like the only way is to search all shards.
> > Depending on available hardware (1 Azul...50 EC2), expected
> > traffic(1qps...1000qps), expected query time(10 msec ... 3 sec),
> > redundancy (it's a large dataset, I don't think you want to loose it),
> > and so on...you'll have to decide how many partitions do you want.
> >
> > It may work with 8-10, it may need 50-64. (I usually use 2^n as it's
> > easier to split each shard in 2 when index grows too much)
> >
> > On such large datasets it's a lot of tuning, custom code, and no
> > one-size-fits-all solution.
> > Lucene is just a tool (a fine one) but you need to use it wisely to
> > archive great results.
> >
> > On Tue, Aug 10, 2010 at 15:55, Shelly_Singh <Shelly_Singh@infosys.com>
> > wrote:
> > > Hmm..I get the point. But, in my application, the document is basically
> a
> > descriptive name of a particular thing. The user will search by name (or
> > part of name) and I need to pull out all info pointed to by that name.
> This
> > info is externalized in a db.
> > >
> > > One option I can think of is-
> > > I can shard based on starting alphabet of any name. So, "Alan Mathur of
> > New Delhi" may go to shard "A". But since the name will have 'n' tokens,
> and
> > the user may type any one token, this will not work. I can further tweak
> > this such that I index the same document into multiple indices (one for
> each
> > token). So, the same document may be indexed into Shard"A", "M", "N" and
> > "D".
> > > I am not able to think of another option.
> > >
> > > Comments welcome.
> > >
> > >
> > > -----Original Message-----
> > > From: Danil ŢORIN [mailto:torindan@gmail.com]
> > > Sent: Tuesday, August 10, 2010 6:11 PM
> > > To: java-user@lucene.apache.org
> > > Subject: Re: Scaling Lucene to 1bln docs
> > >
> > > I'd second that.
> > >
> > > It doesn't have to be date for sharding. Maybe every query has some
> > > specific field, like UserId or something, so you can redirect to
> > > specific shard instead of hitting all 10 indices.
> > >
> > > You have to have some kind of narrowing: searching 1bn documents with
> > > queries that may hit all documents is useless.
> > > An user won't look on more than let say 100 results (if presented
> > > properly..maybe 1000)
> > >
> > > Those fields that narrow the result set are good candidates for
> sharding
> > keys.
> > >
> > >
> > > On Tue, Aug 10, 2010 at 15:32, Dan OConnor <doconnor@acquiremedia.com>
> > wrote:
> > >> Shelly:
> > >>
> > >> You wouldn't necessarily have to use a multisearcher. A suggested
> > alternative is:
> > >>
> > >> - shard into 10 indices. If you need the concept of a date range
> search,
> > I would assign the documents to the shard by date, otherwise random
> > assignment is fine.
> > >> - have a pool of IndexSearchers for each index
> > >> - when a search comes in, allocate a Searcher from each index to the
> > search.
> > >> - perform the search in parallel across all indices.
> > >> - merge the results in your own code using an efficient merging
> > algorithm.
> > >>
> > >> Regards,
> > >> Dan
> > >>
> > >>
> > >>
> > >>
> > >> -----Original Message-----
> > >> From: Shelly_Singh [mailto:Shelly_Singh@infosys.com]
> > >> Sent: Tuesday, August 10, 2010 8:20 AM
> > >> To: java-user@lucene.apache.org
> > >> Subject: RE: Scaling Lucene to 1bln docs
> > >>
> > >> No sort. I will need relevance based on TF. If I shard, I will have to
> > search in al indices.
> > >>
> > >> -----Original Message-----
> > >> From: anshum.gupta@naukri.com [mailto:anshumg@gmail.com]
> > >> Sent: Tuesday, August 10, 2010 1:54 PM
> > >> To: java-user@lucene.apache.org
> > >> Subject: Re: Scaling Lucene to 1bln docs
> > >>
> > >> Would like to know, are you using a particular type of sort? Do you
> need
> > to sort on relevance? Can you shard and restrict your search to a limited
> > set of indexes functionally?
> > >>
> > >> --
> > >> Anshum
> > >> http://blog.anshumgupta.net
> > >>
> > >> Sent from BlackBerry(r)
> > >>
> > >> -----Original Message-----
> > >> From: Shelly_Singh <Shelly_Singh@infosys.com>
> > >> Date: Tue, 10 Aug 2010 13:31:38
> > >> To: java-user@lucene.apache.org<java-user@lucene.apache.org>
> > >> Reply-To: java-user@lucene.apache.org
> > >> Subject: RE: Scaling Lucene to 1bln docs
> > >>
> > >> Hi Anshum,
> > >>
> > >> I am already running with the 'setCompoundFile' option off.
> > >> And thanks for pointing out mergeFactor. I had tried a higher
> > mergeFactor couple of days ago, but got an OOM, so I discarded it. Later
> I
> > figured that OOM was because maxMergeDocs was unlimited and I was using
> > MMap. U r rigt, I should try a higher mergeFactor.
> > >>
> > >> With regards to the multithreaded approach, I was considering creating
> > 10 different threads each indexing 100mln docs coupled with a
> Multisearcher
> > to which I will feed these 10 indices. Do you think this will improve
> > performance.
> > >>
> > >> And just FYI, I have latest reading for 1 bln docs. Indexing time is 2
> > hrs and search time is 15 secs.. I can live with indexing time but the
> > search time is highly unacceptable.
> > >>
> > >> Help again.
> > >>
> > >> -----Original Message-----
> > >> From: Anshum [mailto:anshumg@gmail.com]
> > >> Sent: Tuesday, August 10, 2010 12:55 PM
> > >> To: java-user@lucene.apache.org
> > >> Subject: Re: Scaling Lucene to 1bln docs
> > >>
> > >> Hi Shelly,
> > >> That seems like a reasonable data set size. I'd suggest you increase
> > your
> > >> mergeFactor as a mergeFactor of 10 says, you are only buffering 10
> docs
> > in
> > >> memory before writing it to a file (and incurring I/O). You could
> > actually
> > >> flush by RAM usage instead of a Doc count. Turn off using the Compound
> > file
> > >> structure for indexing as it generally takes more time creating a cfs
> > index.
> > >>
> > >> Plus the time would not grow linearly as the larger the size of
> segments
> > >> get, the more time it'd take to add more docs and merge those together
> > >> intermittently.
> > >> You may also use a multithreaded approach in case reading the source
> > takes
> > >> time in your case, though, the indexwriter would have to be shared
> among
> > all
> > >> threads.
> > >>
> > >> --
> > >> Anshum Gupta
> > >> http://ai-cafe.blogspot.com
> > >>
> > >>
> > >> On Tue, Aug 10, 2010 at 12:24 PM, Shelly_Singh <
> > Shelly_Singh@infosys.com>wrote:
> > >>
> > >>> Hi,
> > >>>
> > >>> I am developing an application which uses Lucene for indexing and
> > searching
> > >>> 1 bln documents. (the document size is very small though. Each
> document
> > has
> > >>> a single field of 5-10 words; so I believe that my data size is
> within
> > the
> > >>> tested limits).
> > >>>
> > >>> I am using the following configuration:
> > >>> 1.      1.5 gig RAM to the jvm
> > >>> 2.      100GB disk space.
> > >>> 3.      Index creation tuning factors:
> > >>> a.      mergeFactor = 10
> > >>> b.      maxFieldLength = 10
> > >>> c.      maxMergeDocs = 5000000 (if I try with a larger value, I get
> an
> > >>> out-of-memory)
> > >>>
> > >>> With these settings, I am able to create an index of 100 million docs
> > (10
> > >>> pow 8)  in 15 mins consuming a disk space of 2.5gb. Which is quite
> > >>> satisfactory for me, but nevertheless, I want to know what else can
> be
> > done
> > >>> to tune it further. Please help.
> > >>> Also, with these settings, can I expect the time and size to grow
> > linearly
> > >>> for 1bln (10 pow 9) documents?
> > >>>
> > >>> Thanks and Regards,
> > >>>
> > >>> Shelly Singh
> > >>> Center For KNowledge Driven Information Systems, Infosys
> > >>> Email: shelly_singh@infosys.com<mailto:shelly_singh@infosys.com>
> > >>> Phone: (M) 91 992 369 7200, (VoIP)2022978622
> > >>>
> > >>>
> > >>>
> > >>>
> > >>
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> > >>
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> > >>
> > >>
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