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From Artem Vasiliev <>
Subject Fwd: Re[2]: Fwd: Re[2]: 30 milllion+ docs on a single server
Date Thu, 05 Oct 2006 05:08:00 GMT
Hello Otis & all,

I benchmarked it only subjectively - typical FieldCache'ing sort was an overkill
for my humble server (now I give sharehound about 200M RAM for 14mln index which
takes about 12G on disk). When sorting (using FieldCache) the first time after index change
takes the whole index field set into memory - that's a big hit for memory and
time (except the index is small). The situation is even worse for me because I
wanted the index to be available for search while crawling the shares (so the
index is relatively frequently updated).

Now my add-on fixes these problems very nice. I'll contribute this add-on to
Lucene soon. Recently I separated this add-on's binaries creation in the
sharehound build procedure and I attach the jar file for convenience (to try
it). However, for example of use you can look at Sharehound code:*checkout*/sharehound/jNetCrawler/src/java/org/sourceforge/sharehound/lucene/

Best regards,

OG> Artem & Co.,

OG> Have you benchmarked this approach against the typical non-caching
OG> Sort?  Both performance and memory benchmark?

OG> If it outperforms FieldCache based sorting, I'm interested in it :)
OG> I'm also interested in a patch or contribution for Lucene itself.

OG> Please follow-up on java-user or java-dev.

OG> Thanks,
OG> Otis

OG> ----- Original Message ----
OG> From: Artem Vasiliev <>
OG> To:;;
OG> Sent: Wednesday, August 23, 2006 1:44:29 PM
OG> Subject: Fwd: Re[2]: 30 milllion+ docs on a single server

OG> Hi guys!

OG> I'm not sure my mail below arrived correctly to the list as I didn't
OG> receive it by mail subscription. I can see it only at Nabble:

OG> I hope the solution below will help.

OG> Best regards,
OG> Artem

OG> ===8<==============Original message text===============
OG> Hi guys!

OG> I have noticed many questions on the list vonsidering Lucene sorting
OG> memory consumption and hope my solution can help someone.

OG> I faced a memory/time consumption problem on sorting in Lucene back in
OG> April. With a help of this list's experts I came to solution which I
OG> like: documents from the sorting set (instead of given the field's
OG> values from the whole index) are lazy-cached in a WeakHashMap so the
OG> cached items are candidates for GC. I didn't create a patch yet (and
OG> I'm going to make it) but the code is ready to be reused and it's used
OG> for a while as a part of my open-source project, sharehound
OG> ( The code can be now reached by a
OG> CVS browser, it's in 4 classes in subdirectories of

OG> They (both classes, as a part of sharehound.jar, and sources) can also
OG> be downloaded with the latest (1.1.3 alpha) sharehound release zip
OG> file.

OG> LazyCachingSortFactory class have an example of use in its header
OG> comments, I duplicate it here:

OG> /**
OG>  * Creates a Sort that doesn't use FieldCache and doesn't therefore
OG> load all the field values from the index while sorting.
OG>  * Instead it uses CachingIndexReader (via
OG> CachingDocFieldComparatorSource) to cache documents from which field values
OG>  * are fetched. If the caller Searcher is based on CachingIndexReader
OG> itself its document cache will be used here.
OG>  *
OG>  *
OG>  * An example of use:
OG>   ...
OG>   hits = getQueryHits(query, getSort(listSorting.getSortFieldName(), listSorting.isSortDescending()));
OG>   ...

OG>   public Sort getSort(String sortFieldName, boolean sortDescending) {
OG>     return LazyCachingSortFactory.create(sortFieldName, sortDescending);
OG>   }
OG>   ...
OG>   protected Hits getQueryHits(Query query, Sort sort) throws IOException {
OG>      IndexSearcher indexSearcher = new
OG> IndexSearcher(CachingIndexReader.decorateIfNeeded(;
OG>      return, sort);
OG>   }

OG> */

OG> This solution does great work saving a memory and in case of
OG> relatively search resultsets it's almost as fast as the default
OG> implementation. Note that this solution is ready only for single-field
OG> sorting currently.

OG> Best regards,
OG> Artem

OG>> This is unlikely to work well/fast.  It will depend on the
OG>> size of the index (not in terms of the number of docs, but its
OG>> physical size), the number of queries/second and desired query
OG>> latency.  If you can wait 10 seconds to get a query and if only a
OG>> few queries are hitting the server at any one time, then you may
OG>> be Ok.  Having things be up to date with non-relevancy sorting
OG>> will be quite tough.  FieldCache will consume some RAM.  Warming
OG>> it up will take some number of seconds.  Re-opening an
OG>> IndexSearcher after index changes will also cost you a bit of time.

OG>> Consider a 64-bit server with more RAM that allowed larger
OG>> Java heaps, and try to fit your index into RAM.

OG>> Otis

OG>> ----- Original Message ----
OG>> From: Mark Miller <>
OG>> To:
OG>> Sent: Saturday, August 12, 2006 7:45:15 PM
OG>> Subject: Re: 30 milllion+ docs on a single server

OG>> The single server is important because I think it will take a lot of
OG>> work to scale it to multiple servers. The index must allow for close to
OG>> real-time updates and additions. It must also remain searchable at all
OG>> times (other than than during the brief period of single updates and
OG>> additions). If it is easy to scale this to multiple servers please tell
OG>> me how.

OG>> - Mark
>>> Why is a single server so important?  I can scale horizontally much
>>> cheaper
>>> than I scale vertically.
>>> On 8/11/06, Mark Miller <> wrote:
>>>> I've made a nice little archive application with lucene. I made it to
>>>> handle our largest need: 2.5 million docs or so on a single server. Now
>>>> the powers that be say: lets use it for a 30+ million document archive
>>>> on a single server! (each doc size maybe 10k small as a 1 or
>>>> 2k) Please tell me why we are in trouble...please tell me why we are
>>>> not. I have tested up to 2 million docs without much trouble but 30
>>>> million...the average search will include a sort on a field as
>>>> well...can I search 30+ million docs with a sort? Man am I worried about
>>>> that. Maybe the server will have 8 procs and 12 billion gigs of RAM.
>>>> Mabye. Even still, Tomcat seems to be able to launch with a max of 1.5
>>>> or 1.6 gig of Ram in Windows. What do you think? 30 million+ sounds like
>>>> too much of a load to me for a single server. Not that they care what I
>>>> think...I only wrote the thing (man I hate my job, offer me a new one :)
>>>> )...please...comments?
>>>> Cheers,
>>>> Miserable Mark
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OG> ===8<===========End of original message text===========

Best regards,
===8<===========End of original message text===========

Best regards,

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