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From mark harwood <>
Subject Re: Question regarding sorting and memory consumption in lucene
Date Fri, 10 Oct 2008 14:43:35 GMT
I think you have your memory cost calculation wrong.
The cost is field size (10 bytes ?) times number of documents NOT number of unique terms.
The cache is essentially an array of  size reader.maxDoc() which is indexed directly into
on docId to retrieve field values.

You are right in needing to factor in the cost of keeping one active cache while busy warming-up
a new one so that effectively doubles the RAM requirements.

----- Original Message ----
From: Aleksander M. Stensby <>
Sent: Friday, 10 October, 2008 15:25:29
Subject: Re: Question regarding sorting and memory consumption in lucene

Unfortunately no, since the documents that are added may come form a new  
"source" containing old documents aswell..:/
I tried deploying our webapplication without any searcher objects and it  
consumes basically ~200mb of memory in tomcat.
With 6 searchers the same applications manages to consume over 2.5 GB of  
memory when warming... :(
I might have done some super-idiotic logic in the way I handle searching,  
but I can seriously not see what that might be...

But I assume that people deal with much larger indexes than this, right?


On Fri, 10 Oct 2008 15:18:46 +0200, mark harwood <>  

> Assuming content is added in chronological order and with no updates to  
> existing docs couldn't you rely on internal Lucene document id to give a  
> chronological sort order?
> That would require no memory cache at all when sorting.
> Querying across multiple indexes simultaneously however may present an  
> added complication...
> ----- Original Message ----
> From: Aleksander M. Stensby <>
> To:
> Sent: Friday, 10 October, 2008 13:51:50
> Subject: Re: Question regarding sorting and memory consumption in lucene
> I'll follow up on my own question...
> Let's say that we have 4 years of data, meaning that there will be  
> roughly
> 4 * 365 = 1460 unique terms for our sort field.
> For one index, lets say with 30 million docs, the cache should use approx
> 100mb, or am I wrong? and thus for 6 indexes we would need approx 600 mb
> for the caches? (and an additional 100mb every time we warm a new  
> searcher
> and swap it out...) As far as the string versus int or long goes, I don't
> really see any big gain in changig it since 1460 * 10  bytes extra memory
> doesnt really make much difference. Or?
> I guess we should consider reducing the index size or at least only allow
> sorted search on a subset of the index (or a pruned version of the
> index...) ? Would that be better for us?
> But then again, I assume that there are much larger lucene-based indexes
> out there than ours, and you guys must have some solution to this issue,
> right? :)
> best regards,
>   Aleksander
> On Fri, 10 Oct 2008 14:09:36 +0200, Aleksander M. Stensby
> <> wrote:
>> Hello, I've read a lot of threads now on memory consumption and sorting,
>> and I think I have a pretty good understanding of how things work, but I
>> could still need some input here..
>> We currently have a system consisting of 6 different lucene indexes (all
>> have the same structure, so you could say it is a form of sharding). We
>> currently use this approach because we want to be able to give users
>> access to different index (but not necessarily  all indexes) etc.
>> (We are planning to move to a solr-based system, but for now we would
>> like to solve this issue with our current lucene-based system.)
>> The thing is, the indexes are rather big (ranging from 5G to 20G per
>> index and 10 - 30 million entries per index.)
>> We keep one searcher object open per index, and when the index is
>> changed (new documents added in batches several times a day), we update
>> the searcher objects.
>> In the warmup procedure we did a couple of searches and things work
>> fine, BUT i realized that in our application we return hits sorted by
>> date by default, and our warmup procedure did non-sorted queries... so
>> still the first searches done by the user after an update was slow
>> (obviously).
>> To cope, I changed the warmup procedure to include a sorted search, and
>> now the user will not notice slow queries. Good!
>> But, the problem at hand is that we are running into memory problems
>> (and I understand that sorting does consume a lot of memory...) But is
>> there any way that is "best practice" to deal with this? The field we
>> sort on is an un_indexed text field representing the date. typically
>> "2008-10-10". I am aware that string field sorting consumes a lot of
>> memory, so should we change this field to something different? Would
>> this help us with the memory problems?
>> As a sidenote / couriosity question: Does it matter if we use the search
>> method returning Hits versus the search method returning TopFieldDocs?
>> (we are not iterating them in any way when this memory issue occurs)
>> Thanks in advance for any guidance we may get.
>> Best regards,
>>   Aleksander M. Stensby

Aleksander M. Stensby
Senior Software Developer
Integrasco A/S
+47 41 22 82 72

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