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From Ian Lea <ian....@gmail.com>
Subject Re: Lucene Indexing out of memory
Date Tue, 02 Mar 2010 13:59:55 GMT
Where exactly are you hitting the OOM exception?  Have you got a stack
trace?  How much memory are you allocating to the JVM? Have you run a
profiler to find out what is using the memory?

If it runs OK for 70K docs then fails, 2 possibilities come to mind:
either the 70K + 1 doc is particularly large, or you or lucene
(unlikely) are holding on to something that you shouldn't be.


--
Ian.


On Tue, Mar 2, 2010 at 1:48 PM, ajay_gupta <ajay978@gmail.com> wrote:
>
> Hi Erick,
> I tried setting setRAMBufferSizeMB  as 200-500MB as well but still it goes
> OOM error.
> I thought its filebased indexing so memory shouldn't be an issue but you
> might be right that when searching it might be using lot of memory ? Is
> there way to load documents in chunks or someothere way to make it scalable
> ?
>
> Thanks in advance
> Ajay
>
>
> Erick Erickson wrote:
>>
>> I'm not following this entirely, but these docs may be huge by the
>> time you add context for every word in them. You say that you
>> "search the existing indices then I get the content and append....".
>> So is it possible that after 70K documents your additions become
>> so huge that you're blowing up? Have you taken any measurements
>> to determine how big the docs get as you index more and more
>> of them?
>>
>> If the above is off base, have you tried setting
>> IndexWriter.setRAMBufferSizeMB?
>>
>> HTH
>> Erick
>>
>> On Tue, Mar 2, 2010 at 8:27 AM, ajay_gupta <ajay978@gmail.com> wrote:
>>
>>>
>>> Hi,
>>> It might be general question though but I couldn't find the answer yet. I
>>> have around 90k documents sizing around 350 MB. Each document contains a
>>> record which has some text content. For each word in this text I want to
>>> store context for that word and index it so I am reading each document
>>> and
>>> for each word in that document I am appending fixed number of surrounding
>>> words. To do that first I search in existing indices if this word already
>>> exist and if it is then I get the content and append the new context and
>>> update the document. In case no context exist I create a document with
>>> fields "word" and "context" and add these two fields with values as word
>>> value and context value.
>>>
>>> I tried this in RAM but after certain no of docs it gave out of memory
>>> error
>>> so I thought to use FSDirectory method but surprisingly after 70k
>>> documents
>>> it also gave OOM error. I have enough disk space but still I am getting
>>> this
>>> error.I am not sure even for disk based indexing why its giving this
>>> error.
>>> I thought disk based indexing will be slow but atleast it will be
>>> scalable.
>>> Could someone suggest what could be the issue ?
>>>
>>> Thanks
>>> Ajay
>>> --
>>> View this message in context:
>>> http://old.nabble.com/Lucene-Indexing-out-of-memory-tp27755872p27755872.html
>>> Sent from the Lucene - Java Users mailing list archive at Nabble.com.
>>>
>>>
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>>>
>>
>>
>
> --
> View this message in context: http://old.nabble.com/Lucene-Indexing-out-of-memory-tp27755872p27756082.html
> Sent from the Lucene - Java Users mailing list archive at Nabble.com.
>
>
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