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From Grant Ingersoll <>
Subject Re: Optimizing index takes too long
Date Mon, 12 Nov 2007 02:30:59 GMT
Not sure the numbers are off w/ documents that big, although I imagine  
you are hitting the token limit w/ docs that big.  Is this all on one  
machine as you described, or are you saying you have a couple of  
these?  If one, have you tried having just one index?

Since you are using 2.3 (note to other readers, 2.3 is NOT released  
yet, he really means 2.3-dev), are which MergeScheduler and  
MergePolicy are you using?  Can you do some profiling to see where is  
spending time?

Also, maybe Mike M. can chime in w/ how compressed fields are merged  
now.  I want to say that with the new indexing changes, they are all  
done right away and not revisited so that shouldn't be an issue.   
Having said that, I am a bit confused by some of your terminology.   
You say some Fields are stored twice, but then say they are not  
stored.  Can you share what the actual Field constructions are?    
There probably isn't a reason to compress the short biblio fields.   
Lucene Field compression, while not deprecated, really isn't  
recommended, b/c it doesn't give the application much control (since  
it uses the highest level of compression and is not tunable.)  The  
better approach is to do the compression yourself and store as a  
binary.  Again, though, it doesn't sound like you need compression for  
those fields.

Are you using compound file format or not?

Also, were you using 2.2 before and upgraded, or is this an  
application built on 2.3 to begin with?  If on 2.2, did you see these  
problems before?


On Nov 11, 2007, at 8:49 PM, Mark Miller wrote:

> For a start, I would lower the merge factor quite a bit. A high  
> merge factor is over rated :) You will build the index faster, but  
> searches will be slower and an optimize takes much longer.  
> Essentially, the time you save when indexing is paid when optimizing  
> anyway. You might as well amortize the cost with a lower merge factor.
> Grant seems to think the numbers are off anyway, so you may have  
> more to do -- just a suggestion about the merge factor. How much RAM  
> are you giving your application?
> With a machine with 8 cores and 15,000rpm, days does seem a little  
> ridiculous.
> - Mark
> Barry Forrest wrote:
>> Hi,
>> Thanks for your help.
>> I'm using Lucene 2.3.
>> Raw document size is about 138G for 1.5M documents, which is about
>> 250k per document.
>> IndexWriter settings are MergeFactor 50, MaxMergeDocs 2000,
>> RAMBufferSizeMB 32, MaxFieldLength Integer.MAX_VALUE.
>> Each document has about 10 short bibliographic fields and 3 longer
>> content fields and 1 field that contains the entire contents of the
>> document.  The longer content fields are stored twice - in a stemmed
>> and unstemmed form.  So actually there are about 8 longer content
>> fields.  (The effect of storing stemmed and unstemmed versions is to
>> approximately double the index size over storing the content only
>> once).  About half the short bibliographic fields are stored
>> (compressed) in the index.  The longer content fields are not stored,
>> and no term vectors are stored.
>> The hardware is quite new and fast: 8 cores, 15,000 RPM disks.
>> Thanks again
>> Barry
>> On Nov 12, 2007 10:41 AM, Grant Ingersoll <>  
>> wrote:
>>> Hmmm, something doesn't sound quite right.  You have 10 million  
>>> docs,
>>> split into 5 or so indexes, right?  And each sub index is 150
>>> gigabytes?  How big are your documents?
>>> Can you provide more info about what your Directory and IndexWriter
>>> settings are?  What version of Lucene are you using?  What are your
>>> Field settings?  Are you storing info?  What about Term Vectors?
>>> Can you explain more about your documents, etc?  10 million doesn't
>>> sound like it would need to be split up that much, if at all,
>>> depending on your hardware.
>>> The wiki has some excellent resources on improving both indexing and
>>> search speed.
>>> -Grant
>>> On Nov 11, 2007, at 6:16 PM, Barry Forrest wrote:
>>>> Hi,
>>>> Optimizing my index of 1.5 million documents takes days and days.
>>>> I have a collection of 10 million documents that I am trying to  
>>>> index
>>>> with Lucene.  I've divided the collection into chunks of about  
>>>> 1.5 - 2
>>>> million documents each.  Indexing 1.5 documents is fast enough  
>>>> (about
>>>> 12 hours), but this results in an index directory containing about
>>>> 35000 files.  Optimizing this index takes several days, which is  
>>>> a bit
>>>> too long for my purposes.  Each sub-index is about 150G.
>>>> What can I do to make this process faster?
>>>> Thanks for your help,
>>>> Barry
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