Yes, I understand that, and I did mean the number of documents, but I read in the javadoc that:

"For String fields, the cache is larger: in addition to the above array, the value of every term in the field is kept in memory. If there are many unique terms in the field, this could be quite large."

and in one of the mails on the mailinglist i read:
"So if your field is an Int your talking numDocs*32 bits for your
cache. For a Long field its numDocs*64. For a String field Lucene caches
a String array with every unique term and then an int array indexing
into the term array."

But yes, I understand that the memory drain should not be significant due to the String field in our case since, but the fact that we have so many documents. Still, if we have 30 000 000 docs * 10 bytes = ~300 mb (ok I was a bit off there... :p) If we had a long field instead, it would be about 220 mb or something like that? hmm..

But does that mean that I will just have to reduce my index (at least for the sorting) ?
No other option?


Cheers, and thanks for your help!
 - Aleks

On Fri, 10 Oct 2008 16:43:35 +0200, mark harwood <[EMAIL PROTECTED]> wrote:

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 <[EMAIL PROTECTED]>
To: java-user@lucene.apache.org
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?

cheers,
  Aleksander


On Fri, 10 Oct 2008 15:18:46 +0200, mark harwood <[EMAIL PROTECTED]>
wrote:

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 <[EMAIL PROTECTED]>
To: java-user@lucene.apache.org
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
<[EMAIL PROTECTED]> 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
[EMAIL PROTECTED]

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