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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