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From Steve Rowe <>
Subject Re: Deep paging in parallel with solr cloud - OutOfMemory
Date Mon, 17 Mar 2014 20:31:02 GMT
Hi Mike,

The OOM you’re seeing is likely a result of the bug described in (and fixed by a commit
under) SOLR-5875: <>.

If you can build from source, it would be great if you could confirm the fix addresses the
issue you’re facing.

This fix will be part of a to-be-released Solr 4.7.1.


On Mar 17, 2014, at 4:14 PM, Mike Hugo <> wrote:

> Hello,
> We recently upgraded to Solr Cloud 4.7 (went from a single node Solr 4.0
> instance to 3 node Solr 4.7 cluster).
> Part of out application does an automated traversal of all documents that
> match a specific query.  It does this by iterating through results by
> setting the start and rows parameters, starting with start=0 and rows=1000,
> then start=1000, rows=1000, start = 2000, rows=1000, etc etc.
> We do this in parallel fashion with multiple workers on multiple nodes.
> It's easy to chunk up the work to be done by figuring out how many total
> results there are and then creating 'chunks' (0-1000, 1000-2000, 2000-3000)
> and sending each chunk to a worker in a pool of multi-threaded workers.
> This worked well for us with a single server.  However upon upgrading to
> solr cloud, we've found that this quickly (within the first 4 or 5
> requests) causes an OutOfMemory error on the coordinating node that
> receives the query.   I don't fully understand what's going on here, but it
> looks like the coordinating node receives the query and sends it to the
> shard requested.  For example, given:
> shards=shard3&sort=id+asc&start=4000&q=*:*&rows=1000
> The coordinating node sends this query to shard3:
> NOW=1395086719189&shard.url=
> http://shard3_url_goes_here:8080/solr/collection1/&fl=id&sort=id+asc&start=0&q=*:*&distrib=false&wt=javabin&isShard=true&fsv=true&version=2&rows=5000
> Notice the rows parameter is 5000 (start + rows).  If the coordinator node
> is able to process the result set (which works for the first few pages,
> after that it will quickly run out of memory), it eventually issues this
> request back to shard3:
> NOW=1395086719189&shard.url=
> and then finally returns the response to the client.
> One possible workaround:  We've found that if we issue non-distributed
> requests to specific shards, that we get performance along the same lines
> that we did before.  E.g. issue a query with shards=shard3&distrib=false
> directly to the url of the shard3 instance, rather than going through the
> cloud solr server solrj API.
> The other workaround is to adapt to use the new new cursorMark
> functionality.  I've manually tried a few requests and it is pretty
> efficient, and doesn't result in the OOM errors on the coordinating node.
> However, i've only done this in single threaded manner.  I'm wondering if
> there would be a way to get cursor marks for an entire result set at a
> given page interval, so that they could then be fed to the pool of parallel
> workers to get the results in parallel rather than single threaded.  Is
> there a way to do this so we could process the results in parallel?
> Any other possible solutions?  Thanks in advance.
> Mike

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