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Date: Thu, 4 Nov 2010 23:02:42 -0400 (EDT)
From: "Lance Norskog (JIRA)" <jira@apache.org>
To: dev@lucene.apache.org
Subject: [jira] Commented: (SOLR-2218) Performance of start= and rows=
 parameters are exponentially slow with large data sets
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    [ https://issues.apache.org/jira/browse/SOLR-2218?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12928457#action_12928457 ] 

Lance Norskog commented on SOLR-2218:
-------------------------------------

There is a workaround for this called _docid_. 

http://www.lucidimagination.com/search/?q=_docid_#/p:solr

> Performance of start= and rows= parameters are exponentially slow with large data sets
> --------------------------------------------------------------------------------------
>
>                 Key: SOLR-2218
>                 URL: https://issues.apache.org/jira/browse/SOLR-2218
>             Project: Solr
>          Issue Type: Improvement
>          Components: Build
>    Affects Versions: 1.4.1
>            Reporter: Bill Bell
>
> With large data sets, > 10M rows.
> Setting start=<large number> and rows=<large numbers> is slow, and gets slower the farther you get from start=0 with a complex query. Random also makes this slower.
> Would like to somehow make this performance faster for looping through large data sets. It would be nice if we could pass a pointer to the result set to loop, or support very large rows=<number>.
> Something like:
> rows=1000
> start=0
> spointer=string_my_query_1
> Then within interval (like 5 mins) I can reference this loop:
> Something like:
> rows=1000
> start=1000
> spointer=string_my_query_1
> What do you think? Since the data is too great the cache is not helping.

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