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From "Bill Bell (JIRA)" <j...@apache.org>
Subject [jira] Commented: (SOLR-2218) Performance of start= and rows= parameters are exponentially slow with large data sets
Date Fri, 05 Nov 2010 16:48:43 GMT

    [ https://issues.apache.org/jira/browse/SOLR-2218?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12928674#action_12928674
] 

Bill Bell commented on SOLR-2218:
---------------------------------

Lance,

Can you point me directly to the document on Lucid's website? That search returns a Luke handler,
that is not what I am asking.

1. I have a query that returns thousands of results.
2. I want to return fl=id, start=1000, rows=1000 and af I move start farther from 0, the results
slow down substantially. 
3. Need the results to come back quickly even when start=10000 if I am looping across all
the results.


> 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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