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https://issues.apache.org/jira/browse/SOLR-2218?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12976606#action_12976606
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Bill Bell commented on SOLR-2218:
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Hoss,
So what you are saying is instead of:
1. http://hostname/solr/select?fl=id&start=20000&rows=1000&q=*:*&sort=id asc
I should use:
LAST_ID=20000
1. http://hostname/solr/select?fl=id&rows=1000&q=*:*&sort=id
asc&fq=id:[<LAST_ID> TO *]
This should definately be faster. Unfortunately, I need the results by highest
score. Does fq support score?
SCORE=5.6
1. http://hostname/solr/select?fl=id,score&rows=1000&q=*:*&sort=score
desc&fq=id:[0 to <SCORE>]
Thoughts?
> 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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