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https://issues.apache.org/jira/browse/IGNITE-4106?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15778467#comment-15778467
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ASF GitHub Bot commented on IGNITE-4106:
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GitHub user AMashenkov opened a pull request:
https://github.com/apache/ignite/pull/1386
IGNITE-4106: SQL: parallelize sql queries over cache local partitions
Tree index splitted into segmentes in GridH2StripedTreeIndex
Tests added
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/gridgain/apache-ignite ignite-4106
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/ignite/pull/1386.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #1386
----
commit d013500bd897505ec6cbfb2f25d54f1f938f2f83
Author: AMRepo <[email protected]>
Date: 2016-12-26T14:54:01Z
Tree index splitted into segmentes in GridH2StripedTreeIndex
Tests added
commit 3202889b6005eaad77026e4682e7b6e8fb336ba5
Author: AMRepo <[email protected]>
Date: 2016-12-26T15:06:11Z
Tree index splitted into segmentes in GridH2StripedTreeIndex
Tests added
----
> SQL: parallelize sql queries over cache local partitions
> --------------------------------------------------------
>
> Key: IGNITE-4106
> URL: https://issues.apache.org/jira/browse/IGNITE-4106
> Project: Ignite
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 1.6, 1.7
> Reporter: Andrew Mashenkov
> Assignee: Andrew Mashenkov
> Labels: performance, sql
> Fix For: 2.0
>
> Attachments: 1node-4thread.jfr, 4node-1thread.jfr
>
>
> If we run SQL query on cache partitioned over several cluster nodes, it will
> be split into several queries running in parallel. But really we will have
> one thread per query on each node.
> So, for now, to improve SQL query performance we need to run more Ignite
> instances or split caches manually.
> It seems to be better to split local SQL queries over cache partitions, so we
> would be able to parallelize SQL query on every single node and utilize CPU
> more efficiently.
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