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https://issues.apache.org/jira/browse/IGNITE-3084?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15794332#comment-15794332
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Vladimir Ozerov commented on IGNITE-3084:
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Val,
Cool analysis! I would say that executing query-on-partition is very useful
feature. Not only it will help us with Spark, but will allow us to perform
certain useful SQL optimizations (e.g. IGNITE-4509 and IGNITE-4510).
I am not quite sure I understand how to work with plans and strategies. Does it
mean that we will have to analyze SQL somehow (e.g. build AST) to give correct
hints to Spark?
> Investigate how Ignite can support Spark DataFrame
> --------------------------------------------------
>
> Key: IGNITE-3084
> URL: https://issues.apache.org/jira/browse/IGNITE-3084
> Project: Ignite
> Issue Type: Task
> Components: Ignite RDD
> Affects Versions: 1.5.0.final
> Reporter: Vladimir Ozerov
> Assignee: Valentin Kulichenko
> Labels: bigdata
> Fix For: 2.0
>
>
> We see increasing demand on nice DataFrame support for our Spark integration.
> Need to investigate how could we do that.
> Looks like we can investigate how MemSQL do that and take it as a starting
> point.
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