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https://issues.apache.org/jira/browse/FLINK-5226?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15715683#comment-15715683
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ASF GitHub Bot commented on FLINK-5226:
---------------------------------------
GitHub user fhueske opened a pull request:
https://github.com/apache/flink/pull/2926
[FLINK-5226] [table] Use correct DataSetCostFactory and improve DataSetCalc
costs.
- Improved DataSetCalc costs make projections cheap and help to push them
down.
- Adapted existing tests that check optimized plans
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/fhueske/flink tableEagerProject
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/flink/pull/2926.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 #2926
----
commit 11142952016f3777eb3305aead0f83e9271fe736
Author: Fabian Hueske <[email protected]>
Date: 2016-12-02T14:28:16Z
[FLINK-5226] [table] Use correct DataSetCostFactory and improve DataSetCalc
costs.
- Improved DataSetCalc costs make projections cheap and help to push them
down.
----
> Eagerly project unused attributes
> ---------------------------------
>
> Key: FLINK-5226
> URL: https://issues.apache.org/jira/browse/FLINK-5226
> Project: Flink
> Issue Type: Improvement
> Components: Table API & SQL
> Affects Versions: 1.2.0
> Reporter: Fabian Hueske
> Assignee: Fabian Hueske
>
> The optimizer does currently not eagerly remove unused attributes.
> For example given a table {{tab5}} with five attributes {{a, b, c, d, e}},
> the following query
> {code}
> SELECT x.a, y.b FROM tab5 AS x, tab5 AS y WHERE x.a = y.a
> {code}
> would result in the non-optimized plan
> {code}
> LogicalProject(a=[$0], b=[$6])
> LogicalFilter(condition=[=($0, $5)])
> LogicalJoin(condition=[true], joinType=[inner])
> LogicalTableScan(table=[[tab5]])
> LogicalTableScan(table=[[tab5]])
> {code}
> and the optimized plan:
> {code}
> DataSetCalc(select=[a, b0 AS b])
> DataSetJoin(where=[=(a, a0)], join=[a, b, c, d, e, a0, b0, c0, d0, e0],
> joinType=[InnerJoin])
> DataSetScan(table=[[_DataSetTable_0]])
> DataSetScan(table=[[_DataSetTable_0]])
> {code}
> This plan is inefficient because it joins all ten attributes of both tables
> instead of eagerly projecting out all unused fields ({{x.b, x.c, x.d, x.e,
> y.c, y.d, y.e}}).
> Since this is one of the most common optimizations, I would assume that
> Calcite provides some rules to extract eager projections. If this is the
> case, the issue can be solved by adding such rules to {{FlinkRuleSets}}.
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