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ASF GitHub Bot commented on FLINK-3226: --------------------------------------- GitHub user vasia opened a pull request: https://github.com/apache/flink/pull/1600 [FLINK-3226] Translate logical aggregations to physical This PR builds on #1567 and addresses @fhueske's comments on translating aggregations. Join translation is not part of this PR. You can merge this pull request into a Git repository by running: $ git pull https://github.com/vasia/flink LogicalToPhysical Alternatively you can review and apply these changes as the patch at: https://github.com/apache/flink/pull/1600.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 #1600 ---- commit 6676aab520bd648c360f70a2047196d004ce1d31 Author: chengxiang li <chengxiang...@intel.com> Date: 2016-02-01T07:18:14Z [Flink-3226] Translate logical plan FlinkRels into physical plan DataSetRels. commit cf41b740d32768185ec692e93754056ff6a16b59 Author: vasia <va...@apache.org> Date: 2016-02-04T14:53:52Z [FLINK-3226] implement GroupReduce translation; enable tests for supported operations - compute average as sum and count for byte, short and int type to avoid rounding errors ---- > Translate optimized logical Table API plans into physical plans representing > DataSet programs > --------------------------------------------------------------------------------------------- > > Key: FLINK-3226 > URL: https://issues.apache.org/jira/browse/FLINK-3226 > Project: Flink > Issue Type: Sub-task > Components: Table API > Reporter: Fabian Hueske > Assignee: Chengxiang Li > > This issue is about translating an (optimized) logical Table API (see > FLINK-3225) query plan into a physical plan. The physical plan is a 1-to-1 > representation of the DataSet program that will be executed. This means: > - Each Flink RelNode refers to exactly one Flink DataSet or DataStream > operator. > - All (join and grouping) keys of Flink operators are correctly specified. > - The expressions which are to be executed in user-code are identified. > - All fields are referenced with their physical execution-time index. > - Flink type information is available. > - Optional: Add physical execution hints for joins > The translation should be the final part of Calcite's optimization process. > For this task we need to: > - implement a set of Flink DataSet RelNodes. Each RelNode corresponds to one > Flink DataSet operator (Map, Reduce, Join, ...). The RelNodes must hold all > relevant operator information (keys, user-code expression, strategy hints, > parallelism). > - implement rules to translate optimized Calcite RelNodes into Flink > RelNodes. We start with a straight-forward mapping and later add rules that > merge several relational operators into a single Flink operator, e.g., merge > a join followed by a filter. Timo implemented some rules for the first SQL > implementation which can be used as a starting point. > - Integrate the translation rules into the Calcite optimization process -- This message was sent by Atlassian JIRA (v6.3.4#6332)