[ https://issues.apache.org/jira/browse/FLINK-3226?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15129042#comment-15129042 ]
ASF GitHub Bot commented on FLINK-3226: --------------------------------------- GitHub user fhueske opened a pull request: https://github.com/apache/flink/pull/1579 [FLINK-3226] Add DataSet scan and conversion to DataSet[Row] You can merge this pull request into a Git repository by running: $ git pull https://github.com/fhueske/flink dataSetTrans Alternatively you can review and apply these changes as the patch at: https://github.com/apache/flink/pull/1579.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 #1579 ---- commit c0073a13fcbbe4a730c2d967561838a28d574c2d Author: Fabian Hueske <fhue...@apache.org> Date: 2016-02-02T16:15:28Z [FLINK-3226] Add DataSet scan and conversion to DataSet[Row] ---- > 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)