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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-3850) Add forward field annotations to DataSet operators generated by the Table API
Date Wed, 08 Mar 2017 22:06:40 GMT

    [ https://issues.apache.org/jira/browse/FLINK-3850?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15902058#comment-15902058

ASF GitHub Bot commented on FLINK-3850:

Github user fhueske commented on a diff in the pull request:

    --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/plan/nodes/dataset/DataSetCorrelate.scala
    @@ -97,18 +103,41 @@ class DataSetCorrelate(
         val sqlFunction = rexCall.getOperator.asInstanceOf[TableSqlFunction]
         val pojoFieldMapping = sqlFunction.getPojoFieldMapping
         val udtfTypeInfo = sqlFunction.getRowTypeInfo.asInstanceOf[TypeInformation[Any]]
    +    val returnType = FlinkTypeFactory.toInternalRowTypeInfo(getRowType)
         val mapFunc = correlateMapFunction(
    +      returnType,
    -    inputDS.flatMap(mapFunc).name(correlateOpName(rexCall, sqlFunction, relRowType))
    +    def getIndices = {
    --- End diff --
    A correlate forwards all fields from the input and the table function like this `[in1,
in2, in3, tf1, tf2]` for an input `[in1, in2, in3]` and table function `[tf1, tf2]`. So we
can do a simple position based mapping of the fields of the input type against the output
type (field names might change). Basically similar to what you are doing with the single row
    We do not need to look at the table function or the condition.

> Add forward field annotations to DataSet operators generated by the Table API
> -----------------------------------------------------------------------------
>                 Key: FLINK-3850
>                 URL: https://issues.apache.org/jira/browse/FLINK-3850
>             Project: Flink
>          Issue Type: Improvement
>          Components: Table API & SQL
>            Reporter: Fabian Hueske
>            Assignee: Nikolay Vasilishin
> The DataSet API features semantic annotations [1] to hint the optimizer which input fields
an operator copies. This information is valuable for the optimizer because it can infer that
certain physical properties such as partitioning or sorting are not destroyed by user functions
and thus generate more efficient execution plans.
> The Table API is built on top of the DataSet API and generates DataSet programs and code
for user-defined functions. Hence, it knows exactly which fields are modified and which not.
We should use this information to automatically generate forward field annotations and attach
them to the operators. This can help to significantly improve the performance of certain jobs.
> [1] https://ci.apache.org/projects/flink/flink-docs-release-1.0/apis/batch/index.html#semantic-annotations

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