[ https://issues.apache.org/jira/browse/FLINK-3226?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15158704#comment-15158704 ]
ASF GitHub Bot commented on FLINK-3226: --------------------------------------- Github user fhueske commented on a diff in the pull request: https://github.com/apache/flink/pull/1679#discussion_r53763441 --- Diff: flink-libraries/flink-table/src/test/scala/org/apache/flink/api/scala/table/test/StringExpressionsITCase.scala --- @@ -18,42 +18,20 @@ package org.apache.flink.api.scala.table.test -import org.apache.flink.api.table.{Row, ExpressionException} import org.apache.flink.api.scala._ import org.apache.flink.api.scala.table._ -import org.apache.flink.test.util.{TestBaseUtils, MultipleProgramsTestBase} +import org.apache.flink.api.table.Row import org.apache.flink.test.util.MultipleProgramsTestBase.TestExecutionMode +import org.apache.flink.test.util.{MultipleProgramsTestBase, TestBaseUtils} import org.junit._ import org.junit.runner.RunWith import org.junit.runners.Parameterized + import scala.collection.JavaConverters._ -import org.apache.flink.api.table.codegen.CodeGenException @RunWith(classOf[Parameterized]) class StringExpressionsITCase(mode: TestExecutionMode) extends MultipleProgramsTestBase(mode) { - @Test(expected = classOf[CodeGenException]) --- End diff -- Why did you remove these tests? The `ScalarFunctionsTest` does not test the feature end-to-end, right? > 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)