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ASF GitHub Bot commented on FLINK-2828: --------------------------------------- Github user aljoscha commented on a diff in the pull request: https://github.com/apache/flink/pull/1237#discussion_r44515720 --- Diff: flink-scala/src/main/scala/org/apache/flink/api/scala/ExecutionEnvironment.scala --- @@ -64,15 +62,19 @@ import scala.reflect.ClassTag * created. If the program is submitted to a cluster a remote execution environment will * be created. */ -class ExecutionEnvironment(javaEnv: JavaEnv) { +class ExecutionEnvironment(javaEnv: JavaEnv) extends AbstractExecutionEnvironment { /** - * @return the Java Execution environment. + * Returns the enclosed Java ExecutionEnvironment for special use cases. + * + * @return reference to the ExecutionEnvironment of the Java API */ def getJavaEnv: JavaEnv = javaEnv + /** * Gets the config object. */ + @Override --- End diff -- In Scala override is done as: ``` override def getConfig ... ``` this is also in StreamExecutionEnvironment.scala > Add interfaces for Table API input formats > ------------------------------------------ > > Key: FLINK-2828 > URL: https://issues.apache.org/jira/browse/FLINK-2828 > Project: Flink > Issue Type: New Feature > Components: Table API > Reporter: Timo Walther > Assignee: Timo Walther > > In order to support input formats for the Table API, interfaces are > necessary. I propose two types of TableSources: > - AdaptiveTableSources can adapt their output to the requirements of the > plan. Although the output schema stays the same, the TableSource can react on > field resolution and/or predicates internally and can return adapted > DataSet/DataStream versions in the "translate" step. > - StaticTableSources are an easy way to provide the Table API with additional > input formats without much implementation effort (e.g. for fromCsvFile()) > TableSources need to be deeply integrated into the Table API. > The TableEnvironment requires a newly introduced AbstractExecutionEnvironment > (common super class of all ExecutionEnvironments for DataSets and > DataStreams). > Here's what a TableSource can see from more complicated queries: > {code} > getTableJava(tableSource1) > .filter("a===5 || a===6") > .select("a as a4, b as b4, c as c4") > .filter("b4===7") > .join(getTableJava(tableSource2)) > .where("a===a4 && c==='Test' && c4==='Test2'") > // Result predicates for tableSource1: > // List("a===5 || a===6", "b===7", "c==='Test2'") > // Result predicates for tableSource2: > // List("c==='Test'") > // Result resolved fields for tableSource1 (true = filtering, > false=selection): > // Set(("a", true), ("a", false), ("b", true), ("b", false), ("c", false), > ("c", true)) > // Result resolved fields for tableSource2 (true = filtering, > false=selection): > // Set(("a", true), ("c", true)) > {code} -- This message was sent by Atlassian JIRA (v6.3.4#6332)