[
https://issues.apache.org/jira/browse/FLINK-2828?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15022068#comment-15022068
]
ASF GitHub Bot commented on FLINK-2828:
---------------------------------------
Github user tillrohrmann commented on a diff in the pull request:
https://github.com/apache/flink/pull/1237#discussion_r45600786
--- Diff:
flink-staging/flink-table/src/main/scala/org/apache/flink/api/java/table/JavaBatchTranslator.scala
---
@@ -54,6 +55,22 @@ class JavaBatchTranslator extends PlanTranslator {
Table(Root(rowDataSet, resultFields))
}
+ override def createTable(tableSource: TableSource): Table = {
+ // a TableSource requires an ExecutionEnvironment
+ if (env.isEmpty) {
+ throw new ExpressionException("This operation requires an
ExecutionEnvironment.")
+ }
+ tableSource match {
+ case adaptive: AdaptiveTableSource => Table(Root(adaptive,
adaptive.getOutputFields()))
+
+ case static: StaticTableSource =>
+ createTable(static.createStaticDataSet(env.get),
--- End diff --
I think it's more scalaesque to use Scala's pattern matching to extract the
`ExecutionEnvironment` from `env` instead of the `if` check with a following
`get`.
> 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)
