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https://issues.apache.org/jira/browse/FLINK-2828?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15045666#comment-15045666
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ASF GitHub Bot commented on FLINK-2828:
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Github user aljoscha commented on the pull request:
https://github.com/apache/flink/pull/1237#issuecomment-162654340
You are right of course and I'm sorry I didn't put in the required time
earlier.
Your are also right about the Calcite thing. If we decide to use calcite
and have the Table API basically as another fronted to generate SQL plans then
the Table API optimization part can be very thin. In that case we would also
not need the Predicate push down as implemented as part of this PR, though, and
can keep it lean and simple.
> 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}
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