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https://issues.apache.org/jira/browse/FLINK-2828?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15258192#comment-15258192
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ASF GitHub Bot commented on FLINK-2828:
---------------------------------------
Github user vasia commented on a diff in the pull request:
https://github.com/apache/flink/pull/1939#discussion_r61098044
--- Diff: docs/apis/batch/libs/table.md ---
@@ -67,6 +67,165 @@ The central concept of the Table API is a `Table` which
represents a table with
The following sections show by example how to use the Table API embedded
in the Scala and Java DataSet APIs.
+### Registering Tables to and Accessing Tables from TableEnvironments
+
+`TableEnvironment`s have an internal table catalog to which tables can be
registered with a unique name. After registration, a table can be accessed from
the `TableEnvironment` by its name. Tables can be registered in different ways.
--- End diff --
Shall we add a comment that registering a table is only required for SQL
queries and not for "pure" Table API programs?
> 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: Fabian Hueske
>
> 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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