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ASF GitHub Bot commented on FLINK-6442: --------------------------------------- Github user fhueske commented on a diff in the pull request: https://github.com/apache/flink/pull/3829#discussion_r136125340 --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/api/TableEnvironment.scala --- @@ -1002,4 +1124,28 @@ object TableEnvironment { case d: DefinedFieldNames => d.getFieldIndices case _ => TableEnvironment.getFieldIndices(tableSource.getReturnType) } + + /** + * Returns field names for a given [[TableSink]]. + * + * @param tableSink The TableSink to extract field names from. + * @tparam A The type of the TableSink. + * @return An array holding the field names. + */ + def getFieldNames[A](tableSink: TableSink[A]): Array[String] = tableSink match { + case d: DefinedFieldNames => d.getFieldNames + case _ => TableEnvironment.getFieldNames(tableSink.getOutputType) + } + + /** + * Returns field indices for a given [[TableSink]]. + * + * @param tableSink The TableSink to extract field indices from. + * @tparam A The type of the TableSink. + * @return An array holding the field indices. + */ + def getFieldIndices[A](tableSink: TableSink[A]): Array[Int] = tableSink match { --- End diff -- We don't need this method. A `TableSink` is configured with a schema. It does not need indicies and should not implement `DefinedFieldNames`. > Extend TableAPI Support Sink Table Registration and ‘insert into’ Clause in > SQL > ------------------------------------------------------------------------------- > > Key: FLINK-6442 > URL: https://issues.apache.org/jira/browse/FLINK-6442 > Project: Flink > Issue Type: New Feature > Components: Table API & SQL > Reporter: lincoln.lee > Assignee: lincoln.lee > Priority: Minor > > Currently in TableAPI there’s only registration method for source table, > when we use SQL writing a streaming job, we should add additional part for > the sink, like TableAPI does: > {code} > val sqlQuery = "SELECT * FROM MyTable WHERE _1 = 3" > val t = StreamTestData.getSmall3TupleDataStream(env) > tEnv.registerDataStream("MyTable", t) > // one way: invoke tableAPI’s writeToSink method directly > val result = tEnv.sql(sqlQuery) > result.writeToSink(new YourStreamSink) > // another way: convert to datastream first and then invoke addSink > val result = tEnv.sql(sqlQuery).toDataStream[Row] > result.addSink(new StreamITCase.StringSink) > {code} > From the api we can see the sink table always be a derived table because its > 'schema' is inferred from the result type of upstream query. > Compare to traditional RDBMS which support DML syntax, a query with a target > output could be written like this: > {code} > insert into table target_table_name > [(column_name [ ,...n ])] > query > {code} > The equivalent form of the example above is as follows: > {code} > tEnv.registerTableSink("targetTable", new YourSink) > val sql = "INSERT INTO targetTable SELECT a, b, c FROM sourceTable" > val result = tEnv.sql(sql) > {code} > It is supported by Calcite’s grammar: > {code} > insert:( INSERT | UPSERT ) INTO tablePrimary > [ '(' column [, column ]* ')' ] > query > {code} > I'd like to extend Flink TableAPI to support such feature. see design doc: > https://goo.gl/n3phK5 -- This message was sent by Atlassian JIRA (v6.4.14#64029)