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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_r139471847 --- Diff: docs/dev/table/sql.md --- @@ -89,15 +117,16 @@ val result2 = tableEnv.sql( Supported Syntax ---------------- -Flink parses SQL using [Apache Calcite](https://calcite.apache.org/docs/reference.html), which supports standard ANSI SQL. DML and DDL statements are not supported by Flink. +Flink parses SQL using [Apache Calcite](https://calcite.apache.org/docs/reference.html), which supports standard ANSI SQL. DDL statements are not supported by Flink. The following BNF-grammar describes the superset of supported SQL features in batch and streaming queries. The [Operations](#operations) section shows examples for the supported features and indicates which features are only supported for batch or streaming queries. ``` query: values - | { + |[ insert into tableReference ] --- End diff -- change to `|[ insert tableReference ]` and verify. Should actually also moved before `values` because we can use this as well to write literal rows to the sink > 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)