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https://issues.apache.org/jira/browse/FLINK-6442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16170688#comment-16170688
]
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_r139522124
--- Diff:
flink-libraries/flink-table/src/main/scala/org/apache/flink/table/api/BatchTableEnvironment.scala
---
@@ -106,6 +106,56 @@ abstract class BatchTableEnvironment(
}
/**
+ * Registers an external [[TableSink]] with given field names and types
in this
+ * [[TableEnvironment]]'s catalog. Registered sink tables can be
referenced in SQL DML clause.
+ *
+ * Examples:
+ *
+ * - predefine a table sink and its field names and types
+ * {{{
+ * val fieldNames: Array[String] = Array("a", "b", "c")
+ * val fieldTypes: Array[TypeInformation[_]] = Array(Types.STRING,
Types.INT, Types.LONG)
+ * val tableSink: TableSink = new YourTableSinkImpl(...)
+ * }}}
+ *
+ * - register an alias for this table sink to catalog
+ * {{{
+ * tableEnv.registerTableSink("example_sink_table", fieldNames,
fieldsTypes, tableSink)
+ * }}}
+ *
+ * - use the registered sink in SQL directly
+ * {{{
+ * tableEnv.sqlInsert("INSERT INTO example_sink_table SELECT a, b, c
FROM sourceTable")
+ * }}}
+ *
+ * @param name The name under which the [[TableSink]] is
registered.
+ * @param tableSink The [[TableSink]] to register.
--- End diff --
add `fieldNames` and `fieldTypes` parameters
> 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
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