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https://issues.apache.org/jira/browse/FLINK-6442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16087344#comment-16087344
]
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_r127459823
--- Diff:
flink-libraries/flink-table/src/test/scala/org/apache/flink/table/api/scala/batch/sql/TableWithSQLITCase.scala
---
@@ -113,4 +116,31 @@ class TableWithSQLITCase(
val results = result.toDataSet[Row].collect()
TestBaseUtils.compareResultAsText(results.asJava, expected)
}
+
+ /** test insert into **/
+ @Test
+ def testInsertIntoTable(): Unit = {
+ val tmpFile = File.createTempFile("flink-sql-table-sink-test1", ".tmp")
+ tmpFile.deleteOnExit()
+ val path = tmpFile.toURI.toString
+
+ val env = ExecutionEnvironment.getExecutionEnvironment
+ val tEnv = TableEnvironment.getTableEnvironment(env)
+
+ val t =
CollectionDataSets.getSmall3TupleDataSet(env).toTable(tEnv).as('a, 'b, 'c)
+ tEnv.registerTable("sourceTable", t)
+
+ val fieldTypes = tEnv.scan("sourceTable").getSchema.getTypes
+ val fieldNames = Seq("d", "e", "f").toArray
+ val sink = new CsvSQLTableSink(path, fieldTypes, fieldNames, ",")
--- End diff --
We could also implement a `TableSink` which stores results in a `static
List` guarded by a lock to synchronize this inserts. This would make the test
faster and more reliable (going of the the filesystem is a reason for flaky
tests).
> 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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