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https://issues.apache.org/jira/browse/FLINK-6442?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16170684#comment-16170684
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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_r139471593
--- Diff: docs/dev/table/sql.md ---
@@ -71,15 +85,29 @@ val ds: DataStream[(Long, String, Integer)] =
env.addSource(...)
// SQL query with an inlined (unregistered) table
val table = ds.toTable(tableEnv, 'user, 'product, 'amount)
-val result = tableEnv.sql(
+val result = tableEnv.sqlQuery(
s"SELECT SUM(amount) FROM $table WHERE product LIKE '%Rubber%'")
// SQL query with a registered table
// register the DataStream under the name "Orders"
tableEnv.registerDataStream("Orders", ds, 'user, 'product, 'amount)
// run a SQL query on the Table and retrieve the result as a new Table
-val result2 = tableEnv.sql(
+val result2 = tableEnv.sqlQuery(
"SELECT product, amount FROM Orders WHERE product LIKE '%Rubber%'")
+
+// SQL update with a registered table
+// register the DataStream as table "Orders"
+tableEnv.registerDataStream("Orders", ds, 'user, 'product, 'amount)
+// create a TableSink
+TableSink csvSink = new CsvTableSink("/path/to/file", ...)
+// define the field names and types
+val fieldNames: Arary[String] = Array("id", "product", "amount")
--- End diff --
fix schema of result (must match query result schema)
> 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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