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ASF GitHub Bot commented on FLINK-6442: --------------------------------------- Github user wuchong commented on a diff in the pull request: https://github.com/apache/flink/pull/3829#discussion_r134177144 --- Diff: flink-libraries/flink-table/src/main/scala/org/apache/flink/table/api/TableEnvironment.scala --- @@ -502,26 +513,140 @@ abstract class TableEnvironment(val config: TableConfig) { * tEnv.sql(s"SELECT * FROM $table") * }}} * - * @param query The SQL query to evaluate. + * @param sql The SQL string to evaluate. * @return The result of the query as Table. */ - def sql(query: String): Table = { + @deprecated + def sql(sql: String): Table = { val planner = new FlinkPlannerImpl(getFrameworkConfig, getPlanner, getTypeFactory) // parse the sql query - val parsed = planner.parse(query) + val parsed = planner.parse(sql) // validate the sql query val validated = planner.validate(parsed) // transform to a relational tree val relational = planner.rel(validated) - new Table(this, LogicalRelNode(relational.rel)) } /** + * Evaluates a SQL Select query on registered tables and retrieves the result as a + * [[Table]]. + * + * All tables referenced by the query must be registered in the TableEnvironment. But + * [[Table.toString]] will automatically register an unique table name and return the + * table name. So it allows to call SQL directly on tables like this: + * + * {{{ + * val table: Table = ... + * // the table is not registered to the table environment + * tEnv.sqlSelect(s"SELECT * FROM $table") + * }}} + * + * @param sql The SQL string to evaluate. + * @return The result of the query as Table or null of the DML insert operation. + */ + def sqlQuery(sql: String): Table = { + val planner = new FlinkPlannerImpl(getFrameworkConfig, getPlanner, getTypeFactory) + // parse the sql query + val parsed = planner.parse(sql) + if (null != parsed && parsed.getKind.belongsTo(SqlKind.QUERY)) { + // validate the sql query + val validated = planner.validate(parsed) + // transform to a relational tree + val relational = planner.rel(validated) + new Table(this, LogicalRelNode(relational.rel)) + } else { + throw new TableException( + "Unsupported sql query! sqlQuery Only accept SELECT, UNION, INTERSECT, EXCEPT, VALUES, " + + "WITH, ORDER_BY, EXPLICIT_TABLE") + } + } + + /** + * Evaluates a SQL statement which must be an SQL Data Manipulation Language (DML) statement, + * such as INSERT, UPDATE or DELETE; or an SQL statement that returns nothing, such as a DDL + * statement; + * Currently only support a SQL INSERT statement on registered tables and has no return value. + * + * All tables referenced by the query must be registered in the TableEnvironment. But + * [[Table.toString]] will automatically register an unique table name and return the + * table name. So it allows to call SQL directly on tables like this: + * + * {{{ + * /// register table sink for insertion + * tEnv.registerTableSink("target_table", ... + * val sourceTable: Table = ... + * // sourceTable is not registered to the table environment + * tEnv.sqlInsert(s"INSERT INTO target_table SELECT * FROM $sourceTable") + * }}} + * + * @param sql The SQL String to evaluate. + */ + def sqlUpdate(sql: String): Unit = { + sqlUpdate(sql, QueryConfig.getQueryConfigFromTableEnv(this)) + } + + /** + * Evaluates a SQL statement which must be an SQL Data Manipulation Language (DML) statement, + * such as INSERT, UPDATE or DELETE; or an SQL statement that returns nothing, such as a DDL + * statement; + * Currently only support a SQL INSERT statement on registered tables and has no return value. + * + * All tables referenced by the query must be registered in the TableEnvironment. But + * [[Table.toString]] will automatically register an unique table name and return the + * table name. So it allows to call SQL directly on tables like this: + * + * {{{ + * /// register table sink for insertion + * tEnv.registerTableSink("target_table", ... + * val sourceTable: Table = ... + * // sourceTable is not registered to the table environment + * tEnv.sqlInsert(s"INSERT INTO target_table SELECT * FROM $sourceTable") + * }}} + * + * @param sql The SQL String to evaluate. + * @param config The [[QueryConfig]] to use. + */ + def sqlUpdate(sql: String, config: QueryConfig): Unit = { + val planner = new FlinkPlannerImpl(getFrameworkConfig, getPlanner, getTypeFactory) + // parse the sql query + val parsed = planner.parse(sql) + parsed match { + case insert: SqlInsert => { + // validate the sql query + planner.validate(parsed) + + // validate sink table + val targetName = insert.getTargetTable.asInstanceOf[SqlIdentifier].names.get(0) + val targetTable = getTable(targetName) + if (null == targetTable || !targetTable.isInstanceOf[TableSinkTable[_]]) { + throw new TableException("SQL INSERT operation need a registered TableSink Table!") + } + // validate unsupported partial insertion to sink table + val sinkTable = targetTable.asInstanceOf[TableSinkTable[_]] + if (null != insert.getTargetColumnList && insert.getTargetColumnList.size() != --- End diff -- Should we validate the field types are equal? > 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)