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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-20599) ConsoleSink should work with write (batch)
Date Mon, 19 Jun 2017 02:22:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-20599?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-20599:
------------------------------------

    Assignee: Apache Spark

> ConsoleSink should work with write (batch)
> ------------------------------------------
>
>                 Key: SPARK-20599
>                 URL: https://issues.apache.org/jira/browse/SPARK-20599
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL, Structured Streaming
>    Affects Versions: 2.2.0
>            Reporter: Jacek Laskowski
>            Assignee: Apache Spark
>            Priority: Minor
>              Labels: starter
>
> I think the following should just work.
> {code}
> spark.
>   read.  // <-- it's a batch query not streaming query if that matters
>   format("kafka").
>   option("subscribe", "topic1").
>   option("kafka.bootstrap.servers", "localhost:9092").
>   load.
>   write.
>   format("console").  // <-- that's not supported currently
>   save
> {code}
> The above combination of {{kafka}} source and {{console}} sink leads to the following
exception:
> {code}
> java.lang.RuntimeException: org.apache.spark.sql.execution.streaming.ConsoleSinkProvider
does not allow create table as select.
>   at scala.sys.package$.error(package.scala:27)
>   at org.apache.spark.sql.execution.datasources.DataSource.write(DataSource.scala:479)
>   at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:48)
>   at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)
>   at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)
>   at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:74)
>   at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)
>   at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:114)
>   at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:135)
>   at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
>   at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:132)
>   at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:113)
>   at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:93)
>   at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:93)
>   at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:610)
>   at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:233)
>   ... 48 elided
> {code}



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