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Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2017/06/19 02:22:00 UTC
[jira] [Commented] (SPARK-20599) ConsoleSink should work with write
(batch)
[ https://issues.apache.org/jira/browse/SPARK-20599?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16053413#comment-16053413 ]
Apache Spark commented on SPARK-20599:
--------------------------------------
User 'lubozhan' has created a pull request for this issue:
https://github.com/apache/spark/pull/18347
> 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
> 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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