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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:14:43 UTC
[jira] [Resolved] (SPARK-21429) show on structured Dataset is
equivalent to writeStream to console once
[ https://issues.apache.org/jira/browse/SPARK-21429?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-21429.
----------------------------------
Resolution: Incomplete
> show on structured Dataset is equivalent to writeStream to console once
> -----------------------------------------------------------------------
>
> Key: SPARK-21429
> URL: https://issues.apache.org/jira/browse/SPARK-21429
> Project: Spark
> Issue Type: Improvement
> Components: Structured Streaming
> Affects Versions: 2.2.0
> Reporter: Jacek Laskowski
> Priority: Minor
> Labels: bulk-closed
>
> While working with Datasets it's often helpful to do {{show}}. It does not work for streaming Datasets (and leads to {{AnalysisException}} - see below), but think it could just be the following under the covers and very helpful (would cut plenty of keystrokes for sure).
> {code}
> val sq = ...
> scala> sq.isStreaming
> res0: Boolean = true
> import org.apache.spark.sql.streaming.Trigger
> scala> sq.writeStream.format("console").trigger(Trigger.Once).start
> {code}
> Since {{show}} returns {{Unit}} that could just work.
> Currently {{show}} reports {{AnalysisException}}.
> {code}
> scala> sq.show
> org.apache.spark.sql.AnalysisException: Queries with streaming sources must be executed with writeStream.start();;
> rate
> at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$.org$apache$spark$sql$catalyst$analysis$UnsupportedOperationChecker$$throwError(UnsupportedOperationChecker.scala:297)
> at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$$anonfun$checkForBatch$1.apply(UnsupportedOperationChecker.scala:36)
> at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$$anonfun$checkForBatch$1.apply(UnsupportedOperationChecker.scala:34)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:126)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:126)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:126)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:126)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$anonfun$foreachUp$1.apply(TreeNode.scala:126)
> at scala.collection.immutable.List.foreach(List.scala:381)
> at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:126)
> at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$.checkForBatch(UnsupportedOperationChecker.scala:34)
> at org.apache.spark.sql.execution.QueryExecution.assertSupported(QueryExecution.scala:63)
> at org.apache.spark.sql.execution.QueryExecution.withCachedData$lzycompute(QueryExecution.scala:74)
> at org.apache.spark.sql.execution.QueryExecution.withCachedData(QueryExecution.scala:72)
> at org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:78)
> at org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:78)
> at org.apache.spark.sql.execution.QueryExecution.sparkPlan$lzycompute(QueryExecution.scala:84)
> at org.apache.spark.sql.execution.QueryExecution.sparkPlan(QueryExecution.scala:80)
> at org.apache.spark.sql.execution.QueryExecution.executedPlan$lzycompute(QueryExecution.scala:89)
> at org.apache.spark.sql.execution.QueryExecution.executedPlan(QueryExecution.scala:89)
> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3027)
> at org.apache.spark.sql.Dataset.head(Dataset.scala:2340)
> at org.apache.spark.sql.Dataset.take(Dataset.scala:2553)
> at org.apache.spark.sql.Dataset.showString(Dataset.scala:241)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:671)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:630)
> at org.apache.spark.sql.Dataset.show(Dataset.scala:639)
> ... 50 elided
> {code}
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