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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2019/10/08 05:44:16 UTC
[jira] [Resolved] (SPARK-22954) ANALYZE TABLE fails with
NoSuchTableException for temporary tables (but should have reported "not
supported on views")
[ https://issues.apache.org/jira/browse/SPARK-22954?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon resolved SPARK-22954.
----------------------------------
Resolution: Incomplete
> ANALYZE TABLE fails with NoSuchTableException for temporary tables (but should have reported "not supported on views")
> ----------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-22954
> URL: https://issues.apache.org/jira/browse/SPARK-22954
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.3.0
> Environment: {code}
> $ ./bin/spark-shell --version
> Welcome to
> ____ __
> / __/__ ___ _____/ /__
> _\ \/ _ \/ _ `/ __/ '_/
> /___/ .__/\_,_/_/ /_/\_\ version 2.3.0-SNAPSHOT
> /_/
> Using Scala version 2.11.8, Java HotSpot(TM) 64-Bit Server VM, 1.8.0_152
> Branch master
> Compiled by user jacek on 2018-01-04T05:44:05Z
> Revision 7d045c5f00e2c7c67011830e2169a4e130c3ace8
> {code}
> Reporter: Jacek Laskowski
> Priority: Minor
> Labels: bulk-closed
>
> {{ANALYZE TABLE}} fails with {{NoSuchTableException: Table or view 'names' not found in database 'default';}} for temporary tables (views) while the reason is that it can only work with permanent tables (which [it can report|https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/command/AnalyzeTableCommand.scala#L38] if it had a chance).
> {code}
> scala> names.createOrReplaceTempView("names")
> scala> sql("ANALYZE TABLE names COMPUTE STATISTICS")
> org.apache.spark.sql.catalyst.analysis.NoSuchTableException: Table or view 'names' not found in database 'default';
> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.requireTableExists(SessionCatalog.scala:181)
> at org.apache.spark.sql.catalyst.catalog.SessionCatalog.getTableMetadata(SessionCatalog.scala:398)
> at org.apache.spark.sql.execution.command.AnalyzeTableCommand.run(AnalyzeTableCommand.scala:36)
> at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
> at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
> at org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:79)
> at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:187)
> at org.apache.spark.sql.Dataset$$anonfun$6.apply(Dataset.scala:187)
> at org.apache.spark.sql.Dataset$$anonfun$51.apply(Dataset.scala:3244)
> at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3243)
> at org.apache.spark.sql.Dataset.<init>(Dataset.scala:187)
> at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:72)
> at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:638)
> ... 50 elided
> {code}
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