[
https://issues.apache.org/jira/browse/SPARK-5203?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yin Huai updated SPARK-5203:
----------------------------
Target Version/s: 1.4.0
> union with different decimal type report error
> ----------------------------------------------
>
> Key: SPARK-5203
> URL: https://issues.apache.org/jira/browse/SPARK-5203
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Reporter: guowei
>
> cases like this
> create table test (a decimal(10,1));
> select a from test union all select a*2 from test;
> 15/01/12 16:28:54 ERROR SparkSQLDriver: Failed in [select a from test union
> all select a*2 from test]
> org.apache.spark.sql.catalyst.errors.package$TreeNodeException: Unresolved
> attributes: *, tree:
> 'Project [*]
> 'Subquery _u1
> 'Union
> Project [a#1]
> MetastoreRelation default, test, None
> Project [CAST((CAST(a#2, DecimalType()) * CAST(CAST(2, DecimalType(10,0)),
> DecimalType())), DecimalType(21,1)) AS _c0#0]
> MetastoreRelation default, test, None
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$$anonfun$1.applyOrElse(Analyzer.scala:85)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$$anonfun$1.applyOrElse(Analyzer.scala:83)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:144)
> at
> org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:135)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$.apply(Analyzer.scala:83)
> at
> org.apache.spark.sql.catalyst.analysis.Analyzer$CheckResolution$.apply(Analyzer.scala:81)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:61)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1$$anonfun$apply$2.apply(RuleExecutor.scala:59)
> at
> scala.collection.IndexedSeqOptimized$class.foldl(IndexedSeqOptimized.scala:51)
> at
> scala.collection.IndexedSeqOptimized$class.foldLeft(IndexedSeqOptimized.scala:60)
> at scala.collection.mutable.WrappedArray.foldLeft(WrappedArray.scala:34)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:59)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor$$anonfun$apply$1.apply(RuleExecutor.scala:51)
> at scala.collection.immutable.List.foreach(List.scala:318)
> at
> org.apache.spark.sql.catalyst.rules.RuleExecutor.apply(RuleExecutor.scala:51)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.analyzed$lzycompute(SQLContext.scala:410)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.analyzed(SQLContext.scala:410)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.withCachedData$lzycompute(SQLContext.scala:411)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.withCachedData(SQLContext.scala:411)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan$lzycompute(SQLContext.scala:412)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.optimizedPlan(SQLContext.scala:412)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan$lzycompute(SQLContext.scala:417)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.sparkPlan(SQLContext.scala:415)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.executedPlan$lzycompute(SQLContext.scala:421)
> at
> org.apache.spark.sql.SQLContext$QueryExecution.executedPlan(SQLContext.scala:421)
> at
> org.apache.spark.sql.hive.HiveContext$QueryExecution.stringResult(HiveContext.scala:369)
> at
> org.apache.spark.sql.hive.thriftserver.AbstractSparkSQLDriver.run(AbstractSparkSQLDriver.scala:58)
> at
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.processCmd(SparkSQLCLIDriver.scala:275)
> at org.apache.hadoop.hive.cli.CliDriver.processLine(CliDriver.java:423)
> at
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver$.main(SparkSQLCLIDriver.scala:211)
> at
> org.apache.spark.sql.hive.thriftserver.SparkSQLCLIDriver.main(SparkSQLCLIDriver.scala)
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