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Posted to issues@spark.apache.org by "Chetan Bhat (Jira)" <ji...@apache.org> on 2021/06/03 14:32:00 UTC
[jira] [Resolved] (SPARK-35631) java.lang.ArithmeticException:
integer overflow when SELECT 2147483647 + 1 executed with set
spark.sql.ansi.enabled=true
[ https://issues.apache.org/jira/browse/SPARK-35631?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Chetan Bhat resolved SPARK-35631.
---------------------------------
Resolution: Invalid
As per the information provided in [https://spark.apache.org/docs/3.1.2/sql-ref-ansi-compliance.html#content] link this is not a issue.
> java.lang.ArithmeticException: integer overflow when SELECT 2147483647 + 1 executed with set spark.sql.ansi.enabled=true
> ------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-35631
> URL: https://issues.apache.org/jira/browse/SPARK-35631
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.1.1
> Environment: Spark 3.1.1
> Reporter: Chetan Bhat
> Priority: Minor
>
> From Spark beeline the queries are executed
> set spark.sql.ansi.enabled=true
> SELECT 2147483647 + 1
>
> Issue : The select query fails with java.lang.ArithmeticException: integer overflow
> 0: jdbc:hive2://10.20.253.239:23040/default> set spark.sql.ansi.enabled=true;
> +-------------------------+--------+
> | key | value |
> +-------------------------+--------+
> | spark.sql.ansi.enabled | true |
> +-------------------------+--------+
> 1 row selected (0.052 seconds)
> 0: jdbc:hive2://10.20.253.239:23040/default> SELECT 2147483647 + 1;
> Error: org.apache.hive.service.cli.HiveSQLException: Error running query: java.lang.ArithmeticException: integer overflow
> at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation.org$apache$spark$sql$hive$thriftserver$SparkExecuteStatementOperation$$execute(SparkExecuteStatementOperation.scala:361)
> at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2$$anon$3.$anonfun$run$2(SparkExecuteStatementOperation.scala:263)
> at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2$$anon$3$$Lambda$1762/209207680.apply$mcV$sp(Unknown Source)
> at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
> at org.apache.spark.sql.hive.thriftserver.SparkOperation.withLocalProperties(SparkOperation.scala:78)
> at org.apache.spark.sql.hive.thriftserver.SparkOperation.withLocalProperties$(SparkOperation.scala:62)
> at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation.withLocalProperties(SparkExecuteStatementOperation.scala:43)
> at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2$$anon$3.run(SparkExecuteStatementOperation.scala:263)
> at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2$$anon$3.run(SparkExecuteStatementOperation.scala:258)
> at java.security.AccessController.doPrivileged(Native Method)
> at javax.security.auth.Subject.doAs(Subject.java:422)
> at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1729)
> at org.apache.spark.sql.hive.thriftserver.SparkExecuteStatementOperation$$anon$2.run(SparkExecuteStatementOperation.scala:272)
> at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
> at java.util.concurrent.FutureTask.run(FutureTask.java:266)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.java:745)
> Caused by: java.lang.ArithmeticException: integer overflow
> at java.lang.Math.addExact(Math.java:790)
> at org.apache.spark.sql.types.IntegerExactNumeric$.plus(numerics.scala:95)
> at org.apache.spark.sql.types.IntegerExactNumeric$.plus(numerics.scala:94)
> at org.apache.spark.sql.catalyst.expressions.Add.nullSafeEval(arithmetic.scala:264)
> at org.apache.spark.sql.catalyst.expressions.BinaryExpression.eval(Expression.scala:567)
> at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$1$$anonfun$applyOrElse$1.applyOrElse(expressions.scala:66)
> at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$1$$anonfun$applyOrElse$1.applyOrElse(expressions.scala:54)
> at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$1(TreeNode.scala:317)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$Lambda$1613/79619382.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:73)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:317)
> at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$3(TreeNode.scala:322)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$Lambda$1615/1159662764.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$mapChildren$1(TreeNode.scala:407)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$Lambda$1601/550689618.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:243)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:405)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapChildren(TreeNode.scala:358)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:322)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$transformExpressionsDown$1(QueryPlan.scala:94)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$Lambda$1315/1031179320.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$mapExpressions$1(QueryPlan.scala:116)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$Lambda$1788/344990949.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:73)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpression$1(QueryPlan.scala:116)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.recursiveTransform$1(QueryPlan.scala:127)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$mapExpressions$3(QueryPlan.scala:132)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$Lambda$1317/222329442.apply(Unknown Source)
> at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:238)
> at scala.collection.TraversableLike$$Lambda$26/999522307.apply(Unknown Source)
> at scala.collection.immutable.List.foreach(List.scala:392)
> at scala.collection.TraversableLike.map(TraversableLike.scala:238)
> at scala.collection.TraversableLike.map$(TraversableLike.scala:231)
> at scala.collection.immutable.List.map(List.scala:298)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.recursiveTransform$1(QueryPlan.scala:132)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.$anonfun$mapExpressions$4(QueryPlan.scala:137)
> at org.apache.spark.sql.catalyst.plans.QueryPlan$$Lambda$1316/732259142.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.trees.TreeNode.mapProductIterator(TreeNode.scala:243)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.mapExpressions(QueryPlan.scala:137)
> at org.apache.spark.sql.catalyst.plans.QueryPlan.transformExpressionsDown(QueryPlan.scala:94)
> at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$1.applyOrElse(expressions.scala:54)
> at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$$anonfun$apply$1.applyOrElse(expressions.scala:53)
> at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDown$1(TreeNode.scala:317)
> at org.apache.spark.sql.catalyst.trees.TreeNode$$Lambda$1613/79619382.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:73)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:317)
> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDown(LogicalPlan.scala:29)
> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDown(AnalysisHelper.scala:171)
> at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDown$(AnalysisHelper.scala:169)
> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
> at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDown(LogicalPlan.scala:29)
> at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:306)
> at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$.apply(expressions.scala:53)
> at org.apache.spark.sql.catalyst.optimizer.ConstantFolding$.apply(expressions.scala:44)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:216)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor$$Lambda$1311/1478530425.apply(Unknown Source)
> at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
> at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
> at scala.collection.immutable.List.foldLeft(List.scala:89)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:213)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:205)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor$$Lambda$1310/802758091.apply(Unknown Source)
> at scala.collection.immutable.List.foreach(List.scala:392)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:205)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:183)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor$$Lambda$1303/1329861157.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88)
> at org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:183)
> at org.apache.spark.sql.execution.QueryExecution.$anonfun$optimizedPlan$1(QueryExecution.scala:87)
> at org.apache.spark.sql.execution.QueryExecution$$Lambda$1636/2090796568.apply(Unknown Source)
> at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
> at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:143)
> at
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