[ https://issues.apache.org/jira/browse/SPARK-35631?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Chetan Bhat closed SPARK-35631. ------------------------------- this is not a issue. Closed without handling. > 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 -- This message was sent by Atlassian Jira (v8.3.4#803005) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org