jinchengchenghh opened a new issue, #10963: URL: https://github.com/apache/incubator-gluten/issues/10963
### Backend VL (Velox) ### Bug description https://github.com/apache/incubator-gluten/pull/10962 ``` 2025-10-28T16:28:46.7157558Z - SPARK-35955: Aggregate avg should not return wrong results for decimal overflow *** FAILED *** 2025-10-28T16:28:46.7159939Z org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 279.0 failed 1 times, most recent failure: Lost task 0.0 in stage 279.0 (TID 364) (68c6faa8b5ed executor driver): java.lang.ArithmeticException: Decimal precision 39 exceeds max precision 38 2025-10-28T16:28:46.7162228Z at org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:1013) 2025-10-28T16:28:46.7163396Z at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) 2025-10-28T16:28:46.7164100Z at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:578) 2025-10-28T16:28:46.7164788Z at org.apache.spark.sql.types.Decimal.apply(Decimal.scala) 2025-10-28T16:28:46.7165652Z at org.apache.spark.sql.catalyst.expressions.UnsafeRow.getDecimal(UnsafeRow.java:396) 2025-10-28T16:28:46.7167280Z at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.hashAgg_doAggregateWithoutKey_0$(Unknown Source) 2025-10-28T16:28:46.7168986Z at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) 2025-10-28T16:28:46.7170319Z at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) 2025-10-28T16:28:46.7171521Z at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760) 2025-10-28T16:28:46.7172520Z at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460) 2025-10-28T16:28:46.7173231Z at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460) 2025-10-28T16:28:46.7174065Z at org.apache.spark.util.Utils$.getIteratorSize(Utils.scala:1931) 2025-10-28T16:28:46.7174748Z at org.apache.spark.rdd.RDD.$anonfun$count$1(RDD.scala:1274) 2025-10-28T16:28:46.7175437Z at org.apache.spark.rdd.RDD.$anonfun$count$1$adapted(RDD.scala:1274) 2025-10-28T16:28:46.7176366Z at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2268) 2025-10-28T16:28:46.7177192Z at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) 2025-10-28T16:28:46.7177902Z at org.apache.spark.scheduler.Task.run(Task.scala:136) 2025-10-28T16:28:46.7178667Z at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:548) 2025-10-28T16:28:46.7179507Z at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1504) 2025-10-28T16:28:46.7180279Z at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:551) 2025-10-28T16:28:46.7181255Z at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136) 2025-10-28T16:28:46.7182356Z at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635) 2025-10-28T16:28:46.7183173Z at java.base/java.lang.Thread.run(Thread.java:833) 2025-10-28T16:28:46.7183641Z 2025-10-28T16:28:46.7183778Z Driver stacktrace: 2025-10-28T16:28:46.7184504Z at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2672) 2025-10-28T16:28:46.7185615Z at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2608) 2025-10-28T16:28:46.7186841Z at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2607) 2025-10-28T16:28:46.7187865Z at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) 2025-10-28T16:28:46.7188779Z at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) 2025-10-28T16:28:46.7189647Z at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) 2025-10-28T16:28:46.7190530Z at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2607) 2025-10-28T16:28:46.7191567Z at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1182) 2025-10-28T16:28:46.7192823Z at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1182) 2025-10-28T16:28:46.7193689Z at scala.Option.foreach(Option.scala:407) 2025-10-28T16:28:46.7194117Z ... 2025-10-28T16:28:46.7194667Z Cause: java.lang.ArithmeticException: Decimal precision 39 exceeds max precision 38 2025-10-28T16:28:46.7196197Z at org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:1013) 2025-10-28T16:28:46.7197447Z at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) 2025-10-28T16:28:46.7198153Z at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:578) 2025-10-28T16:28:46.7198842Z at org.apache.spark.sql.types.Decimal.apply(Decimal.scala) 2025-10-28T16:28:46.7199687Z at org.apache.spark.sql.catalyst.expressions.UnsafeRow.getDecimal(UnsafeRow.java:396) 2025-10-28T16:28:46.7201396Z at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.hashAgg_doAggregateWithoutKey_0$(Unknown Source) 2025-10-28T16:28:46.7203065Z at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) 2025-10-28T16:28:46.7204394Z at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) 2025-10-28T16:28:46.7205583Z at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:760) 2025-10-28T16:28:46.7206728Z at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:460) 2025-10-28T16:28:46.7207275Z ... ``` ### Gluten version _No response_ ### Spark version None ### Spark configurations _No response_ ### System information _No response_ ### Relevant logs ```bash ``` -- This is an automated message from the Apache Git Service. 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