[ https://issues.apache.org/jira/browse/SPARK-37420?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
t oo updated SPARK-37420: ------------------------- Description: reading oracle jdbc is not working as expected, i thought a simple df show should work. {code:java} /usr/local/bin/pyspark --driver-class-path "/home/user/extra_jar_spark/*" --jars "/home/user/extra_jar_spark/*" jdbc2DF = spark.read \ .format("jdbc") \ .option("url", "jdbc:oracle:thin:@redact") \ .option("driver", "oracle.jdbc.OracleDriver") \ .option("dbtable", "s.t") \ .option("user", "redact") \ .option("password", "redact") \ .option("fetchsize", 10000) \ .load() jdbc2DF.printSchema() root |-- ID: decimal(38,10) (nullable = true) |-- OBJECT_VERSION_NUMBER: decimal(9,0) (nullable = true) |-- START_DATE: timestamp (nullable = true) |-- END_DATE: timestamp (nullable = true) |-- CREATED_BY: decimal(15,0) (nullable = true) |-- CREATION_DATE: timestamp (nullable = true) |-- LAST_UPDATED_BY: decimal(15,0) (nullable = true) |-- LAST_UPDATE_DATE: timestamp (nullable = true) |-- LAST_UPDATE_LOGIN: decimal(15,0) (nullable = true) |-- CONTINGENCY: string (nullable = true) |-- CONTINGENCY_ID: decimal(38,10) (nullable = true) jdbc2DF.show() 21/11/20 23:42:00 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 2) java.lang.ArithmeticException: Decimal precision 49 exceeds max precision 38 at org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) 21/11/20 23:42:00 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2) (localhost executor driver): java.lang.ArithmeticException: Decimal precision 49 exceeds max precision 38 at org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)21/11/20 23:42:00 ERROR TaskSetManager: Task 0 in stage 2.0 failed 1 times; aborting job Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python3.7/site-packages/pyspark/sql/dataframe.py", line 494, in show print(self._jdf.showString(n, 20, vertical)) File "/usr/local/lib/python3.7/site-packages/pyspark/python/lib/py4j-0.10.9.2-src.zip/py4j/java_gateway.py", line 1310, in __call__ File "/usr/local/lib/python3.7/site-packages/pyspark/sql/utils.py", line 111, in deco return f(*a, **kw) File "/usr/local/lib/python3.7/site-packages/pyspark/python/lib/py4j-0.10.9.2-src.zip/py4j/protocol.py", line 328, in get_return_value py4j.protocol.Py4JJavaError: An error occurred while calling o109.showString. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID 2) (localhost executor driver): java.lang.ArithmeticException: Decimal precision 49 exceeds max precision 38 at org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2403) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2352) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2351) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2351) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1109) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1109) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1109) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2591) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2533) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2522) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:898) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2235) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2254) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:476) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:429) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48) at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715) at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3704) at org.apache.spark.sql.Dataset.head(Dataset.scala:2728) at org.apache.spark.sql.Dataset.take(Dataset.scala:2935) at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287) at org.apache.spark.sql.Dataset.showString(Dataset.scala:326) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:282) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182) at py4j.ClientServerConnection.run(ClientServerConnection.java:106) at java.lang.Thread.run(Thread.java:748) Caused by: java.lang.ArithmeticException: Decimal precision 49 exceeds max precision 38 at org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) ... 1 more {code} as you can see oracle type is 38,10 so not sure why spark thinks precision is greater than 38. It seems to be adding scale to precision was: reading oracle jdbc is not working as expected, i thought a simple df show should work. {code:java} /usr/local/bin/pyspark --driver-class-path "/home/user/extra_jar_spark/*" --jars "/home/user/extra_jar_spark/*" jdbc2DF = spark.read \ .format("jdbc") \ .option("url", "jdbc:oracle:thin:@redact") \ .option("driver", "oracle.jdbc.OracleDriver") \ .option("dbtable", "s.t") \ .option("user", "redact") \ .option("password", "redact") \ .option("fetchsize", 10000) \ .load() jdbc2DF.printSchema() root |-- ID: decimal(38,10) (nullable = true) |-- OBJECT_VERSION_NUMBER: decimal(9,0) (nullable = true) |-- START_DATE: timestamp (nullable = true) |-- END_DATE: timestamp (nullable = true) |-- CREATED_BY: decimal(15,0) (nullable = true) |-- CREATION_DATE: timestamp (nullable = true) |-- LAST_UPDATED_BY: decimal(15,0) (nullable = true) |-- LAST_UPDATE_DATE: timestamp (nullable = true) |-- LAST_UPDATE_LOGIN: decimal(15,0) (nullable = true) |-- CONTINGENCY: string (nullable = true) |-- CONTINGENCY_ID: decimal(38,10) (nullable = true) jdbc2DF.show() 21/11/20 23:42:00 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 2) java.lang.ArithmeticException: Decimal precision 49 exceeds max precision 38 at org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) 21/11/20 23:42:00 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2) (localhost executor driver): java.lang.ArithmeticException: Decimal precision 49 exceeds max precision 38 at org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)21/11/20 23:42:00 ERROR TaskSetManager: Task 0 in stage 2.0 failed 1 times; aborting job Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python3.7/site-packages/pyspark/sql/dataframe.py", line 494, in show print(self._jdf.showString(n, 20, vertical)) File "/usr/local/lib/python3.7/site-packages/pyspark/python/lib/py4j-0.10.9.2-src.zip/py4j/java_gateway.py", line 1310, in __call__ File "/usr/local/lib/python3.7/site-packages/pyspark/sql/utils.py", line 111, in deco return f(*a, **kw) File "/usr/local/lib/python3.7/site-packages/pyspark/python/lib/py4j-0.10.9.2-src.zip/py4j/protocol.py", line 328, in get_return_value py4j.protocol.Py4JJavaError: An error occurred while calling o109.showString. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 (TID 2) (localhost executor driver): java.lang.ArithmeticException: Decimal precision 49 exceeds max precision 38 at org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748)Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2403) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2352) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2351) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2351) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1109) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1109) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1109) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2591) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2533) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2522) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:898) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2235) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2254) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:476) at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:429) at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48) at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715) at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728) at org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3704) at org.apache.spark.sql.Dataset.head(Dataset.scala:2728) at org.apache.spark.sql.Dataset.take(Dataset.scala:2935) at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287) at org.apache.spark.sql.Dataset.showString(Dataset.scala:326) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:498) at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) at py4j.Gateway.invoke(Gateway.java:282) at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) at py4j.commands.CallCommand.execute(CallCommand.java:79) at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182) at py4j.ClientServerConnection.run(ClientServerConnection.java:106) at java.lang.Thread.run(Thread.java:748) Caused by: java.lang.ArithmeticException: Decimal precision 49 exceeds max precision 38 at org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) at org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) at org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) ... 1 more {code} > Oracle JDBC - java.lang.ArithmeticException: Decimal precision 49 exceeds max > precision 38 > ------------------------------------------------------------------------------------------ > > Key: SPARK-37420 > URL: https://issues.apache.org/jira/browse/SPARK-37420 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 3.2.0 > Reporter: t oo > Priority: Major > > reading oracle jdbc is not working as expected, i thought a simple df show > should work. > > {code:java} > /usr/local/bin/pyspark --driver-class-path "/home/user/extra_jar_spark/*" > --jars "/home/user/extra_jar_spark/*" > jdbc2DF = spark.read \ > .format("jdbc") \ > .option("url", "jdbc:oracle:thin:@redact") \ > .option("driver", "oracle.jdbc.OracleDriver") \ > .option("dbtable", "s.t") \ > .option("user", "redact") \ > .option("password", "redact") \ > .option("fetchsize", 10000) \ > .load() > > jdbc2DF.printSchema() > root > |-- ID: decimal(38,10) (nullable = true) > |-- OBJECT_VERSION_NUMBER: decimal(9,0) (nullable = true) > |-- START_DATE: timestamp (nullable = true) > |-- END_DATE: timestamp (nullable = true) > |-- CREATED_BY: decimal(15,0) (nullable = true) > |-- CREATION_DATE: timestamp (nullable = true) > |-- LAST_UPDATED_BY: decimal(15,0) (nullable = true) > |-- LAST_UPDATE_DATE: timestamp (nullable = true) > |-- LAST_UPDATE_LOGIN: decimal(15,0) (nullable = true) > |-- CONTINGENCY: string (nullable = true) > |-- CONTINGENCY_ID: decimal(38,10) (nullable = true) > jdbc2DF.show() > 21/11/20 23:42:00 ERROR Executor: Exception in task 0.0 in stage 2.0 (TID 2) > java.lang.ArithmeticException: Decimal precision 49 exceeds max precision 38 > at > org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) > at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) > at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) > at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) > at > org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) > at > org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) > at > org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) > at > org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) > at > org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) > at org.apache.spark.scheduler.Task.run(Task.scala:131) > at > org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) > at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > at java.lang.Thread.run(Thread.java:748) > 21/11/20 23:42:00 WARN TaskSetManager: Lost task 0.0 in stage 2.0 (TID 2) > (localhost executor driver): java.lang.ArithmeticException: Decimal precision > 49 exceeds max precision 38 > at > org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) > at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) > at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) > at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) > at > org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) > at > org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) > at > org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) > at > org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) > at > org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) > at org.apache.spark.scheduler.Task.run(Task.scala:131) > at > org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) > at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > at java.lang.Thread.run(Thread.java:748)21/11/20 23:42:00 ERROR > TaskSetManager: Task 0 in stage 2.0 failed 1 times; aborting job > Traceback (most recent call last): > File "<stdin>", line 1, in <module> > File "/usr/local/lib/python3.7/site-packages/pyspark/sql/dataframe.py", > line 494, in show > print(self._jdf.showString(n, 20, vertical)) > File > "/usr/local/lib/python3.7/site-packages/pyspark/python/lib/py4j-0.10.9.2-src.zip/py4j/java_gateway.py", > line 1310, in __call__ > File "/usr/local/lib/python3.7/site-packages/pyspark/sql/utils.py", line > 111, in deco > return f(*a, **kw) > File > "/usr/local/lib/python3.7/site-packages/pyspark/python/lib/py4j-0.10.9.2-src.zip/py4j/protocol.py", > line 328, in get_return_value > py4j.protocol.Py4JJavaError: An error occurred while calling o109.showString. > : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 > in stage 2.0 failed 1 times, most recent failure: Lost task 0.0 in stage 2.0 > (TID 2) (localhost executor driver): java.lang.ArithmeticException: Decimal > precision 49 exceeds max precision 38 > at > org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) > at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) > at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) > at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) > at > org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) > at > org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) > at > org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) > at > org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) > at > org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) > at org.apache.spark.scheduler.Task.run(Task.scala:131) > at > org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) > at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > at java.lang.Thread.run(Thread.java:748)Driver stacktrace: > at > org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2403) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2352) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2351) > at > scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) > at > scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) > at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) > at > org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2351) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1109) > at > org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1109) > at scala.Option.foreach(Option.scala:407) > at > org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1109) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2591) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2533) > at > org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2522) > at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) > at > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:898) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2235) > at org.apache.spark.SparkContext.runJob(SparkContext.scala:2254) > at > org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:476) > at > org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:429) > at > org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48) > at org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715) > at org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728) > at > org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706) > at > org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) > at > org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) > at > org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) > at > org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) > at > org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) > at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3704) > at org.apache.spark.sql.Dataset.head(Dataset.scala:2728) > at org.apache.spark.sql.Dataset.take(Dataset.scala:2935) > at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287) > at org.apache.spark.sql.Dataset.showString(Dataset.scala:326) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:498) > at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) > at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) > at py4j.Gateway.invoke(Gateway.java:282) > at > py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) > at py4j.commands.CallCommand.execute(CallCommand.java:79) > at > py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182) > at py4j.ClientServerConnection.run(ClientServerConnection.java:106) > at java.lang.Thread.run(Thread.java:748) > Caused by: java.lang.ArithmeticException: Decimal precision 49 exceeds max > precision 38 > at > org.apache.spark.sql.errors.QueryExecutionErrors$.decimalPrecisionExceedsMaxPrecisionError(QueryExecutionErrors.scala:847) > at org.apache.spark.sql.types.Decimal.set(Decimal.scala:123) > at org.apache.spark.sql.types.Decimal$.apply(Decimal.scala:572) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$4(JdbcUtils.scala:418) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.nullSafeConvert(JdbcUtils.scala:546) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:418) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:416) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:367) > at > org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:349) > at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) > at > org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) > at > org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) > at > org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown > Source) > at > org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) > at > org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) > at > org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:349) > at > org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) > at > org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) > at > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) > at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) > at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) > at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) > at org.apache.spark.scheduler.Task.run(Task.scala:131) > at > org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) > at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462) > at > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) > at > java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) > at > java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) > ... 1 more {code} > > as you can see oracle type is 38,10 so not sure why spark thinks precision is > greater than 38. It seems to be adding scale to precision -- This message was sent by Atlassian Jira (v8.20.1#820001) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org