How can I use a saveAsTextFile() function in Apache Spark? - apache-spark

I am new in Spark, and I have some problems to register informations in a file.
The problem is the following:
I have declared the avglens RDD with the following command:
var avglens = sc.textFile("C:/Program Files/spark-3.1.1-bin-hadoop2.7/README.md")
.flatMap(line => line.split(' '))
.map(word => (word(0), word.length))
.groupByKey()
.map(pair => (pair._1, pair._2.sum/pair._2.size.toDouble))
then, I wanted to save informations of my avglens RDD in a new file named avglens-output.
To do that, I have launched the following command:
avglens.saveAsTextFile("avglen-output")
But, it returns the following error:
21/06/17 13:15:44 ERROR Executor: Exception in task 1.0 in stage 0.0 (TID 1)/ 2]
java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.$anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
21/06/17 13:15:44 WARN TaskSetManager: Lost task 1.0 in stage 0.0 (TID 1) (192.168.1.20 executor driver): java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.$anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
21/06/17 13:15:44 ERROR TaskSetManager: Task 1 in stage 0.0 failed 1 times; aborting job
21/06/17 13:15:44 ERROR SparkHadoopWriter: Aborting job job_202106171315432560914192953511091_0007.
org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 0.0 failed 1 times, most recent failure: Lost task 1.0 in stage 0.0 (TID 1) (192.168.1.20 executor driver): java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.$anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
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:2253)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2202)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2201)
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:2201)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1078)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1078)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1078)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2440)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2382)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2371)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2202)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2223)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2255)
at org.apache.spark.internal.io.SparkHadoopWriter$.write(SparkHadoopWriter.scala:83)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopDataset$1(PairRDDFunctions.scala:1090)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopDataset(PairRDDFunctions.scala:1088)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$4(PairRDDFunctions.scala:1061)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1026)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$3(PairRDDFunctions.scala:1008)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1007)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$2(PairRDDFunctions.scala:964)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:962)
at org.apache.spark.rdd.RDD.$anonfun$saveAsTextFile$2(RDD.scala:1578)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1578)
at org.apache.spark.rdd.RDD.$anonfun$saveAsTextFile$1(RDD.scala:1564)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1564)
at $line18.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:26)
at $line18.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:30)
at $line18.$read$$iw$$iw$$iw$$iw$$iw$$iw.<init>(<console>:32)
at $line18.$read$$iw$$iw$$iw$$iw$$iw.<init>(<console>:34)
at $line18.$read$$iw$$iw$$iw$$iw.<init>(<console>:36)
at $line18.$read$$iw$$iw$$iw.<init>(<console>:38)
at $line18.$read$$iw$$iw.<init>(<console>:40)
at $line18.$read$$iw.<init>(<console>:42)
at $line18.$read.<init>(<console>:44)
at $line18.$read$.<init>(<console>:48)
at $line18.$read$.<clinit>(<console>)
at $line18.$eval$.$print$lzycompute(<console>:7)
at $line18.$eval$.$print(<console>:6)
at $line18.$eval.$print(<console>)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:745)
at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1021)
at scala.tools.nsc.interpreter.IMain.$anonfun$interpret$1(IMain.scala:574)
at scala.reflect.internal.util.ScalaClassLoader.asContext(ScalaClassLoader.scala:41)
at scala.reflect.internal.util.ScalaClassLoader.asContext$(ScalaClassLoader.scala:37)
at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:41)
at scala.tools.nsc.interpreter.IMain.loadAndRunReq$1(IMain.scala:573)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:600)
at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:570)
at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:894)
at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:762)
at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:464)
at scala.tools.nsc.interpreter.ILoop.loop(ILoop.scala:485)
at org.apache.spark.repl.SparkILoop.process(SparkILoop.scala:239)
at org.apache.spark.repl.Main$.doMain(Main.scala:78)
at org.apache.spark.repl.Main$.main(Main.scala:58)
at org.apache.spark.repl.Main.main(Main.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.spark.deploy.JavaMainApplication.start(SparkApplication.scala:52)
at org.apache.spark.deploy.SparkSubmit.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:951)
at org.apache.spark.deploy.SparkSubmit.doRunMain$1(SparkSubmit.scala:180)
at org.apache.spark.deploy.SparkSubmit.submit(SparkSubmit.scala:203)
at org.apache.spark.deploy.SparkSubmit.doSubmit(SparkSubmit.scala:90)
at org.apache.spark.deploy.SparkSubmit$$anon$2.doSubmit(SparkSubmit.scala:1030)
at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:1039)
at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
Caused by: java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $line14.$read$$iw$$iw$$iw$$iw$$iw$$iw$$iw$$iw.$anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
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)
21/06/17 13:15:44 WARN TaskSetManager: Lost task 0.0 in stage 0.0 (TID 0) (192.168.1.20 executor driver): TaskKilled (Stage cancelled)
org.apache.spark.SparkException: Job aborted.
at org.apache.spark.internal.io.SparkHadoopWriter$.write(SparkHadoopWriter.scala:105)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopDataset$1(PairRDDFunctions.scala:1090)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopDataset(PairRDDFunctions.scala:1088)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$4(PairRDDFunctions.scala:1061)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1026)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$3(PairRDDFunctions.scala:1008)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:1007)
at org.apache.spark.rdd.PairRDDFunctions.$anonfun$saveAsHadoopFile$2(PairRDDFunctions.scala:964)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.PairRDDFunctions.saveAsHadoopFile(PairRDDFunctions.scala:962)
at org.apache.spark.rdd.RDD.$anonfun$saveAsTextFile$2(RDD.scala:1578)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1578)
at org.apache.spark.rdd.RDD.$anonfun$saveAsTextFile$1(RDD.scala:1564)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:414)
at org.apache.spark.rdd.RDD.saveAsTextFile(RDD.scala:1564)
... 47 elided
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 0.0 failed 1 times, most recent failure: Lost task 1.0 in stage 0.0 (TID 1) (192.168.1.20 executor driver): java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2253)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2202)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2201)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2201)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1078)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1078)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1078)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2440)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2382)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2371)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:868)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2202)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2223)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2255)
at org.apache.spark.internal.io.SparkHadoopWriter$.write(SparkHadoopWriter.scala:83)
... 83 more
Caused by: java.lang.StringIndexOutOfBoundsException: String index out of range: 0
at java.lang.String.charAt(String.java:658)
at scala.collection.immutable.StringOps$.apply$extension(StringOps.scala:41)
at $anonfun$avglens$2(<console>:24)
at scala.collection.Iterator$$anon$10.next(Iterator.scala:459)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:156)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Also, a new folder avglens-output is created in my C:\Program Files\spark-3.1.1-bin-hadoop2.7\bin folder, but it is empty.
I don't understand why this errors appears, I have however authorized the writing on the bin folder.


Your problem seems to be in the map with word(0), not in the saveAsTextFile.
Since you are doing the split in the flatMap, the output of that step is a RDD with each word as a row, there is not an array for each element, just single word.
FlatMap flattens the array.
Check the difference
flatMap
scala> val rdd = sc.textFile("/Users/my_name/Workspace/spark-3.0.2-bin-hadoop2.7/README.md").flatMap(line => line.split(' '))
scala> rdd.take(5).foreach(println)
#
Apache
Spark
Spark
map
scala> val rdd = sc.textFile("/Users/sergio.couto/Workspace/spark-3.0.2-bin-hadoop2.7/README.md").map(line => line.split(' '))
scala> rdd.take(5).foreach(println)
[Ljava.lang.String;#7cd1d235
[Ljava.lang.String;#1736262a
[Ljava.lang.String;#7252e063
[Ljava.lang.String;#5edd0a7e
[Ljava.lang.String;#2c6f2bea
So you don't need to do word(0), it's not an array, you can just do word => (word, word.length)
Full Example:
val rdd = sc.textFile("/Users/my_name/Workspace/spark-3.0.2-bin-hadoop2.7/README.md")
.flatMap(line => line.split(' '))
.map(word => (word, word.length))
.groupByKey()
.map(pair => (pair._1, pair._2.sum/pair._2.size.toDouble))
scala> rdd.take(10).foreach(println)
(package,7.0)
(this,4.0)
(integration,11.0)
(Python,6.0)
(cluster.,8.0)
(its,3.0)
([run,4.0)
(There,5.0)
(general,7.0)
(YARN,,5.0)
Then you will be able to perform saveAsTextFile or whichever method you need

Related

Spark Error "java.nio.charset.MalformedInputException: Input length = 1"

I'm trying to run a Spark job with PySpark on Mac, and my Spark instance is in cluster mode. It's working well with simple spark.sql() tests. However, when I executed some action functions with big transformations, the job failed. It's strange that I always get an error: java.nio.charset.MalformedInputException: Input length = 1 but there is no code reading files here.
I also tried to add spark.driver.extraJavaOptions=-Dfile.encoding=utf-8 into the configuration, but still no success.
Code Example:
from pyspark.sql.window import Window
import pyspark.sql.functions as sf
import pyspark.sql.types as st
conf = SparkConf()
...
conf.set("spark.archives", "hdfs://.../pyspark_conda_env_0.1.tar.gz#environment")
conf.set("spark.yarn.dist.archives", "hdfs://.../pyspark_conda_env_0.1.tar.gz#environment")
conf.set("spark.yarn.appMasterEnv.PYSPARK_PYTHON", "./environment/bin/python")
conf.set("spark.driver.extraJavaOptions", "-Dfile.encoding=utf-8")
sc = SparkContext(conf=conf)
spark = SparkSession.builder.enableHiveSupport().getOrCreate()
df = spark.sql("...")
df.cache()
df.take(1) # passed
df = df.withColumn(...)
df = df.groupBy("uid", sf.window(sf.col("ts"), "14 days", startTime="11 days")).agg(...)
df = df.withColumn(...)
df.count() # failed
df.take(1) # failed
Error:
Py4JJavaError: An error occurred while calling o790.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 57.0 failed 4 times, most recent failure: Lost task 2.3 in stage 57.0 (TID 2910) (xx.xx.x.xxx executor 2): java.nio.charset.MalformedInputException: Input length = 1
at java.base/java.nio.charset.CoderResult.throwException(Unknown Source)
at java.base/sun.nio.cs.StreamDecoder.implRead(Unknown Source)
at java.base/sun.nio.cs.StreamDecoder.read(Unknown Source)
at java.base/java.io.InputStreamReader.read(Unknown Source)
at java.base/java.io.BufferedReader.fill(Unknown Source)
at java.base/java.io.BufferedReader.readLine(Unknown Source)
at java.base/java.io.BufferedReader.readLine(Unknown Source)
at scala.io.BufferedSource$BufferedLineIterator.hasNext(BufferedSource.scala:74)
at scala.collection.Iterator.foreach(Iterator.scala:943)
at scala.collection.Iterator.foreach$(Iterator.scala:943)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
at scala.collection.TraversableOnce.addString(TraversableOnce.scala:424)
at scala.collection.TraversableOnce.addString$(TraversableOnce.scala:407)
at scala.collection.AbstractIterator.addString(Iterator.scala:1431)
at scala.collection.TraversableOnce.mkString(TraversableOnce.scala:377)
at scala.collection.TraversableOnce.mkString$(TraversableOnce.scala:376)
at scala.collection.AbstractIterator.mkString(Iterator.scala:1431)
at scala.collection.TraversableOnce.mkString(TraversableOnce.scala:379)
at scala.collection.TraversableOnce.mkString$(TraversableOnce.scala:379)
at scala.collection.AbstractIterator.mkString(Iterator.scala:1431)
at org.apache.spark.util.Utils$.getStderr(Utils.scala:2006)
at org.apache.spark.api.python.PythonWorkerFactory.$anonfun$startDaemon$1(PythonWorkerFactory.scala:254)
at scala.Option.flatMap(Option.scala:271)
at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:254)
at org.apache.spark.api.python.PythonWorkerFactory.liftedTree1$1(PythonWorkerFactory.scala:143)
at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:136)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:106)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:121)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:162)
at org.apache.spark.sql.execution.python.BatchEvalPythonExec.evaluate(BatchEvalPythonExec.scala:81)
at org.apache.spark.sql.execution.python.EvalPythonExec.$anonfun$doExecute$2(EvalPythonExec.scala:130)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:863)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:863)
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.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.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.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
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$TaskRunner.run(Executor.scala:509)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.base/java.lang.Thread.run(Unknown Source)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2454)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2403)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2402)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2402)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1160)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1160)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1160)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2642)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2584)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2573)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2235)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2254)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:476)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:429)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48)
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$executeCollect$1(AdaptiveSparkPlanExec.scala:338)
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.withFinalPlanUpdate(AdaptiveSparkPlanExec.scala:366)
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.executeCollect(AdaptiveSparkPlanExec.scala:338)
at org.apache.spark.sql.Dataset.$anonfun$collectToPython$1(Dataset.scala:3538)
at org.apache.spark.sql.Dataset.$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.collectToPython(Dataset.scala:3535)
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:750)
Caused by: java.nio.charset.MalformedInputException: Input length = 1
at java.nio.charset.CoderResult.throwException(Unknown Source)
at sun.nio.cs.StreamDecoder.implRead(Unknown Source)
at sun.nio.cs.StreamDecoder.read(Unknown Source)
at java.io.InputStreamReader.read(Unknown Source)
at java.io.BufferedReader.fill(Unknown Source)
at java.io.BufferedReader.readLine(Unknown Source)
at java.io.BufferedReader.readLine(Unknown Source)
at scala.io.BufferedSource$BufferedLineIterator.hasNext(BufferedSource.scala:74)
at scala.collection.Iterator.foreach(Iterator.scala:943)
at scala.collection.Iterator.foreach$(Iterator.scala:943)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
at scala.collection.TraversableOnce.addString(TraversableOnce.scala:424)
at scala.collection.TraversableOnce.addString$(TraversableOnce.scala:407)
at scala.collection.AbstractIterator.addString(Iterator.scala:1431)
at scala.collection.TraversableOnce.mkString(TraversableOnce.scala:377)
at scala.collection.TraversableOnce.mkString$(TraversableOnce.scala:376)
at scala.collection.AbstractIterator.mkString(Iterator.scala:1431)
at scala.collection.TraversableOnce.mkString(TraversableOnce.scala:379)
at scala.collection.TraversableOnce.mkString$(TraversableOnce.scala:379)
at scala.collection.AbstractIterator.mkString(Iterator.scala:1431)
at org.apache.spark.util.Utils$.getStderr(Utils.scala:2006)
at org.apache.spark.api.python.PythonWorkerFactory.$anonfun$startDaemon$1(PythonWorkerFactory.scala:254)
at scala.Option.flatMap(Option.scala:271)
at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:254)
at org.apache.spark.api.python.PythonWorkerFactory.liftedTree1$1(PythonWorkerFactory.scala:143)
at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:136)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:106)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:121)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:162)
at org.apache.spark.sql.execution.python.BatchEvalPythonExec.evaluate(BatchEvalPythonExec.scala:81)
at org.apache.spark.sql.execution.python.EvalPythonExec.$anonfun$doExecute$2(EvalPythonExec.scala:130)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:863)
at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:863)
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.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.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.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
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$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(Unknown Source)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(Unknown Source)
at java.lang.Thread.run(Unknown Source)
Any ideas? Thanks!

Cant write (save) spark dataframe in parquet fromat to S3

I have 12 smaller parquet files which I successfully read them and combine them. I'm trying to save the combined dataframe in one parquet file in S3 but It shows me an error
from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('combine_files').getOrCreate()
the files are in this dir
df=spark.read.parquet("s3://aws-emr-resources-359367213591-us-east-1/taxi_data_2020/*").coalesce(1)
df.count()
24649092
when I try to write (save the dataframe in parquet format in s3 folder)
df.write.parquet("s3://aws-emr-resources-359367213591-us-east-1/merged_data_2020/single")
it shows me this error, how i can solve it
An error was encountered:
An error occurred while calling o268.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:202)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:174)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:178)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:174)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:202)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:199)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:174)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:114)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:112)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
at org.apache.spark.sql.execution.SQLExecution$.org$apache$spark$sql$execution$SQLExecution$$executeQuery$1(SQLExecution.scala:83)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1$$anonfun$apply$1.apply(SQLExecution.scala:94)
at org.apache.spark.sql.execution.QueryExecutionMetrics$.withMetrics(QueryExecutionMetrics.scala:141)
at org.apache.spark.sql.execution.SQLExecution$.org$apache$spark$sql$execution$SQLExecution$$withMetrics(SQLExecution.scala:178)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:93)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:200)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:92)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:696)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:305)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:291)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:249)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:586)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:750)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 7.0 failed 4 times, most recent failure: Lost task 0.3 in stage 7.0 (TID 13, ip-172-31-75-44.ec2.internal, executor 6): org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:174)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:173)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:411)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:417)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
Caused by: java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainDoubleDictionary
at org.apache.parquet.column.Dictionary.decodeToInt(Dictionary.java:45)
at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToInt(ParquetDictionary.java:31)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getInt(OnHeapColumnVector.java:298)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:585)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:248)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:246)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:252)
... 10 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2171)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2159)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2158)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2158)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1011)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1011)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1011)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2419)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2368)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2357)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:822)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2111)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:171)
... 37 more
Caused by: org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:174)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:173)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:411)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:417)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainDoubleDictionary
at org.apache.parquet.column.Dictionary.decodeToInt(Dictionary.java:45)
at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToInt(ParquetDictionary.java:31)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getInt(OnHeapColumnVector.java:298)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:585)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:248)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:246)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:252)
... 10 more
Traceback (most recent call last):
File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 847, in parquet
self._jwrite.parquet(path)
File "/usr/lib/spark/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in call
answer, self.gateway_client, self.target_id, self.name)
File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/usr/lib/spark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o268.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:202)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:174)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:178)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:174)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:202)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:199)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:174)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:114)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:112)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:696)
at org.apache.spark.sql.execution.SQLExecution$.org$apache$spark$sql$execution$SQLExecution$$executeQuery$1(SQLExecution.scala:83)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1$$anonfun$apply$1.apply(SQLExecution.scala:94)
at org.apache.spark.sql.execution.QueryExecutionMetrics$.withMetrics(QueryExecutionMetrics.scala:141)
at org.apache.spark.sql.execution.SQLExecution$.org$apache$spark$sql$execution$SQLExecution$$withMetrics(SQLExecution.scala:178)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:93)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:200)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:92)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:696)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:305)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:291)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:249)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:586)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:750)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 7.0 failed 4 times, most recent failure: Lost task 0.3 in stage 7.0 (TID 13, ip-172-31-75-44.ec2.internal, executor 6): org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:174)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:173)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:411)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:417)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)
Caused by: java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainDoubleDictionary
at org.apache.parquet.column.Dictionary.decodeToInt(Dictionary.java:45)
at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToInt(ParquetDictionary.java:31)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getInt(OnHeapColumnVector.java:298)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:585)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:248)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:246)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:252)
... 10 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2171)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2159)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2158)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2158)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1011)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1011)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1011)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2419)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2368)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2357)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:822)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2111)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:171)
... 37 more
Caused by: org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:261)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:174)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:173)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:123)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:411)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:417)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.lang.UnsupportedOperationException: org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainDoubleDictionary
at org.apache.parquet.column.Dictionary.decodeToInt(Dictionary.java:45)
at org.apache.spark.sql.execution.datasources.parquet.ParquetDictionary.decodeToInt(ParquetDictionary.java:31)
at org.apache.spark.sql.execution.vectorized.OnHeapColumnVector.getInt(OnHeapColumnVector.java:298)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$13$$anon$1.hasNext(WholeStageCodegenExec.scala:585)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:248)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:246)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:252)
... 10 more

df.write.parquet("s3a://aws-emr-resources-359367213591-us-east-1/merged_data_2020/single")

AWS Glue Bad value for type BigDecimal : NaN

I'm trying to export a table I crawled from a postgres(rds) database into glue. There's one field with a decimal(10, 2) type. Now I have several problems.
Exporting the table from glue(using spark 2.4, 3.1 python 3) into s3 with the following code:
datasource = glueContext.create_dynamic_frame.from_catalog(
database='source_database',
table_name='table',
)
glueContext.write_dynamic_frame.from_options(
frame=datasource,
connection_type="s3",
connection_options={"path": "s3//..."},
format='parquet',
)
Results in the error:
py4j.protocol.Py4JJavaError: An error occurred while calling o89.pyWriteDynamicFrame.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:231)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:195)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:108)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:106)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:131)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:185)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:223)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:220)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:181)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:134)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:133)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:989)
at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107)
at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232)
at org.apache.spark.sql.execution.SQLExecution$.executeQuery$1(SQLExecution.scala:110)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:135)
at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107)
at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:135)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:253)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:134)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:68)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:989)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:301)
at com.amazonaws.services.glue.SparkSQLDataSink.$anonfun$writeDynamicFrame$3(DataSink.scala:595)
at com.amazonaws.services.glue.SparkSQLDataSink.$anonfun$writeDynamicFrame$3$adapted(DataSink.scala:582)
at com.amazonaws.services.glue.util.FileSchemeWrapper.$anonfun$executeWithQualifiedScheme$1(FileSchemeWrapper.scala:77)
at com.amazonaws.services.glue.util.FileSchemeWrapper.executeWith(FileSchemeWrapper.scala:70)
at com.amazonaws.services.glue.util.FileSchemeWrapper.executeWithQualifiedScheme(FileSchemeWrapper.scala:77)
at com.amazonaws.services.glue.SparkSQLDataSink.writeDynamicFrame(DataSink.scala:582)
at com.amazonaws.services.glue.DataSink.pyWriteDynamicFrame(DataSink.scala:64)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3) (172.31.12.229 executor 1): org.postgresql.util.PSQLException: Bad value for type BigDecimal : NaN
at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3059)
at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3068)
at org.postgresql.jdbc.PgResultSet.getNumeric(PgResultSet.java:2486)
at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:2438)
at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:406)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:403)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:401)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:352)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:334)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$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:755)
at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:225)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.$anonfun$prepareShuffleDependency$10(ShuffleExchangeExec.scala:379)
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.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.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
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:2465)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2414)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2413)
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:2413)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1124)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1124)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1124)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2679)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2621)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2610)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:914)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2238)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:200)
... 45 more
Caused by: org.postgresql.util.PSQLException: Bad value for type BigDecimal : NaN
at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3059)
at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3068)
at org.postgresql.jdbc.PgResultSet.getNumeric(PgResultSet.java:2486)
at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:2438)
at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:406)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:403)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:401)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:352)
at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:334)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$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:755)
at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:225)
at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.$anonfun$prepareShuffleDependency$10(ShuffleExchangeExec.scala:379)
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.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.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
2021-09-13 09:52:47,872 ERROR [main] glue.ProcessLauncher "/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 277, in write_dynamic_frame_from_options format, format_options, transformation_ctx) File "/opt/amazon/lib/python3.6/site-packages/awsglue/context.py", line 300, in write_from_options return sink.write(frame_or_dfc) File "/opt/amazon/lib/python3.6/site-packages/awsglue/data_sink.py", line 35, in write return self.writeFrame(dynamic_frame_or_dfc, info) File "/opt/amazon/lib/python3.6/site-packages/awsglue/data_sink.py", line 31, in writeFrame return DynamicFrame(self._jsink.pyWriteDynamicFrame(dynamic_frame._jdf, callsite(), info), dynamic_frame.glue_ctx, dynamic_frame.name + "_errors") File "/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py", line 1305, in __call__ answer, self.gateway_client, self.target_id, self.name) File "/opt/amazon/spark/python/lib/pyspark.zip/pyspark/sql/utils.py", line 111, in deco return f(*a, **kw) File "/opt/amazon/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py", line 328, in get_return_value format(target_id, ".", name), value) py4j.protocol.Py4JJavaError: An error occurred while calling o89.pyWriteDynamicFrame. : org.apache.spark.SparkException: Job aborted. at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:231) at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:195) at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:108) at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:106) at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:131) at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:185) at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:223) at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:220) at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:181) at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:134) at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:133) at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:989) at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107) at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232) at org.apache.spark.sql.execution.SQLExecution$.executeQuery$1(SQLExecution.scala:110) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$6(SQLExecution.scala:135) at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:107) at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:232) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:135) at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:253) at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:134) at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:772) at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:68) at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:989) at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:438) at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:415) at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:301) at com.amazonaws.services.glue.SparkSQLDataSink.$anonfun$writeDynamicFrame$3(DataSink.scala:595) at com.amazonaws.services.glue.SparkSQLDataSink.$anonfun$writeDynamicFrame$3$adapted(DataSink.scala:582) at com.amazonaws.services.glue.util.FileSchemeWrapper.$anonfun$executeWithQualifiedScheme$1(FileSchemeWrapper.scala:77) at com.amazonaws.services.glue.util.FileSchemeWrapper.executeWith(FileSchemeWrapper.scala:70) at com.amazonaws.services.glue.util.FileSchemeWrapper.executeWithQualifiedScheme(FileSchemeWrapper.scala:77) at com.amazonaws.services.glue.SparkSQLDataSink.writeDynamicFrame(DataSink.scala:582) at com.amazonaws.services.glue.DataSink.pyWriteDynamicFrame(DataSink.scala:64) 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.GatewayConnection.run(GatewayConnection.java:238) at java.lang.Thread.run(Thread.java:748) Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3) (172.31.12.229 executor 1): org.postgresql.util.PSQLException: Bad value for type BigDecimal : NaN at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3059) at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3068) at org.postgresql.jdbc.PgResultSet.getNumeric(PgResultSet.java:2486) at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:2438) at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:406) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:403) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:401) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:352) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:334) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755) at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:225) at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.$anonfun$prepareShuffleDependency$10(ShuffleExchangeExec.scala:379) at org.apache.spark.rdd.RDD.$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.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.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2465) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2414) at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2413) at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2413) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1124) at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1124) at scala.Option.foreach(Option.scala:407) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1124) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2679) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2621) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2610) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:914) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2238) at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:200) ... 45 more Caused by: org.postgresql.util.PSQLException: Bad value for type BigDecimal : NaN at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3059) at org.postgresql.jdbc.PgResultSet.toBigDecimal(PgResultSet.java:3068) at org.postgresql.jdbc.PgResultSet.getNumeric(PgResultSet.java:2486) at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:2438) at org.postgresql.jdbc.PgResultSet.getBigDecimal(PgResultSet.java:406) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3(JdbcUtils.scala:403) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.$anonfun$makeGetter$3$adapted(JdbcUtils.scala:401) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:352) at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anon$1.getNext(JdbcUtils.scala:334) at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:755) at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:225) at org.apache.spark.sql.execution.exchange.ShuffleExchangeExec$.$anonfun$prepareShuffleDependency$10(ShuffleExchangeExec.scala:379) at org.apache.spark.rdd.RDD.$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.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.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52) at org.apache.spark.scheduler.Task.run(Task.scala:131) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) ... 1 more
I also changed the datatype of the field with this decimal type(within the glue catalog) to a double within the catalog to a double but glue(spark) seems to pick the original schema of the table.
There's a similar post to this mine but I don't have direct access to call the .getDouble() method since I'm not interfacing with the java/scala code within glue.
How can I resolve this?

If any of the column have 'NaN' value in table, then it will show 'AWS Glue Bad value for type BigDecimal : NaN' error while trying to create frame.

FileAlreadyExistsException while using Spark insertInto

I used following code to write a dataframe to a hive partitioned table by using pyspark Insertinto function.
spark.conf.set("spark.sql.sources.partitionOverwriteMode", "DYNAMIC")
df.write.mode("overwrite").insertInto(table, overwrite=True)
When the cluster is running some other heavy jobs. It has a 1/3 probability of error.
I think it maybe happens when the task seems to have failed but not fail indeed and yarn started another task to run this job.So two tasks conflict.
Traceback (most recent call last):
File "dataframe.py", line 39, in save
df.write.mode("overwrite").insertInto(table, overwrite=True)
File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/sql/readwriter.py", line 745, in insertInto
File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/py4j-0.10.7-src.zip/py4j/java_gateway.py", line 1257, in __call__
File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/pyspark.zip/pyspark/sql/utils.py", line 63, in deco
File "/opt/cloudera/parcels/SPARK2-2.4.0.cloudera2-1.cdh5.13.3.p0.1041012/lib/spark2/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o2575.insertInto.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:198)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:159)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:104)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:102)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:122)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:676)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:676)
at org.apache.spark.sql.DataFrameWriter.insertInto(DataFrameWriter.scala:334)
at org.apache.spark.sql.DataFrameWriter.insertInto(DataFrameWriter.scala:320)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 53 in stage 535.0 failed 4 times, most recent failure: Lost task 53.4 in stage 535.0 (TID 137333, hadoop138, executor 3401): org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:257)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:170)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:169)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.hadoop.fs.FileAlreadyExistsException: /user/hive/warehouse/test.db/test/.spark-staging-77bf12fc-6606-4b84-8c89-81ec7431c729/dt=20200214/part-00053-77bf12fc-6606-4b84-8c89-81ec7431c729.c000.snappy.parquet for client 192.168.1.1 already exists
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInternal(FSNamesystem.java:2935)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2824)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2709)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:602)
at org.apache.hadoop.hdfs.server.namenode.AuthorizationProviderProxyClientProtocol.create(AuthorizationProviderProxyClientProtocol.java:115)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:412)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2226)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2222)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1917)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2220)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.ipc.RemoteException.instantiateException(RemoteException.java:106)
at org.apache.hadoop.ipc.RemoteException.unwrapRemoteException(RemoteException.java:73)
at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:2105)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1767)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1691)
at org.apache.hadoop.hdfs.DistributedFileSystem$7.doCall(DistributedFileSystem.java:437)
at org.apache.hadoop.hdfs.DistributedFileSystem$7.doCall(DistributedFileSystem.java:433)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:433)
at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:374)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:926)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:907)
at parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:220)
at parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:311)
at parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:282)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:37)
at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anon$1.newInstance(ParquetFileFormat.scala:150)
at org.apache.spark.sql.execution.datasources.DynamicPartitionDataWriter.newOutputWriter(FileFormatDataWriter.scala:236)
at org.apache.spark.sql.execution.datasources.DynamicPartitionDataWriter.write(FileFormatDataWriter.scala:260)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:245)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:242)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:248)
... 10 more
Caused by: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.fs.FileAlreadyExistsException): /user/hive/warehouse/test.db/test/.spark-staging-77bf12fc-6606-4b84-8c89-81ec7431c729/dt=20200214/part-00053-77bf12fc-6606-4b84-8c89-81ec7431c729.c000.snappy.parquet for client 192.168.1.1 already exists
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInternal(FSNamesystem.java:2935)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2824)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2709)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:602)
at org.apache.hadoop.hdfs.server.namenode.AuthorizationProviderProxyClientProtocol.create(AuthorizationProviderProxyClientProtocol.java:115)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:412)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2226)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2222)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1917)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2220)
at org.apache.hadoop.ipc.Client.call(Client.java:1504)
at org.apache.hadoop.ipc.Client.call(Client.java:1441)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:230)
at com.sun.proxy.$Proxy17.create(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.create(ClientNamenodeProtocolTranslatorPB.java:311)
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 org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:260)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:104)
at com.sun.proxy.$Proxy18.create(Unknown Source)
at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:2100)
... 30 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1889)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1877)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1876)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1876)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:926)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:926)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2110)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2059)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2048)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:167)
... 31 more
Caused by: org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:257)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:170)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:169)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:121)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$10.apply(Executor.scala:408)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1405)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:414)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: org.apache.hadoop.fs.FileAlreadyExistsException: /user/hive/warehouse/test.db/test/.spark-staging-77bf12fc-6606-4b84-8c89-81ec7431c729/dt=20200214/part-00053-77bf12fc-6606-4b84-8c89-81ec7431c729.c000.snappy.parquet for client 192.168.1.1 already exists
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInternal(FSNamesystem.java:2935)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2824)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2709)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:602)
at org.apache.hadoop.hdfs.server.namenode.AuthorizationProviderProxyClientProtocol.create(AuthorizationProviderProxyClientProtocol.java:115)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:412)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2226)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2222)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1917)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2220)
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
at org.apache.hadoop.ipc.RemoteException.instantiateException(RemoteException.java:106)
at org.apache.hadoop.ipc.RemoteException.unwrapRemoteException(RemoteException.java:73)
at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:2105)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1767)
at org.apache.hadoop.hdfs.DFSClient.create(DFSClient.java:1691)
at org.apache.hadoop.hdfs.DistributedFileSystem$7.doCall(DistributedFileSystem.java:437)
at org.apache.hadoop.hdfs.DistributedFileSystem$7.doCall(DistributedFileSystem.java:433)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:433)
at org.apache.hadoop.hdfs.DistributedFileSystem.create(DistributedFileSystem.java:374)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:926)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:907)
at parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:220)
at parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:311)
at parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:282)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:37)
at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anon$1.newInstance(ParquetFileFormat.scala:150)
at org.apache.spark.sql.execution.datasources.DynamicPartitionDataWriter.newOutputWriter(FileFormatDataWriter.scala:236)
at org.apache.spark.sql.execution.datasources.DynamicPartitionDataWriter.write(FileFormatDataWriter.scala:260)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:245)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:242)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1439)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:248)
... 10 more
Caused by: org.apache.hadoop.ipc.RemoteException(org.apache.hadoop.fs.FileAlreadyExistsException): /user/hive/warehouse/test.db/test/.spark-staging-77bf12fc-6606-4b84-8c89-81ec7431c729/dt=20200214/part-00053-77bf12fc-6606-4b84-8c89-81ec7431c729.c000.snappy.parquet for client 192.168.1.1 already exists
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInternal(FSNamesystem.java:2935)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFileInt(FSNamesystem.java:2824)
at org.apache.hadoop.hdfs.server.namenode.FSNamesystem.startFile(FSNamesystem.java:2709)
at org.apache.hadoop.hdfs.server.namenode.NameNodeRpcServer.create(NameNodeRpcServer.java:602)
at org.apache.hadoop.hdfs.server.namenode.AuthorizationProviderProxyClientProtocol.create(AuthorizationProviderProxyClientProtocol.java:115)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolServerSideTranslatorPB.create(ClientNamenodeProtocolServerSideTranslatorPB.java:412)
at org.apache.hadoop.hdfs.protocol.proto.ClientNamenodeProtocolProtos$ClientNamenodeProtocol$2.callBlockingMethod(ClientNamenodeProtocolProtos.java)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Server$ProtoBufRpcInvoker.call(ProtobufRpcEngine.java:617)
at org.apache.hadoop.ipc.RPC$Server.call(RPC.java:1073)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2226)
at org.apache.hadoop.ipc.Server$Handler$1.run(Server.java:2222)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1917)
at org.apache.hadoop.ipc.Server$Handler.run(Server.java:2220)
at org.apache.hadoop.ipc.Client.call(Client.java:1504)
at org.apache.hadoop.ipc.Client.call(Client.java:1441)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:230)
at com.sun.proxy.$Proxy17.create(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.create(ClientNamenodeProtocolTranslatorPB.java:311)
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 org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:260)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:104)
at com.sun.proxy.$Proxy18.create(Unknown Source)
at org.apache.hadoop.hdfs.DFSOutputStream.newStreamForCreate(DFSOutputStream.java:2100)
... 30 more

This issue is fixed in Spark 3.1.0.
Reference:
https://issues.apache.org/jira/browse/SPARK-27194
https://issues.apache.org/jira/browse/SPARK-29302

Spark job fails when processing a larger dataset

I am passing a function to Spark. That function solves an optimization problem which takes about a half second for each data row to solve. However, If my dataset is only 10 samples, Spark will process everything just fine as expected. However, this error stack appears if I process a dataset of say 100 rows or more:
2018-06-23 21:42:16 WARN NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
2018-06-23 21:42:17 WARN Utils:66 - Service 'SparkUI' could not bind on port 4040. Attempting port 4041.
[Stage 0:> (0 + 1) / 1]2018-06-23 21:48:54 ERROR Executor:91 - Exception in task 0.0 in stage 0.0 (TID 0)
java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:210)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:284)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:431)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.hasNext(RDD.scala:860)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.foreach(RDD.scala:859)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.to(RDD.scala:859)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toBuffer(RDD.scala:859)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toArray(RDD.scala:859)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
2018-06-23 21:48:54 WARN TaskSetManager:66 - Lost task 0.0 in stage 0.0 (TID 0, localhost, executor driver): java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:210)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:284)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:431)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.hasNext(RDD.scala:860)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.foreach(RDD.scala:859)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.to(RDD.scala:859)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toBuffer(RDD.scala:859)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toArray(RDD.scala:859)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
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)
2018-06-23 21:48:54 ERROR TaskSetManager:70 - Task 0 in stage 0.0 failed 1 times; aborting job
Traceback (most recent call last):
File "C:/Users/salman/PycharmProjects/TestingPySpark/testingUDF.py", line 68, in <module>
appended.collect()
File "C:\Users\salman\AppData\Local\Programs\Python\Python36\lib\site-packages\pyspark\rdd.py", line 834, in collect
sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "C:\Users\salman\AppData\Local\Programs\Python\Python36\lib\site-packages\py4j\java_gateway.py", line 1257, in __call__
answer, self.gateway_client, self.target_id, self.name)
File "C:\Users\salman\AppData\Local\Programs\Python\Python36\lib\site-packages\pyspark\sql\utils.py", line 63, in deco
return f(*a, **kw)
File "C:\Users\salman\AppData\Local\Programs\Python\Python36\lib\site-packages\py4j\protocol.py", line 328, in get_return_value
format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most recent failure: Lost task 0.0 in stage 0.0 (TID 0, localhost, executor driver): java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:210)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:284)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:431)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.hasNext(RDD.scala:860)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.foreach(RDD.scala:859)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.to(RDD.scala:859)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toBuffer(RDD.scala:859)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toArray(RDD.scala:859)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1602)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1590)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1589)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1589)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1823)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1772)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1761)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:162)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
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.GatewayConnection.run(GatewayConnection.java:238)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.net.SocketException: Connection reset
at java.net.SocketInputStream.read(SocketInputStream.java:210)
at java.net.SocketInputStream.read(SocketInputStream.java:141)
at java.io.BufferedInputStream.read1(BufferedInputStream.java:284)
at java.io.BufferedInputStream.read(BufferedInputStream.java:345)
at java.io.DataInputStream.readFully(DataInputStream.java:195)
at java.io.DataInputStream.readFully(DataInputStream.java:169)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:431)
at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421)
at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.hasNext(RDD.scala:860)
at scala.collection.Iterator$class.foreach(Iterator.scala:893)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.foreach(RDD.scala:859)
at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48)
at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.to(RDD.scala:859)
at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toBuffer(RDD.scala:859)
at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289)
at org.apache.spark.rdd.RDD$$anonfun$zip$1$$anonfun$apply$27$$anon$2.toArray(RDD.scala:859)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.rdd.RDD$$anonfun$collect$1$$anonfun$12.apply(RDD.scala:939)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2074)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Process finished with exit code 1
Here is my code:
spark = SparkSession \
.builder \
.appName("testingUDF") \
.getOrCreate()
temp_input = spark.read.text("demands_only.csv").rdd.map(myFunc2)
obj = SolveDemand.SolveDemand()
lines = spark.read.text("demands_only.csv").rdd.map(obj.solve)
appended = temp_input.zip(lines)
appended.collect()
any suggestion about the error?

Seems like memory issue and python process got OOM killed.
Add into your command
--executor-memory 10G
--driver-memory 10G
Example :
./bin/spark-submit \
--class org.apache.spark.examples.SparkPi \
--master spark://master.node:7077 \
--executor-memory 8G \
--total-executor-cores 100 \
/path/to/vaquarkhan-example.jar \
1000
https://community.hortonworks.com/articles/42803/spark-on-yarn-executor-resource-allocation-optimiz.html
http://blog.cloudera.com/blog/2015/03/how-to-tune-your-apache-spark-jobs-part-1/
http://blog.cloudera.com/blog/2015/03/how-to-tune-your-apache-spark-jobs-part-2/

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