An error occurred while calling o7344.save

An error occurred while calling o7344.save - apache-spark

I am running spark jobs using datafactory in azure databricks.
My cluster vesion is 9.1 LTS ML (includes Apache Spark 3.1.2, Scala 2.12).
I am writing data on azure blob storage.
While writing job gives me error.
It shows error on line
AllDataDF.coalesce(1).write.format("delta").mode("append").option("mergeSchema", "true").save(path)
And traceback in as below.
/databricks/spark/python/pyspark/sql/readwriter.py in save(self, path, format, mode, partitionBy, **options)
1134 self._jwrite.save()
1135 else:
-> 1136 self._jwrite.save(path)
1137
1138 #since(1.4)
/databricks/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py in __call__(self, *args)
1302
1303 answer = self.gateway_client.send_command(command)
-> 1304 return_value = get_return_value(
1305 answer, self.gateway_client, self.target_id, self.name)
1306
/databricks/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
115 def deco(*a, **kw):
116 try:
--> 117 return f(*a, **kw)
118 except py4j.protocol.Py4JJavaError as e:
119 converted = convert_exception(e.java_exception)
/databricks/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
325 if answer[1] == REFERENCE_TYPE:
--> 326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
328 format(target_id, ".", name), value)
Py4JJavaError: An error occurred while calling o7344.save.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:307)
at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.$anonfun$writeFiles$5(TransactionalWriteEdge.scala:349)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$5(SQLExecution.scala:130)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:273)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$1(SQLExecution.scala:104)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:854)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:77)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:223)
at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.$anonfun$writeFiles$1(TransactionalWriteEdge.scala:296)
at com.databricks.spark.util.FrameProfiler$.record(FrameProfiler.scala:80)
at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.$anonfun$recordDeltaOperation$5(DeltaLogging.scala:122)
at com.databricks.logging.UsageLogging.$anonfun$recordOperation$1(UsageLogging.scala:395)
at com.databricks.logging.UsageLogging.executeThunkAndCaptureResultTags$1(UsageLogging.scala:484)
at com.databricks.logging.UsageLogging.$anonfun$recordOperationWithResultTags$4(UsageLogging.scala:504)
at com.databricks.logging.UsageLogging.$anonfun$withAttributionContext$1(UsageLogging.scala:266)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:62)
at com.databricks.logging.UsageLogging.withAttributionContext(UsageLogging.scala:261)
at com.databricks.logging.UsageLogging.withAttributionContext$(UsageLogging.scala:258)
at com.databricks.spark.util.PublicDBLogging.withAttributionContext(DatabricksSparkUsageLogger.scala:20)
at com.databricks.logging.UsageLogging.withAttributionTags(UsageLogging.scala:305)
at com.databricks.logging.UsageLogging.withAttributionTags$(UsageLogging.scala:297)
at com.databricks.spark.util.PublicDBLogging.withAttributionTags(DatabricksSparkUsageLogger.scala:20)
at com.databricks.logging.UsageLogging.recordOperationWithResultTags(UsageLogging.scala:479)
at com.databricks.logging.UsageLogging.recordOperationWithResultTags$(UsageLogging.scala:404)
at com.databricks.spark.util.PublicDBLogging.recordOperationWithResultTags(DatabricksSparkUsageLogger.scala:20)
at com.databricks.logging.UsageLogging.recordOperation(UsageLogging.scala:395)
at com.databricks.logging.UsageLogging.recordOperation$(UsageLogging.scala:367)
at com.databricks.spark.util.PublicDBLogging.recordOperation(DatabricksSparkUsageLogger.scala:20)
at com.databricks.spark.util.PublicDBLogging.recordOperation0(DatabricksSparkUsageLogger.scala:57)
at com.databricks.spark.util.DatabricksSparkUsageLogger.recordOperation(DatabricksSparkUsageLogger.scala:137)
at com.databricks.spark.util.UsageLogger.recordOperation(UsageLogger.scala:71)
at com.databricks.spark.util.UsageLogger.recordOperation$(UsageLogger.scala:58)
at com.databricks.spark.util.DatabricksSparkUsageLogger.recordOperation(DatabricksSparkUsageLogger.scala:98)
at com.databricks.spark.util.UsageLogging.recordOperation(UsageLogger.scala:429)
at com.databricks.spark.util.UsageLogging.recordOperation$(UsageLogger.scala:408)
at com.databricks.sql.transaction.tahoe.OptimisticTransaction.recordOperation(OptimisticTransaction.scala:98)
at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.recordDeltaOperation(DeltaLogging.scala:120)
at com.databricks.sql.transaction.tahoe.metering.DeltaLogging.recordDeltaOperation$(DeltaLogging.scala:104)
at com.databricks.sql.transaction.tahoe.OptimisticTransaction.recordDeltaOperation(OptimisticTransaction.scala:98)
at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.writeFiles(TransactionalWriteEdge.scala:213)
at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.writeFiles$(TransactionalWriteEdge.scala:207)
at com.databricks.sql.transaction.tahoe.OptimisticTransaction.writeFiles(OptimisticTransaction.scala:98)
at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.writeFiles(TransactionalWriteEdge.scala:389)
at com.databricks.sql.transaction.tahoe.files.TransactionalWriteEdge.writeFiles$(TransactionalWriteEdge.scala:382)
at com.databricks.sql.transaction.tahoe.OptimisticTransaction.writeFiles(OptimisticTransaction.scala:98)
at com.databricks.sql.transaction.tahoe.files.TransactionalWrite.writeFiles(TransactionalWrite.scala:158)
at com.databricks.sql.transaction.tahoe.files.TransactionalWrite.writeFiles$(TransactionalWrite.scala:155)
at com.databricks.sql.transaction.tahoe.OptimisticTransaction.writeFiles(OptimisticTransaction.scala:98)
at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.write(WriteIntoDelta.scala:175)
at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.$anonfun$run$2(WriteIntoDelta.scala:91)
at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.$anonfun$run$2$adapted(WriteIntoDelta.scala:83)
at com.databricks.sql.transaction.tahoe.DeltaLog.withNewTransaction(DeltaLog.scala:206)
at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.$anonfun$run$1(WriteIntoDelta.scala:83)
at com.databricks.sql.acl.CheckPermissions$.trusted(CheckPermissions.scala:1413)
at com.databricks.sql.transaction.tahoe.commands.WriteIntoDelta.run(WriteIntoDelta.scala:82)
at com.databricks.sql.transaction.tahoe.sources.DeltaDataSource.createRelation(DeltaDataSource.scala:164)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:48)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:75)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:73)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:96)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:213)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:257)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:165)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:253)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:209)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:167)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:166)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:1080)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$5(SQLExecution.scala:130)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:273)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$1(SQLExecution.scala:104)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:854)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:77)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:223)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:1080)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:469)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:386)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:304)
at sun.reflect.GeneratedMethodAccessor531.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:380)
at py4j.Gateway.invoke(Gateway.java:295)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:251)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 8352.0 failed 4 times, most recent failure: Lost task 0.3 in stage 8352.0 (TID 10576) (10.139.64.18 executor 17): org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:396)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$15(FileFormatWriter.scala:284)
at org.apache.spark.scheduler.ResultTask.$anonfun$runTask$3(ResultTask.scala:75)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.ResultTask.$anonfun$runTask$1(ResultTask.scala:75)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:55)
at org.apache.spark.scheduler.Task.doRunTask(Task.scala:150)
at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:119)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.Task.run(Task.scala:91)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$13(Executor.scala:813)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1620)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:816)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:672)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.util.NoSuchElementException
at org.apache.spark.sql.vectorized.ColumnarBatch$1.next(ColumnarBatch.java:69)
at org.apache.spark.sql.vectorized.ColumnarBatch$1.next(ColumnarBatch.java:58)
at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:44)
at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$4.next(ArrowConverters.scala:401)
at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$4.next(ArrowConverters.scala:382)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage138.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:757)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage183.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:757)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:488)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeTask$2(FileFormatWriter.scala:374)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1654)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:383)
... 19 more
Suppressed: java.io.IOException: can not write PageHeader(type:DICTIONARY_PAGE, uncompressed_page_size:176, compressed_page_size:101, crc:-1384879305, dictionary_page_header:DictionaryPageHeader(num_values:22, encoding:PLAIN_DICTIONARY))
at org.apache.parquet.format.Util.write(Util.java:224)
at org.apache.parquet.format.Util.writePageHeader(Util.java:61)
at org.apache.parquet.format.converter.ParquetMetadataConverter.writeDictionaryPageHeader(ParquetMetadataConverter.java:1190)
at org.apache.parquet.hadoop.ParquetFileWriter.writeDictionaryPage(ParquetFileWriter.java:374)
at org.apache.parquet.hadoop.ColumnChunkPageWriteStore$ColumnChunkPageWriter.writeToFileWriter(ColumnChunkPageWriteStore.java:238)
at org.apache.parquet.hadoop.ColumnChunkPageWriteStore.flushToFileWriter(ColumnChunkPageWriteStore.java:316)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.flushRowGroupToStore(InternalParquetRecordWriter.java:202)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.close(InternalParquetRecordWriter.java:127)
at org.apache.parquet.hadoop.ParquetRecordWriter.close(ParquetRecordWriter.java:165)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.close(ParquetOutputWriter.scala:41)
at org.apache.spark.sql.execution.datasources.FileFormatDataWriter.releaseResources(FileFormatDataWriter.scala:58)
at org.apache.spark.sql.execution.datasources.FileFormatDataWriter.abort(FileFormatDataWriter.scala:84)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeTask$3(FileFormatWriter.scala:380)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1665)
... 20 more
Caused by: shaded.parquet.org.apache.thrift.transport.TTransportException: java.io.IOException: Stream is closed!
at shaded.parquet.org.apache.thrift.transport.TIOStreamTransport.write(TIOStreamTransport.java:147)
at shaded.parquet.org.apache.thrift.transport.TTransport.write(TTransport.java:107)
at shaded.parquet.org.apache.thrift.protocol.TCompactProtocol.writeByteDirect(TCompactProtocol.java:482)
at shaded.parquet.org.apache.thrift.protocol.TCompactProtocol.writeByteDirect(TCompactProtocol.java:489)
at shaded.parquet.org.apache.thrift.protocol.TCompactProtocol.writeFieldBeginInternal(TCompactProtocol.java:252)
at shaded.parquet.org.apache.thrift.protocol.TCompactProtocol.writeFieldBegin(TCompactProtocol.java:234)
at org.apache.parquet.format.InterningProtocol.writeFieldBegin(InterningProtocol.java:74)
at org.apache.parquet.format.PageHeader$PageHeaderStandardScheme.write(PageHeader.java:1068)
at org.apache.parquet.format.PageHeader$PageHeaderStandardScheme.write(PageHeader.java:966)
at org.apache.parquet.format.PageHeader.write(PageHeader.java:847)
at org.apache.parquet.format.Util.write(Util.java:222)
... 33 more
Caused by: java.io.IOException: Stream is closed!
at shaded.databricks.azurebfs.org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.close(AbfsOutputStream.java:344)
at shaded.databricks.azurebfs.org.apache.hadoop.fs.azurebfs.services.PageCRCVerifyingAbfsOutputStream.close(PageCRCVerifyingAbfsOutputStream.java:48)
at org.apache.hadoop.fs.FSDataOutputStream$PositionCache.close(FSDataOutputStream.java:72)
at org.apache.hadoop.fs.FSDataOutputStream.close(FSDataOutputStream.java:106)
at com.databricks.backend.daemon.data.common.CancellableOutputStream.cancel(CancellableOutputStream.scala:24)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2.$anonfun$create$4(DatabricksFileSystemV2.scala:630)
at org.apache.spark.SparkUtils$.$anonfun$onTaskFailure$2(SparkUtils.scala:58)
at org.apache.spark.SparkUtils$.$anonfun$onTaskFailure$2$adapted(SparkUtils.scala:57)
at org.apache.spark.TaskContext$$anon$2.onTaskFailure(TaskContext.scala:177)
at org.apache.spark.TaskContextImpl.$anonfun$invokeTaskFailureListeners$1(TaskContextImpl.scala:150)
at org.apache.spark.TaskContextImpl.$anonfun$invokeTaskFailureListeners$1$adapted(TaskContextImpl.scala:150)
at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:197)
at org.apache.spark.TaskContextImpl.invokeTaskFailureListeners(TaskContextImpl.scala:150)
at org.apache.spark.TaskContextImpl.markTaskFailed(TaskContextImpl.scala:127)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1663)
... 20 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2828)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2775)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2769)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2769)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1305)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1305)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1305)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:3036)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2977)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2965)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:1067)
at org.apache.spark.SparkContext.runJobInternal(SparkContext.scala:2477)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2460)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:274)
... 88 more
Caused by: org.apache.spark.SparkException: Task failed while writing rows.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:396)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$15(FileFormatWriter.scala:284)
at org.apache.spark.scheduler.ResultTask.$anonfun$runTask$3(ResultTask.scala:75)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.ResultTask.$anonfun$runTask$1(ResultTask.scala:75)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:55)
at org.apache.spark.scheduler.Task.doRunTask(Task.scala:150)
at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:119)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.Task.run(Task.scala:91)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$13(Executor.scala:813)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1620)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:816)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:672)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.util.NoSuchElementException
at org.apache.spark.sql.vectorized.ColumnarBatch$1.next(ColumnarBatch.java:69)
at org.apache.spark.sql.vectorized.ColumnarBatch$1.next(ColumnarBatch.java:58)
at scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:44)
at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$4.next(ArrowConverters.scala:401)
at org.apache.spark.sql.execution.arrow.ArrowConverters$$anon$4.next(ArrowConverters.scala:382)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage138.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:757)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage183.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:757)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:488)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeTask$2(FileFormatWriter.scala:374)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1654)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:383)
... 19 more
Suppressed: java.io.IOException: can not write PageHeader(type:DICTIONARY_PAGE, uncompressed_page_size:176, compressed_page_size:101, crc:-1384879305, dictionary_page_header:DictionaryPageHeader(num_values:22, encoding:PLAIN_DICTIONARY))
at org.apache.parquet.format.Util.write(Util.java:224)
at org.apache.parquet.format.Util.writePageHeader(Util.java:61)
at org.apache.parquet.format.converter.ParquetMetadataConverter.writeDictionaryPageHeader(ParquetMetadataConverter.java:1190)
at org.apache.parquet.hadoop.ParquetFileWriter.writeDictionaryPage(ParquetFileWriter.java:374)
at org.apache.parquet.hadoop.ColumnChunkPageWriteStore$ColumnChunkPageWriter.writeToFileWriter(ColumnChunkPageWriteStore.java:238)
at org.apache.parquet.hadoop.ColumnChunkPageWriteStore.flushToFileWriter(ColumnChunkPageWriteStore.java:316)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.flushRowGroupToStore(InternalParquetRecordWriter.java:202)
at org.apache.parquet.hadoop.InternalParquetRecordWriter.close(InternalParquetRecordWriter.java:127)
at org.apache.parquet.hadoop.ParquetRecordWriter.close(ParquetRecordWriter.java:165)
at org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.close(ParquetOutputWriter.scala:41)
at org.apache.spark.sql.execution.datasources.FileFormatDataWriter.releaseResources(FileFormatDataWriter.scala:58)
at org.apache.spark.sql.execution.datasources.FileFormatDataWriter.abort(FileFormatDataWriter.scala:84)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$executeTask$3(FileFormatWriter.scala:380)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1665)
... 20 more
Caused by: shaded.parquet.org.apache.thrift.transport.TTransportException: java.io.IOException: Stream is closed!
at shaded.parquet.org.apache.thrift.transport.TIOStreamTransport.write(TIOStreamTransport.java:147)
at shaded.parquet.org.apache.thrift.transport.TTransport.write(TTransport.java:107)
at shaded.parquet.org.apache.thrift.protocol.TCompactProtocol.writeByteDirect(TCompactProtocol.java:482)
at shaded.parquet.org.apache.thrift.protocol.TCompactProtocol.writeByteDirect(TCompactProtocol.java:489)
at shaded.parquet.org.apache.thrift.protocol.TCompactProtocol.writeFieldBeginInternal(TCompactProtocol.java:252)
at shaded.parquet.org.apache.thrift.protocol.TCompactProtocol.writeFieldBegin(TCompactProtocol.java:234)
at org.apache.parquet.format.InterningProtocol.writeFieldBegin(InterningProtocol.java:74)
at org.apache.parquet.format.PageHeader$PageHeaderStandardScheme.write(PageHeader.java:1068)
at org.apache.parquet.format.PageHeader$PageHeaderStandardScheme.write(PageHeader.java:966)
at org.apache.parquet.format.PageHeader.write(PageHeader.java:847)
at org.apache.parquet.format.Util.write(Util.java:222)
... 33 more
Caused by: java.io.IOException: Stream is closed!
at shaded.databricks.azurebfs.org.apache.hadoop.fs.azurebfs.services.AbfsOutputStream.close(AbfsOutputStream.java:344)
at shaded.databricks.azurebfs.org.apache.hadoop.fs.azurebfs.services.PageCRCVerifyingAbfsOutputStream.close(PageCRCVerifyingAbfsOutputStream.java:48)
at org.apache.hadoop.fs.FSDataOutputStream$PositionCache.close(FSDataOutputStream.java:72)
at org.apache.hadoop.fs.FSDataOutputStream.close(FSDataOutputStream.java:106)
at com.databricks.backend.daemon.data.common.CancellableOutputStream.cancel(CancellableOutputStream.scala:24)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2.$anonfun$create$4(DatabricksFileSystemV2.scala:630)
at org.apache.spark.SparkUtils$.$anonfun$onTaskFailure$2(SparkUtils.scala:58)
at org.apache.spark.SparkUtils$.$anonfun$onTaskFailure$2$adapted(SparkUtils.scala:57)
at org.apache.spark.TaskContext$$anon$2.onTaskFailure(TaskContext.scala:177)
at org.apache.spark.TaskContextImpl.$anonfun$invokeTaskFailureListeners$1(TaskContextImpl.scala:150)
at org.apache.spark.TaskContextImpl.$anonfun$invokeTaskFailureListeners$1$adapted(TaskContextImpl.scala:150)
at org.apache.spark.TaskContextImpl.invokeListeners(TaskContextImpl.scala:197)
at org.apache.spark.TaskContextImpl.invokeTaskFailureListeners(TaskContextImpl.scala:150)
at org.apache.spark.TaskContextImpl.markTaskFailed(TaskContextImpl.scala:127)
at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1663)
... 20 more
Job runs every month so it should not be a code error.

Related

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")

Error when writing pyspark's dataframe into parquet

cleaned_mercury.write.mode('overwrite').parquet("../data/transformed-data/cleaned_mercury.parquet")
cleaned_mercury is a dataframe, whenever i try to convert the data into parquet it returns an error, i tried looking for answer everywhere but i couldn't find one
~\AppData\Local\Temp/ipykernel_19676/2099139696.py in <module>
----> 1 cleaned_mercury.write.mode('overwrite').parquet("../data/transformed-data/cleaned_mercury.parquet")
2 cleaned_watsons.write.mode('overwrite').parquet("../data/transformed-data/cleaned_watsons.parquet")
3 cleaned_tgp.write.mode('overwrite').parquet("../data/transformed-data/cleaned_tgp.parquet")
4 cleaned_ssd.write.mode('overwrite').parquet("../data/transformed-data/cleaned_ssd.parquet")
5 cleaned_rose.write.mode('overwrite').parquet("../data/transformed-data/cleaned_rose.parquet")
C:\spark-3.2.0-bin-hadoop3.2\python\pyspark\sql\readwriter.py in parquet(self, path, mode, partitionBy, compression)
883 self.partitionBy(partitionBy)
884 self._set_opts(compression=compression)
--> 885 self._jwrite.parquet(path)
886
887 def text(self, path, compression=None, lineSep=None):
C:\spark-3.2.0-bin-hadoop3.2\python\lib\py4j-0.10.9.2-src.zip\py4j\java_gateway.py in __call__(self, *args)
1307
1308 answer = self.gateway_client.send_command(command)
-> 1309 return_value = get_return_value(
1310 answer, self.gateway_client, self.target_id, self.name)
1311
C:\spark-3.2.0-bin-hadoop3.2\python\pyspark\sql\utils.py in deco(*a, **kw)
109 def deco(*a, **kw):
110 try:
--> 111 return f(*a, **kw)
112 except py4j.protocol.Py4JJavaError as e:
113 converted = convert_exception(e.java_exception)
C:\spark-3.2.0-bin-hadoop3.2\python\lib\py4j-0.10.9.2-src.zip\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name)
324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
325 if answer[1] == REFERENCE_TYPE:
--> 326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
328 format(target_id, ".", name), value)
Py4JJavaError: An error occurred while calling o1594.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.errors.QueryExecutionErrors$.jobAbortedError(QueryExecutionErrors.scala:496)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:251)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:186)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:113)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:111)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.executeCollect(commands.scala:125)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.$anonfun$applyOrElse$1(QueryExecution.scala:110)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:110)
at org.apache.spark.sql.execution.QueryExecution$$anonfun$eagerlyExecuteCommands$1.applyOrElse(QueryExecution.scala:106)
at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:481)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:82)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:481)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:30)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:30)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:457)
at org.apache.spark.sql.execution.QueryExecution.eagerlyExecuteCommands(QueryExecution.scala:106)
at org.apache.spark.sql.execution.QueryExecution.commandExecuted$lzycompute(QueryExecution.scala:93)
at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:91)
at org.apache.spark.sql.execution.QueryExecution.assertCommandExecuted(QueryExecution.scala:128)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:848)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:382)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:355)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:239)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:781)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(Unknown Source)
at java.lang.reflect.Method.invoke(Unknown Source)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
at java.lang.Thread.run(Unknown Source)
Caused by: java.lang.UnsatisfiedLinkError: org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Ljava/lang/String;I)Z
at org.apache.hadoop.io.nativeio.NativeIO$Windows.access0(Native Method)
at org.apache.hadoop.io.nativeio.NativeIO$Windows.access(NativeIO.java:793)
at org.apache.hadoop.fs.FileUtil.canRead(FileUtil.java:1215)
at org.apache.hadoop.fs.FileUtil.list(FileUtil.java:1420)
at org.apache.hadoop.fs.RawLocalFileSystem.listStatus(RawLocalFileSystem.java:601)
at org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1972)
at org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:2014)
at org.apache.hadoop.fs.ChecksumFileSystem.listStatus(ChecksumFileSystem.java:761)
at org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:1972)
at org.apache.hadoop.fs.FileSystem.listStatus(FileSystem.java:2014)
at org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.getAllCommittedTaskPaths(FileOutputCommitter.java:334)
at org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJobInternal(FileOutputCommitter.java:404)
at org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter.commitJob(FileOutputCommitter.java:377)
at org.apache.parquet.hadoop.ParquetOutputCommitter.commitJob(ParquetOutputCommitter.java:48)
at org.apache.spark.internal.io.HadoopMapReduceCommitProtocol.commitJob(HadoopMapReduceCommitProtocol.scala:182)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$20(FileFormatWriter.scala:240)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.util.Utils$.timeTakenMs(Utils.scala:605)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:240)
... 42 more

Turns out i dont have hadoop.dll installed, why do i figure out the answer on my own once i post my question here in stackoverflow https://github.com/steveloughran/winutils/blob/master/hadoop-2.7.1/bin/hadoop.dll

Databricks Notebook 8.3 (Apache Spark 3.1.1, Scala 2.12) | pyspark | Parquet write exception | Multiple failures in stage materialization

This is a Production code running fine until last week. Then, this parquet write error showed up and never getting resolved.
While writing to AWS S3 in parquet format, I tried several dataframe.repartitions(300) - 300, 500, 2400, 6000. But no luck. The code by itself runs fine, but some times gives count error if I add a count() on a dataframe. (intermittently).
So I removed all the count()s in the code to run the code without errors. Now, It fails while writing to the AWS s3 location.
The code is running on Databricks notebook - Databricks Runtime Version
8.3 (includes Apache Spark 3.1.1, Scala 2.12). The code is written in pyspark(python 3.8). The code runs on AWS r5.8xlarge instances.
I am stuck with this, any help is very much appreciated.
Py4JJavaError Traceback (most recent call last)
<command-2026517708936858> in <module>
3
4 #save data_agg for next step
----> 5 dataframe.repartition(6000).write.parquet(s3://path_to_write, mode='overwrite')
/databricks/spark/python/pyspark/sql/readwriter.py in parquet(self, path, mode, partitionBy, compression)
1275 self.partitionBy(partitionBy)
1276 self._set_opts(compression=compression)
-> 1277 self._jwrite.parquet(path)
1278
1279 def text(self, path, compression=None, lineSep=None):
/databricks/spark/python/lib/py4j-0.10.9-src.zip/py4j/java_gateway.py in __call__(self, *args)
1302
1303 answer = self.gateway_client.send_command(command)
-> 1304 return_value = get_return_value(
1305 answer, self.gateway_client, self.target_id, self.name)
1306
/databricks/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
115 def deco(*a, **kw):
116 try:
--> 117 return f(*a, **kw)
118 except py4j.protocol.Py4JJavaError as e:
119 converted = convert_exception(e.java_exception)
/databricks/spark/python/lib/py4j-0.10.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
325 if answer[1] == REFERENCE_TYPE:
--> 326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
328 format(target_id, ".", name), value)
Py4JJavaError: An error occurred while calling o1773.parquet.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:289)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:203)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:121)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:119)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:144)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:196)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:240)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:165)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:236)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:192)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:167)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:166)
at org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:1079)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$5(SQLExecution.scala:126)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:267)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withCustomExecutionEnv$1(SQLExecution.scala:104)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:852)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:77)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:217)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:1079)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:468)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:438)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:303)
at org.apache.spark.sql.DataFrameWriter.parquet(DataFrameWriter.scala:964)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:380)
at py4j.Gateway.invoke(Gateway.java:295)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:251)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Multiple failures in stage materialization.
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.cleanUpAndThrowException(AdaptiveSparkPlanExec.scala:838)
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.$anonfun$getFinalPhysicalPlan$1(AdaptiveSparkPlanExec.scala:321)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:852)
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.getFinalPhysicalPlan(AdaptiveSparkPlanExec.scala:276)
at org.apache.spark.sql.execution.adaptive.AdaptiveSparkPlanExec.doExecute(AdaptiveSparkPlanExec.scala:378)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$execute$1(SparkPlan.scala:196)
at org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:240)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:165)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:236)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:192)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:233)
... 34 more
Suppressed: org.apache.spark.SparkException: Job aborted due to stage failure: ShuffleMapStage 46 (parquet at NativeMethodAccessorImpl.java:0) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.FetchFailedException: Connecting to /100.64.19.5:4048 failed in the last 4750 ms, fail this connection directly
at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:771)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.$anonfun$next$1(ShuffleBlockFetcherIterator.scala:686)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:577)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70)
at org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29) at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.agg_doAggregateWithKeys_0$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.sort_addToSorter_0$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.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:757)
at org.apache.spark.sql.execution.RowIteratorFromScala.advanceNext(RowIterator.scala:83)
at org.apache.spark.sql.execution.joins.SortMergeFullOuterJoinScanner.advancedLeft(SortMergeJoinExec.scala:1088)
at org.apache.spark.sql.execution.joins.SortMergeFullOuterJoinScanner.<init>(SortMergeJoinExec.scala:1078)
at org.apache.spark.sql.execution.joins.SortMergeJoinExec.$anonfun$doExecute$1(SortMergeJoinExec.scala:222)
at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:125)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380) at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:344)
at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
at org.apache.spark.scheduler.ShuffleMapTask.$anonfun$runTask$3(ShuffleMapTask.scala:81)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.ShuffleMapTask.$anonfun$runTask$1(ShuffleMapTask.scala:81)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.doRunTask(Task.scala:150)
at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:119)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.scheduler.Task.run(Task.scala:91)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$13(Executor.scala:812)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1643)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:815)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:671)
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: java.io.IOException: Connecting to /100.64.19.5:4048 failed in the last 4750 ms, fail this connection directly
at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214)
at org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:101)
at org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153)
at org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30)
... 1 more
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2765)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2712)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2706)
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:2706)
at org.apache.spark.scheduler.DAGScheduler.handleTaskCompletion(DAGScheduler.scala:2263)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2970)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2914)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2902)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
Suppressed: [CIRCULAR REFERENCE: org.apache.spark.SparkException: Job aborted due to stage failure: ShuffleMapStage 46 (parquet at NativeMethodAccessorImpl.java:0) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.FetchFailedException: Connecting to /100.64.19.5:4048 failed in the last 4750 ms, fail this connection directly at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:771) at org.apache.spark.storage.ShuffleBlockFetcherIterator.$anonfun$next$1(ShuffleBlockFetcherIterator.scala:686) at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:577) at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:70) at org.apache.spark.util.CompletionIterator.next(CompletionIterator.scala:29) at scala.collection.Iterator$$anon$11.nextCur(Iterator.scala:484) at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:490) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458) at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:31) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.agg_doAggregateWithKeys_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.sort_addToSorter_0$(Unknown Source) at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage14.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:757) at org.apache.spark.sql.execution.RowIteratorFromScala.advanceNext(RowIterator.scala:83) at org.apache.spark.sql.execution.joins.SortMergeFullOuterJoinScanner.advancedLeft(SortMergeJoinExec.scala:1088) at org.apache.spark.sql.execution.joins.SortMergeFullOuterJoinScanner.<init>(SortMergeJoinExec.scala:1078) at org.apache.spark.sql.execution.joins.SortMergeJoinExec.$anonfun$doExecute$1(SortMergeJoinExec.scala:222) at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:125) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380) at org.apache.spark.rdd.RDD.iterator(RDD.scala:344) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380) at org.apache.spark.rdd.RDD.iterator(RDD.scala:344) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380) at org.apache.spark.rdd.RDD.iterator(RDD.scala:344) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:60) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:380) at org.apache.spark.rdd.RDD.iterator(RDD.scala:344) at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59) at org.apache.spark.scheduler.ShuffleMapTask.$anonfun$runTask$3(ShuffleMapTask.scala:81) at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110) at org.apache.spark.scheduler.ShuffleMapTask.$anonfun$runTask$1(ShuffleMapTask.scala:81) at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41) at org.apache.spark.scheduler.Task.doRunTask(Task.scala:150) at org.apache.spark.scheduler.Task.$anonfun$run$1(Task.scala:119) at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110) at org.apache.spark.scheduler.Task.run(Task.scala:91) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$13(Executor.scala:812) at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1643) at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:815) at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23) at com.databricks.spark.util.ExecutorFrameProfiler$.record(ExecutorFrameProfiler.scala:110) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:671) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at java.lang.Thread.run(Thread.java:748) Caused by: java.io.IOException: Connecting to /100.64.19.5:4048 failed in the last 4750 ms, fail this connection directly at org.apache.spark.network.client.TransportClientFactory.createClient(TransportClientFactory.java:214) at org.apache.spark.network.shuffle.ExternalBlockStoreClient.lambda$fetchBlocks$0(ExternalBlockStoreClient.java:101) at org.apache.spark.network.shuffle.RetryingBlockFetcher.fetchAllOutstanding(RetryingBlockFetcher.java:153) at org.apache.spark.network.shuffle.RetryingBlockFetcher.lambda$initiateRetry$0(RetryingBlockFetcher.java:181) at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511) at java.util.concurrent.FutureTask.run(FutureTask.java:266) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) at io.netty.util.concurrent.FastThreadLocalRunnable.run(FastThreadLocalRunnable.java:30) ... 1 more ]

I am getting the following error due to stage materialization.
Connect timed out. Verify the connection properties. Make sure that an
instance of SQL Server is running on the host and accepting TCP/IP
connections at the port. Make sure that TCP connections to the port are not
blocked by a firewall.
Stage materialization may happen due to connection issues at intermediate stages where a connection required to be established may have broken.

In case it helps: Are you using .checkpoint or .local_checkpoint? I was facing a similar issue (stage materialization) and found it helpful:
If this problem persists, you may consider using rdd.checkpoint() instead, which is slower than local checkpointing but more fault-tolerant.

Unable to reading the textfile using Jupyter notebook in pyspark

Below is my code to access the text file using Pyspark from Jupyter notebook. I am running the Jupyter notebook in a Linux environment(Ubuntu).
from pyspark import SparkConf, SparkContext
import collections
conf = SparkConf().setMaster("local").setAppName("Ratings")
sc = SparkContext.getOrCreate(conf=conf)
lines = sc.textFile("/home/ajit/Desktop/u.data")
ratings = lines.map(lambda x : x.split()[2])
result = ratings.countByValue()
When I try to run the "result = ratings.countByValue()" I am facing below error saying "java.io.IOException: Cannot run program "python": error=2, No such file or directory"
Py4JJavaError Traceback (most recent call last)
<ipython-input-5-d0433aff12c2> in <module>
1 ratings = lines.map(lambda x : x.split()[2])
2 #ratings.collect()
----> 3 result = ratings.countByValue()
4 #ratings.
~/spark-3.0.0-preview2-bin-hadoop2.7/python/pyspark/rdd.py in countByValue(self)
1332 m1[k] += v
1333 return m1
-> 1334 return self.mapPartitions(countPartition).reduce(mergeMaps)
1335
1336 def top(self, num, key=None):
~/spark-3.0.0-preview2-bin-hadoop2.7/python/pyspark/rdd.py in reduce(self, f)
915 yield reduce(f, iterator, initial)
916
--> 917 vals = self.mapPartitions(func).collect()
918 if vals:
919 return reduce(f, vals)
~/spark-3.0.0-preview2-bin-hadoop2.7/python/pyspark/rdd.py in collect(self)
887 """
888 with SCCallSiteSync(self.context) as css:
--> 889 sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
890 return list(_load_from_socket(sock_info, self._jrdd_deserializer))
891
~/.local/lib/python3.8/site-packages/py4j/java_gateway.py in __call__(self, *args)
1302
1303 answer = self.gateway_client.send_command(command)
-> 1304 return_value = get_return_value(
1305 answer, self.gateway_client, self.target_id, self.name)
1306
~/.local/lib/python3.8/site-packages/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
324 value = OUTPUT_CONVERTER[type](answer[2:], gateway_client)
325 if answer[1] == REFERENCE_TYPE:
--> 326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
328 format(target_id, ".", name), value)
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 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1, 10.0.2.15, executor driver): java.io.IOException: Cannot run program "python": error=2, No such file or directory
at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1128)
at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1071)
at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:209)
at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:132)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:105)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:118)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:126)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:441)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:444)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
at java.base/java.lang.Thread.run(Thread.java:834)
Caused by: java.io.IOException: error=2, No such file or directory
at java.base/java.lang.ProcessImpl.forkAndExec(Native Method)
at java.base/java.lang.ProcessImpl.<init>(ProcessImpl.java:340)
at java.base/java.lang.ProcessImpl.start(ProcessImpl.java:271)
at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1107)
... 17 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:1989)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:1977)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:1976)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1976)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:956)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:956)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:956)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2206)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2155)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2144)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:758)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2116)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2137)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2156)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2181)
at org.apache.spark.rdd.RDD.$anonfun$collect$1(RDD.scala:1004)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:388)
at org.apache.spark.rdd.RDD.collect(RDD.scala:1003)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:168)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.base/java.lang.reflect.Method.invoke(Method.java:566)
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.base/java.lang.Thread.run(Thread.java:834)
Caused by: java.io.IOException: Cannot run program "python": error=2, No such file or directory
at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1128)
at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1071)
at org.apache.spark.api.python.PythonWorkerFactory.startDaemon(PythonWorkerFactory.scala:209)
at org.apache.spark.api.python.PythonWorkerFactory.createThroughDaemon(PythonWorkerFactory.scala:132)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:105)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:118)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:126)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:313)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:127)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:441)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:444)
at java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1128)
at java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:628)
... 1 more
Caused by: java.io.IOException: error=2, No such file or directory
at java.base/java.lang.ProcessImpl.forkAndExec(Native Method)
at java.base/java.lang.ProcessImpl.<init>(ProcessImpl.java:340)
at java.base/java.lang.ProcessImpl.start(ProcessImpl.java:271)
at java.base/java.lang.ProcessBuilder.start(ProcessBuilder.java:1107)
... 17 more
Please help me with this as I am new to the PySpark.

try:
lines = sc.textFile("file:///home/ajit/Desktop/u.data")
i believe the error is due to improper syntax and the above statement should resolve it

What you need to do is put file in HDFS with below command then the path will work.
HDFS command to copy file to cluster. This should be run in jupyter terminal :
hdfs dfs -put /home/ajit/Desktop/u.data /user/ajit
After that the spark read command should work as below :
lines = sc.textFile("/user/ajit/u.data")

Error with Collect() in PySpark and Jupyter-notebook

I am learning to code with PySpark and Jupyter-notebook with Python.
In the first example I got an error that I didn't understand.
I have installed Java in the folder C:\ProgramFiles\Java\jdk1.8.0_201. Since I read that Java may produce problem if its installation folder name has spaces, I installed over in the folder mentioned above. The version of Java is 8.
I installed Spark according to: https://mas-dse.github.io/DSE230/installation/windows/#install and configured the different variables https://jaceklaskowski.gitbooks.io/mastering-apache-spark/spark-tips-and-tricks-running-spark-windows.html
import findspark
findspark.init()
from pyspark import SparkContext
sc = SparkContext(master="local[4]")
A=sc.parallelize(range(3))
L=A.collect()
When the collect() command runs, I get the following errors
Py4JJavaError Traceback (most recent call last)
<ipython-input-5-6b63599b99af> in <module>()
----> 1 L=A.collect()
2 #print(type(L))
3 #print(L)
C:\opt\spark\python\pyspark\rdd.py in collect(self)
814 """
815 with SCCallSiteSync(self.context) as css:
--> 816 sock_info = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
817 return list(_load_from_socket(sock_info, self._jrdd_deserializer))
818
C:\opt\spark\python\lib\py4j-0.10.7-src.zip\py4j\java_gateway.py in __call__(self, *args)
1255 answer = self.gateway_client.send_command(command)
1256 return_value = get_return_value(
-> 1257 answer, self.gateway_client, self.target_id, self.name)
1258
1259 for temp_arg in temp_args:
C:\opt\spark\python\lib\py4j-0.10.7-src.zip\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name)
326 raise Py4JJavaError(
327 "An error occurred while calling {0}{1}{2}.\n".
--> 328 format(target_id, ".", name), value)
329 else:
330 raise Py4JError(
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 3 in stage 0.0 failed 1 times, most recent failure: Lost task 3.0 in stage 0.0 (TID 3, localhost, executor driver): org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
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$$anonfun$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:135)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:199)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1887)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1875)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1874)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1874)
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:2108)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2057)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2046)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:737)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2061)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2082)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2101)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2126)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:166)
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: org.apache.spark.SparkException: Python worker failed to connect back.
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:170)
at org.apache.spark.api.python.PythonWorkerFactory.create(PythonWorkerFactory.scala:97)
at org.apache.spark.SparkEnv.createPythonWorker(SparkEnv.scala:117)
at org.apache.spark.api.python.BasePythonRunner.compute(PythonRunner.scala:108)
at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:65)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
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$10.apply(Executor.scala:402)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1360)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:408)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.net.SocketTimeoutException: Accept timed out
at java.net.DualStackPlainSocketImpl.waitForNewConnection(Native Method)
at java.net.DualStackPlainSocketImpl.socketAccept(DualStackPlainSocketImpl.java:135)
at java.net.AbstractPlainSocketImpl.accept(AbstractPlainSocketImpl.java:409)
at java.net.PlainSocketImpl.accept(PlainSocketImpl.java:199)
at java.net.ServerSocket.implAccept(ServerSocket.java:545)
at java.net.ServerSocket.accept(ServerSocket.java:513)
at org.apache.spark.api.python.PythonWorkerFactory.createSimpleWorker(PythonWorkerFactory.scala:164)
... 14 more

After several days looking for a solution to my problem, I found a recommendation in internet to install the previous version of Spark (2.3 instead of 2.4).
I tested it in my computer with windows 10 64bit system, and this worked for me to solve the problem above mentioned.
If you want more details, look at Python worker failed to connect back
Regards,
Diego

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Databricks Notebook 8.3 (Apache Spark 3.1.1, Scala 2.12) | pyspark | Parquet write exception | Multiple failures in stage materialization

Unable to reading the textfile using Jupyter notebook in pyspark

Error with Collect() in PySpark and Jupyter-notebook

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