ERROR when I use 'textFile.count()' - pyspark

I don't know where is the problem and how to fix it.The spark version is 2.1.0 and the python version is 3.4.6.
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/__ / .__/\_,_/_/ /_/\_\ version 2.1.0
/_/
Using Python version 3.4.6 (default, Mar 9 2017 19:57:54)
SparkSession available as 'spark'.
##This is the command i code as the official document
>>> input_data = sc.textFile('my python')
>>> input_data.count()
but it is not work.
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/local/spark/python/pyspark/rdd.py", line 1041, in count
return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
File "/usr/local/spark/python/pyspark/rdd.py", line 1032, in sum
return self.mapPartitions(lambda x: [sum(x)]).fold(0, operator.add)
File "/usr/local/spark/python/pyspark/rdd.py", line 906, in fold
vals = self.mapPartitions(func).collect()
File "/usr/local/spark/python/pyspark/rdd.py", line 809, in collect
port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
File "/usr/local/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in __call__
File "/usr/local/spark/python/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/usr/local/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: java.net.ConnectException: Call From hadoop/192.168.81.129 to localhost:9000 failed on connection exception: java.net.ConnectException: 拒绝连接; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:57)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:526)
at org.apache.hadoop.net.NetUtils.wrapWithMessage(NetUtils.java:792)
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:732)
at org.apache.hadoop.ipc.Client.call(Client.java:1479)
at org.apache.hadoop.ipc.Client.call(Client.java:1412)
at org.apache.hadoop.ipc.ProtobufRpcEngine$Invoker.invoke(ProtobufRpcEngine.java:229)
at com.sun.proxy.$Proxy19.getFileInfo(Unknown Source)
at org.apache.hadoop.hdfs.protocolPB.ClientNamenodeProtocolTranslatorPB.getFileInfo(ClientNamenodeProtocolTranslatorPB.java:771)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at com.sun.proxy.$Proxy20.getFileInfo(Unknown Source)
at org.apache.hadoop.hdfs.DFSClient.getFileInfo(DFSClient.java:2108)
at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1305)
at org.apache.hadoop.hdfs.DistributedFileSystem$22.doCall(DistributedFileSystem.java:1301)
at org.apache.hadoop.fs.FileSystemLinkResolver.resolve(FileSystemLinkResolver.java:81)
at org.apache.hadoop.hdfs.DistributedFileSystem.getFileStatus(DistributedFileSystem.java:1301)
at org.apache.hadoop.fs.Globber.getFileStatus(Globber.java:57)
at org.apache.hadoop.fs.Globber.glob(Globber.java:252)
at org.apache.hadoop.fs.FileSystem.globStatus(FileSystem.java:1674)
at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:259)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:202)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
at org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:53)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1958)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:935)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:934)
at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:453)
at org.apache.spark.api.python.PythonRDD.collectAndServe(PythonRDD.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.net.ConnectException: 拒绝连接
at sun.nio.ch.SocketChannelImpl.checkConnect(Native Method)
at sun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:744)
at org.apache.hadoop.net.SocketIOWithTimeout.connect(SocketIOWithTimeout.java:206)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:531)
at org.apache.hadoop.net.NetUtils.connect(NetUtils.java:495)
at org.apache.hadoop.ipc.Client$Connection.setupConnection(Client.java:614)
at org.apache.hadoop.ipc.Client$Connection.setupIOstreams(Client.java:712)
at org.apache.hadoop.ipc.Client$Connection.access$2900(Client.java:375)
at org.apache.hadoop.ipc.Client.getConnection(Client.java:1528)
at org.apache.hadoop.ipc.Client.call(Client.java:1451)
... 56 more
>>>

Related

Writing PySpark Dataframe to CSV Py4JJavaError

I am getting a Py4JJavaError when I try to write a PySpark Dataframe to a csv. It is creating a folder in the path with the title of my csv file but there is nothing inside of the folder. Here is my code:
students.write.mode("overwrite").csv('write_test.csv')
When I run that code I get the following error:
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
C:\Users\MICHAE~1\AppData\Local\Temp/ipykernel_3904/767700963.py in <module>
----> 1 students.write.mode("overwrite").csv('write_test.csv')
~\anaconda3\lib\site-packages\pyspark\sql\readwriter.py in csv(self, path, mode, compression, sep, quote, escape, header, nullValue, escapeQuotes, quoteAll, dateFormat, timestampFormat, ignoreLeadingWhiteSpace, ignoreTrailingWhiteSpace, charToEscapeQuoteEscaping, encoding, emptyValue, lineSep)
953 charToEscapeQuoteEscaping=charToEscapeQuoteEscaping,
954 encoding=encoding, emptyValue=emptyValue, lineSep=lineSep)
--> 955 self._jwrite.csv(path)
956
957 def orc(self, path, mode=None, partitionBy=None, compression=None):
~\anaconda3\lib\site-packages\py4j\java_gateway.py in __call__(self, *args)
1319
1320 answer = self.gateway_client.send_command(command)
-> 1321 return_value = get_return_value(
1322 answer, self.gateway_client, self.target_id, self.name)
1323
~\anaconda3\lib\site-packages\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)
~\anaconda3\lib\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 o264.csv.
: 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$lzycompute(QueryExecution.scala:93)
at org.apache.spark.sql.execution.QueryExecution.commandExecuted(QueryExecution.scala:91)
at org.apache.spark.sql.execution.QueryExecution.assertCommandExecuted(QueryExecution.scala:128)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:848)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:382)
at org.apache.spark.sql.DataFrameWriter.saveInternal(DataFrameWriter.scala:355)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:239)
at org.apache.spark.sql.DataFrameWriter.csv(DataFrameWriter.scala:839)
at sun.reflect.GeneratedMethodAccessor59.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:282)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182)
at py4j.ClientServerConnection.run(ClientServerConnection.java:106)
at java.lang.Thread.run(Thread.java:748)
Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 43.0 failed 1 times, most recent failure: Lost task 0.0 in stage 43.0 (TID 39) (AXIOM-NINJA executor driver): java.io.IOException: (null) entry in command string: null chmod 0644 C:\Users\MichaelDallas\Desktop\PySpark_Course\Jupyter\Code_Along\write_test.csv\_temporary\0\_temporary\attempt_202201281318408036701241482801437_0043_m_000000_39\part-00000-e4b8b459-f358-464a-ac99-6d80a2741fb7-c000.csv
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:869)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:852)
at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:733)
at org.apache.hadoop.fs.RawLocalFileSystem$LocalFSFileOutputStream.<init>(RawLocalFileSystem.java:225)
at org.apache.hadoop.fs.RawLocalFileSystem$LocalFSFileOutputStream.<init>(RawLocalFileSystem.java:209)
at org.apache.hadoop.fs.RawLocalFileSystem.createOutputStreamWithMode(RawLocalFileSystem.java:307)
at org.apache.hadoop.fs.RawLocalFileSystem.create(RawLocalFileSystem.java:296)
at org.apache.hadoop.fs.RawLocalFileSystem.create(RawLocalFileSystem.java:328)
at org.apache.hadoop.fs.ChecksumFileSystem$ChecksumFSOutputSummer.<init>(ChecksumFileSystem.java:398)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:461)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:440)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:911)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:892)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:789)
at org.apache.spark.sql.execution.datasources.CodecStreams$.createOutputStream(CodecStreams.scala:81)
at org.apache.spark.sql.execution.datasources.CodecStreams$.createOutputStreamWriter(CodecStreams.scala:92)
at org.apache.spark.sql.execution.datasources.csv.CsvOutputWriter.<init>(CsvOutputWriter.scala:38)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anon$1.newInstance(CSVFileFormat.scala:85)
at org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:161)
at org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:146)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:290)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$16(FileFormatWriter.scala:229)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2403)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2352)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2351)
at scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62)
at scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2351)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1109)
at org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1109)
at scala.Option.foreach(Option.scala:407)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1109)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2591)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2533)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2522)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:898)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:218)
... 41 more
Caused by: java.io.IOException: (null) entry in command string: null chmod 0644 C:\Users\MichaelDallas\Desktop\PySpark_Course\Jupyter\Code_Along\write_test.csv\_temporary\0\_temporary\attempt_202201281318408036701241482801437_0043_m_000000_39\part-00000-e4b8b459-f358-464a-ac99-6d80a2741fb7-c000.csv
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:773)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:869)
at org.apache.hadoop.util.Shell.execCommand(Shell.java:852)
at org.apache.hadoop.fs.RawLocalFileSystem.setPermission(RawLocalFileSystem.java:733)
at org.apache.hadoop.fs.RawLocalFileSystem$LocalFSFileOutputStream.<init>(RawLocalFileSystem.java:225)
at org.apache.hadoop.fs.RawLocalFileSystem$LocalFSFileOutputStream.<init>(RawLocalFileSystem.java:209)
at org.apache.hadoop.fs.RawLocalFileSystem.createOutputStreamWithMode(RawLocalFileSystem.java:307)
at org.apache.hadoop.fs.RawLocalFileSystem.create(RawLocalFileSystem.java:296)
at org.apache.hadoop.fs.RawLocalFileSystem.create(RawLocalFileSystem.java:328)
at org.apache.hadoop.fs.ChecksumFileSystem$ChecksumFSOutputSummer.<init>(ChecksumFileSystem.java:398)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:461)
at org.apache.hadoop.fs.ChecksumFileSystem.create(ChecksumFileSystem.java:440)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:911)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:892)
at org.apache.hadoop.fs.FileSystem.create(FileSystem.java:789)
at org.apache.spark.sql.execution.datasources.CodecStreams$.createOutputStream(CodecStreams.scala:81)
at org.apache.spark.sql.execution.datasources.CodecStreams$.createOutputStreamWriter(CodecStreams.scala:92)
at org.apache.spark.sql.execution.datasources.csv.CsvOutputWriter.<init>(CsvOutputWriter.scala:38)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anon$1.newInstance(CSVFileFormat.scala:85)
at org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:161)
at org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:146)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:290)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$16(FileFormatWriter.scala:229)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1462)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
I was able to get it to work by deleting the hadoop.dll file from the folder that contained winutils.exe. I also made sure that the hadoop.dll file was located in my System32 folder. I ensured that I had all of the hadoop, spark, and java jdk installs completed correctly. I ensure that the Environment Variables were pointing to the correct directories. Also, the Java 8 jdk seems to work the best with the hadoop 2.7 configuration.

org.apache.spark.SparkException: Job aborted due to stage failure in databricks

Sorry, for same type of question. I saw so many post in SO for stage failure. But none of those were able to resolve my issue. So I'm posting it again.
I'm running in databricks,Runtime 7.3 LTS. I have a spark dataframe df2.While I'm running the command
df2.show()
I'm getting following error message. Can you help me to resolve the issue?
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 231.0 failed 4 times, most recent failure: Lost task 0.3 in stage 231.0 (TID 6106, 10.52.98.16, executor 0): com.databricks.sql.io.FileReadException: Error while reading file dbfs:/user/hive/warehouse/p_suggestedpricefornegotiation/part-00000-e64f3491-8afe-44a9-a55d-3495bc7a1395-c000.snappy.parquet. A file referenced in the transaction log cannot be found. This occurs when data has been manually deleted from the file system rather than using the table `DELETE` statement. For more information, see https://learn.microsoft.com/azure/databricks/delta/delta-intro#frequently-asked-questions
Py4JJavaError Traceback (most recent call last)
<command-780007467828035> in <module>
----> 1 df2.show()
/databricks/spark/python/pyspark/sql/dataframe.py in show(self, n, truncate, vertical)
382 """
383 if isinstance(truncate, bool) and truncate:
--> 384 print(self._jdf.showString(n, 20, vertical))
385 else:
386 print(self._jdf.showString(n, int(truncate), vertical))
/databricks/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:
/databricks/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
/databricks/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 o804.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 231.0 failed 4 times, most recent failure: Lost task 0.3 in stage 231.0 (TID 6106, 10.52.98.16, executor 0): com.databricks.sql.io.FileReadException: Error while reading file dbfs:/user/hive/warehouse/p_suggestedpricefornegotiation/part-00000-e64f3491-8afe-44a9-a55d-3495bc7a1395-c000.snappy.parquet. A file referenced in the transaction log cannot be found. This occurs when data has been manually deleted from the file system rather than using the table `DELETE` statement. For more information, see https://learn.microsoft.com/azure/databricks/delta/delta-intro#frequently-asked-questions
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anon$2.logFileNameAndThrow(FileScanRDD.scala:331)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anon$2.getNext(FileScanRDD.scala:297)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anonfun$prepareNextFile$1.apply(FileScanRDD.scala:463)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anonfun$prepareNextFile$1.apply(FileScanRDD.scala:451)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable$$anonfun$run$1.apply$mcV$sp(SparkThreadLocalForwardingThreadPoolExecutor.scala:104)
at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable$$anonfun$run$1.apply(SparkThreadLocalForwardingThreadPoolExecutor.scala:104)
at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable$$anonfun$run$1.apply(SparkThreadLocalForwardingThreadPoolExecutor.scala:104)
at org.apache.spark.util.threads.SparkThreadLocalCapturingHelper$class.runWithCaptured(SparkThreadLocalForwardingThreadPoolExecutor.scala:68)
at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable.runWithCaptured(SparkThreadLocalForwardingThreadPoolExecutor.scala:101)
at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable.run(SparkThreadLocalForwardingThreadPoolExecutor.scala:104)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Caused by: java.io.FileNotFoundException: dbfs:/user/hive/warehouse/p_suggestedpricefornegotiation/part-00000-e64f3491-8afe-44a9-a55d-3495bc7a1395-c000.snappy.parquet
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2$$anonfun$getFileStatus$1$$anonfun$apply$15.apply(DatabricksFileSystemV2.scala:770)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2$$anonfun$getFileStatus$1$$anonfun$apply$15.apply(DatabricksFileSystemV2.scala:756)
at com.databricks.s3a.S3AExeceptionUtils$.convertAWSExceptionToJavaIOException(DatabricksStreamUtils.scala:108)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2$$anonfun$getFileStatus$1.apply(DatabricksFileSystemV2.scala:756)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2$$anonfun$getFileStatus$1.apply(DatabricksFileSystemV2.scala:756)
at com.databricks.logging.UsageLogging$$anonfun$recordOperation$1.apply(UsageLogging.scala:428)
at com.databricks.logging.UsageLogging$$anonfun$withAttributionContext$1.apply(UsageLogging.scala:238)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at com.databricks.logging.UsageLogging$class.withAttributionContext(UsageLogging.scala:233)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2.withAttributionContext(DatabricksFileSystemV2.scala:450)
at com.databricks.logging.UsageLogging$class.withAttributionTags(UsageLogging.scala:275)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2.withAttributionTags(DatabricksFileSystemV2.scala:450)
at com.databricks.logging.UsageLogging$class.recordOperation(UsageLogging.scala:409)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2.recordOperation(DatabricksFileSystemV2.scala:450)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2.getFileStatus(DatabricksFileSystemV2.scala:755)
at com.databricks.backend.daemon.data.client.DatabricksFileSystem.getFileStatus(DatabricksFileSystem.scala:201)
at com.databricks.spark.metrics.FileSystemWithMetrics.getFileStatus(FileSystemWithMetrics.scala:295)
at org.apache.parquet.hadoop.util.HadoopInputFile.fromPath(HadoopInputFile.java:39)
at org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:452)
at com.databricks.sql.io.parquet.CachingParquetFileReader.readFooter(CachingParquetFileReader.java:366)
at org.apache.spark.sql.execution.datasources.parquet.SpecificParquetRecordReaderBase.prepare(SpecificParquetRecordReaderBase.java:128)
at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReaderWithPartitionValues$1.apply(ParquetFileFormat.scala:477)
at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReaderWithPartitionValues$1.apply(ParquetFileFormat.scala:390)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anon$2.getNext(FileScanRDD.scala:281)
... 14 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2362)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2350)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2349)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2349)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1102)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1102)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1102)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2582)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2529)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2517)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:897)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2280)
at org.apache.spark.sql.execution.collect.Collector.runSparkJobs(Collector.scala:270)
at org.apache.spark.sql.execution.collect.Collector.collect(Collector.scala:280)
at org.apache.spark.sql.execution.collect.Collector$.collect(Collector.scala:80)
at org.apache.spark.sql.execution.collect.Collector$.collect(Collector.scala:86)
at org.apache.spark.sql.execution.ResultCacheManager.getOrComputeResult(ResultCacheManager.scala:508)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollectResult(limit.scala:57)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectResult(Dataset.scala:2905)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:3517)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2634)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2634)
at org.apache.spark.sql.Dataset$$anonfun$54.apply(Dataset.scala:3501)
at org.apache.spark.sql.Dataset$$anonfun$54.apply(Dataset.scala:3496)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withCustomExecutionEnv$1$$anonfun$apply$1.apply(SQLExecution.scala:112)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:232)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withCustomExecutionEnv$1.apply(SQLExecution.scala:98)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:835)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:74)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:184)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$withAction(Dataset.scala:3496)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2634)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2848)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:279)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:316)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:380)
at py4j.Gateway.invoke(Gateway.java:295)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:251)
at java.lang.Thread.run(Thread.java:748)
Caused by: com.databricks.sql.io.FileReadException: Error while reading file dbfs:/user/hive/warehouse/p_suggestedpricefornegotiation/part-00000-e64f3491-8afe-44a9-a55d-3495bc7a1395-c000.snappy.parquet. A file referenced in the transaction log cannot be found. This occurs when data has been manually deleted from the file system rather than using the table `DELETE` statement. For more information, see https://learn.microsoft.com/azure/databricks/delta/delta-intro#frequently-asked-questions
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anon$2.logFileNameAndThrow(FileScanRDD.scala:331)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anon$2.getNext(FileScanRDD.scala:297)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anonfun$prepareNextFile$1.apply(FileScanRDD.scala:463)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anonfun$prepareNextFile$1.apply(FileScanRDD.scala:451)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.liftedTree1$1(Future.scala:24)
at scala.concurrent.impl.Future$PromiseCompletingRunnable.run(Future.scala:24)
at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable$$anonfun$run$1.apply$mcV$sp(SparkThreadLocalForwardingThreadPoolExecutor.scala:104)
at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable$$anonfun$run$1.apply(SparkThreadLocalForwardingThreadPoolExecutor.scala:104)
at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable$$anonfun$run$1.apply(SparkThreadLocalForwardingThreadPoolExecutor.scala:104)
at org.apache.spark.util.threads.SparkThreadLocalCapturingHelper$class.runWithCaptured(SparkThreadLocalForwardingThreadPoolExecutor.scala:68)
at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable.runWithCaptured(SparkThreadLocalForwardingThreadPoolExecutor.scala:101)
at org.apache.spark.util.threads.SparkThreadLocalCapturingRunnable.run(SparkThreadLocalForwardingThreadPoolExecutor.scala:104)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
Caused by: java.io.FileNotFoundException: dbfs:/user/hive/warehouse/p_suggestedpricefornegotiation/part-00000-e64f3491-8afe-44a9-a55d-3495bc7a1395-c000.snappy.parquet
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2$$anonfun$getFileStatus$1$$anonfun$apply$15.apply(DatabricksFileSystemV2.scala:770)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2$$anonfun$getFileStatus$1$$anonfun$apply$15.apply(DatabricksFileSystemV2.scala:756)
at com.databricks.s3a.S3AExeceptionUtils$.convertAWSExceptionToJavaIOException(DatabricksStreamUtils.scala:108)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2$$anonfun$getFileStatus$1.apply(DatabricksFileSystemV2.scala:756)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2$$anonfun$getFileStatus$1.apply(DatabricksFileSystemV2.scala:756)
at com.databricks.logging.UsageLogging$$anonfun$recordOperation$1.apply(UsageLogging.scala:428)
at com.databricks.logging.UsageLogging$$anonfun$withAttributionContext$1.apply(UsageLogging.scala:238)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at com.databricks.logging.UsageLogging$class.withAttributionContext(UsageLogging.scala:233)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2.withAttributionContext(DatabricksFileSystemV2.scala:450)
at com.databricks.logging.UsageLogging$class.withAttributionTags(UsageLogging.scala:275)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2.withAttributionTags(DatabricksFileSystemV2.scala:450)
at com.databricks.logging.UsageLogging$class.recordOperation(UsageLogging.scala:409)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2.recordOperation(DatabricksFileSystemV2.scala:450)
at com.databricks.backend.daemon.data.client.DatabricksFileSystemV2.getFileStatus(DatabricksFileSystemV2.scala:755)
at com.databricks.backend.daemon.data.client.DatabricksFileSystem.getFileStatus(DatabricksFileSystem.scala:201)
at com.databricks.spark.metrics.FileSystemWithMetrics.getFileStatus(FileSystemWithMetrics.scala:295)
at org.apache.parquet.hadoop.util.HadoopInputFile.fromPath(HadoopInputFile.java:39)
at org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:452)
at com.databricks.sql.io.parquet.CachingParquetFileReader.readFooter(CachingParquetFileReader.java:366)
at org.apache.spark.sql.execution.datasources.parquet.SpecificParquetRecordReaderBase.prepare(SpecificParquetRecordReaderBase.java:128)
at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReaderWithPartitionValues$1.apply(ParquetFileFormat.scala:477)
at org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anonfun$buildReaderWithPartitionValues$1.apply(ParquetFileFormat.scala:390)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anon$2.getNext(FileScanRDD.scala:281)
... 14 more
Whenever I encounter such issues, they are mostly coz of the databricks cluster being backed up. Most of the times a cluster restart has helped me in fixing the issue.

PySpark - Impossible to show predictions of a random forest model (Failed to execute user defined function($anonfun$1: (vector) => vector))

I'm using PySpark (Python 3.5.2 and Spark 2.2.0.2.6.4.0-91) and I have a Dataframe of predicted values (through a random forest model defined with the MLlib library) with the following structure :
DataFrame[id: bigint, features: vector, rawPrediction: vector, probability: vector, prediction: double]
I got it with :
rf_predictions = random_forest_model.transform(dataframe)
But when I want to display the content of it, it only works with the 2 first columns "id" and "features" :
rf_predictions.select("id","features").show()
But when I try :
rf_predictions.select("prediction").show()
In order to display the "prediction" column (same problem with the columns "rawPrediction" or "probability"), it returns me the following bug :
19/09/20 18:33:31 WARN TaskSetManager: Lost task 0.0 in stage 51.0 (TID 169, slmupd5hsn03.zres.ztech, executor 1): org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => vector)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:234)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:228)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ArrayIndexOutOfBoundsException
19/09/20 18:33:32 ERROR TaskSetManager: Task 0 in stage 51.0 failed 4 times; aborting job
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/usr/hdp/current/spark2-client/python/pyspark/sql/dataframe.py", line 336, in show
print(self._jdf.showString(n, 20))
File "/usr/hdp/current/spark2-client/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in __call__
File "/usr/hdp/current/spark2-client/python/pyspark/sql/utils.py", line 63, in deco
return f(*a, **kw)
File "/usr/hdp/current/spark2-client/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o1887.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 51.0 failed 4 times, most recent failure: Lost task 0.3 in stage 51.0 (TID 172, slmupd5hsn01.zres.ztech, executor 2): org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => vector)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:234)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:228)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.lang.ArrayIndexOutOfBoundsException
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1517)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1505)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1504)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1504)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1732)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1687)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1676)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2029)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2050)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2069)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:336)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:2861)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2150)
at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2150)
at org.apache.spark.sql.Dataset$$anonfun$55.apply(Dataset.scala:2842)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:2841)
at org.apache.spark.sql.Dataset.head(Dataset.scala:2150)
at org.apache.spark.sql.Dataset.take(Dataset.scala:2363)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:241)
at sun.reflect.GeneratedMethodAccessor69.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:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.SparkException: Failed to execute user defined function($anonfun$1: (vector) => vector)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:234)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:228)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:827)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:108)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more
Caused by: java.lang.ArrayIndexOutOfBoundsException
And yet I don't use any UDF functions as you can see. Would you know why I get this bug or how I could avoid/fix it please ?
Do you think there is a way to transforming this column to a RDD, List or whatever else and then rebuild it as a dataframe column in order to be able to get the predicted labels ?
Thank you very much in advance.
Best regards
try
rf_predictions.select("rawPrediction").show()
or to map rawPrediction to prediction use Pipeline
try adding Pipeline to your code:
from pyspark.ml import Pipeline
# Chain indexers and forest in a Pipeline
# Train a RandomForest model.
rf = RandomForestClassifier(labelCol="", featuresCol="", numTrees=10)
pipeline = Pipeline(stages=[labelConverter])
# Train model. This also runs the indexers.
model = pipeline.fit(dataframe)
# Make predictions.
predictions = model.transform(testData)

Runing in local model the wordcount lines=sc.textFile('../spark_test.txt') lines.count()

I run pyspark in the local model to learn the wordcount case. I write a spark_test.txt in current file, and run pyspark command , lines = sc.textFile('../spark_test.txt') lines.count(), it throws out a bug:
Input path does not exist: file:/Users/lisl/myproject/spark_test.txt
** I tried:**
sc.textFile('spark_test.txt')
lines = sc.textFile('../spark_test.txt')
lines.count()
i expect the outpub be the number of lines of the file , but the actual output is :
file "/Users/lisl/.pyenv/versions/3.7.1/lib/python3.7/site-packages/pyspark/python/lib/py4j-0.10.7-src.zip/py4j/protocol.py", line 328, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: file:/Users/lisl/myproject/learn_test/spark_test.txt
at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:287)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315)
at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:204)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
at org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:55)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:253)
at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:251)
at scala.Option.getOrElse(Option.scala:121)
at org.apache.spark.rdd.RDD.partitions(RDD.scala:251)
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 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:567)
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:835)
First of all, some lines of code are missing. Please try the code below and make sure that the path to your file exist and you have given read access for all to it (chmod a+r yourFile)
text_file = sc.textFile("path/to/your/input/file")
wordCounts = text_file.flatMap(lambda line: line.split(" ")) \
.map(lambda word: (word, 1)) \
.reduceByKey(lambda a, b: a + b)
wordCounts.saveAsTextFile("path/to/your/output/file")

In Spark, What is the reason of getting EOF exception, Seek past end of file?

I am reading some data (8 GB) data from multiple files, filter the data doing some null check and performing some upliftings (operations) on columns like cleaning column value for this I have 6 to 7 functions (custom functionality, cannot use spark functions) that are registered as UDFs. Then I write the final result to tables and CSV files, now on 'dataframe.write.saveAsTable()' and on writing 'CSV' I get EOF exception Seek past end of file. This exception does not occur everytime, like if I run 20 times it may occur once. I am unable to find its reason and cause because it is not reproduce-able, (Getting this in both in scala and pyspark), will appreciate any help or hint. Looking forward. Thanks
---------------------------------------------------------------------------
Py4JJavaError Traceback (most recent call last)
<command-4146672194126555> in <module>()
331 saveMergedLogs(
332 dataframeLogs
333 );
<command-3860558353011740> in saveMergedLogs(dataframeLogs)
45 # ---------------------------------------------------------------------------------------------------------------------------------
46 spark.sql("DROP TABLE IF EXISTS dbo.UsageLogs");
---> 47 dataframeLogs.write.saveAsTable("dbo.UsageLogs")
/databricks/spark/python/pyspark/sql/readwriter.py in saveAsTable(self, name, format, mode, partitionBy, **options)
773 if format is not None:
774 self.format(format)
--> 775 self._jwrite.saveAsTable(name)
776
777 #since(1.4)
/databricks/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:
/databricks/spark/python/pyspark/sql/utils.py in deco(*a, **kw)
61 def deco(*a, **kw):
62 try:
---> 63 return f(*a, **kw)
64 except py4j.protocol.Py4JJavaError as e:
65 s = e.java_exception.toString()
/databricks/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 o3615.saveAsTable.
: org.apache.spark.SparkException: Job aborted.
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:196)
at org.apache.spark.sql.execution.datasources.InsertIntoHadoopFsRelationCommand.run(InsertIntoHadoopFsRelationCommand.scala:192)
at org.apache.spark.sql.execution.datasources.DataSource.writeAndRead(DataSource.scala:553)
at org.apache.spark.sql.execution.command.CreateDataSourceTableAsSelectCommand.saveDataIntoTable(createDataSourceTables.scala:216)
at org.apache.spark.sql.execution.command.CreateDataSourceTableAsSelectCommand.run(createDataSourceTables.scala:175)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult$lzycompute(commands.scala:110)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.sideEffectResult(commands.scala:108)
at org.apache.spark.sql.execution.command.DataWritingCommandExec.doExecute(commands.scala:128)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:143)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$5.apply(SparkPlan.scala:183)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:180)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:131)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:114)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:114)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:690)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:690)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withCustomExecutionEnv$1.apply(SQLExecution.scala:99)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:228)
at org.apache.spark.sql.execution.SQLExecution$.withCustomExecutionEnv(SQLExecution.scala:85)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:158)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:690)
at org.apache.spark.sql.DataFrameWriter.createTable(DataFrameWriter.scala:487)
at org.apache.spark.sql.DataFrameWriter.saveAsTable(DataFrameWriter.scala:466)
at org.apache.spark.sql.DataFrameWriter.saveAsTable(DataFrameWriter.scala:414)
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: Job aborted due to stage failure: Task 9 in stage 58.0 failed 4 times, most recent failure: Lost task 9.3 in stage 58.0 (TID 8630, 10.139.64.7, executor 0): java.io.EOFException: Cannot seek past end of file
at com.microsoft.azure.datalake.store.ADLFileInputStream.seek(ADLFileInputStream.java:262)
at com.databricks.adl.AdlFsInputStream.seek(AdlFsInputStream.java:64)
at org.apache.hadoop.fs.FSDataInputStream.seek(FSDataInputStream.java:62)
at com.databricks.spark.metrics.FSInputStreamWithMetrics.seek(FileSystemWithMetrics.scala:207)
at org.apache.hadoop.fs.FSDataInputStream.seek(FSDataInputStream.java:62)
at org.apache.hadoop.mapreduce.lib.input.LineRecordReader.initialize(LineRecordReader.java:107)
at org.apache.spark.sql.execution.datasources.HadoopFileLinesReader.<init>(HadoopFileLinesReader.scala:65)
at org.apache.spark.sql.execution.datasources.HadoopFileLinesReader.<init>(HadoopFileLinesReader.scala:47)
at org.apache.spark.sql.execution.datasources.csv.TextInputCSVDataSource$.readFile(CSVDataSource.scala:201)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anonfun$buildReader$2.apply(CSVFileFormat.scala:147)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anonfun$buildReader$2.apply(CSVFileFormat.scala:140)
at org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(FileFormat.scala:147)
at org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(FileFormat.scala:134)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anon$2.getNext(FileScanRDD.scala:226)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:196)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:338)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:196)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage443.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$11$$anon$1.hasNext(WholeStageCodegenExec.scala:622)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
at org.apache.spark.scheduler.Task.doRunTask(Task.scala:139)
at org.apache.spark.scheduler.Task.run(Task.scala:112)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$13.apply(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1432)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:503)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:2100)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2088)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:2087)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2087)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1076)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:1076)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1076)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2319)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2267)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2255)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:873)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2252)
at org.apache.spark.sql.execution.datasources.FileFormatWriter$.write(FileFormatWriter.scala:166)
... 36 more
Caused by: java.io.EOFException: Cannot seek past end of file
at com.microsoft.azure.datalake.store.ADLFileInputStream.seek(ADLFileInputStream.java:262)
at com.databricks.adl.AdlFsInputStream.seek(AdlFsInputStream.java:64)
at org.apache.hadoop.fs.FSDataInputStream.seek(FSDataInputStream.java:62)
at com.databricks.spark.metrics.FSInputStreamWithMetrics.seek(FileSystemWithMetrics.scala:207)
at org.apache.hadoop.fs.FSDataInputStream.seek(FSDataInputStream.java:62)
at org.apache.hadoop.mapreduce.lib.input.LineRecordReader.initialize(LineRecordReader.java:107)
at org.apache.spark.sql.execution.datasources.HadoopFileLinesReader.<init>(HadoopFileLinesReader.scala:65)
at org.apache.spark.sql.execution.datasources.HadoopFileLinesReader.<init>(HadoopFileLinesReader.scala:47)
at org.apache.spark.sql.execution.datasources.csv.TextInputCSVDataSource$.readFile(CSVDataSource.scala:201)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anonfun$buildReader$2.apply(CSVFileFormat.scala:147)
at org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anonfun$buildReader$2.apply(CSVFileFormat.scala:140)
at org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(FileFormat.scala:147)
at org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(FileFormat.scala:134)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1$$anon$2.getNext(FileScanRDD.scala:226)
at org.apache.spark.util.NextIterator.hasNext(NextIterator.scala:73)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:196)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:338)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:196)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage443.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$11$$anon$1.hasNext(WholeStageCodegenExec.scala:622)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:55)
at org.apache.spark.scheduler.Task.doRunTask(Task.scala:139)
at org.apache.spark.scheduler.Task.run(Task.scala:112)
at org.apache.spark.executor.Executor$TaskRunner$$anonfun$13.apply(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1432)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:503)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
... 1 more
So I worked a lot on it, but there is no solution for it. The way I managed was I specified a retry in ADF databricks activity. So when ever this issue occurs it can rerun the notebook in databricks and it passes. Still this is not a perfect solution but it works.
I met same issue when reading data from multiple files. The files have same columns but the order of the columns are not exactly the same. Since in pandas we can set sort=True when append DataFrame so that same columns in different position won't get confused, I suspected it is the order of the columns that cause the issue. I'm not 100% sure but it worked after I re-write the files with same order of columns.