Hi , I am not able to use .map function in Spark. My codes are as below :-
*1) Create Parse function:-* from datetime import datetime from collections import namedtuple fields = ('date','airline','flightnum','origin','dest','dep','dep_delay','arv','arv_delay','airtime','distance') Flight = namedtuple('Flight',fields,verbose=True) DATE_FMT = "%y-%m-%d" TIME_FMT = "%H%M" def parse(row) : row[0] = datetime.strptime(row[0], DATE_FMT).date() row[5] = datetime.strptime(row[5], TIME_FMT).time() row[6] = float(row[6]) row[7] = datetime.strptime(row[7], TIME_FMT).time() row[8] = float(row[8]) row[9] = float(row[9]) row[10] = float(row[10]) return Flight(*row[:11]) *2) Using Parse to parse my RDD* flightsParsedMap = flights.map(lambda x: x.split(',')).map(parse) *3) Checking Parsed RDD * flightsParsedMap *Output is :- * *PythonRDD[8] at RDD at PythonRDD.scala:48* *4) Checking first row :-* flightsParsedMap.first() Here i am getting issue:- ---------------------------------------------------------------------------Py4JJavaError Traceback (most recent call last)<ipython-input-30-2f844be53361> in <module>()----> 1 flightsParsedMap.first() C:\spark\spark\python\pyspark\rdd.py in first(self) 1374 ValueError: RDD is empty 1375 """-> 1376 rs = self.take(1) 1377 if rs: 1378 return rs[0] C:\spark\spark\python\pyspark\rdd.py in take(self, num) 1356 1357 p = range(partsScanned, min(partsScanned + numPartsToTry, totalParts))-> 1358 res = self.context.runJob(self, takeUpToNumLeft, p) 1359 1360 items += res C:\spark\spark\python\pyspark\context.py in runJob(self, rdd, partitionFunc, partitions, allowLocal) 999 # SparkContext#runJob. 1000 mappedRDD = rdd.mapPartitions(partitionFunc)-> 1001 port = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, partitions) 1002 return list(_load_from_socket(port, mappedRDD._jrdd_deserializer)) 1003 C:\spark\spark\python\lib\py4j-0.10.6-src.zip\py4j\java_gateway.py in __call__(self, *args) 1158 answer = self.gateway_client.send_command(command) 1159 return_value = get_return_value(-> 1160 answer, self.gateway_client, self.target_id, self.name) 1161 1162 for temp_arg in temp_args: C:\spark\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() C:\spark\spark\python\lib\py4j-0.10.6-src.zip\py4j\protocol.py in get_return_value(answer, gateway_client, target_id, name) 318 raise Py4JJavaError( 319 "An error occurred while calling {0}{1}{2}.\n".--> 320 format(target_id, ".", name), value) 321 else: 322 raise Py4JError( Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.runJob. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 8.0 failed 1 times, most recent failure: Lost task 0.0 in stage 8.0 (TID 9, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "C:\spark\spark\python\lib\pyspark.zip\pyspark\worker.py", line 229, in main File "C:\spark\spark\python\lib\pyspark.zip\pyspark\worker.py", line 224, in process File "C:\spark\spark\python\lib\pyspark.zip\pyspark\serializers.py", line 372, in dump_stream vs = list(itertools.islice(iterator, batch)) File "C:\spark\spark\python\pyspark\rdd.py", line 1354, in takeUpToNumLeft yield next(iterator) File "<ipython-input-28-35fca1a45bf3>", line 8, in parse File "C:\ProgramData\Anaconda3\lib\_strptime.py", line 565, in _strptime_datetime tt, fraction = _strptime(data_string, format) File "C:\ProgramData\Anaconda3\lib\_strptime.py", line 362, in _strptime (data_string, format)) ValueError: time data '"FL_DATE"' does not match format '%y-%m-%d' at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421) at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$class.foreach(Iterator.scala:893) at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28) at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48) at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310) at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28) at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302) at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28) at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289) at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28) at org.apache.spark.api.python.PythonRDD$$anonfun$1.apply(PythonRDD.scala:141) at org.apache.spark.api.python.PythonRDD$$anonfun$1.apply(PythonRDD.scala:141) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:109) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) at java.lang.Thread.run(Thread.java:745) Driver stacktrace: at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1599) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1587) at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1586) at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59) at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48) at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1586) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831) at scala.Option.foreach(Option.scala:257) at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1820) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1769) at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1758) at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48) at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2027) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2048) at org.apache.spark.SparkContext.runJob(SparkContext.scala:2067) at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:141) at org.apache.spark.api.python.PythonRDD.runJob(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:214) at java.lang.Thread.run(Thread.java:745) Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last): File "C:\spark\spark\python\lib\pyspark.zip\pyspark\worker.py", line 229, in main File "C:\spark\spark\python\lib\pyspark.zip\pyspark\worker.py", line 224, in process File "C:\spark\spark\python\lib\pyspark.zip\pyspark\serializers.py", line 372, in dump_stream vs = list(itertools.islice(iterator, batch)) File "C:\spark\spark\python\pyspark\rdd.py", line 1354, in takeUpToNumLeft yield next(iterator) File "<ipython-input-28-35fca1a45bf3>", line 8, in parse File "C:\ProgramData\Anaconda3\lib\_strptime.py", line 565, in _strptime_datetime tt, fraction = _strptime(data_string, format) File "C:\ProgramData\Anaconda3\lib\_strptime.py", line 362, in _strptime (data_string, format)) ValueError: time data '"FL_DATE"' does not match format '%y-%m-%d' at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.handlePythonException(PythonRunner.scala:298) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:438) at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRunner.scala:421) at org.apache.spark.api.python.BasePythonRunner$ReaderIterator.hasNext(PythonRunner.scala:252) at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37) at scala.collection.Iterator$class.foreach(Iterator.scala:893) at org.apache.spark.InterruptibleIterator.foreach(InterruptibleIterator.scala:28) at scala.collection.generic.Growable$class.$plus$plus$eq(Growable.scala:59) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:104) at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:48) at scala.collection.TraversableOnce$class.to(TraversableOnce.scala:310) at org.apache.spark.InterruptibleIterator.to(InterruptibleIterator.scala:28) at scala.collection.TraversableOnce$class.toBuffer(TraversableOnce.scala:302) at org.apache.spark.InterruptibleIterator.toBuffer(InterruptibleIterator.scala:28) at scala.collection.TraversableOnce$class.toArray(TraversableOnce.scala:289) at org.apache.spark.InterruptibleIterator.toArray(InterruptibleIterator.scala:28) at org.apache.spark.api.python.PythonRDD$$anonfun$1.apply(PythonRDD.scala:141) at org.apache.spark.api.python.PythonRDD$$anonfun$1.apply(PythonRDD.scala:141) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067) at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:2067) at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at org.apache.spark.scheduler.Task.run(Task.scala:109) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617) ... 1 more Please help me in this . Thanks. Nandan Priyadarshi