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
