CODEWITHSUNDEEP
pythonapache-sparkpysparkrdd
Srinivas
Srinivas

Reputation: 35

How to use flatMap() on a pipelined RDD?

I have a sql dataframe named 'all_tweets' which has only one column text.

all_tweets.show(5)

+--------------------+
|                text|
+--------------------+
|@always_nidhi @Yo...|
|@OnlyDancers Bell...|
|Taste of Iceland!...|
|Serasi ade haha @...|
|@BeezyDH_ it's li...|
+--------------------+
only showing top 5 rows

Now, I am converting this dataframe to an RDD to perform some transformations and action on it.

[I] all_twt_rdd = all_tweets.rdd

[I] type(all_twt_rdd)

[O] pyspark.rdd.RDD

[I] all_twt_rdd.first()

[O] Row(text=u'@always_nidhi @YouTube no i dnt understand bt i loved the music nd their dance awesome all the song of this mve is rocking')

Now, I am trying to run flatMap on it to split the sentence in to words. 

[I] user_cnt = all_twt_rdd.flatMap(lambda line: line.split(" ")).take(5)

When I run the above, I receive below error. RDD has data. But I don't understand why it errored. Doesn't pipelined RDD inherit the functions of an RDD?

[O]
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-101-31527190732e> in <module>()
----> 1 user_cnt = all_twt_rdd.flatMap(lambda line: line.split(" ")).take(2)

/home/notebook/spark-1.6.0-bin-hadoop2.6/python/pyspark/rdd.pyc in take(self, num)
   1295 
   1296             p = range(partsScanned, min(partsScanned + numPartsToTry, totalParts))
-> 1297             res = self.context.runJob(self, takeUpToNumLeft, p)
   1298 
   1299             items += res

/home/notebook/spark-1.6.0-bin-hadoop2.6/python/pyspark/context.pyc in runJob(self, rdd, partitionFunc, partitions, allowLocal)
    937         # SparkContext#runJob.
    938         mappedRDD = rdd.mapPartitions(partitionFunc)
--> 939         port = self._jvm.PythonRDD.runJob(self._jsc.sc(), mappedRDD._jrdd, partitions)
    940         return list(_load_from_socket(port, mappedRDD._jrdd_deserializer))
    941 

/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/py4j-0.9-src.zip/py4j/java_gateway.py in __call__(self, *args)
    811         answer = self.gateway_client.send_command(command)
    812         return_value = get_return_value(
--> 813             answer, self.gateway_client, self.target_id, self.name)
    814 
    815         for temp_arg in temp_args:

/home/notebook/spark-1.6.0-bin-hadoop2.6/python/pyspark/sql/utils.pyc in deco(*a, **kw)
     43     def deco(*a, **kw):
     44         try:
---> 45             return f(*a, **kw)
     46         except py4j.protocol.Py4JJavaError as e:
     47             s = e.java_exception.toString()

/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/py4j-0.9-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    306                 raise Py4JJavaError(
    307                     "An error occurred while calling {0}{1}{2}.\n".
--> 308                     format(target_id, ".", name), value)
    309             else:
    310                 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 50.0 failed 1 times, most recent failure: Lost task 0.0 in stage 50.0 (TID 456, localhost): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/worker.py", line 111, in main
    process()
  File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/worker.py", line 106, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/serializers.py", line 263, in dump_stream
    vs = list(itertools.islice(iterator, batch))
  File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/pyspark/rdd.py", line 1293, in takeUpToNumLeft
    yield next(iterator)
  File "<ipython-input-101-31527190732e>", line 1, in <lambda>
  File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/sql/types.py", line 1272, in __getattr__
    raise AttributeError(item)
AttributeError: split

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:89)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    at java.lang.Thread.run(Thread.java:745)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1431)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1419)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1418)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:799)
    at scala.Option.foreach(Option.scala:236)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1845)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1858)
    at org.apache.spark.api.python.PythonRDD$.runJob(PythonRDD.scala:393)
    at org.apache.spark.api.python.PythonRDD.runJob(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:231)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
    at py4j.Gateway.invoke(Gateway.java:259)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:209)
    at java.lang.Thread.run(Thread.java:745)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/worker.py", line 111, in main
    process()
  File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/worker.py", line 106, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/serializers.py", line 263, in dump_stream
    vs = list(itertools.islice(iterator, batch))
  File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/pyspark/rdd.py", line 1293, in takeUpToNumLeft
    yield next(iterator)
  File "<ipython-input-101-31527190732e>", line 1, in <lambda>
  File "/home/notebook/spark-1.6.0-bin-hadoop2.6/python/lib/pyspark.zip/pyspark/sql/types.py", line 1272, in __getattr__
    raise AttributeError(item)
AttributeError: split

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:166)
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:207)
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:125)
    at org.apache.spark.api.python.PythonRDD.compute(PythonRDD.scala:70)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
    at org.apache.spark.scheduler.Task.run(Task.scala:89)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:213)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
    ... 1 more

Upvotes: 0

Views: 3979

Answers (1)

Akshat Mahajan
Akshat Mahajan

Reputation: 9856

The problem is that you're calling .split() on a Row, not a string. Row objects have no .split() method - only strings do. You want to split its text attribute, so call it explicitly:

user_cnt = all_twt_rdd.flatMap(lambda line: line.text.split(" ")).take(5)

Upvotes: 2

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