0
votes

I have a weird spark RDD, I am not sure what is wrong or how to go about troubleshooting. I am running Spark 1.6.2 with python 3.4.3 through an ipython notebook.

Here is how I am pulling in the data:

sqlContext = SQLContext(sc)
hdfs = 'hdfs://192.168.1.213:54310/TEMP/*' 

def make_Row(item):
    temp = {}
    if 'desc' in item:
        temp['desc']=str(item['desc']).lower()
    if 'cat' in item:
        temp['cat']= parse_cats(str(item['cat']).lower())
    if 'cat' in temp and 'desc' in temp:
        return Row(**temp)

raw_data = sc.wholeTextFiles(hdfs, 15).map(lambda x: json.loads(x[1])).flatMap(lambda x: x).map(lambda d: make_Row(d)).cache()
raw_data.count()

This brings me the count of the data:

Weird parts:

  1. raw_data.show() gives the following exception. I checked 'PipelinedRDD' object has no attribute 'toDF' in PySpark, but I do have sqlContext defined.

    AttributeErrorTraceback (most recent call last) in () ----> 1 raw_data.show()

    AttributeError: 'PipelinedRDD' object has no attribute 'show'

  2. raw_data.toDF().show() works fine.

  3. raw_data.toDF().columns shows: ['cat', 'desc'], but raw_data.toDF().describe('cat').show() throws the following:

    Py4JJavaErrorTraceback (most recent call last)
        <ipython-input-110-45e3ce9b4e4b> in <module>()
        ----> 1 raw_data.toDF().describe('cat').show()
    
        /apps/spark/python/pyspark/sql/dataframe.py in describe(self, *cols)
            772         if len(cols) == 1 and isinstance(cols[0], list):
            773             cols = cols[0]
        --> 774         jdf = self._jdf.describe(self._jseq(cols))
            775         return DataFrame(jdf, self.sql_ctx)
            776 
    
        /apps/spark/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:
    
        /apps/spark/python/pyspark/sql/utils.py 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()
    
        /apps/spark/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 o1689.describe.
        : org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 68.0 failed 4 times, most recent failure: Lost task 2.3 in stage 68.0 (TID 352, solrmain): java.lang.NullPointerException
            at org.apache.spark.api.python.SerDeUtil$$anonfun$toJavaArray$1.apply(SerDeUtil.scala:102)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.processCurrentSortedGroup(SortBasedAggregationIterator.scala:122)
            at org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.next(SortBasedAggregationIterator.scala:152)
            at org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.next(SortBasedAggregationIterator.scala:29)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:149)
            at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
            at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
            at org.apache.spark.scheduler.Task.run(Task.scala:89)
            at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
            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$$failJobAndIndependentStages(DAGScheduler.scala:1431)
            at org.apache.spark.scheduler.DAGScheduler$$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.sql.execution.SparkPlan.executeTake(SparkPlan.scala:212)
            at org.apache.spark.sql.execution.Limit.executeCollect(basicOperators.scala:165)
            at org.apache.spark.sql.execution.SparkPlan.executeCollectPublic(SparkPlan.scala:174)
            at org.apache.spark.sql.DataFrame$$anonfun$org$apache$spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1499)
            at org.apache.spark.sql.DataFrame$$anonfun$org$apache$spark$sql$DataFrame$$execute$1$1.apply(DataFrame.scala:1499)
            at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:56)
            at org.apache.spark.sql.DataFrame.withNewExecutionId(DataFrame.scala:2086)
            at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$execute$1(DataFrame.scala:1498)
            at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$collect(DataFrame.scala:1505)
            at org.apache.spark.sql.DataFrame$$anonfun$head$1.apply(DataFrame.scala:1375)
            at org.apache.spark.sql.DataFrame$$anonfun$head$1.apply(DataFrame.scala:1374)
            at org.apache.spark.sql.DataFrame.withCallback(DataFrame.scala:2099)
            at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1374)
            at org.apache.spark.sql.DataFrame.head(DataFrame.scala:1383)
            at org.apache.spark.sql.DataFrame$$anonfun$describe$1.apply(DataFrame.scala:1352)
            at org.apache.spark.sql.DataFrame$$anonfun$describe$1.apply(DataFrame.scala:1335)
            at org.apache.spark.sql.DataFrame.org$apache$spark$sql$DataFrame$$withPlan(DataFrame.scala:2126)
            at org.apache.spark.sql.DataFrame.describe(DataFrame.scala:1335)
            at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
            at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
            at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
            at java.lang.reflect.Method.invoke(Method.java:498)
            at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:231)
            at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:381)
            at py4j.Gateway.invoke(Gateway.java:259)
            at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:133)
            at py4j.commands.CallCommand.execute(CallCommand.java:79)
            at py4j.GatewayConnection.run(GatewayConnection.java:209)
        at java.lang.Thread.run(Thread.java:745)
    Caused by: java.lang.NullPointerException
            at org.apache.spark.api.python.SerDeUtil$$anonfun$toJavaArray$1.apply(SerDeUtil.scala:102)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.processCurrentSortedGroup(SortBasedAggregationIterator.scala:122)
            at org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.next(SortBasedAggregationIterator.scala:152)
            at org.apache.spark.sql.execution.aggregate.SortBasedAggregationIterator.next(SortBasedAggregationIterator.scala:29)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at scala.collection.Iterator$$anon$11.next(Iterator.scala:328)
            at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:149)
            at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
            at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
            at org.apache.spark.scheduler.Task.run(Task.scala:89)
            at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:227)
            at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
            at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
            ... 1 more
    

Thanks in advance

2

2 Answers

0
votes

The RDD API does not have a show() method, hence the error in #1. You need to either convert to a dataframe (as you do in #2) or use something like:

raw_data.take(5)

to get a list of your row objects.

Re #3, the toDF method is a little finicky depending on the distribution you're using. Try this:

df = sqlContext.createDataFrame(raw_data)

then run your other operations.

0
votes

Number 1 has already been answered: RDD does not have a show() method.

Number 3: Try raw_data.toDF().describe(['cat']).show()