Question

我有一个奇怪的火花RDD，我不确定有什么问题或如何进行故障排除。我通过ipython笔记本运行Spark 1.6.2和python 3.4.3。

以下是我如何提取数据：

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()

这给我带来了数据的计数：

奇怪的部分：

raw_data.show()提供以下异常。我检查了'PipelinedRDD' object has no attribute 'toDF' in PySpark，但我确实定义了sqlContext。

AttributeErrorTraceback（最近一次调用最后一次） in（） ----＆GT; 1 raw_data.show（）

AttributeError：＆＃39; PipelinedRDD＆＃39;对象没有属性＆＃39;显示＆＃39;
raw_data.toDF().show()工作正常。

raw_data.toDF().columns显示：['cat', 'desc']，但raw_data.toDF().describe('cat').show()会抛出以下内容：

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

提前致谢

Answer 1

RDD API没有show()方法，因此错误在＃1中。您需要转换为数据框（就像在＃2中一样）或使用类似：

的内容

raw_data.take(5)

获取行对象的列表。

Re＃3，根据你使用的发行版，toDF方法有点挑剔。试试这个：

df = sqlContext.createDataFrame(raw_data)

然后运行您的其他操作。

Answer 2

已回答数字1：RDD没有window.open("http://www.sitename.com", '_system');方法。

3号：尝试show()

Spark RDD出了点问题

2 个答案: