如何在流水线 RDD 上使用 flatMap()？
How to use flatMap() on a pipelined RDD?
我有一个名为 'all_tweets' 的 sql 数据框，它只有一列文本。
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
现在，我正在将此数据帧转换为 RDD 以对其执行一些转换和操作。
[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')
现在，我正在尝试 运行 flatMap 将句子拆分成单词。
[I] user_cnt = all_twt_rdd.flatMap(lambda line: line.split(" ")).take(5)
当我 运行 以上时，我收到以下错误。 RDD 有数据。但是我不明白为什么会出错。 pipelined RDD不是继承了RDD的功能吗？
[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$$anon.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon.<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.apply(DAGScheduler.scala:1419)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$anon.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$$anon.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon.<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
问题是您在 Row 上调用 .split()，而不是字符串。行对象没有 .split() 方法——只有字符串有。你想拆分它的 text 属性，所以显式调用它：
user_cnt = all_twt_rdd.flatMap(lambda line: line.text.split(" ")).take(5)
我有一个名为 'all_tweets' 的 sql 数据框，它只有一列文本。
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
现在，我正在将此数据帧转换为 RDD 以对其执行一些转换和操作。
[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')
现在，我正在尝试 运行 flatMap 将句子拆分成单词。
[I] user_cnt = all_twt_rdd.flatMap(lambda line: line.split(" ")).take(5)
当我 运行 以上时，我收到以下错误。 RDD 有数据。但是我不明白为什么会出错。 pipelined RDD不是继承了RDD的功能吗？
[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$$anon.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon.<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.apply(DAGScheduler.scala:1419)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage.apply(DAGScheduler.scala:1418)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1418)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed.apply(DAGScheduler.scala:799)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:799)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1640)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1599)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1588)
at org.apache.spark.util.EventLoop$$anon.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$$anon.read(PythonRDD.scala:166)
at org.apache.spark.api.python.PythonRunner$$anon.<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
问题是您在 Row 上调用 .split()，而不是字符串。行对象没有 .split() 方法——只有字符串有。你想拆分它的 text 属性，所以显式调用它：
user_cnt = all_twt_rdd.flatMap(lambda line: line.text.split(" ")).take(5)