Question

我试图从我的RDD读取但是低于错误。请指教。该文件存在于HDFS中。我使用hadoop文件系统命令将文件移动到HDFS。

代码：

baby_names = sc.textFile("/user/rahul/baby_names.csv")

rows = baby_names.map(lambda line:line.split(","))

for row in rows.take(rows.count()):print(row[1])

错误：

Py4JJavaError                             Traceback (most recent call last)
<ipython-input-7-b9dcd91a9f1c> in <module>()
----> 1 for row in rows.take(rows.count()):print(row[1])

/home/rahul/Hadoop/spark/python/pyspark/rdd.pyc in count(self)
   1039         3
   1040         """
-> 1041         return self.mapPartitions(lambda i: [sum(1 for _ in i)]).sum()
   1042 
   1043     def stats(self):

/home/rahul/Hadoop/spark/python/pyspark/rdd.pyc in sum(self)
   1030         6.0
   1031         """
-> 1032         return self.mapPartitions(lambda x: [sum(x)]).fold(0, operator.add)
   1033 
   1034     def count(self):

/home/rahul/Hadoop/spark/python/pyspark/rdd.pyc in fold(self, zeroValue, op)
    904         # zeroValue provided to each partition is unique from the one provided
    905         # to the final reduce call
--> 906         vals = self.mapPartitions(func).collect()
    907         return reduce(op, vals, zeroValue)
    908 

/home/rahul/Hadoop/spark/python/pyspark/rdd.pyc in collect(self)
    807         """
    808         with SCCallSiteSync(self.context) as css:
--> 809             port = self.ctx._jvm.PythonRDD.collectAndServe(self._jrdd.rdd())
    810         return list(_load_from_socket(port, self._jrdd_deserializer))
    811 

/home/rahul/Hadoop/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py in __call__(self, *args)
   1131         answer = self.gateway_client.send_command(command)
   1132         return_value = get_return_value(
-> 1133             answer, self.gateway_client, self.target_id, self.name)
   1134 
   1135         for temp_arg in temp_args:

/home/rahul/Hadoop/spark/python/pyspark/sql/utils.pyc 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()

/home/rahul/Hadoop/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py in get_return_value(answer, gateway_client, target_id, name)
    317                 raise Py4JJavaError(
    318                     "An error occurred while calling {0}{1}{2}.\n".
--> 319                     format(target_id, ".", name), value)
    320             else:
    321                 raise Py4JError(

Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
: org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: file:/user/rahul/baby_names.csv
    at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:287)
    at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:229)
    at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:315)
    at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:202)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
    at org.apache.spark.rdd.MapPartitionsRDD.getPartitions(MapPartitionsRDD.scala:35)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
    at org.apache.spark.api.python.PythonRDD.getPartitions(PythonRDD.scala:53)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:252)
    at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:250)
    at scala.Option.getOrElse(Option.scala:121)
    at org.apache.spark.rdd.RDD.partitions(RDD.scala:250)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:1958)
    at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:935)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:934)
    at org.apache.spark.api.python.PythonRDD$.collectAndServe(PythonRDD.scala:453)
    at org.apache.spark.api.python.PythonRDD.collectAndServe(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:280)
    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)

如果有火花配置更改的链接，请分享。

Answer 1

为什么不使用collect()，如果你想读取所有行？

baby_names = sc.textFile("/user/rahul/baby_names.csv")

rows = baby_names.map(lambda line:line.split(",")) \
                 .filter(lambda line: len(line)>1) \
                 .map(lambda line: (line[0],line[1]))

for row in rows.collect():print(row)

或者

no_rows = rows.count()
for row in rows.take(no_rows):print(row)

collect（） - 将数据集的所有元素作为数组返回   司机程序。这通常在过滤器或其他之后有用   返回足够小的数据子集的操作。

  count（） - 返回数据集中的元素数。

take（n） - 返回   包含数据集的前n个元素的数组。

PYSPARK：从RDD读取错误

1 个答案: