PySpark Dataframe基于类方法创建新列

时间：2019-04-09 10:39:20

标签： python dataframe pyspark

我想从类方法中添加列，但是遇到一些错误。

首先，这是我的数据框

from pyspark.sql.functions import udf
import pandas as pd 

df = spark.createDataFrame(pd.DataFrame([[1,1,1],[2,2,2]],columns=['a','b','c']))

+---+---+---+
|  a|  b|  c|
+---+---+---+
|  1|  1|  1|
|  2|  2|  2|
+---+---+---+

然后，我创建类方法

class Test(object):

    def __init__(self):

        pass

    @staticmethod
    def A(self,num):

        return num+1

然后，我使用“ udf”声明函数

fun  = udf(Test.A)

然后，我想添加列“ c3”以应用函数“ fun”，如下所示：

df2 = df.withColumn('c3',fun('c'))

但是这里遇到这样的错误：

df2.show()
Py4JJavaError                             Traceback (most recent call last)
<ipython-input-58-1d45a0548e2e> in <module>
----> 1 df2.show()

/export/soft/spark-2.1.0/python/pyspark/sql/dataframe.py in show(self, n, truncate)
    334         """
    335         if isinstance(truncate, bool) and truncate:
--> 336             print(self._jdf.showString(n, 20))
    337         else:
    338             print(self._jdf.showString(n, int(truncate)))

/export/soft/spark-2.1.0/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:

/export/soft/spark-2.1.0/python/pyspark/sql/utils.py 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()

/export/soft/spark-2.1.0/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 o441.showString.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 30.0 failed 1 times, most recent failure: Lost task 2.0 in stage 30.0 (TID 64, localhost, executor driver): org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 177, in main
    process()
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 172, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 220, in dump_stream
    self.serializer.dump_stream(self._batched(iterator), stream)
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 138, in dump_stream
    for obj in iterator:
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 209, in _batched
    for item in iterator:
  File "<string>", line 1, in <lambda>
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 71, in <lambda>
    return lambda *a: f(*a)
TypeError: A() missing 1 required positional argument: 'text'

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
    at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:144)
    at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:87)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:797)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:797)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:108)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
    at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1487)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1486)
    at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
    at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
    at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
    at scala.Option.foreach(Option.scala:257)
    at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1714)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1669)
    at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1658)
    at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
    at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:630)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2022)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2043)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2062)
    at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:336)
    at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
    at org.apache.spark.sql.Dataset.org$apache$spark$sql$Dataset$$collectFromPlan(Dataset.scala:2853)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2153)
    at org.apache.spark.sql.Dataset$$anonfun$head$1.apply(Dataset.scala:2153)
    at org.apache.spark.sql.Dataset$$anonfun$55.apply(Dataset.scala:2837)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:65)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:2836)
    at org.apache.spark.sql.Dataset.head(Dataset.scala:2153)
    at org.apache.spark.sql.Dataset.take(Dataset.scala:2366)
    at org.apache.spark.sql.Dataset.showString(Dataset.scala:245)
    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:748)
Caused by: org.apache.spark.api.python.PythonException: Traceback (most recent call last):
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 177, in main
    process()
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 172, in process
    serializer.dump_stream(func(split_index, iterator), outfile)
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 220, in dump_stream
    self.serializer.dump_stream(self._batched(iterator), stream)
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 138, in dump_stream
    for obj in iterator:
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/serializers.py", line 209, in _batched
    for item in iterator:
  File "<string>", line 1, in <lambda>
  File "/export/soft/spark-2.1.0/python/lib/pyspark.zip/pyspark/worker.py", line 71, in <lambda>
    return lambda *a: f(*a)
TypeError: A() missing 1 required positional argument: 'text'

    at org.apache.spark.api.python.PythonRunner$$anon$1.read(PythonRDD.scala:193)
    at org.apache.spark.api.python.PythonRunner$$anon$1.<init>(PythonRDD.scala:234)
    at org.apache.spark.api.python.PythonRunner.compute(PythonRDD.scala:152)
    at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:144)
    at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1.apply(BatchEvalPythonExec.scala:87)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:797)
    at org.apache.spark.rdd.RDD$$anonfun$mapPartitions$1$$anonfun$apply$23.apply(RDD.scala:797)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
    at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
    at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
    at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
    at org.apache.spark.scheduler.Task.run(Task.scala:108)
    at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
    at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
    at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
    ... 1 more

此外，定义一个正常功能，并且该功能可以正常工作， 这意味着：

def fun2(intext):
    return intext+1

fun2 = udf(fun2)

df  = df.withColumn('c3',fun2('c'))

这种方法可以工作，但是由于组织代码的更好方法，我需要使用类方法来解决此问题。

我该怎么办。请指导，谢谢。

1 个答案:

答案 0 :(得分：0)

静态函数A以self作为参数是否正常？

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