为什么dropna（）不工作？ [英] Why does dropna() not work?

问题描述

系统：星火1.3.0（蟒蛇Python的DIST）上Cloudera的快速启动VM 5.4

System: Spark 1.3.0 (Anaconda Python dist.) on Cloudera Quickstart VM 5.4

下面是一个星火数据框：

Here's a Spark DataFrame:

from pyspark.sql import SQLContext
from pyspark.sql.types import *
sqlContext = SQLContext(sc)

data = sc.parallelize([('Foo',41,'US',3),
                       ('Foo',39,'UK',1),
                       ('Bar',57,'CA',2),
                       ('Bar',72,'CA',3),
                       ('Baz',22,'US',6),
                       (None,75,None,7)])

schema = StructType([StructField('Name', StringType(), True),
                     StructField('Age', IntegerType(), True),
                     StructField('Country', StringType(), True),
                     StructField('Score', IntegerType(), True)])

df = sqlContext.createDataFrame(data,schema)

data.show（）

Name Age Country Score
Foo  41  US      3    
Foo  39  UK      1    
Bar  57  CA      2    
Bar  72  CA      3    
Baz  22  US      6    
null 75  null    7 

不过这些都不工作了！

However neither of these work!

df.dropna()
df.na.drop()

我得到这个消息：

I get this message:

>>> df.show()
Name Age Country Score
Foo  41  US      3    
Foo  39  UK      1    
Bar  57  CA      2    
Bar  72  CA      3    
Baz  22  US      6    
null 75  null    7    
>>> df.dropna().show()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/lib/spark/python/pyspark/sql/dataframe.py", line 580, in __getattr__
    jc = self._jdf.apply(name)
  File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/java_gateway.py", line 538, in __call__
  File "/usr/lib/spark/python/lib/py4j-0.8.2.1-src.zip/py4j/protocol.py", line 300, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o50.apply.
: org.apache.spark.sql.AnalysisException: Cannot resolve column name "dropna" among (Name, Age, Country, Score);
    at org.apache.spark.sql.DataFrame$$anonfun$resolve$1.apply(DataFrame.scala:162)
    at org.apache.spark.sql.DataFrame$$anonfun$resolve$1.apply(DataFrame.scala:162)
    at scala.Option.getOrElse(Option.scala:120)
    at org.apache.spark.sql.DataFrame.resolve(DataFrame.scala:161)
    at org.apache.spark.sql.DataFrame.col(DataFrame.scala:436)
    at org.apache.spark.sql.DataFrame.apply(DataFrame.scala:426)
    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:379)
    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:207)
    at java.lang.Thread.run(Thread.java:745)

有其他人遇到这个问题？有什么解决办法？ Pyspark似乎，我在寻找一个叫娜一栏的东西。任何帮助将是AP preciated！

Has anybody else experienced this problem? What's the workaround? Pyspark seems to thing that I am looking for a column called "na". Any help would be appreciated!

推荐答案

TL;博士的方法呐和 dropna 只是因为星火1.3.1可用。

tl;dr The methods na and dropna are only available since Spark 1.3.1.

几个错误：

1. 数据= sc.parallelize（[....（''，75'，7）]），您打算使用重新present 无，但是，它只是一个字符串，而不是空

1. data = sc.parallelize([....('',75,'', 7 )]), you intended to use '' to represent None, however, it's just a String instead of null

呐和 dropna 是在数据框类两种方法，因此，你应该把它叫做你东风。

na and dropna are both methods on dataFrame class, therefore, you should call it with your df.

的Runnable code：

Runnable Code:

data = sc.parallelize([('Foo',41,'US',3),
                       ('Foo',39,'UK',1),
                       ('Bar',57,'CA',2),
                       ('Bar',72,'CA',3),
                       ('Baz',22,'US',6),
                       (None, 75, None, 7)])

schema = StructType([StructField('Name', StringType(), True),
                 StructField('Age', IntegerType(), True),
                 StructField('Country', StringType(), True),
                 StructField('Score', IntegerType(), True)])

df = sqlContext.createDataFrame(data,schema)

df.dropna().show()
df.na.drop().show()

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