运行python文件时出错:列数不为';不匹配。\n旧列名(1):\u c0\n新列名(4)

运行python文件时出错:列数不为';不匹配。\n旧列名(1):\u c0\n新列名(4),python,pyspark,pyspark-sql,pyspark-dataframes,Python,Pyspark,Pyspark Sql,Pyspark Dataframes,当我运行以下代码时,出现了一些错误,表明列数不匹配。\n旧列名(1):\u c0\n新列名(4):由于我是python新手,我想知道如何解决此问题: from pyspark import SparkContext from pyspark.sql import SparkSession from pyspark.sql import functions as F # create Spark context and session with necessary configuration s

当我运行以下代码时,出现了一些错误,表明列数不匹配。\n旧列名(1):\u c0\n新列名(4):由于我是python新手,我想知道如何解决此问题:

from pyspark import SparkContext
from pyspark.sql import SparkSession
from pyspark.sql import functions as F

# create Spark context and session with necessary configuration
sc = SparkContext('local[1]', '2_program_2a_avg')
spark = SparkSession(sc)

# read as dataframe with using delimiter
df = spark.read \
     .format('csv') \
     .options(header='false', delimiter=' ') \
     .load('/home/hduser/Desktop/sample1/avg/input_avg.csv') \
     .toDF('ownerid','houseid','zipcode','value')

# select the necessary columns
df = df.select('zipcode', 'value')

# compute the average house value of each zipcode
df = df.groupBy('zipcode').agg(F.mean('value'), F.count('value')).orderBy('avg(value)', ascending=True)

# show the result
df.show()

# change it to rdd so that we can save the output as text file
df = df.rdd.saveAsTextFile('/home/hduser/Desktop/sample1/avg/')

# stop spark context
sc.stop()
输出

*/home/hduser/PycharmProjects/Assignment2/venv/bin/python /home/hduser/PycharmProjects/HelloWorld/avg_value.py
    19/11/12 10:47:49 WARN Utils: Your hostname, hadoop resolves to a loopback address: 127.0.1.1; using 10.0.2.15 instead (on interface enp0s3)
    19/11/12 10:47:49 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another address
    19/11/12 10:47:51 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
    Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
    Setting default log level to "WARN".
    To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
    Traceback (most recent call last):
      File "/opt/spark/python/pyspark/sql/utils.py", line 63, in deco
        return f(*a, **kw)
      File "/home/hduser/PycharmProjects/Assignment2/venv/lib/python3.6/site-packages/py4j/protocol.py", line 328, in get_return_value
        format(target_id, ".", name), value)
    py4j.protocol.Py4JJavaError: An error occurred while calling o28.toDF.
    : java.lang.IllegalArgumentException: requirement failed: The number of columns doesn't match.
    Old column names (1): _c0
    New column names (4): ownerid, houseid, zipcode, value
        at scala.Predef$.require(Predef.scala:224)
        at org.apache.spark.sql.Dataset.toDF(Dataset.scala:447)
        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:282)
        at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
        at py4j.commands.CallCommand.execute(CallCommand.java:79)
        at py4j.GatewayConnection.run(GatewayConnection.java:238)
        at java.lang.Thread.run(Thread.java:748)


    During handling of the above exception, another exception occurred:

    Traceback (most recent call last):
      File "/home/hduser/PycharmProjects/HelloWorld/avg_value.py", line 15, in <module>
        .toDF(*columns)
      File "/opt/spark/python/pyspark/sql/dataframe.py", line 2055, in toDF
        jdf = self._jdf.toDF(self._jseq(cols))
      File "/home/hduser/PycharmProjects/Assignment2/venv/lib/python3.6/site-packages/py4j/java_gateway.py", line 1257, in __call__
        answer, self.gateway_client, self.target_id, self.name)
      File "/opt/spark/python/pyspark/sql/utils.py", line 79, in deco
        raise IllegalArgumentException(s.split(': ', 1)[1], stackTrace)
    pyspark.sql.utils.IllegalArgumentException: "requirement failed: The number of columns doesn't match.\nOld column names (1): _c0\nNew column names (4): ownerid, houseid, zipcode, value"

    Process finished with exit code 1*
*/home/hduser/PycharmProjects/Assignment2/venv/bin/python/home/hduser/PycharmProjects/HelloWorld/avg_value.py
19/11/12 10:47:49警告Utils:您的主机名,hadoop解析为环回地址:127.0.1.1;改用10.0.2.15(在接口enp0s3上)
19/11/12 10:47:49警告Utils:如果需要绑定到其他地址,请设置SPARK_LOCAL_IP
19/11/12 10:47:51警告NativeCodeLoader:无法为您的平台加载本机hadoop库。。。在适用的情况下使用内置java类
使用Spark的默认log4j配置文件:org/apache/Spark/log4j-defaults.properties
将默认日志级别设置为“警告”。
要调整日志记录级别,请使用sc.setLogLevel(newLevel)。对于SparkR,使用setLogLevel(newLevel)。
回溯(最近一次呼叫最后一次):
文件“/opt/spark/python/pyspark/sql/utils.py”,第63行,deco格式
返回f(*a,**kw)
文件“/home/hduser/PycharmProjects/Assignment2/venv/lib/python3.6/site packages/py4j/protocol.py”,第328行,在get_return_值中
格式(目标id,“.”,名称),值)
py4j.protocol.Py4JJavaError:调用o28.toDF时出错。
:java.lang.IllegalArgumentException:需求失败:列数不匹配。
旧列名(1):\u c0
新列名(4):ownerid、houseid、zipcode、value
在scala.Predef$.require处(Predef.scala:224)
位于org.apache.spark.sql.Dataset.toDF(Dataset.scala:447)
在sun.reflect.NativeMethodAccessorImpl.invoke0(本机方法)处
位于sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
在sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)中
位于java.lang.reflect.Method.invoke(Method.java:498)
位于py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
位于py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
在py4j.Gateway.invoke处(Gateway.java:282)
位于py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
在py4j.commands.CallCommand.execute(CallCommand.java:79)
在py4j.GatewayConnection.run处(GatewayConnection.java:238)
运行(Thread.java:748)
在处理上述异常期间,发生了另一个异常:
回溯(最近一次呼叫最后一次):
文件“/home/hduser/PycharmProjects/HelloWorld/avg_value.py”,第15行,在
.toDF(*列)
文件“/opt/spark/python/pyspark/sql/dataframe.py”,第2055行,在toDF中
jdf=self.\u jdf.toDF(self.\u jseq(cols))
文件“/home/hduser/PycharmProjects/Assignment2/venv/lib/python3.6/site packages/py4j/java_gateway.py”,第1257行,in_ucall__
回答,self.gateway\u客户端,self.target\u id,self.name)
文件“/opt/spark/python/pyspark/sql/utils.py”,第79行,deco格式
引发IllegalArgumentException(s.split(“:”,1)[1],stackTrace)
pyspark.sql.utils.IllegalArgumentException:“要求失败:列数不匹配。\n旧列名(1):\u c0\n新列名(4):ownerid、houseid、zipcode、value”
进程已完成,退出代码为1*

我刚刚修改了一行代码&它现在可以正常工作了

df = spark.read \
 .format('csv') \
 .options(header='true').load('/home/hduser/Desktop/sample1/avg/input_avg.csv')
这似乎与你的问题有关。它与csv中需要处理的空值有关。请参阅以更好地处理您的案例。