无法解析...给定的输入列 [英] can't resolve ... given input columns

问题描述

我正在阅读O'Reilly的 Spark:The Definitive Guide 一书，尝试执行简单的DataFrame操作时遇到错误.

I'm going through the Spark: The Definitive Guide book from O'Reilly and I'm running into an error when I try to do a simple DataFrame operation.

数据类似于:

DEST_COUNTRY_NAME,ORIGIN_COUNTRY_NAME,count
United States,Romania,15
United States,Croatia,1
...

然后我用(在Pyspark中)阅读它:

I then read it with (in Pyspark):

flightData2015 = spark.read.option("inferSchema", "true").option("header","true").csv("./data/flight-data/csv/2015-summary.csv")

然后我尝试运行以下命令:

Then I try to run the following command:

flightData2015.select(max("count")).take(1)

我收到以下错误:

pyspark.sql.utils.AnalysisException: "cannot resolve '`u`' given input columns: [DEST_COUNTRY_NAME, ORIGIN_COUNTRY_NAME, count];;
'Project ['u]
+- AnalysisBarrier
      +- Relation[DEST_COUNTRY_NAME#10,ORIGIN_COUNTRY_NAME#11,count#12] csv"

我什至不知道"u"的来源，因为它不在我的代码中，也不在数据文件头中.我阅读了另一条建议，认为这可能是由标头中的空格引起的，但这不适用于此处.知道尝试什么吗?

I don't know where "u" is even coming from, since it's not in my code and it isn't in the data file header either. I read another suggestion that this could be caused by spaces in the header, but that's not applicable here. Any idea what to try?

注意:奇怪的是，当我使用SQL而不是DataFrame转换时，同样的事情也起作用.这有效:

NOTE: The strange thing is, the same thing works when I use SQL instead of the DataFrame transformations. This works:

flightData2015.createOrReplaceTempView("flight_data_2015")
spark.sql("SELECT max(count) from flight_data_2015").take(1)

我还可以执行以下操作，并且效果很好:

I can also do the following and it works fine:

flightData2015.show()

推荐答案

您的问题是您正在调用内置的max函数，而不是

Your issue is that you are calling the built-in max function, not pyspark.sql.functions.max.

当python在代码中评估max("count")时，它返回字母'u'，这是组成字符串的字母集合中的最大值.

When python evaluates max("count") in your code it returns the letter 'u', which is the maximum value in the collection of letters that make up the string.

print(max("count"))
#'u'

尝试以下方法:

import pyspark.sql.functions as f
flightData2015.select(f.max("count")).show()

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