ValueError：无法将列转换为布尔

Question

我正在尝试在数据框上建立一个新列，如下所示：

l = [(2, 1), (1,1)]
df = spark.createDataFrame(l)

def calc_dif(x,y):
    if (x>y) and (x==1):
        return x-y

dfNew = df.withColumn("calc", calc_dif(df["_1"], df["_2"]))
dfNew.show()

但是，我得到：

Traceback (most recent call last):
  File "/tmp/zeppelin_pyspark-2807412651452069487.py", line 346, in <module>
Exception: Traceback (most recent call last):
  File "/tmp/zeppelin_pyspark-2807412651452069487.py", line 334, in <module>
  File "<stdin>", line 38, in <module>
  File "<stdin>", line 36, in calc_dif
  File "/usr/hdp/current/spark2-client/python/pyspark/sql/column.py", line 426, in __nonzero__
    raise ValueError("Cannot convert column into bool: please use '&' for 'and', '|' for 'or', "
ValueError: Cannot convert column into bool: please use '&' for 'and', '|' for 'or', '~' for 'not' when building DataFrame boolean expressions.

为什么会发生？我该如何解决？

Answer 1

可以使用udf：

from pyspark.sql.functions import udf

@udf("integer")
def calc_dif(x,y):
    if (x>y) and (x==1):
        return x-y

或情况（推荐）

from pyspark.sql.functions import when

def calc_dif(x,y):
    when(( x > y) & (x == 1), x - y)

第一个在Python对象上计算，第二个在Spark上计算 Columns

Answer 2

这是在抱怨，因为您为 calc_dif 函数提供了整个列对象，而不是相应行的实际数据。您需要使用 audf来包装您的calc_dif功能：

from pyspark.sql.types import IntegerType
from pyspark.sql.functions import udf

l = [(2, 1), (1,1)]
df = spark.createDataFrame(l)

def calc_dif(x,y):
    # using the udf the calc_dif is called for every row in the dataframe
    # x and y are the values of the two columns 
    if (x>y) and (x==1):
        return x-y

udf_calc = udf(calc_dif, IntegerType())

dfNew = df.withColumn("calc", udf_calc("_1", "_2"))
dfNew.show()

# since x < y calc_dif returns None
+---+---+----+
| _1| _2|calc|
+---+---+----+
|  2|  1|null|
|  1|  1|null|
+---+---+----+

Answer 3

对于遇到相同错误消息的任何人，请检查括号。有时布尔表达式需要更具体的表达式，例如；

DF_New= 
df1.withColumn('EventStatus',\
                  F.when(((F.col("Adjusted_Timestamp")) <\
                          (F.col("Event_Finish"))) &\
                         ((F.col("Adjusted_Timestamp"))>\ 
                           F.col("Event_Start"))),1).otherwise(0))