在Spark Dataframe中将空值替换为空 [英] Replace Empty values with nulls in Spark Dataframe
问题描述
我有一个n列数的数据框,我想用空值替换所有这些列中的空字符串.
I have a data frame with n number of columns and I want to replace empty strings in all these columns with nulls.
我尝试使用
val ReadDf = rawDF.na.replace("columnA", Map( "" -> null));
和
val ReadDf = rawDF.withColumn("columnA", if($"columnA"=="") lit(null) else $"columnA" );
他们两个都不起作用.
任何潜在客户都将受到高度赞赏.谢谢.
Any leads would be highly appreciated. Thanks.
推荐答案
由于错误导致replace
不能用null替换值的错误,您的第一种方法接缝失败,请参见
Your first approach seams to fail due to a bug that prevents replace
from being able to replace values with nulls, see here.
您的第二种方法失败了,因为您将驱动程序端Scala代码与执行程序端Dataframe指令相混淆:您的if-else表达式将在驱动程序上进行一次一次求值(而不是按记录);您想用对when
函数的调用来代替它;此外,要比较列的值,您需要使用===
运算符,而不是Scala的==
,后者只是比较驱动程序端Column
对象:
Your second approach fails because you're confusing driver-side Scala code for executor-side Dataframe instructions: your if-else expression would be evaluated once on the driver (and not per record); You'd want to replace it with a call to when
function; Moreover, to compare a column's value you need to use the ===
operator, and not Scala's ==
which just compares the driver-side Column
object:
import org.apache.spark.sql.functions._
rawDF.withColumn("columnA", when($"columnA" === "", lit(null)).otherwise($"columnA"))
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