用 Spark Dataframe 中的空值替换空值 [英] Replace Empty values with nulls in Spark Dataframe

问题描述

我有一个包含 n 列的数据框，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" );

它们都不起作用.

任何线索将不胜感激.谢谢.

Any leads would be highly appreciated. Thanks.

推荐答案

您的第一种方法由于一个错误而失败，该错误阻止了 replace 能够用空值替换值，请参阅 这里.

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 指令混淆:您的 if-else 表达式将在 驱动程序 上被评估一次(而不是每条记录)；你想用对 when 函数的调用来替换它；此外，要比较列的值，您需要使用 === 运算符，而不是 Scala 的 == ，它只是比较驱动程序端的 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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