How to replace null values in Spark DataFrame

+1 vote

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I want to remove null values from a csv file. So tried the following things.

val df ="com.databricks.spark.csv").option("header", "true").load("/usr/local/spark/cars.csv")

After loading the file it looks like as shown below. Now, I want to remove null values.

So, I do this :"e",Seq("blank"))
But the null values didn't change.Can anyone help me?

May 31, 2018 in Apache Spark by kurt_cobain
• 9,390 points

edited Dec 15, 2020 by MD 74,744 views

8 answers to this question.

0 votes

This is basically very simple. You'll need to create a new DataFrame. I'm using the DataFrame df that you have defined earlier.

val newDf ="e",Seq("blank"))

DataFrames are immutable structures. Each time you perform a transformation which you need to store, you'll need to affect the transformed DataFrame to a new value.

You can even check out the details of a successful Spark developers with the Pyspark training course.

answered May 31, 2018 by nitinrawat895
• 11,380 points
0 votes
val map = Map("comment" -> "a", "blank" -> "a2")
answered Dec 10, 2018 by Sute
0 votes
df1 ="e",Seq("blank"));
answered Dec 10, 2018 by Shanti
0 votes
String[] colNames = {"NameOfColumn"}
dataframe ="ValueToBeFilled", colNames)
answered Dec 10, 2018 by Sada
0 votes
def isEvenOption(n: Integer): Option[Boolean] = {
  val num = Option(n).getOrElse(return None)
  Some(num % 2 == 0)

val isEvenOptionUdf = udf[Option[Boolean], Integer](isEvenOption)

Source: Dealing with null in Spark

answered Dec 10, 2018 by Mohan
For ,we have to use, drop()

drop() will remove all the null from the DF
0 votes

Hi i hope this will help for you.


val df ="com.databricks.spark.csv").option("nullValue","defaultvalue").option("header", "true").load("/usr/local/spark/cars.csv"

answered Feb 5, 2019 by Srinivasreddy
• 140 points
Is a closed parenthesis missing at the end of the command?
Sir, Can you please explain this code?
0 votes
in spark 2.x you can directly use df.dropna()  you can drop null from dataframe
answered Mar 29, 2020 by gaurav
0 votes


In Spark, fill() function of DataFrameNaFunctions class is used to replace NULL values on the DataFrame column with either zero(0), empty string, space, or any constant literal values.

//Replace all integer and long columns

//Replace with specific columns,Array("population"))
answered Dec 15, 2020 by MD
• 95,440 points

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