Pyspark replace strings in Spark dataframe column

Question

I\'d like to perform some basic stemming on a Spark Dataframe column by replacing substrings. What\'s the quickest way to do this?

In my current use case, I have a

Answer 1

For Spark 1.5 or later, you can use the functions package:

from pyspark.sql.functions import *
newDf = df.withColumn('address', regexp_replace('address', 'lane', 'ln'))

Quick explanation:

• The function withColumn is called to add (or replace, if the name exists) a column to the data frame.
• The function regexp_replace will generate a new column by replacing all substrings that match the pattern.