Introduction

In this tutorial, we will show you how to concatenate multiple string columns of a PySpark DataFrame into a single column. In order to do this, we will use the functions concat() and concat_ws() of PySpark.

Import Libraries

First, we import the following python modules:

from pyspark.sql import SparkSession
from pyspark.sql.functions import col, concat, concat_ws

Create SparkSession

Before we can work with Pyspark, we need to create a SparkSession. A SparkSession is the entry point into all functionalities of Spark.

In order to create a basic SparkSession programmatically, we use the following command:

spark = SparkSession \
    .builder \
    .appName("Python PySpark Example") \
    .getOrCreate()

Create PySpark DataFrame

Next, we create the PySpark DataFrame with some example data from a list. To do this, we use the method createDataFrame() and pass the data and the column names as arguments.

column_names = ["language", "framework", "users"]
data = [
    ("Python", "Django", 20000), 
    ("Python", "FastAPI", 9000), 
    ("Java", "Spring", 7000), 
    ("JavaScript", "ReactJS", 5000)
]
df = spark.createDataFrame(data, column_names)
df.show()

Concatenate String Columns

We want to concatenate the string columns "language" and "framework" of the PySpark DataFrame into a single column named "language_framework".

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