How to Order Pyspark dataframe by list of columns ?

In this article, we are going to apply OrderBy with multiple columns over pyspark dataframe in Python. Ordering the rows means arranging the rows in ascending or descending order. 

Method 1: Using OrderBy()

OrderBy() function is used to sort an object by its index value.

Syntax: dataframe.orderBy([‘column1′,’column2′,’column n’], ascending=True).show()

where,

• dataframe is the dataframe name created from the nested lists using pyspark
• where columns are the list of columns
• ascending=True specifies order the dataframe in increasing order, ascending=Falsespecifies order the dataframe in decreasing order
• show() method id used to display the columns.

Let’s create a sample dataframe

Python3

# importing module
import pyspark

# importing sparksession from pyspark.sql module
from pyspark.sql import SparkSession

# creating sparksession and giving an app name
spark = SparkSession.builder.appName('sparkdf').getOrCreate()

# list  of students  data
data = [["1", "sravan", "vignan"], ["2", "ojaswi", "vvit"],
        ["3", "rohith", "vvit"], ["4", "sridevi", "vignan"],
        ["1", "sravan", "vignan"], ["5", "gnanesh", "iit"]]

# specify column names
columns = ['student ID', 'student NAME', 'college']

# creating a dataframe from the lists of data
dataframe = spark.createDataFrame(data, columns)

print("Actual data in dataframe")
# show dataframe
dataframe.show()

Output:

Applying OrderBy with multiple columns

Python3

# show dataframe by sorting the dataframe
# based on two columns in ascending
# order using orderby() function
dataframe.orderBy(['student ID', 'student NAME'],
                  ascending=True).show()

Output:

Python3

# show dataframe by sorting the dataframe
# based on two columns in descending
# order using orderby() function
dataframe.orderBy(['student ID', 'student NAME'],
                  ascending=False).show()

Output:

Method 2: Using sort()

It takes the Boolean value as an argument to sort in ascending or descending order.

 Syntax: dataframe.sort([‘column1′,’column2′,’column n’],ascending=True).show()

where,

1. dataframe is the dataframe name created from the nested lists using pyspark
2. where columns are the llst of columns
3. ascending=True specifies order the dataframe in increasing order,ascending=Falsespecifies order the dataframe in decreasing order
4. show() method id used to display the columns.

Python3

# show dataframe by sorting the dataframe
# based on two columns in descending order
dataframe.sort(['college', 'student NAME'], ascending=False).show()

Output: