Performing aggregations with Apache Spark

In this recipe, we will discuss how to perform aggregations on DataFrames in Apache Spark. We will use Python as our primary programming language and the PySpark API and go over the various techniques for aggregating your data in Apache Spark.

How to do it...

1. Import the libraries: Import the required libraries and create a SparkSession object:

   from pyspark.sql import SparkSession

   from pyspark.sql.functions import col, max, count, min, approx_count_distinct

   from pyspark.sql.types import StructType, StructField, StringType, IntegerType, DateType

   spark = (SparkSession.builder

       .appName("perform-aagregations")

       .master("spark://spark-master:7077")

       .config("spark.executor.memory", "512m")

       .getOrCreate())

   spark.sparkContext.setLogLevel("ERROR")

2. Read file: Read the netfix_titles.csv file using the read...