Departmental Salary Insights: with SQL and PySpark
Departmental Salary Insights: with SQL and PySpark Description: This article dives into the SQL and PySpark methodologies to identify employees who earn more than the average salary within their respective departments. INPUT: SQL QUERY: SELECT Name, Salary FROM ( SELECT Name, Salary, AVG (Salary) OVER ( PARTITION BY Department) AS avg_sal FROM Employee ) AS department_salaries WHERE Salary > avg_sal; PYSPARK QUERY: from pyspark.sql import SparkSession from pyspark.sql.window import Window as w from pyspark.sql.functions import avg, col from pyspark.sql.types import StructType, StructField, StringType, DoubleType # Define the schema for the DataFrame schema = StructType([ StructField( "EmpID" , StringType(), True ), StructField( "Name" , StringType(), True ), StructField( "Department" , StringType(), True ), StructField( "Salary" , DoubleType(), True ) ]) # Initialize a Spark session spark = SparkSessio...