PySpark – Spark Application Lifecycle Overview Table Of Contents: Spark Application Starts Driver Program Is Launched Cluster Manager Allocates Resources Job is Created on Action DAG Scheduler Breaks Job into Stages Tasks are Sent to Executors Results Returned to Driver SparkContext Stops / Application Ends (1) Spark Application Start from pyspark.sql import SparkSession spark = SparkSession.builder.appName("MyApp").getOrCreate() We need to first initialize a Spark application to enable distributed data processing with Apache Spark. you are initializing a Spark application. This is the entry point for using Spark. (2) Driver Program Is Launched from pyspark.sql import SparkSession # This runs on the

Read More