Broadcast Join vs Shuffle Hash Join Explained | PySpark Join Strategies in Databricks

In this video, we will understand how joins happen internally in PySpark and Spark. You’ll learn about the two main join strategies — Broadcast Join and Shuffle Hash Join, how Spark decides which one to use, and how you can control this behavior in Databricks using configuration settings and hints. What you’ll learn: Internal working of Spark joins What is Broadcast Join and how it avoids data shuffling How Shuffle Hash Join works when both datasets are large Performance comparison: Broadcast Join vs Shuffle Join Understanding data shuffling in Spark Configure autoBroadcastJoinThreshold for custom tuning Use spark.conf.set to adjust join size limits Identify join type using explain() in PySpark Use broadcast hints in PySpark and SQL Learn how Databricks Photon Engine optimizes joins #pyspark #pysparktutorial #databricks #databrickstutorial