Different Types of “Join Strategies” in “Apache Spark”

<h1>What is “Join Selection Strategy”?</h1> <ul> <li>When “Any Type” of “Join”, like the “Left Join”, or, the “Inner Join” is “Performed” between “Two DataFrames”, “Apache Spark” “Internally” decides which “Algorithm” will be used to “Perform” the “Join” Operations between the “Two DataFrames”.</li> <li>That particular “Algorithm” that is “Responsible” for “Planning” the “Join” Operation between the “Two DataFrames”, is called as the “Join Selection Strategy”.</li> </ul> <h1>Why Learning About “Join Selection Strategies” is Important?</h1> <ul> <li>To “Optimize” a “Spark Job” that “Involves” a “Lot of Joins”, the “Developers” need to be very much aware about the “Internal Algorithm” that “Apache Spark” will “Choose” to “Perform” “Any” of the “Join” Operations between “Two DataFrames”.</li> <li>The “Developers” need to know about the “Join Selection Strategies” so that the “Wrong Join Selection Strategy” is “Not Used” in the “Join” Operation between “Two DataFrames”.</li> <li>An “Incorrect Join Selection Strategy” will “Increase” the “Execition Time” of the “Join” Operation, and, the “Join” Operation becomes a “Heavy Operation” on the “Executors” as well.</li> </ul> <a href="https://oindrila-chakraborty88.medium.com/different-types-of-join-strategies-in-apache-spark-5c0066999d0d">Learn More</a>