Getting Execution Plans In Spark

Anubhav Tarar shows how to get an execution plan for a Spark job:

There are three types of logical plans:

  1. Parsed logical plan.
  2. Analyzed logical plan.
  3. Optimized logical plan.

Analyzed logical plans go through a series of rules to resolve. Then, the optimized logical plan is produced. The optimized logical plan normally allows Spark to plug in a set of optimization rules. You can plug in your own rules for the optimized logical plan.

Click through for the details.

Related Posts

From pandas to Spark with koalas

Achilleus tries out Koalas: Python is widely used programming language when it comes to Data science workloads and Python has way too many different libraries to back this fact. Most of the data scientists are familiar with Python and pandas mostly. But the main issue with Pandas is it works great for small and medium […]

Read More

Choosing Between Merge Join and Hash Join

Erik Darling gives us a Sophie’s Choice: It could have chosen a Hash Join, but then the order of the Id column from the Posts table wouldn’t have been preserved on the other side. Merge Joins are order preserving, Hash Joins aren’t. If we use a Hash Join, we’re looking at ordering the results of […]

Read More

Categories