PySpark Joins Explained | Inner, Outer, Left, Right, Semi & Cross Joins in Databricks
In this video, we will explore how to join tables in PySpark using various join types — inner join, outer join, left outer, right outer, left semi, left anti, and cross join. We’ll also discuss how to handle duplicates and columns with same names between multiple tables in Databricks.
What you’ll learn:
Create sample tables and data frames in PySpark
Understand inner join and how it filters common records
Learn outer joins (full, left, right) with practical examples
Use left semi and left anti joins for data filtering
Perform cross joins to combine all rows between tables
Handle duplicate data using dropDuplicates() and distinct
Resolve same column name conflicts with renaming and aliasing
Compare join operations in PySpark vs Spark SQL
Join multiple tables in one PySpark statement
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