In this article, I will explain how to do PySpark join on multiple columns of DataFrames by using join() and SQL, and I will also explain how to eliminate duplicate columns after join. Joining on multiple columns required to perform multiple conditions using & and | operators. Advertisements ...
PySpark DataFrame has ajoin()operation which is used to combine fields from two or multiple DataFrames (by chaining join()), in this article, you will learn how to do aPySpark Join on Two or Multiple DataFramesby applying conditions on the same or different columns. also, you will learn ...
Fonctions filter where en PySpark | Conditions Multiples PySpark Check Column Exists in DataFrame PySpark Convert Dictionary/Map to Multiple Columns PySpark Join Two or Multiple DataFrames PySpark split() Column into Multiple Columns PySpark Where Filter Function | Multiple Conditions PySpark JSON Function...
Spark filter() or where() function filters the rows from DataFrame or Dataset based on the given one or multiple conditions. You can use where() operator