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When to use pyspark when otherwise in sql?


Asked by Olive Wang on Dec 10, 2021 SQL



PySpark When Otherwise – when () is a SQL function that returns a Column type and otherwise () is a function of Column, if otherwise () is not used, it returns a None/NULL value. PySpark SQL Case When – This is similar to SQL expression, Usage: CASE WHEN cond1 THEN result WHEN cond2 THEN result... ELSE result END.
Keeping this in consideration,
Any existing column in a DataFrame can be updated with the when function based on certain conditions needed. PySpark DataFrame uses SQL statements to work with the data. And WHEN is a SQL function used to restructure the DataFrame in spark.
Besides, In PySpark DataFrame, “when otherwise” is used derive a column or update an existing column based on some conditions from existing columns data. when () is a SQL function with a return type Column and other () is a function in sql.Column class.
Likewise,
In PySpark DataFrame use when ().otherwise () SQL functions to find out if a column has an empty value and use withColumn () transformation to replace a value of an existing column.
Also Know,
1 Using “ when otherwise ” on Spark D ataFrame. when is a Spark function, so to use it first we should import using import org.apache.spark.sql.functions.when before. ... 2 Using “ case when ” on Spark DataFrame. Similar to SQL syntax, we could use “case when” with expression expr () . ... 3 Using && and || operator