PySpark pyspark.sql.types.ArrayType (ArrayType extends DataType class) is used to define an array data type column on DataFrame that holds the same type of elements, In this article, I will explain…
PySpark StructType & StructField classes are used to programmatically specify the schema to the DataFrame and creating complex columns like nested struct, array and map columns. StructType is a collection…
Problem: How to convert a DataFrame array to multiple columns in Spark? Solution: Spark doesn't have any predefined functions to convert the DataFrame array column to multiple columns however, we…
Spark Schema defines the structure of the DataFrame which you can get by calling printSchema() method on the DataFrame object. Spark SQL provides StructType & StructField classes to programmatically specify…
Problem: How to create a Spark DataFrame with Array of struct column using Spark and Scala? Using StructType and ArrayType classes we can create a DataFrame with Array of Struct…
Problem: How to define Spark DataFrame using the nested array column (Array of Array)? Solution: Using StructType we can define an Array of Array (Nested Array) ArrayType(ArrayType(StringType)) DataFrame column using…
Problem: How to explode & flatten nested array (Array of Array) DataFrame columns into rows using PySpark. Solution: PySpark explode function can be used to explode an Array of Array…
In this article, I will explain how to explode array or list and map columns to rows using different PySpark DataFrame functions (explode, explore_outer, posexplode, posexplode_outer) with Python example. Before…
Problem: How to flatten the Array of Array or Nested Array DataFrame column into a single array column using Spark. Solution: Spark SQL provides flatten function to convert an Array…
Problem: How to explode & flatten the Array of Array (Nested Array) DataFrame columns into rows using Spark. Solution: Spark explode function can be used to explode an Array of…