Explode¶

Overview¶

The Explode expression transforms an array or map into multiple rows, creating one row for each element in the input collection. Unlike PosExplode, it does not include positional information and focuses solely on extracting the values from the collection.

Syntax¶

SELECT explode(array_or_map_column) FROM table_name

df.select(explode(col("array_or_map_column")))

Arguments¶

Argument	Type	Description
child	Expression	The array or map expression to be exploded into multiple rows

Return Type¶

For arrays: Returns the element type of the input array
For maps: Returns a struct with key-value pairs

Supported Data Types¶

Array types (ArrayType) with any element type
Map types (MapType) with any key-value types

Algorithm¶

Inherits core explosion logic from ExplodeBase parent class
Sets position flag to false to exclude positional information from output
Processes each element in the input collection sequentially
Generates one output row per collection element
Uses copy-based child replacement for expression tree transformations

Partitioning Behavior¶

Does not preserve partitioning as it fundamentally changes row cardinality
May require shuffle operations when used in distributed computations
Output rows are distributed based on the partitioning of input rows containing the collections

Edge Cases¶

Null input collections result in no output rows (empty result)
Empty arrays or maps produce no output rows
Null elements within arrays are preserved as null values in output rows
Map entries with null keys or values are preserved in the output

Code Generation¶

Inherits code generation capabilities from the ExplodeBase parent class, supporting Tungsten code generation for optimized execution when possible.

Examples¶

-- Array explosion
SELECT explode(array(10, 20, 30)) AS value;
-- Result:
-- 10
-- 20
-- 30

-- Map explosion  
SELECT explode(map('a', 1, 'b', 2)) AS (key, value);
-- Result:
-- a  1
-- b  2

// Array explosion
val df = Seq(Array(1, 2, 3), Array(4, 5)).toDF("numbers")
df.select(explode(col("numbers"))).show()

// Map explosion
val mapDf = Seq(Map("x" -> 10, "y" -> 20)).toDF("pairs") 
mapDf.select(explode(col("pairs"))).show()