pyspark.sql.tvf.TableValuedFunction.explode#

TableValuedFunction.explode(collection)[source]#

Returns a DataFrame containing a new row for each element in the given array or map. Uses the default column name col for elements in the array and key and value for elements in the map unless specified otherwise.

New in version 4.0.0.

Parameters

collectionColumn: Target column to work on.

Returns

DataFrame

See also

pyspark.sql.functions.explode()

Examples

Example 1: Exploding an array column

>>> import pyspark.sql.functions as sf
>>> spark.tvf.explode(sf.array(sf.lit(1), sf.lit(2), sf.lit(3))).show()
+---+
|col|
+---+
|  1|
|  2|
|  3|
+---+

Example 2: Exploding a map column

>>> import pyspark.sql.functions as sf
>>> spark.tvf.explode(
...     sf.create_map(sf.lit("a"), sf.lit("b"), sf.lit("c"), sf.lit("d"))
... ).show()
+---+-----+
|key|value|
+---+-----+
|  a|    b|
|  c|    d|
+---+-----+

Example 3: Exploding an array of struct column

>>> import pyspark.sql.functions as sf
>>> spark.tvf.explode(sf.array(
...     sf.named_struct(sf.lit("a"), sf.lit(1), sf.lit("b"), sf.lit(2)),
...     sf.named_struct(sf.lit("a"), sf.lit(3), sf.lit("b"), sf.lit(4))
... )).select("col.*").show()
+---+---+
|  a|  b|
+---+---+
|  1|  2|
|  3|  4|
+---+---+

Example 4: Exploding an empty array column

>>> import pyspark.sql.functions as sf
>>> spark.tvf.explode(sf.array()).show()
+---+
|col|
+---+
+---+

Example 5: Exploding an empty map column

>>> import pyspark.sql.functions as sf
>>> spark.tvf.explode(sf.create_map()).show()
+---+-----+
|key|value|
+---+-----+
+---+-----+