pyspark.sql.functions.explode_outer#

pyspark.sql.functions.explode_outer(col)[source]#

Returns a new row for each element in the given array or map. Unlike explode, if the array/map is null or empty then null is produced. 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 2.3.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

colColumn or str: target column to work on.

Returns

Column: one row per array item or map key value.

Examples

>>> df = spark.createDataFrame(
...     [(1, ["foo", "bar"], {"x": 1.0}), (2, [], {}), (3, None, None)],
...     ("id", "an_array", "a_map")
... )
>>> df.select("id", "an_array", explode_outer("a_map")).show()
+---+----------+----+-----+
| id|  an_array| key|value|
+---+----------+----+-----+
|  1|[foo, bar]|   x|  1.0|
|  2|        []|NULL| NULL|
|  3|      NULL|NULL| NULL|
+---+----------+----+-----+

>>> df.select("id", "a_map", explode_outer("an_array")).show()
+---+----------+----+
| id|     a_map| col|
+---+----------+----+
|  1|{x -> 1.0}| foo|
|  1|{x -> 1.0}| bar|
|  2|        {}|NULL|
|  3|      NULL|NULL|
+---+----------+----+