pyspark.sql.functions.inline_outer#

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

Explodes an array of structs into a table. Unlike inline, if the array is null or empty then null is produced for each nested column.

Added in version 3.4.0.

Parameters:

colColumn or column name: input column of values to explode.

Returns:

Column: generator expression with the inline exploded result.

See also

pyspark.sql.functions.explode()
pyspark.sql.functions.explode_outer()
pyspark.sql.functions.posexplode()
pyspark.sql.functions.posexplode_outer()
pyspark.sql.functions.inline()

Notes

Supports Spark Connect.

Examples

>>> from pyspark.sql import functions as sf
>>> df = spark.sql('SELECT * FROM VALUES (1,ARRAY(NAMED_STRUCT("a",1,"b",2), NULL, NAMED_STRUCT("a",3,"b",4))), (2,ARRAY()), (3,NULL) AS t(i,s)')
>>> df.printSchema()
root
 |-- i: integer (nullable = false)
 |-- s: array (nullable = true)
 |    |-- element: struct (containsNull = true)
 |    |    |-- a: integer (nullable = false)
 |    |    |-- b: integer (nullable = false)

>>> df.select('*', sf.inline_outer('s')).show(truncate=False)
+---+----------------------+----+----+
|i  |s                     |a   |b   |
+---+----------------------+----+----+
|1  |[{1, 2}, NULL, {3, 4}]|1   |2   |
|1  |[{1, 2}, NULL, {3, 4}]|NULL|NULL|
|1  |[{1, 2}, NULL, {3, 4}]|3   |4   |
|2  |[]                    |NULL|NULL|
|3  |NULL                  |NULL|NULL|
+---+----------------------+----+----+