inline_outer
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.
Syntax
Python
from pyspark.sql import functions as sf
sf.inline_outer(col)
Parameters
Parameter | Type | Description |
|---|---|---|
|
| Input column of values to explode. |
Returns
pyspark.sql.Column: generator expression with the inline exploded result.
Examples
Python
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()
Output
root
|-- i: integer (nullable = false)
|-- s: array (nullable = true)
| |-- element: struct (containsNull = true)
| | |-- a: integer (nullable = false)
| | |-- b: integer (nullable = false)
Python
df.select('*', sf.inline_outer('s')).show(truncate=False)
Output
+---+----------------------+----+----+
|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|
+---+----------------------+----+----+