transform

Returns an array of elements after applying a transformation to each element in the input array. Supports Spark Connect.

For the corresponding Databricks SQL function, see transform function.

Syntax

Python

from pyspark.databricks.sql import functions as dbf

dbf.transform(col=<col>, f=<f>)

Parameters

Parameter	Type	Description
col	pyspark.sql.Column or str	Name of column or expression.
f	function	A function that is applied to each element of the input array. Can take one of the following forms: Unary (x: Column) -> Column or Binary (x: Column, i: Column) -> Column where the second argument is a 0-based index of the element.

Returns

pyspark.sql.Column: a new array of transformed elements.

Examples

Example 1: Transform array elements with a simple function

Python

from pyspark.databricks.sql import functions as dbf
df = spark.createDataFrame([(1, [1, 2, 3, 4])], ("key", "values"))
df.select(dbf.transform("values", lambda x: x * 2).alias("doubled")).show()

Output

+------------+
|     doubled|
+------------+
|[2, 4, 6, 8]|
+------------+

Example 2: Transform array elements using index

Python

from pyspark.databricks.sql import functions as dbf
df = spark.createDataFrame([(1, [1, 2, 3, 4])], ("key", "values"))
def alternate(x, i):
    return dbf.when(i % 2 == 0, x).otherwise(-x)
df.select(dbf.transform("values", alternate).alias("alternated")).show()

Output

+--------------+
|    alternated|
+--------------+
|[1, -2, 3, -4]|
+--------------+