shuffle

Generates a random permutation of the given array. The shuffle function is non-deterministic, meaning the order of the output array can be different for each execution.

Syntax

Python

from pyspark.sql import functions as sf

sf.shuffle(col, seed=None)

Parameters

Parameter	Type	Description
col	pyspark.sql.Column or str	The name of the column or expression to be shuffled.
seed	pyspark.sql.Column or int, optional	Seed value for the random generator.

Returns

pyspark.sql.Column: A new column that contains an array of elements in random order.

Examples

Example 1: Shuffling a simple array

Python

import pyspark.sql.functions as sf
df = spark.sql("SELECT ARRAY(1, 20, 3, 5) AS data")
df.select("*", sf.shuffle(df.data, sf.lit(123))).show()

Output

+-------------+-------------+
|         data|shuffle(data)|
+-------------+-------------+
|[1, 20, 3, 5]|[5, 1, 20, 3]|
+-------------+-------------+

Example 2: Shuffling an array with null values

Python

import pyspark.sql.functions as sf
df = spark.sql("SELECT ARRAY(1, 20, NULL, 5) AS data")
df.select("*", sf.shuffle(sf.col("data"), 234)).show()

Output

+----------------+----------------+
|            data|   shuffle(data)|
+----------------+----------------+
|[1, 20, NULL, 5]|[NULL, 5, 20, 1]|
+----------------+----------------+

Example 3: Shuffling an array with duplicate values

Python

import pyspark.sql.functions as sf
df = spark.sql("SELECT ARRAY(1, 2, 2, 3, 3, 3) AS data")
df.select("*", sf.shuffle("data", 345)).show()

Output

+------------------+------------------+
|              data|     shuffle(data)|
+------------------+------------------+
|[1, 2, 2, 3, 3, 3]|[2, 3, 3, 1, 2, 3]|
+------------------+------------------+