collect_set

Collects the values from a column into a set, eliminating duplicates, and returns this set of objects. This function is non-deterministic as the order of collected results depends on the order of the rows, which may be non-deterministic after any shuffle operations.

Syntax

from pyspark.sql import functions as sf

sf.collect_set(col)

Parameters

Parameter	Type	Description
col	pyspark.sql.Column or column name	The target column on which the function is computed.

Returns

pyspark.sql.Column: A new Column object representing a set of collected values, duplicates excluded.

Examples

Example 1: Collect values from a DataFrame and sort the result in ascending order

from pyspark.sql import functions as sf
df = spark.createDataFrame([(1,), (2,), (2,)], ('value',))
df.select(sf.sort_array(sf.collect_set('value')).alias('sorted_set')).show()

+----------+
|sorted_set|
+----------+
|    [1, 2]|
+----------+

Example 2: Collect values from a DataFrame and sort the result in descending order

from pyspark.sql import functions as sf
df = spark.createDataFrame([(2,), (5,), (5,)], ('age',))
df.select(sf.sort_array(sf.collect_set('age'), asc=False).alias('sorted_set')).show()

+----------+
|sorted_set|
+----------+
|    [5, 2]|
+----------+

Example 3: Collect values from a DataFrame with multiple columns and sort the result

from pyspark.sql import functions as sf
df = spark.createDataFrame([(1, "John"), (2, "John"), (3, "Ana")], ("id", "name"))
df = df.groupBy("name").agg(sf.sort_array(sf.collect_set('id')).alias('sorted_set'))
df.orderBy(sf.desc("name")).show()

+----+----------+
|name|sorted_set|
+----+----------+
|John|    [1, 2]|
| Ana|       [3]|
+----+----------+