pyspark.sql.functions.array_distinct

pyspark.sql.functions.array_distinct(col)

Array function: removes duplicate values from the array.

New in version 2.4.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

colColumn or str

name of column or expression

Returns

Column

A new column that is an array of unique values from the input column.

Examples

Example 1: Removing duplicate values from a simple array

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([([1, 2, 3, 2],)], ['data'])
>>> df.select(sf.array_distinct(df.data)).show()
+--------------------+
|array_distinct(data)|
+--------------------+
|           [1, 2, 3]|
+--------------------+

Example 2: Removing duplicate values from multiple arrays

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([([1, 2, 3, 2],), ([4, 5, 5, 4],)], ['data'])
>>> df.select(sf.array_distinct(df.data)).show()
+--------------------+
|array_distinct(data)|
+--------------------+
|           [1, 2, 3]|
|              [4, 5]|
+--------------------+

Example 3: Removing duplicate values from an array with all identical values

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([([1, 1, 1],)], ['data'])
>>> df.select(sf.array_distinct(df.data)).show()
+--------------------+
|array_distinct(data)|
+--------------------+
|                 [1]|
+--------------------+

Example 4: Removing duplicate values from an array with no duplicate values

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([([1, 2, 3],)], ['data'])
>>> df.select(sf.array_distinct(df.data)).show()
+--------------------+
|array_distinct(data)|
+--------------------+
|           [1, 2, 3]|
+--------------------+

Example 5: Removing duplicate values from an empty array

>>> from pyspark.sql import functions as sf
>>> from pyspark.sql.types import ArrayType, IntegerType, StructType, StructField
>>> schema = StructType([
...   StructField("data", ArrayType(IntegerType()), True)
... ])
>>> df = spark.createDataFrame([([],)], schema)
>>> df.select(sf.array_distinct(df.data)).show()
+--------------------+
|array_distinct(data)|
+--------------------+
|                  []|
+--------------------+