countDistinct

Returns a new Column for distinct count of col or cols. Supports Spark Connect.

An alias of count_distinct, and it is encouraged to use count_distinct directly.

Syntax

Python

from pyspark.databricks.sql import functions as dbf

dbf.countDistinct(col=<col>, *cols)

Parameters

Parameter	Type	Description
col	pyspark.sql.Column or column name	First column to compute on.
cols	pyspark.sql.Column or column name	Other columns to compute on.

Examples

Python

from pyspark.databricks.sql import functions as dbf
df = spark.createDataFrame([(1,), (1,), (3,)], ["value"])
df.select(dbf.count_distinct(df.value)).show()

Output

+---------------------+
|count(DISTINCT value)|
+---------------------+
|                    2|
+---------------------+

Python

from pyspark.databricks.sql import functions as dbf
df = spark.createDataFrame([(1,), (1,), (3,)], ["value"])
df.select(dbf.countDistinct(df.value)).show()

Output

+---------------------+
|count(DISTINCT value)|
+---------------------+
|                    2|
+---------------------+