Pastaba.
Prieigai prie šio puslapio reikalingas įgaliojimas. Galite bandyti prisijungti arba pakeisti katalogus.
Prieigai prie šio puslapio reikalingas įgaliojimas. Galite bandyti pakeisti katalogus.
Computes the max value for each numeric column for each group.
Syntax
max(*cols)
Parameters
| Parameter | Type | Description |
|---|---|---|
cols |
str | Column names. Non-numeric columns are ignored. |
Returns
DataFrame
Examples
df = spark.createDataFrame([
(2, "Alice", 80), (3, "Alice", 100),
(5, "Bob", 120), (10, "Bob", 140)], ["age", "name", "height"])
# Group-by name, and calculate the max of the age in each group.
df.groupBy("name").max("age").sort("name").show()
# +-----+--------+
# | name|max(age)|
# +-----+--------+
# |Alice| 3|
# | Bob| 10|
# +-----+--------+
# Calculate the max of the age and height in all data.
df.groupBy().max("age", "height").show()
# +--------+-----------+
# |max(age)|max(height)|
# +--------+-----------+
# | 10| 140|
# +--------+-----------+