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PySpark SQL Functions | max method

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PySpark SQL Functions
schedule Jul 1, 2022
Last updated
local_offer PySpark
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PySpark SQL Functions' max(~) method returns the maximum value in the specified column.

Parameters

1. col | string or Column

The column in which to obtain the maximum value.

Return Value

A PySpark Column (pyspark.sql.column.Column).

Examples

Consider the following PySpark DataFrame:

df = spark.createDataFrame([["Alex", 25], ["Bob", 30]], ["name", "age"])
df.show()
+----+---+
|name|age|
+----+---+
|Alex| 25|
| Bob| 30|
+----+---+

Getting the maximum value of a PySpark column

To obtain the maximum age:

import pyspark.sql.functions as F
df.select(F.max("age")).show()
+--------+
|max(age)|
+--------+
| 30|
+--------+

To obtain the maximum age as an integer:

list_rows = df.select(F.max("age")).collect()
list_rows[0][0]
30

Here, the collect() method returns a list of Row objects, which in this case is length one because the PySpark DataFrame returned by select(~) only has one row. The content of the Row object can be accessed via [0].

Getting the maximum value of each group in PySpark

Consider the following PySpark DataFrame:

df = spark.createDataFrame([["Alex", 20, "A"],\
["Bob", 30, "B"],\
["Cathy", 50, "A"]],
["name", "age", "class"])
df.show()
+-----+---+-----+
| name|age|class|
+-----+---+-----+
| Alex| 20| A|
| Bob| 30| B|
|Cathy| 50| A|
+-----+---+-----+

To get the maximum age of each class:

df.groupby("class").agg(F.max("age").alias("MAX AGE")).show()
+-----+-------+
|class|MAX AGE|
+-----+-------+
| A| 50|
| B| 30|
+-----+-------+

Here, we are using the alias(~) method to assign a label to the aggregated age column.

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Published by Isshin Inada
Edited by 0 others
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