Fidning max/min value of a list in pyspark

Question

I know this is a very trivial question, and I am quite surprised I could not find an answer on the internet, but can one find the max or min value o a list in pyspark? In Python it is easily done by

max(list)

However, when I try the same in pyspark I get the following error:

An error was encountered:
An error occurred while calling z:org.apache.spark.sql.functions.max. Trace:
py4j.Py4JException: Method max([class java.util.ArrayList]) does not exist
    at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:318)
    at py4j.reflection.ReflectionEngine.getMethod(ReflectionEngine.java:339)
    at py4j.Gateway.invoke(Gateway.java:276)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:238)
    at java.lang.Thread.run(Thread.java:748)

Any ideas as to what I am doing wrong?

UPDATE: Adding what exactly I did: This is my list:

cur_datelist

Output:

['2020-06-10', '2020-06-11', '2020-06-12', '2020-06-13', '2020-06-14', '2020-06-15', '2020-06-16', '2020-06-17', '2020-06-18', '2020-06-19', '2020-06-20', '2020-06-21', '2020-06-22', '2020-06-23', '2020-06-24', '2020-06-25', '2020-06-26', '2020-06-27', '2020-06-28', '2020-06-29', '2020-06-30', '2020-07-01', '2020-07-02', '2020-07-03', '2020-07-04', '2020-07-05', '2020-07-06', '2020-07-07', '2020-07-08', '2020-07-09', '2020-07-10', '2020-07-11', '2020-07-12', '2020-07-13', '2020-07-14', '2020-07-15', '2020-07-16', '2020-07-17', '2020-07-18', '2020-07-19', '2020-07-20', '2020-07-21', '2020-07-22', '2020-07-23', '2020-07-24', '2020-07-25', '2020-07-26', '2020-07-27', '2020-07-28', '2020-07-29', '2020-07-30', '2020-07-31', '2020-08-01', '2020-08-02', '2020-08-03', '2020-08-04', '2020-08-05', '2020-08-06', '2020-08-07', '2020-08-08', '2020-08-09', '2020-08-10', '2020-08-11', '2020-08-12', '2020-08-13', '2020-08-14', '2020-08-15', '2020-08-16', '2020-08-17', '2020-08-18', '2020-08-19', '2020-08-20', '2020-08-21', '2020-08-22', '2020-08-23', '2020-08-24', '2020-08-25', '2020-08-26', '2020-08-27', '2020-08-28', '2020-08-29', '2020-08-30', '2020-08-31']

The class is 'list': type(cur_datelist)

<class 'list'>

I assumed that to be a normal pythonic list. So when I tried max(cur_datelist), I get the above mentioned error.

Answer 1

It is not different between pyspark and python for the list but the column is difference. This is the result of my pyspark.

# just a list
l = [1, 2, 3]
print(max(l))

# 3

# dataframe with the array column
df = spark.createDataFrame([(1, [1, 2, 3]), (2, [4, 5, 6])]).toDF('id', 'list')

import pyspark.sql.functions as f

df.withColumn('max', f.array_max(f.col('list'))).show()

#+---+---------+---+
#| id|     list|max|
#+---+---------+---+
#|  1|[1, 2, 3]|  3|
#|  2|[4, 5, 6]|  6|
#+---+---------+---+

Your error comes from the max function overlap between the python native one and the spark column function! To avoid this, specify your pyspark function. Then max denotes the python original.

import pyspark.sql.functions as f

l = ['2020-06-10', '2020-06-11', '2020-06-12', '2020-06-13', '2020-06-14', '2020-06-15', '2020-06-16', '2020-06-17', '2020-06-18', '2020-06-19', '2020-06-20', '2020-06-21', '2020-06-22', '2020-06-23', '2020-06-24', '2020-06-25', '2020-06-26', '2020-06-27', '2020-06-28', '2020-06-29', '2020-06-30', '2020-07-01', '2020-07-02', '2020-07-03', '2020-07-04', '2020-07-05', '2020-07-06', '2020-07-07', '2020-07-08', '2020-07-09', '2020-07-10', '2020-07-11', '2020-07-12', '2020-07-13', '2020-07-14', '2020-07-15', '2020-07-16', '2020-07-17', '2020-07-18', '2020-07-19', '2020-07-20', '2020-07-21', '2020-07-22', '2020-07-23', '2020-07-24', '2020-07-25', '2020-07-26', '2020-07-27', '2020-07-28', '2020-07-29', '2020-07-30', '2020-07-31', '2020-08-01', '2020-08-02', '2020-08-03', '2020-08-04', '2020-08-05', '2020-08-06', '2020-08-07', '2020-08-08', '2020-08-09', '2020-08-10', '2020-08-11', '2020-08-12', '2020-08-13', '2020-08-14', '2020-08-15', '2020-08-16', '2020-08-17', '2020-08-18', '2020-08-19', '2020-08-20', '2020-08-21', '2020-08-22', '2020-08-23', '2020-08-24', '2020-08-25', '2020-08-26', '2020-08-27', '2020-08-28', '2020-08-29', '2020-08-30', '2020-08-31']
print(max(l))

# 2020-08-31

Or,

import builtins as p

print(p.max(l))
# 2020-08-31