Problem Statement: -

Find the first login date for each player. Return the result table in any order.

Dataframe API Solution: -

from pyspark.sql.types import *
from pyspark.sql.functions import *
from pyspark.sql.window import *

# Define the schema for the "Activity" 
activity_schema = StructType([ StructField("player_id", IntegerType(), True), 
                               StructField("device_id", IntegerType(), True), 
                               StructField("event_date", StringType(), True), 
                               StructField("games_played", IntegerType(), True) ])

# Define data for the "Activity" 
activity_data = [ (1, 2, '2016-03-01', 5), 
                  (1, 2, '2016-05-02', 6), 
                  (2, 3, '2017-06-25', 1), 
                  (3, 1, '2016-03-02', 0), 
                  (3, 4, '2018-07-03', 5) ]

df = spark.createDataFrame(activity_data,activity_schema)
df = df.withColumn("event_date",to_date("event_date","yyyy-MM-dd"))

df.show()
df.printSchema()

+---------+---------+----------+------------+
|player_id|device_id|event_date|games_played|
+---------+---------+----------+------------+
|        1|        2|2016-03-01|           5|
|        1|        2|2016-05-02|           6|
|        2|        3|2017-06-25|           1|
|        3|        1|2016-03-02|           0|
|        3|        4|2018-07-03|           5|
+---------+---------+----------+------------+

root
 |-- player_id: integer (nullable = true)
 |-- device_id: integer (nullable = true)
 |-- event_date: date (nullable = true)
 |-- games_played: integer (nullable = true)

window_spec = Window.partitionBy("player_id").orderBy(col("event_date"))

res_df = df.withColumn("first_login",first_value(col("event_date")).over(window_spec))

result_df = res_df.select("player_id","first_login").distinct()
result_df.show()

+---------+-----------+
|player_id|first_login|
+---------+-----------+
|        1| 2016-03-01|
|        2| 2017-06-25|
|        3| 2016-03-02|
+---------+-----------+

Spark SQL Solution: -

df.createOrReplaceTempView("Games")
result_df = spark.sql("""
SELECT DISTINCT
    player_id,
    first_value(event_date) OVER (PARTITION BY player_id ORDER BY event_date) AS First_login
FROM Games
""")

result_df.show()