Скачать или смотреть 19. pyspark interview questions and answer - customer analysis

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🔥 Crack your next PySpark interview with confidence! In this video, we dive into recently asked PySpark interview questions focused on customer analysis. Learn how to work with large datasets, use PySpark transformations, and apply advanced analytical techniques to solve real-world problems. We'll cover:

customer first login
customer last login
customer total login
etc.

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script

from pyspark.sql import SparkSession
from pyspark.sql.types import StructType, StructField, StringType, TimestampType

schema = ["UserID", "UserName", "Login", "Logout"]

Sample data for users with multiple login/logout sessions
data = [
("U001", "Alice Johnson", "2024-12-15 08:30:00", "2024-12-15 09:30:00"),
("U001", "Alice Johnson", "2024-12-15 10:00:00", "2024-12-15 11:00:00"),
("U002", "Bob Smith", "2024-12-15 09:00:00", "2024-12-15 09:45:00"),
("U002", "Bob Smith", "2024-12-15 10:30:00", "2024-12-15 12:00:00"),
("U002", "Bob Smith", "2024-12-15 13:00:00", "2024-12-15 14:00:00"),
("U003", "Charlie Brown", "2024-12-15 08:45:00", None),
("U003", "Charlie Brown", "2024-12-15 14:00:00", "2024-12-15 15:30:00"),
("U004", "Diana Prince", "2024-12-15 10:00:00", "2024-12-15 11:30:00"),
("U004", "Diana Prince", "2024-12-15 12:00:00", None)
]

df=spark.createDataFrame(data,schema)
df.show()
df.printSchema()

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what we have covered in this video:


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Hope you liked this video and learned something new :)
See you in next video, until then Bye-Bye!

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