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Showing posts with the label hadoop-2x-vs-3x

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Python Set Operations Explained: From Theory to Real-Time Applications

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A  set  in Python is an unordered collection of unique elements. It is useful when storing distinct values and performing operations like union, intersection, or difference. Real-Time Example: Removing Duplicate Customer Emails in a Marketing Campaign Imagine you are working on an email marketing campaign for your company. You have a list of customer emails, but some are duplicated. Using a set , you can remove duplicates efficiently before sending emails. Code Example: # List of customer emails (some duplicates) customer_emails = [ "alice@example.com" , "bob@example.com" , "charlie@example.com" , "alice@example.com" , "david@example.com" , "bob@example.com" ] # Convert list to a set to remove duplicates unique_emails = set (customer_emails) # Convert back to a list (if needed) unique_email_list = list (unique_emails) # Print the unique emails print ( "Unique customer emails:" , unique_email_list) Ou...

Hadoop 2x vs 3x top differences

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In many interviews, the first question for Hadoop developers is what are the differences between Hadoop 2 and 3. You already know that Hadoop upgraded from version 1. The below list is useful to know the differences. I have given Hadoop details in the form of questions and answers so that beginners can understand. Hadoop 2.x Vs 3.x The major change in hadoop 3 is no storage overhead. So, you may be curious about how Hadoop 3 is managing storage. My plan is for you is first to go through the list of differences and check the references section, to learn more about Hadoop storage management. References Real story of storage management in Hadoop Follow me on twitter Applyanalytics