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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...
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Big Data:Top Hadoop Interview Questions (2 of 5)

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Frequently asked Hadoop interview questions.


1. What is Hadoop?Hadoop is a framework that allows users the power of distributed computing.

2.What is the difference between SQL and Hadoop?

SQL is allowed to work with structured data. But SQL is most suitable for legacy technologies. Hadoop is suitable for unstructured data. And, it is well suited for modern technologis.
Hadoop

3. What is Hadoop framework?

It is distributed network of commodity servers(A server can contain multiple clusters, and a cluster can have multiple nodes)

4. What are 4 properties of Hadoop?

Accessible-Hadoop runs on large clusters of commodity machinesRobust-An assumption that low commodity machines cause many machine failures. But it handles these tactfully. Scalable-Hadoop scales linearly to handle larger data by adding more nodes to the cluster. Simple-Hadoop allows users to quickly write efficient parallel code

5. What kind of data Hadoop needs?

Traditional RDBMS having relational structure with data resides in tables. In Hadoop. data should be in Key,Value pair.

6. Is Hadoop suitable for on the fly processing?

Hadoop is not suitable. It is suitable only for off-line processing. That means, we can not use Hadoop on active web logs. We can use it on web logs data,which already generated. So, in this property Hadoop is matching to traditional data warehouses.

7. What is Map reduce?

Map reduce is a data processing model, which contain mappers, and reducers. It takes unstructred data as input, and create as Key,Value pairs for processing on Hadoop.

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