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Why Use Dynamic City Parameters for Flexible Complaint Analysis?
User-defined location input in Hadoop Pig scripts enables dynamic city filtering for complaint analysis, enhancing flexibility without code changes—essential for Hive & Pig certification projects targeting location-specific insights.
Question
How does user-defined location input enhance analysis flexibility?
A. It deletes old location data before each analysis
B. It lets users dynamically specify any city for filtering complaints
C. It automatically generates a Hive table for each city
D. It limits the user to predefined city names
Answer
B. It lets users dynamically specify any city for filtering complaints
Explanation
User-defined location input enhances analysis flexibility in the Customer Complaint project by allowing interactive specification of any city or region during Pig script execution, enabling dynamic filtering of massive complaint datasets without code modifications or predefined parameters hardcoded into scripts. This parameter passing via command line arguments (e.g., pig -param city=KL complaints_analysis.pig) or parameters files injects runtime values into Pig Latin LOAD, FILTER, GROUP, and FOREACH operations, supporting ad-hoc queries like “complaints in Cyberjaya last month” or “top issues in Selangor stores,” which accelerates iterative analysis, accommodates varying business questions, and leverages Hadoop’s scalability for location-specific insights across petabytes of retail data.