Table of Contents
Why Use Dynamic Location Parameters in Pig Complaint Scripts?
User-defined location input in Hadoop Pig scripts enables custom city filtering of complaint data, supporting flexible location-based insights without code changes—vital for Hive & Pig certification’s dynamic analysis capabilities.
Question
How does user-defined location input improve the analysis?
A. It enables custom filtering of complaint data by user-specified city
B. It exports the filtered data into SQL
C. It generates visual dashboards automatically
D. It limits users to fixed city lists
Answer
A. It enables custom filtering of complaint data by user-specified city
Explanation
User-defined location input improves analysis in the Customer Complaint project by allowing dynamic specification of any city through Pig script parameters (e.g., pig -param city=KualaLumpur complaints.pig), injecting runtime values into FILTER operations on location fields within massive HDFS datasets without requiring script modifications or recompilation. This flexibility supports ad-hoc business queries like isolating complaints from Cyberjaya stores or comparing Selangor vs. Johor Bahru issue patterns, accelerating iterative exploration while leveraging Pig’s automatic MapReduce parallelization for scalable processing of filtered complaint records grouped by issue category and timestamp. The approach enhances decision-making by delivering location-specific insights on-demand, complementing Hive’s structured querying for comprehensive geospatial complaint analytics in Hadoop certification workflows.