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What Results from Grouping Complaints by Location in Pig Scripts?
Grouping complaints by location in Hadoop Pig yields segmented reports of issues per city/region, driving targeted business fixes—crucial outcome for Hive & Pig certification’s Customer Complaint Analysis project.
Question
What outcome is expected from grouping complaints by location?
A. A report showing product sales by city
B. Segmented complaint reports showing issues per city or region
C. A single list of all complaints across India
D. Charts comparing online and offline payments
Answer
B. Segmented complaint reports showing issues per city or region
Explanation
Grouping complaints by location in the Customer Complaint Analysis project using Pig’s GROUP BY operation on location fields produces segmented reports that aggregate complaint counts, categories, and sentiment scores per city or region, revealing disproportionate issue prevalence like high delivery delays in specific areas or product defects concentrated in certain stores. This MapReduce-optimized grouping enables efficient computation of metrics such as top complaint types per location, average resolution time by region, and issue frequency trends, stored as output relations for subsequent Hive querying or visualization, empowering stakeholders to prioritize resource allocation, dispatch targeted quality audits, and implement location-specific remedies that address root causes rather than generic fixes.