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Home/Questions/SQL/Your Kafka consumer shows significant lag during peak hours. What strategies would you employ to reduce lag and ensure timely data processing?

Your Kafka consumer shows significant lag during peak hours. What strategies would you employ to reduce lag and ensure timely data processing?

SQLmedium0.4 min readPremium
Frequency
Low
Asked at 1 company
Category
487
questions in SQL
Difficulty Split
130E|271M|86H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Dunnhumby
Key Concepts Tested
partition
Expert AnswerPremium
76 wordsInterview-ready
**Strategies**: (1) Scale consumers—add instances up to partition count. (2) Increase parallelism—more threads per consumer. (3) Batch processing—increase fetch size; process in batches. (4) Optimize processing—async I/O; avoid blocking calls. (5) Add partitions—if under-partitioned. (6) Rebalancing—ensure even partition assignment. (7) Kafka Streams/Flink for stateful processing. (8) Separate slow and fast topics. **Why**: Lag = throughput < production rate....
The complete answer continues with detailed implementation patterns, architectural trade-offs, and production-grade considerations. It covers performance optimization strategies, common pitfalls to avoid, and real-world examples from companies like Dunnhumby. The answer also includes follow-up discussion points that interviewers commonly explore.

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