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Can you explain dynamic resource allocation in Spark? How does it help optimize job performance?

Spark/Big Dataeasy0.5 min readPremium
Frequency
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Asked at 1 company
Category
452
questions in Spark/Big Data
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88E|81M|283H
in this category
Total Bank
1,863
across 7 categories
Asked at these companies
Coforge
Key Concepts Tested
spark
Expert AnswerPremium
91 wordsInterview-ready
**Why dynamic allocation matters**: Static executors = overpay when idle, underperform when backlogged. **Mechanism**: `spark.dynamicAllocation.enabled=true`. Executors scale up when task backlog grows; scale down when idle for `executorIdleTimeout`. Min/max bounds control range. **Scalability trade-offs**: Scale-up has latency—initial tasks may queue. Scale-down frees resources for other jobs. Works with YARN, K8s; requires external shuffle service for shuffle data retention....
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