Job Scheduling with Minimizing Data Communication Costs
Summary: Proposes data-aware scheduling of interdependent jobs to minimize makespan under data-communication costs in distributed file systems like HDFS. Evaluates algorithms that trade data locality for parallelism while honoring input dependencies in query plans. (summarized by gpt-5-nano on Feb 09 2026)
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