When tuning a Hadoop cluster, what aspect is crucial for optimizing MapReduce job performance?
- Input Split Size
- JVM Heap Size
- Output Compression
- Task Parallelism
When tuning a Hadoop cluster, optimizing the Input Split Size is crucial for MapReduce job performance. It determines the amount of data each mapper processes, and an appropriate split size helps in achieving better parallelism and efficiency in job execution.
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