Mochi, a new visual, log-analysis based debugging tool correlates Hadoop’s behavior in space, time and volume, and extracts a causal, unified control- and dataflow model of Hadoop across the nodes of a cluster. Mochi’s analysis produces visualizations of Hadoop’s behavior using which users can reason about and debug performance issues. We provide examples of Mochi’s value in revealing a Hadoop job’s structure, in optimizing real-world workloads, and in identifying anomalous Hadoop behavior, on the Yahoo! M45 Hadoop cluster
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Pan et al. (2018) studied this question.
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