Mochi: Visual Log-Analysis Based Tools for Debugging Hadoop
journal contributionposted on 15.06.2009 by Jiaqui Tan, Xinghao Pan, Soila Kavulya, Rajeev Ghandi, Priya Narasimhan
Any type of content formally published in an academic journal, usually following a peer-review process.
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