SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Performance debugging for distributed systems of black boxes
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
Capturing, indexing, clustering, and retrieving system history
Proceedings of the twentieth ACM symposium on Operating systems principles
MapReduce: simplified data processing on large clusters
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Using magpie for request extraction and workload modelling
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Mochi: visual log-analysis based tools for debugging hadoop
HotCloud'09 Proceedings of the 2009 conference on Hot topics in cloud computing
Hunting for problems with Artemis
WASL'08 Proceedings of the First USENIX conference on Analysis of system logs
SALSA: analyzing logs as state machines
WASL'08 Proceedings of the First USENIX conference on Analysis of system logs
X-trace: a pervasive network tracing framework
NSDI'07 Proceedings of the 4th USENIX conference on Networked systems design & implementation
Detecting application-level failures in component-based Internet services
IEEE Transactions on Neural Networks
HotOS'13 Proceedings of the 13th USENIX conference on Hot topics in operating systems
Theia: visual signatures for problem diagnosis in large hadoop clusters
lisa'12 Proceedings of the 26th international conference on Large Installation System Administration: strategies, tools, and techniques
Performance troubleshooting in data centers: an annotated bibliography?
ACM SIGOPS Operating Systems Review
Adtributor: revenue debugging in advertising systems
NSDI'14 Proceedings of the 11th USENIX Conference on Networked Systems Design and Implementation
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Ganesha aims to diagnose faults transparently (in a black-box manner) in MapReduce systems, by analyzing OS-level metrics. Ganesha's approach is based on peer-symmetry under fault-free conditions, and can diagnose faults that manifest asymmetrically at nodes within a MapReduce system. We evaluate Ganesha by diagnosing Hadoop problems for the Gridmix Hadoop benchmark on 10-node and 50-node MapReduce clusters on Amazon's EC2. We also candidly highlight faults that escape Ganesha's diagnosis.