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Preview of [doi]
🔗 Source: usenix.org
📊 Size: 3.66 MB
👤 Author: srikanth,U-REDMOND\srikanth,S-1-5-21-2127521184-1604012920-1887927527-4873210
⬇️ Downloads: 132

Summary

Mantri is a system that monitors and manages outliers in Map-Reduce clusters, improving job completion times by 32% on average. Outliers are tasks that take significantly longer to complete than similar tasks, causing delays in job completion. Mantri identifies the causes of outliers, including resource contention, disk failures, network congestion, and workload imbalance, and uses techniques such as restarting outlier tasks, network-aware placement of tasks, and protecting output of valuable tasks to mitigate their impact. Mantri's strategies are based on real-time progress reports and consider the opportunity cost of actions, allowing it to improve over prior work that only duplicates laggard tasks. Deployment in Bing's production clusters and simulations show that Mantri reduces job completion times by 32% on average, with median reduction improving by 6.1x over the next best scheme while using fewer resources.

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Description

Mantri is a system that monitors and manages outliers in Map-Reduce clusters, improving job completion times by 32% on average.

Technical Information

  • File Format: PDF
  • File Size: 3.66 MB
  • Pages: 14
  • Language: EN
  • Author: srikanth,U-REDMOND\srikanth,S-1-5-21-2127521184-1604012920-1887927527-4873210
  • Total Downloads: 132
  • Last Updated: 3 weeks ago

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