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sailfish

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Sailfish tries to improve the disk subsystem performance for large scale Map-Reduce computations. This work is based on the observation that bandwidth within a datacenter will substantially increase over the coming years. Such an increase can be harnessed to build network-wide data aggregation and thereby improve disk throughput. That is, "group-commit" data to disk by batching data from multiple writers that run on different machines in the network. There are two key ideas in the Sailfish design: 1. I-files, a network-wide data aggregation abstraction 1. Use I-files to aggregate intermediate data (namely, map output) in a Map-Reduce computation. Gather statistics on the aggregated data to plan the reduce phase of execution. Using I-files to transport map output helps improve disk performance when handling TB"s of intermediate data. Dynamically planning the reduce phase improves auto-tune/auto-scale functionality: Sailfish handles skew as well

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