The Quantcast File System (QFS) is an efficient alternative to the Hadoop Distributed File System (HDFS). QFS is written in C++, is plugin compatible with Hadoop MapReduce, and offers several efficiency improvements relative to HDFS: 50% disk space savings through erasure coding instead of replication, a resulting doubling of write throughput, a faster name node, support for faster sorting and logging through a concurrent append feature, a native command line client much faster than hadoop fs, and global feedback-directed I/O device management. As QFS works out of the box with Hadoop, migrating data from HDFS to QFS involves simply executing hadoop distcp. QFS is being developed fully open source and is available under an Apache license from https://github.com/quantcast/qfs. Multi-petabyte QFS instances have been in heavy production use since 2011.
In this paper, we present Sailfish, a new Map-Reduce framework for large scale data processing. The Sailfish design is centered around aggregating intermediate data, specifically data produced by map tasks and consumed later by reduce tasks, to improve performance by batching disk I/O. We introduce an abstraction called I-files for supporting data aggregation, and describe how we implemented it as an extension of the distributed filesystem, to efficiently batch data written by multiple writers and read by multiple readers. Sailfish adapts the Map-Reduce layer in Hadoop to use I-files for transporting data from map tasks to reduce tasks. We present experimental results demonstrating that Sailfish improves performance of standard Hadoop; in particular, we show 20% to 5 times faster performance on a representative mix of real jobs and datasets at Yahoo!. We also demonstrate that the Sailfish design enables auto-tuning functionality that handles changes in data volume and skewed distributions effectively, thereby addressing an important practical drawback of Hadoop, which in contrast relies on programmers to configure system parameters appropriately for each job, for each input dataset. Our Sailfish implementation and the other software components developed as part of this paper has been released as open source.
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