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VeloxDFS: Streaming Access to Distributed Datasets to Reduce Disk Seeks

In this work, we design and implement VeloxDFS, a distributed file system for ETL MapReduce frameworks, which has compatible APIs with HDFS. VeloxDFS is a decentralized, consistent, hash-based file system that dynamically adjusts the size of partitioned blocks. Rather than the conventional static and coarse-grained partitioning scheme, VeloxDFS employs a fine- grained logical partitioning scheme and provides an abstraction of various sized blocks based on the I/O consumption rate. VeloxDFS avoids I/O contention and straggler problems by employing a block stream manager that coordinates the I/O requests of multiple tasks during runtime. By reducing the I/O contention of concurrent tasks, VeloxDFS enables overcommit scheduling that schedules a larger number of tasks than the available physical CPU cores, leveraging the OS scheduler to improve the computing resource utilization of a cluster. Our extensive performance study shows that VeloxDFS with the over- commit scheduling policy shows up to 1.7x higher job processing throughput than HDFS for multiple concurrent workloads.