Building workload-independent storage with VT-trees
Building workload-independent storage with VT-trees
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发表时间：
2013-02
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通讯作者：
P. Shetty;Richard P. Spillane;Ravikant Malpani;B. Andrews;Justin Seyster;E. Zadok
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作者：
P. Shetty;Richard P. Spillane;Ravikant Malpani;B. Andrews;Justin Seyster;E. Zadok
随着互联网和数据增长的数量，数据尺寸的变化也会增长 - 从大型VM图像到大型VM图像。当前的存储系统专注于对一个工作负载的优化，以其他工作负载为代价，这是由于现有的存储系统数据结构的限制。称为VT-Tree，它扩展了LSM-Tree以有效处理顺序和文件系统工作负载，我们设计了一个基于VT-Trees的系统，该系统可以通过文件系统和数据库API，交易保证提供对数据的同时访问不论我们的访问模式如何其他工作负载的平均开销很小。
As the Internet and the amount of data grows, the variability of data sizes grows too--from small MP3 tags to large VM images. With applications using increasingly more complex queries and larger data-sets, data access patterns have become more complex and randomized. Current storage systems focus on optimizing for one band of workloads at the expense of other workloads due to limitations in existing storage system data structures. We designed a novel workload-independent data structure called the VT-tree which extends the LSM-tree to efficiently handle sequential and file-system workloads. We designed a system based solely on VT-trees which offers concurrent access to data via file system and database APIs, transactional guarantees, and consequently provides efficient and scalable access to both large and small data items regardless of the access pattern. Our evaluation shows that our user-level system has 2-6.6× better performance for random-write workloads and only a small average overhead for other workloads.