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Snapshot-based data index in cloud storage systems

机译:云存储系统中基于快照的数据索引

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摘要

With the arrival of the big data era, the data in storage system becomes lager and lager. The size of data index also increasing in a high speed. It is a crucial problem that how to index data quickly in a distributed data storage system. Meanwhile, because of the increasing size of data index, the traditional way, which rebuilding the index or fully backup the index before the data is changed, cannot match the need of today's big data index. In this paper, a double-layer B+ tree based index structure that overcomes the throughput limitation triggered by single index server is proposed. Then a high efficient snapshot-based B+ tree structure is designed to adapt dynamic cloud environment. Finally, experimental results show our snapshot based solution is feasible and efficient.
机译:随着大数据时代的到来,存储系统中的数据变得越来越大。数据索引的大小也在高速增加。至关重要的问题是如何在分布式数据存储系统中快速索引数据。同时,由于数据索引的大小不断增加,在数据更改之前重建索引或完全备份索引的传统方式已无法满足当今大数据索引的需求。本文提出了一种基于双层B +树的索引结构,该结构克服了单索引服务器触发的吞吐量限制。然后设计了一种基于快照的高效B +树结构来适应动态云环境。最后,实验结果表明我们基于快照的解决方案是可行和高效的。

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