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DLIDX: A Double Level Index for Cloud Storage Environment

机译:DLIDX:云存储环境的双层索引

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As data grows in amount, the researchers focus on the multiple condition query problem in cloud store data. The traditional index structures which are used in the relationship database. They have defects in maintenance and query efficiency in the cloud storage environment. This paper proposes a double level index framework(DLIDX). In DLIDX, the index of cloud storage is constructed by global index and local indexes. Each property of cloud data forms a dimension. For each dimension, the global index establishes the mapping relationship between the property and the node devices by inverting the hash table. The local indexes, a kind of bitmap index, are stored in the node devices. The bitmap indexes support local query of nodes. This framework can reduce the unnecessary retrieval cost. Meanwhile, the executive efficiency of the framework is less affected by the dataset. The experimental result proves that the performance of DLIDX is better than other methods.
机译:随着数据量的增长,研究人员将重点放在云存储数据中的多条件查询问题上。关系数据库中使用的传统索引结构。它们在云存储环境中的维护和查询效率方面存在缺陷。本文提出了一种双层索引框架(DLIDX)。在DLIDX中,云存储的索引由全局索引和本地索引构成。云数据的每个属性都构成一个维度。对于每个维度,全局索引通过反转哈希表来建立属性与节点设备之间的映射关系。本地索引是一种位图索引,存储在节点设备中。位图索引支持节点的本地查询。该框架可以减少不必要的检索成本。同时,该框架的执行效率受数据集的影响较小。实验结果证明,DLIDX的性能优于其他方法。

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