云上大容量交通日志数据集的高性能分布式索引和检索

Wen Yang, Yinan Dou
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引用次数: 2

摘要

在本文中,我们提出了一个高性能的分布式系统,用于存储、索引和检索大量的网络交通日志数据集。本系统基于开源的Map Reduce框架Hadoop,对Hadoop的功能进行了扩展。我们的工作主要集中在三个值得注意的方面:在Hadoop分布式文件系统(HDFS)上存储大型数据集的方法,大型分布式数据集的适当索引算法,建立在Hadoop上的分布式检索架构。与分布式、稀疏、NoSQL数据库HBase相比,该系统的查询响应延迟接近实时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-Performance Distributed Indexing and Retrieval for Large Volume Traffic Log Datasets on the Cloud
In this paper, we present a high-performance distributed system for storage, indexing and retrieval for large volume web traffic log datasets. This system is Based on the open source Map Reduce framework Hadoop and extends the functionality of Hadoop. We mainly focus on three noteworthy aspects of our work: the approach of large datasets storage on the Hadoop Distributed File System (HDFS), the appropriate indexing algorithm for large distributed datasets, a distributed retrieval architecture built on Hadoop. It has been proved that our system is efficient and the query response latency approach real time compared with HBase, a distributed, sparse, NoSQL database.
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