Multiple big data processing platforms

B. Chang, H. Tsai, Yi-Sheng Chang, Chien-Feng Huang
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引用次数: 1

Abstract

The integration of Hive, Impala and Spark SQL platforms has achieved to perform rapid data retrieval using SQL query in big data environment. This paper is to design the optimized platform selection for highly improving the response of data retrieval. It can automatically choose the best-perform platform to best perform SQL commands. In addition, the distributed memory storage systems using Memcached and the distributed file system Hadoop HDFS have implemented the caching so that the fastest data retrieval has done once the repeated SQL command has applied.
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多个大数据处理平台
Hive、Impala和Spark SQL平台的集成,实现了大数据环境下SQL查询的快速数据检索。本文旨在设计优化的平台选择,以提高数据检索的响应速度。它可以自动选择性能最佳的平台来最佳地执行SQL命令。此外,使用Memcached的分布式内存存储系统和分布式文件系统Hadoop HDFS已经实现了缓存,这样一旦应用了重复的SQL命令,数据检索就会以最快的速度完成。
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