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Research of Distributed Query and Optimization Method Based onMetadata

机译:基于元数据的分布式查询与优化方法研究

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A method of distributed query based on metadata, which uses metadata to define and manage the virtual tablecontaining key information of the data source, has been studied in this paper. Then, in view of the different data level, designedtwo different data solutions based on query and optimization, for applying to common data and huge data respectively.In common data query, using the virtual table, the syntax analysis tree and memory database was realized by; copying,moving, and dividing the branch from virtual SQL query syntax tree to make the query optimized. In terms of hugeamounts of data query, Pig, Hadoop, Python is used to implement data query; by optimizing the Pig code, using multipleprocesses, processing file merging and file uploading or downloading in HDFS, making index on high frequency businessand so on to achieve optimization of big data.
机译:本文研究了一种基于元数据的分布式查询方法,该方法使用元数据来定义和管理包含数据源关键信息的虚拟表。然后针对不同的数据层次,设计了两种基于查询和优化的数据解决方案,分别应用于公共数据和海量数据。在公共数据查询中,利用虚拟表,通过以下方式实现了语法分析树和内存数据库: ;从虚拟SQL查询语法树中复制,移动和划分分支,以优化查询。在海量数据查询方面,Pig,Hadoop,Python用于实现数据查询。通过优化Pig代码,使用多个进程,在HDFS中处理文件合并以及文件上载或下载,在高频业务上建立索引等来实现大数据的优化。

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