Query Performance Optimization in Databases for Big Data

M. Muniswamaiah, T. Agerwala, C. Tappert
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引用次数: 3

Abstract

Organizations maintain different databases to store and process big data which is huge in volume and have different data models. Querying and analysing big data for insight is critical for business. The data warehouses built should be able to meet the ever growing demand of data. With new requirements it is important to have near real times response from the big data gathered. All the data cannot be fit in to one particular database “One Size Does Not Fit All” since data originating from sources have different formats. The main focus of our research is to find an adequate solution using optimized data created by data engineers to improve the performance of query execution in a big data ecosystem.
面向大数据的数据库查询性能优化
组织维护不同的数据库来存储和处理海量数据,并且具有不同的数据模型。查询和分析大数据以获取洞察力对业务至关重要。所构建的数据仓库应该能够满足不断增长的数据需求。对于新的需求,从收集到的大数据中获得近乎实时的响应非常重要。所有的数据都不可能适合一个特定的数据库,因为来自数据源的数据有不同的格式。我们研究的主要重点是利用数据工程师创建的优化数据找到一个适当的解决方案,以提高大数据生态系统中查询执行的性能。
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