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Parallelism: Interference between the data and indexes using major of indexing types

机译:并行性:使用主要索引类型的数据和索引之间的干扰

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摘要

As in engineering and research, database tuning becomes an inescapable part of big projects since the conception phase. The needs of companies including big data have increased to databases optimization. A lot of systems cause many blockages at least the five years after the production, because they didn't take into account the optimization and its rules since the conception phase, these reasons were of a paramount of importance to prepare this paper. Indexing is the most suitable way to optimize databases system, further one of the best ways of optimizing the index is the application of parallelization. In this paper we will talk about parallelization, and we will use different query with different types of indexes and we will compare the results gotten from each index, to top it all, the most suitable interference between the major types of index: b*tree index, bitmap index, composite index, local index and global index.
机译:与工程和研究一样,自构思阶段以来,数据库调整已成为大型项目不可回避的一部分。包括大数据在内的公司的需求已经增加到数据库优化。许多系统至少在生产后的五年内会造成很多阻塞,因为它们从构思阶段开始就没有考虑优化及其规则,因此,这些原因对于编写本文至关重要。索引是最优化数据库系统的方法,而优化索引的最佳方法之一是并行化的应用。在本文中,我们将讨论并行化,并且将对不同类型的索引使用不同的查询,并将比较从每个索引获得的结果,最重要的是,主要索引之间的最合适干扰:b * tree索引,位图索引,复合索引,局部索引和全局索引。

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