如Google框架MapReduce; MR描述了一种使用Map功能实现并行性的方法,它将大型数据分割成多个键-值对。
Like the Google framework MapReduce; MR describes a way of implementing parallelism using the Map function which splits a large data into multiple key-value pairs.
SQL查询的优化利用了一些复杂的功能,例如:查询重写、多连接(join)方法、详细的统计、并行性等。
The optimization of SQL queries utilize sophisticated features, such as: query rewrite, multiple join methods, detailed statistics, parallelism etc.
为了进一步地发掘嵌套循环的并行性和数据访问的时间局部性,对算法增加了一个线性循环变换的功能模块来进行改进。
To further excavate the nesting loop parallelism and the data access-time locality, a linearity cyclic transformation functional module is used to improve the algorithm.
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