本篇文章主要介绍了"MySQL 优化之 MRR Multi-Range Read:二级索引合并回表"，主要涉及到require,索引方面的内容，对于MySql感兴趣的同学可以参考一下：
MySQL5.6中引入了MRR，专门来优化：二级索引的范围扫描并且需要回表的情况。它的原理是，将多个需要回表的二级索引根据主键进行排序，然后一起回表，将原来的回...
MySQL5.6中引入了MRR，专门来优化：二级索引的范围扫描并且需要回表的情况。它的原理是，将多个需要回表的二级索引根据主键进行排序，然后一起回表，将原来的回表时进行的随机IO，转变成顺序IO。文档地址：http://dev.mysql.com/doc/refman/5.6/en/mrr-optimization.html
Reading rows using a range scan on a secondary index can result in many random disk accesses to the base table when the table is large and not stored in the storage engine's cache. With the Disk-Sweep Multi-Range Read (MRR) optimization, MySQL tries to reduce the number of random disk access for range scans by first scanning the index only and collecting the keys for the relevant rows. Then the keys are sorted and finally the rows are retrieved from the base table using the order of the primary key. The motivation for Disk-sweep MRR is to reduce the number of random disk accesses and instead achieve a more sequential scan of the base table data.
首先对二级索引进行范围扫描，对于符合条件的 key, 按照主键进行排序，然后一起根据key来读取基表。
The Multi-Range Read optimization provides these benefits:
MRR enables data rows to be accessed sequentially rather than in random order, based on index tuples. The server obtains a set of index tuples that satisfy the query conditions, sorts them according to data row ID order, and uses the sorted tuples to retrieve data rows in order. This makes data access more efficient and less expensive.
MRR enables batch processing of requests for key access for operations that require access to data rows through index tuples, such as range index scans and equi-joins that use an index for the join attribute. MRR iterates over a sequence of index ranges to obtain qualifying index tuples. As these results accumulate, they are used to access the corresponding data rows. It is not necessary to acquire all index tuples before starting to read data rows.
MRR的主要优势：将随机IO转换成顺序IO；使用在 索引范围扫描 和 使用索引进行join 时；
