由于GROUP BY 实际上也同样会进行排序操作,而且与ORDER BY 相比,GROUP BY 主要只是多了排序之后的分组操作。当然,如果在分组的时候还使用了其他的一些聚合函数,那么还需要一些聚合函数的计算。所以,在GROUP BY 的实现过程中,与 ORDER BY 一样也可以利用到索引。
在MySQL 中,GROUP BY 的实现同样有多种(三种)方式,其中有两种方式会利用现有的索引信息来完成 GROUP BY,另外一种为完全无法使用索引的场景下使用。下面我们分别针对这三种实现方式做一个分析。
1.使用松散(Loose)索引扫描实现 GROUP BY
何谓松散索引扫描实现 GROUP BY 呢?实际上就是当 MySQL 完全利用索引扫描来实现 GROUP BY 的时候,并不需要扫描所有满足条件的索引键即可完成操作得出结果。
下面我们通过一个示例来描述松散索引扫描实现 GROUP BY,在示例之前我们需要首先调整一下 group_message 表的索引,将 gmt_create 字段添加到 group_id 和 user_id 字段的索引中:
1 sky@localhost : example 08:49:45> create index idx_gid_uid_gc
2
3 -> on group_message(group_id,user_id,gmt_create);
4
5 Query OK, rows affected (0.03 sec)
6
7 Records: 96 Duplicates: 0 Warnings: 0
8
9 sky@localhost : example 09:07:30> drop index idx_group_message_gid_uid
10
11 -> on group_message;
12
13 Query OK, 96 rows affected (0.02 sec)
14
15 Records: 96 Duplicates: 0 Warnings: 0
然后再看如下 Query 的执行计划:
1 sky@localhost : example 09:26:15> EXPLAIN
2
3 -> SELECT user_id,max(gmt_create)
4
5 -> FROM group_message
6
7 -> WHERE group_id 8
9 -> GROUP BY group_id,user_idG
10
11 *************************** 1. row ***************************
12
13 id: 1
14
15 select_type: SIMPLE
16
17 table: group_message
18
19 type: range
20
21 possible_keys: idx_gid_uid_gc
22
23 key: idx_gid_uid_gc
24
25 key_len: 8
26
27 ref: NULL
28
29 rows: 4
30
31 Extra: Using where; Using index for group-by
32
33 1 row in set (0.00 sec)

ACID attributes include atomicity, consistency, isolation and durability, and are the cornerstone of database design. 1. Atomicity ensures that the transaction is either completely successful or completely failed. 2. Consistency ensures that the database remains consistent before and after a transaction. 3. Isolation ensures that transactions do not interfere with each other. 4. Persistence ensures that data is permanently saved after transaction submission.

MySQL is not only a database management system (DBMS) but also closely related to programming languages. 1) As a DBMS, MySQL is used to store, organize and retrieve data, and optimizing indexes can improve query performance. 2) Combining SQL with programming languages, embedded in Python, using ORM tools such as SQLAlchemy can simplify operations. 3) Performance optimization includes indexing, querying, caching, library and table division and transaction management.

MySQL uses SQL commands to manage data. 1. Basic commands include SELECT, INSERT, UPDATE and DELETE. 2. Advanced usage involves JOIN, subquery and aggregate functions. 3. Common errors include syntax, logic and performance issues. 4. Optimization tips include using indexes, avoiding SELECT* and using LIMIT.

MySQL is an efficient relational database management system suitable for storing and managing data. Its advantages include high-performance queries, flexible transaction processing and rich data types. In practical applications, MySQL is often used in e-commerce platforms, social networks and content management systems, but attention should be paid to performance optimization, data security and scalability.

The relationship between SQL and MySQL is the relationship between standard languages and specific implementations. 1.SQL is a standard language used to manage and operate relational databases, allowing data addition, deletion, modification and query. 2.MySQL is a specific database management system that uses SQL as its operating language and provides efficient data storage and management.

InnoDB uses redologs and undologs to ensure data consistency and reliability. 1.redologs record data page modification to ensure crash recovery and transaction persistence. 2.undologs records the original data value and supports transaction rollback and MVCC.

Key metrics for EXPLAIN commands include type, key, rows, and Extra. 1) The type reflects the access type of the query. The higher the value, the higher the efficiency, such as const is better than ALL. 2) The key displays the index used, and NULL indicates no index. 3) rows estimates the number of scanned rows, affecting query performance. 4) Extra provides additional information, such as Usingfilesort prompts that it needs to be optimized.

Usingtemporary indicates that the need to create temporary tables in MySQL queries, which are commonly found in ORDERBY using DISTINCT, GROUPBY, or non-indexed columns. You can avoid the occurrence of indexes and rewrite queries and improve query performance. Specifically, when Usingtemporary appears in EXPLAIN output, it means that MySQL needs to create temporary tables to handle queries. This usually occurs when: 1) deduplication or grouping when using DISTINCT or GROUPBY; 2) sort when ORDERBY contains non-index columns; 3) use complex subquery or join operations. Optimization methods include: 1) ORDERBY and GROUPB


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