• 新功能初探 | MySQL 8.0 Multi-Valued Indexes功能简述


    顾名思义,索引上对于同一个Primary key, 可以建立多个二级索引项,实际上已经对array类型的基础功能做了支持,并基于array来构建二级索引。
    这意味着该二级索引的记录数可以是多于聚集索引记录数的,因而该索引不可以用于通常意义的查询,只能通过特定的接口函数来使用,下面的例子里会说明。

    范例

    摘录自官方文档

    root@test 04:08:50>show create table customersG                                                                                                                                  
      `id` bigint(20) NOT NULL AUTO_INCREMENT,
      `modified` datetime DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
      `custinfo` json DEFAULT NULL,
      PRIMARY KEY (`id`),
      KEY `zips` ((cast(json_extract(`custinfo`,_latin1'$.zip') as unsigned array)))
    ) ENGINE=InnoDB AUTO_INCREMENT=6 DEFAULT CHARSET=latin1
    1 row in set (0.00 sec)
    
    root@test 04:08:53>select * from customers;
    +----+---------------------+-------------------------------------------------------------------+
    | id | modified            | custinfo                                                          |
    +----+---------------------+-------------------------------------------------------------------+
    |  1 | 2019-08-14 16:08:50 | {"user": "Jack", "user_id": 37, "zipcode": [94582, 94536]}        |
    |  2 | 2019-08-14 16:08:50 | {"user": "Jill", "user_id": 22, "zipcode": [94568, 94507, 94582]} |
    |  3 | 2019-08-14 16:08:50 | {"user": "Bob", "user_id": 31, "zipcode": [94477, 94536]}         |
    |  4 | 2019-08-14 16:08:50 | {"user": "Mary", "user_id": 72, "zipcode": [94536]}               |
    |  5 | 2019-08-14 16:08:50 | {"user": "Ted", "user_id": 56, "zipcode": [94507, 94582]}         |
    +----+---------------------+-------------------------------------------------------------------+
    5 rows in set (0.00 sec)
    

    通过如下三个函数member of, json_contains, json_overlaps可以使用到该索引

    root@test 04:09:00>SELECT * FROM customers WHERE 94507 MEMBER OF(custinfo->'$.zipcode');
    +----+---------------------+-------------------------------------------------------------------+
    | id | modified            | custinfo                                                          |
    +----+---------------------+-------------------------------------------------------------------+
    |  2 | 2019-08-14 16:08:50 | {"user": "Jill", "user_id": 22, "zipcode": [94568, 94507, 94582]} |
    |  5 | 2019-08-14 16:08:50 | {"user": "Ted", "user_id": 56, "zipcode": [94507, 94582]}         |
    +----+---------------------+-------------------------------------------------------------------+
    2 rows in set (0.00 sec)
    
    root@test 04:09:41>SELECT * FROM customers  WHERE JSON_CONTAINS(custinfo->'$.zipcode', CAST('[94507,94582]' AS JSON));
    +----+---------------------+-------------------------------------------------------------------+
    | id | modified            | custinfo                                                          |
    +----+---------------------+-------------------------------------------------------------------+
    |  2 | 2019-08-14 16:08:50 | {"user": "Jill", "user_id": 22, "zipcode": [94568, 94507, 94582]} |
    |  5 | 2019-08-14 16:08:50 | {"user": "Ted", "user_id": 56, "zipcode": [94507, 94582]}         |
    +----+---------------------+-------------------------------------------------------------------+
    2 rows in set (0.00 sec)
    
    root@test 04:09:54>SELECT * FROM customers   WHERE JSON_OVERLAPS(custinfo->'$.zipcode', CAST('[94507,94582]' AS JSON));
    +----+---------------------+-------------------------------------------------------------------+
    | id | modified            | custinfo                                                          |
    +----+---------------------+-------------------------------------------------------------------+
    |  1 | 2019-08-14 16:08:50 | {"user": "Jack", "user_id": 37, "zipcode": [94582, 94536]}        |
    |  2 | 2019-08-14 16:08:50 | {"user": "Jill", "user_id": 22, "zipcode": [94568, 94507, 94582]} |
    |  5 | 2019-08-14 16:08:50 | {"user": "Ted", "user_id": 56, "zipcode": [94507, 94582]}         |
    +----+---------------------+-------------------------------------------------------------------+
    3 rows in set (0.00 sec)

    接口函数

    multi-value index是functional index的一种实现,列的定义是一个虚拟列,值是从json column上取出来的数组。

    数组上存在相同值的话,会只存储一个到索引上。支持的类型:DECIMAL, INTEGER, DATETIME,VARCHAR/CHAR。另外index上只能有一个multi-value column。
    下面简单介绍下相关的接口函数

    数组最大容量:

    入口函数:
    ha_innobase::mv_key_capacity

    插入记录:

    入口函数:
    row_ins_sec_index_multi_value_entry
    通过类Multi_value_entry_builder_insert来构建tuple, 然后调用正常的接口函数row_ins_sec_index_entry插入到二级索引中。
    已经解析好,排序并去重的数据存储在结构struct multi_value_data , 指针在dfield_t::data中. multi_value_data结构也是multi-value具体值的内存表现

    删除记录:

    入口函数:
    row_upd_del_multi_sec_index_entry
    基于类Multi_value_entry_builder_normal构建tuple, 并依次从索引中删除

    更新记录

    入口函数:
    row_upd_multi_sec_index_entry
    由于可能不是所有的二级索引记录都需要更新,需要计算出diff,找出要更新的记录calc_row_difference --> innobase_get_multi_value_and_diff, 设置一个需要更新的bitmap

    事务回滚

    相关函数:

    row_undo_ins_remove_multi_sec
    row_undo_mod_upd_del_multi_sec
    row_undo_mod_del_mark_multi_sec

    回滚的时候通过trx_undo_rec_get_multi_value从undo log中获取multi-value column的值,通过接口Multi_value_logger::read来构建并存储到field data中

    记录undo log

    函数: trx_undo_store_multi_value
    通过Multi_value_logger::log将multi-value的信息存储到Undo log中. 'Multi_value_logger'是一个辅助类,用于记录multi-value column的值以及如何读出来

    purge 二级索引记录

    入口函数:

    row_purge_del_mark
    row_purge_upd_exist_or_extern_func
        |--> row_purge_remove_multi_sec_if_poss

    本文作者: Roin123

    原文链接

    本文为云栖社区原创内容,未经允许不得转载。

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  • 原文地址:https://www.cnblogs.com/zhaowei121/p/11990682.html
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