<ruby id="bdb3f"></ruby>

    <p id="bdb3f"><cite id="bdb3f"></cite></p>

      <p id="bdb3f"><cite id="bdb3f"><th id="bdb3f"></th></cite></p><p id="bdb3f"></p>
        <p id="bdb3f"><cite id="bdb3f"></cite></p>

          <pre id="bdb3f"></pre>
          <pre id="bdb3f"><del id="bdb3f"><thead id="bdb3f"></thead></del></pre>

          <ruby id="bdb3f"><mark id="bdb3f"></mark></ruby><ruby id="bdb3f"></ruby>
          <pre id="bdb3f"><pre id="bdb3f"><mark id="bdb3f"></mark></pre></pre><output id="bdb3f"></output><p id="bdb3f"></p><p id="bdb3f"></p>

          <pre id="bdb3f"><del id="bdb3f"><progress id="bdb3f"></progress></del></pre>

                <ruby id="bdb3f"></ruby>

                企業??AI智能體構建引擎,智能編排和調試,一鍵部署,支持知識庫和私有化部署方案 廣告
                MySQL 5.7.7 labs版本開始InnoDB存儲引擎已經原生支持JSON格式,該格式不是簡單的BLOB類似的替換。原生的JSON格式支持有以下的優勢: JSON數據有效性檢查:BLOB類型無法在數據庫層做這樣的約束性檢查 查詢性能的提升:查詢不需要遍歷所有字符串才能找到數據 支持索引:通過虛擬列的功能可以對JSON中的部分數據進行索引 ~~~ mysql> create table user ( uid int auto_increment, -> data json,primary key(uid))engine=innodb; Query OK, 0 rows affected (0.01 sec) mysql> insert into user values (NULL, -> '{"name":"David","mail":"jiangchengyao@gmail.com","address":"Shangahai"}'); Query OK, 1 row affected (0.00 sec) mysql> insert into user values (NULL,'{"name":"Amy","mail":"amy@gmail.com"}'); Query OK, 1 row affected (0.00 sec) ~~~ 我們新建了表user,并且將列data定義為了JSON類型。這意味著我們可以對插入的數據做JSON格式檢查,確保其符合JSON格式的約束。 MySQL 5.7提供了一系列函數來高效地處理JSON字符,而不是需要遍歷所有字符來查找,這不得不說是對 MariaDB dynamic column 的巨大改進: ~~~ mysql> select jsn_extract(data, '$.name'),jsn_extract(data,'$.address') from user; +-----------------------------+-------------------------------+ | jsn_extract(data, '$.name') | jsn_extract(data,'$.address') | +-----------------------------+-------------------------------+ | "David" | "Shangahai" | | "Amy" | NULL | +-----------------------------+-------------------------------+ 2 rows in set (0.00 sec) ~~~ 應該是MySQL 5.7最令人的激動的功能,虛擬列功能,通過傳統的B+樹索引即可實現對JSON格式部分屬性的快速查詢。使用方法是首先創建該虛擬列,然后在該虛擬列上創建索引 ~~~ mysql> ALTER TABLE user ADD user_name varchar(128) -> GENERATED ALWAYS AS (jsn_extract(data,'$.name')) VIRTUAL; Query OK, 0 rows affected (0.01 sec) Records: 0 Duplicates: 0 Warnings: 0 mysql> select user_name from user; +-----------+ | user_name | +-----------+ | "Amy" | | "David" | +-----------+ 2 rows in set (0.00 sec) mysql> alter table user add index idx_username (user_name); Query OK, 2 rows affected (0.01 sec) Records: 2 Duplicates: 0 Warnings: 0 ~~~ 然后可以通過添加的索引對用戶名進行快速的查詢,這和普通類型的列查詢一樣。而通過explain可以驗證優化器已經選擇了在虛擬列上創建的新索引: ~~~ mysql> explain select * from user where user_name='"Amy"'\G *************************** 1. row *************************** id: 1 select_type: SIMPLE table: user partitions: NULL type: ref possible_keys: idx_username key: idx_username key_len: 131 ref: const rows: 1 filtered: 100.00 Extra: NULL 1 row in set, 1 warning (0.00 sec) ~~~ 可以發現MySQL 5.7對于JSON格式堪稱完美 * * * * * http://database.51cto.com/art/201504/472302.htm
                  <ruby id="bdb3f"></ruby>

                  <p id="bdb3f"><cite id="bdb3f"></cite></p>

                    <p id="bdb3f"><cite id="bdb3f"><th id="bdb3f"></th></cite></p><p id="bdb3f"></p>
                      <p id="bdb3f"><cite id="bdb3f"></cite></p>

                        <pre id="bdb3f"></pre>
                        <pre id="bdb3f"><del id="bdb3f"><thead id="bdb3f"></thead></del></pre>

                        <ruby id="bdb3f"><mark id="bdb3f"></mark></ruby><ruby id="bdb3f"></ruby>
                        <pre id="bdb3f"><pre id="bdb3f"><mark id="bdb3f"></mark></pre></pre><output id="bdb3f"></output><p id="bdb3f"></p><p id="bdb3f"></p>

                        <pre id="bdb3f"><del id="bdb3f"><progress id="bdb3f"></progress></del></pre>

                              <ruby id="bdb3f"></ruby>

                              哎呀哎呀视频在线观看