Question

我想模拟数据库中的大量数据，并测试我的查询在这种情况下的执行情况。当查询结果很慢时，我并不感到惊讶。所以我在这里寻求有关如何更好地索引表格和改进查询的建议。

在我发布表的sql和我使用的查询之前，让我解释一下是什么。我有一个用户的表，其中填充了100 000条记录。其中的大多数列都是枚举类型，如头发颜色，looking_for等...我在搜索完成时会生成第一个查询。查询将包含where语句，其中搜索某些或所有列值，并且仅检索由20限制的ID。

然后我还有3个表，每个用户拥有大约50-1000条记录，因此数字可能会真正增长。这些表格包含有关谁访问了谁的个人资料，谁标记了谁是谁，谁阻止谁以及消息传递表的信息。我的目标是检索20条符合搜索条件的记录，同时确定我（浏览的用户）是否有：

阻止他们
收藏他们
受到他们的青睐
有来自他们的未读消息
已发送或接收任何来自他们的消息

为此，我尝试使用连接和子查询，但问题是检索上面列出的用户和数据的第二个查询仍然很慢。我想我需要一个更好的索引，可能还有更好的查询。这就是我现在所拥有的，首先是表定义，最后是2个查询。首先解决并确定ID，第二次使用来自第一次查询的ID来检索数据。我希望你们能帮助我创建更好的索引并优化查询。

CREATE TABLE user (id BIGINT AUTO_INCREMENT, dname VARCHAR(255) NOT NULL, email VARCHAR(255) NOT NULL UNIQUE, email_code VARCHAR(255), email_confirmed TINYINT(1) DEFAULT '0', password VARCHAR(255) NOT NULL, gender ENUM('male', 'female'), description TEXT, dob DATE, height MEDIUMINT, looks ENUM('thin', 'average', 'athletic', 'heavy'), looking_for ENUM('marriage', 'dating', 'friends'), looking_for_age1 BIGINT, looking_for_age2 BIGINT, color_hair ENUM('black', 'brown', 'blond', 'red'), color_eyes ENUM('black', 'brown', 'blue', 'green', 'grey'), marital_status ENUM('single', 'married', 'divorced', 'widowed'), smokes ENUM('no', 'yes', 'sometimes'), drinks ENUM('no', 'yes', 'sometimes'), has_children ENUM('no', 'yes'), wants_children ENUM('no', 'yes'), education ENUM('school', 'college', 'university', 'masters', 'phd'), occupation ENUM('no', 'yes'), country_id BIGINT, city_id BIGINT, lastlogin_at DATETIME, deleted_at DATETIME, created_at DATETIME NOT NULL, updated_at DATETIME NOT NULL, INDEX country_id_idx (country_id), INDEX city_id_idx (city_id), INDEX image_id_idx (image_id), PRIMARY KEY(id)) DEFAULT CHARACTER SET utf8 COLLATE utf8_unicode_ci ENGINE = INNODB;

CREATE TABLE block (id BIGINT AUTO_INCREMENT, blocker_id BIGINT, blocked_id BIGINT, created_at DATETIME NOT NULL, updated_at DATETIME NOT NULL, INDEX blocker_id_idx (blocker_id), INDEX blocked_id_idx (blocked_id), PRIMARY KEY(id)) DEFAULT CHARACTER SET utf8 COLLATE utf8_unicode_ci ENGINE = INNODB;

CREATE TABLE city (id BIGINT AUTO_INCREMENT, name_eng VARCHAR(30), name_geo VARCHAR(30), name_geo_shi VARCHAR(30), name_geo_is VARCHAR(30), country_id BIGINT NOT NULL, active TINYINT(1) DEFAULT '0', INDEX country_id_idx (country_id), PRIMARY KEY(id)) DEFAULT CHARACTER SET utf8 COLLATE utf8_unicode_ci ENGINE = INNODB;

CREATE TABLE country (id BIGINT AUTO_INCREMENT, code VARCHAR(2), name_eng VARCHAR(30), name_geo VARCHAR(30), name_geo_shi VARCHAR(30), name_geo_is VARCHAR(30), active TINYINT(1) DEFAULT '1', PRIMARY KEY(id)) DEFAULT CHARACTER SET utf8 COLLATE utf8_unicode_ci ENGINE = INNODB;

CREATE TABLE favorite (id BIGINT AUTO_INCREMENT, favoriter_id BIGINT, favorited_id BIGINT, created_at DATETIME NOT NULL, updated_at DATETIME NOT NULL, INDEX favoriter_id_idx (favoriter_id), INDEX favorited_id_idx (favorited_id), PRIMARY KEY(id)) DEFAULT CHARACTER SET utf8 COLLATE utf8_unicode_ci ENGINE = INNODB;

CREATE TABLE message (id BIGINT AUTO_INCREMENT, body TEXT, sender_id BIGINT, receiver_id BIGINT, read_at DATETIME, created_at DATETIME NOT NULL, updated_at DATETIME NOT NULL, INDEX sender_id_idx (sender_id), INDEX receiver_id_idx (receiver_id), PRIMARY KEY(id)) DEFAULT CHARACTER SET utf8 COLLATE utf8_unicode_ci ENGINE = INNODB;

CREATE TABLE visitor (id BIGINT AUTO_INCREMENT, visitor_id BIGINT, visited_id BIGINT, created_at DATETIME NOT NULL, updated_at DATETIME NOT NULL, INDEX visitor_id_idx (visitor_id), INDEX visited_id_idx (visited_id), PRIMARY KEY(id)) DEFAULT CHARACTER SET utf8 COLLATE utf8_unicode_ci ENGINE = INNODB;


SELECT s.id AS s__id FROM user s WHERE (s.gender = 'female' AND s.marital_status = 'single' AND s.smokes = 'no' AND s.deleted_at IS NULL) LIMIT 20

SELECT s.id AS s__id, s.dname AS s__dname, s.gender AS s__gender, s.height AS s__height, s.dob AS s__dob, s3.id AS s3__id, s3.code AS s3__code, s3.name_geo AS s3__name_geo, s4.id AS s4__id, s4.name_geo AS s4__name_geo, s5.id AS s5__id, s6.id AS s6__id, s7.id AS s7__id, s8.id AS s8__id, s9.id AS s9__id FROM user s LEFT JOIN country s3 ON s.country_id = s3.id LEFT JOIN city s4 ON s.city_id = s4.id LEFT JOIN block s5 ON ((s.id = s5.blocked_id AND s5.blocker_id = '1')) LEFT JOIN favorite s6 ON ((s.id = s6.favorited_id AND s6.favoriter_id = '1')) LEFT JOIN favorite s7 ON ((s.id = s7.favoriter_id AND s7.favorited_id = '1')) LEFT JOIN message s8 ON ((s.id = s8.sender_id AND s8.receiver_id = '1' AND s8.read_at IS NULL)) LEFT JOIN message s9 ON (((s.id = s9.sender_id AND s9.receiver_id = '1') OR (s.id = s9.receiver_id AND s9.sender_id = '1'))) WHERE (s.id IN ('22', '36', '53', '105', '152', '156', '169', '182', '186', '192', '201', '215', '252', '287', '288', '321', '330', '351', '366', '399')) GROUP BY s.id ORDER BY s.id

以下是上述2个查询的EXPLAIN结果：

首先：

1   SIMPLE  s   ALL NULL    NULL    NULL    NULL    100420  Using Where

第二

1   SIMPLE  s   range   PRIMARY PRIMARY 8   NULL    20  Using where; Using temporary; Using filesort
1   SIMPLE  s2  eq_ref  PRIMARY PRIMARY 8   sagule.s.image_id   1   Using index
1   SIMPLE  s3  eq_ref  PRIMARY PRIMARY 8   sagule.s.country_id 1
1   SIMPLE  s4  eq_ref  PRIMARY PRIMARY 8   sagule.s.city_id    1
1   SIMPLE  s5  ref blocker_id_idx,blocked_id_idx   blocked_id_idx  9   sagule.s.id 5
1   SIMPLE  s6  ref favoriter_id_idx,favorited_id_idx   favorited_id_idx    9   sagule.s.id 6
1   SIMPLE  s7  ref favoriter_id_idx,favorited_id_idx   favoriter_id_idx    9   sagule.s.id 6
1   SIMPLE  s8  ref sender_id_idx,receiver_id_idx   sender_id_idx   9   sagule.s.id 7
1   SIMPLE  s9  index_merge sender_id_idx,receiver_id_idx   receiver_id_idx,sender_id_idx   9,9 NULL    66  Using union(receiver_id_idx,sender_id_idx); Using where

Answer 1

在第二个SELECT查询中，您可以删除GROUP BY子句，因为您没有在SELECT子句中使用任何聚合函数（count，min，max ...）。

我怀疑这会有助于提高性能。

无论如何，我建议观看本演讲的前半部分“看看MySQL DBA的工具箱”。（视频的前三分之二是关于Unix上mysql的免费开源管理工具，最后三分之一是关于复制）

视频A Look into a MySQL DBA's Toolchest

来自同一个演讲：The Guide To Understanding mysqlreport

Answer 2

如果没有一些数据可供测试，那么提出一个好的建议并不容易。

为经常搜索的字段生成索引可以帮助您更快地查询。但是使用索引，您的插入和更新可能会变慢。你必须考虑权衡。因此，索引频繁搜索的列，但测试数据上的新索引，以便查看它是否运行得更快。

我不知道您使用的是哪种工具，但使用MySQL Workbench时，在“查询”-Menu下有一个命令“解释当前语句”。在那里，您可以看到MySQL执行了哪些操作以及使用了哪些键。您的查询显示“null”，这意味着没有使用密钥，MySQL必须与搜索词进行比较才能运行整个数据。

希望这有点帮助。

尝试优化查询并正确索引表

3 个答案: