不能使连接正常工作

，我有以下数据：不能使连接正常工作

customer 
+---------------------------------------------------------------------------------------------+ 
| id | email    | firstname  | lastname  | no_pub | customer_address | 
|---------------------------------------------------------------------------------------------| 
| 1  | [email protected] | Martin  | Scorcese  | 0   | 4     | 
| 2  | [email protected] | Robert  | De Niro  | 0   | 7     | 
| 3  | [email protected];com | Bruce   | Willis  | 0   | 10     | 
+---------------------------------------------------------------------------------------------+ 

address 
+------------------------------------------+ 
| id | city    | zipcode  | 
|------------------------------------------| 
| 4  | Paris   | 75001   | 
| 7  | Marseille  | 13000   | 
| 10 | Bordeaux   | 33000   | 
+------------------------------------------+ 

sf_geo_cities 
+------------------------------------------+ 
| id | region_id | zipcode   | 
|------------------------------------------| 
| 1  | 1   | 75001    | 
| 2  | 2   | 13000    | 
| 2  | 3   | 33000    | 
+------------------------------------------+ 

sf_geo_regions 
+------------------------------------------+ 
| id | name    | zipcode  | 
|------------------------------------------| 
| 1  | Ile-de-France | 75001   | 
| 2  | Cote d'Azur  | 13000   | 
| 2  | Gironde   | 33000   | 
+------------------------------------------+

这是一个样本，有很明显这些表中的方式更多的数据（300K +的客户，400K +的地址）在结束，我想获得以下数据：

+---------------------------------------------------------------------------------------------+ 
| id | email    | firstname  | lastname  | city   | region   | 
|---------------------------------------------------------------------------------------------| 
| 1  | [email protected] | Martin  | Scorcese  | Paris   | Ile-de-France | 
| 2  | [email protected] | Robert  | De Niro  | Marseille  | Cote d'Azur  | 
| 3  | [email protected];com | Bruce   | Willis  | NULL   | NULL   | 
+---------------------------------------------------------------------------------------------+

我尝试以下SQL查询：

SELECT c.id, c.email, c.firstname, c.lastname, gc.name, gr.name 
FROM customer c 
LEFT JOIN address ad ON ad.id = c.customer_address 
JOIN sf_geo_cities gc ON gc.zipcode = ad.zipcode 
JOIN sf_geo_regions gr ON gr.id = gc.region_id 
WHERE no_pub = 0

但它需要很长时间，我不得不关闭mysql服务。连接乘以行可能存在问题。

是否有一个简单的查询来获取我期望的数据？

更新＃1： 这里是EXPLAIN要求在下面留言：

id select_type  table type possible_keys           key   key_len  ref       rows Extra 
1 SIMPLE   c  ref  PRIMARY,UNIQ_81398E097D3656A4,UNIQ_81398E09E7927C7... no_pub  1   const      136220 Using where 
1 SIMPLE   a  eq_ref PRIMARY             PRIMARY  8   evotest.c.account   1  Using index 
1 SIMPLE   ad  eq_ref PRIMARY             PRIMARY  8   evotest.c.customer_address 1  NULL 
1 SIMPLE   gc  ALL  zipcode             NULL  NULL  NULL      38194 Range checked for each record (index map: 0x8) 
1 SIMPLE   gr  eq_ref PRIMARY             PRIMARY  4   evotest.gc.region_id  1  NULL

更新＃2：数据库样本这里是我的数据库以最小的样本数据。

-- 
-- Structure de la table `account` 
-- 

CREATE TABLE IF NOT EXISTS `account` (
`id` bigint(20) unsigned NOT NULL, 
    `identifier` varchar(255) COLLATE utf8_bin NOT NULL 
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_bin AUTO_INCREMENT=315688 ; 

-- 
-- Structure de la table `customer` 
-- 

CREATE TABLE IF NOT EXISTS `customer` (
`id` bigint(20) unsigned NOT NULL, 
    `account` bigint(20) unsigned NOT NULL, 
    `customer_address` bigint(20) unsigned DEFAULT NULL, 
    `email` varchar(255) COLLATE utf8_bin NOT NULL, 
    `lastname` varchar(255) COLLATE utf8_bin NOT NULL, 
    `firstname` varchar(255) COLLATE utf8_bin NOT NULL, 
    `no_pub` tinyint(1) NOT NULL DEFAULT '0' 
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_bin AUTO_INCREMENT=315224 ; 

-- 
-- Structure de la table `address` 
-- 

CREATE TABLE IF NOT EXISTS `address` (
`id` bigint(20) unsigned NOT NULL, 
    `city` varchar(64) COLLATE utf8_bin DEFAULT NULL, 
    `street` varchar(255) COLLATE utf8_bin DEFAULT NULL, 
    `complement` varchar(128) COLLATE utf8_bin DEFAULT NULL, 
    `zipcode` varchar(16) COLLATE utf8_bin DEFAULT NULL, 
    `country_id` int(11) DEFAULT NULL, 
    `cedex` tinyint(1) NOT NULL DEFAULT '0', 
    `abroad` tinyint(1) NOT NULL DEFAULT '0' 
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_bin AUTO_INCREMENT=442743 ; 

-- 
-- Structure de la table `sf_geo_cities` 
-- 

CREATE TABLE IF NOT EXISTS `sf_geo_cities` (
`id` int(11) NOT NULL, 
    `region_id` int(11) NOT NULL, 
    `name` varchar(255) NOT NULL, 
    `slug` varchar(255) NOT NULL, 
    `zipcode` varchar(5) NOT NULL, 
    `insee_code` int(11) NOT NULL, 
    `latitude` float NOT NULL, 
    `longitude` float NOT NULL 
) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=38106 ; 

CREATE TABLE IF NOT EXISTS `sf_geo_regions` (
`id` int(11) NOT NULL, 
    `name` varchar(255) NOT NULL 
) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=25 ; 

CREATE TABLE IF NOT EXISTS `sf_geo_countries` (
`id` int(11) NOT NULL, 
    `code` int(11) NOT NULL, 
    `alpha2` varchar(2) NOT NULL, 
    `alpha3` varchar(3) NOT NULL, 
    `name_en` varchar(45) NOT NULL, 
    `name_fr` varchar(45) NOT NULL, 
    `is_default` tinyint(1) NOT NULL 
) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=242 ; 

CREATE TABLE IF NOT EXISTS `sf_user_data` (
`id` int(11) NOT NULL, 
    `user_id` bigint(20) unsigned NOT NULL, 
    `main_activity_type_id` int(11) DEFAULT NULL, 
    `main_activity_id` int(11) DEFAULT NULL 
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci AUTO_INCREMENT=19001 ; 


CREATE TABLE IF NOT EXISTS `sf_activity_types` (
`id` int(11) NOT NULL, 
    `name` varchar(255) COLLATE utf8_unicode_ci NOT NULL, 
    `identifier` varchar(255) COLLATE utf8_unicode_ci NOT NULL COMMENT 'Ne doit pas être modifié, il s agit de la clé dans le tableau de constantes $constants stockant les taux dans l entité Calculator' 
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci AUTO_INCREMENT=3 ; 

CREATE TABLE IF NOT EXISTS `sf_activities` (
`id` int(11) NOT NULL, 
    `name` varchar(255) COLLATE utf8_unicode_ci NOT NULL, 
    `asks_for_custom` tinyint(1) NOT NULL DEFAULT '0' 
) ENGINE=InnoDB DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci AUTO_INCREMENT=27 ; 

-- 
-- Index pour les tables exportées 
-- 

ALTER TABLE `account` 
ADD PRIMARY KEY (`id`), ADD UNIQUE KEY `identifier_UNIQUE` (`identifier`); 

ALTER TABLE `customer` 
ADD PRIMARY KEY (`id`), ADD UNIQUE KEY `UNIQ_81398E097D3656A4` (`account`), ADD UNIQUE KEY `UNIQ_81398E09E7927C74` (`email`), ADD UNIQUE KEY `UNIQ_81398E091193CB3F` (`customer_address`), ADD KEY `no_pub` (`no_pub`); 

ALTER TABLE `address` 
ADD PRIMARY KEY (`id`), ADD KEY `IDX_D4E6F81F92F3E70` (`country_id`), ADD KEY `zipcode` (`zipcode`); 

ALTER TABLE `sf_geo_cities` 
ADD PRIMARY KEY (`id`), ADD KEY `IDX_B56556A198260155` (`region_id`), ADD KEY `zipcode` (`zipcode`); 

ALTER TABLE `sf_geo_regions` 
ADD PRIMARY KEY (`id`); 

ALTER TABLE `sf_geo_countries` 
ADD PRIMARY KEY (`id`), ADD KEY `IDX_F86325E277153098` (`code`), ADD KEY `IDX_F86325E2B762D672` (`alpha2`), ADD KEY `IDX_F86325E2C065E6E4` (`alpha3`); 

ALTER TABLE `sf_user_data` 
ADD PRIMARY KEY (`id`), ADD UNIQUE KEY `UNIQ_E904BFD1A76ED395` (`user_id`), ADD KEY `IDX_E904BFD12E864BE8` (`main_activity_type_id`), ADD KEY `IDX_E904BFD15543A800` (`main_activity_id`); 

ALTER TABLE `sf_activity_types` 
ADD PRIMARY KEY (`id`); 

ALTER TABLE `sf_activities` 
ADD PRIMARY KEY (`id`); 

-- 
-- Contraintes pour les tables exportées 
-- 

ALTER TABLE `customer` 
ADD CONSTRAINT `FK_81398E091193CB3F` FOREIGN KEY (`customer_address`) REFERENCES `address` (`id`), 
ADD CONSTRAINT `FK_81398E097D3656A4` FOREIGN KEY (`account`) REFERENCES `account` (`id`); 

ALTER TABLE `address` 
ADD CONSTRAINT `FK_D4E6F81F92F3E70` FOREIGN KEY (`country_id`) REFERENCES `sf_geo_countries` (`id`); 

ALTER TABLE `sf_geo_cities` 
ADD CONSTRAINT `FK_B56556A198260155` FOREIGN KEY (`region_id`) REFERENCES `sf_geo_regions` (`id`); 

ALTER TABLE `sf_user_data` 
ADD CONSTRAINT `FK_E904BFD12E864BE8` FOREIGN KEY (`main_activity_type_id`) REFERENCES `sf_activity_types` (`id`), 
ADD CONSTRAINT `FK_E904BFD15543A800` FOREIGN KEY (`main_activity_id`) REFERENCES `sf_activities` (`id`), 
ADD CONSTRAINT `FK_E904BFD1A76ED395` FOREIGN KEY (`user_id`) REFERENCES `account` (`id`); 


INSERT INTO `account` (`id`, `identifier`) VALUES ('1', '[email protected]'), ('2', '[email protected]'), ('3', '[email protected]'); 

INSERT INTO `sf_geo_countries` (`id`, `code`, `alpha2`, `alpha3`, `name_en`, `name_fr`, `is_default`) VALUES ('1', '1', 'FR', 'FRA', 'France', 'France', '1'); 

INSERT INTO `address` (`id`, `city`, `street`, `complement`, `zipcode`, `country_id`, `cedex`, `abroad`) VALUES ('1', 'Paris', '1 rue de Paris', NULL, '75001', '1', '0', '0'), ('2', 'Marseille', '1 rue de Marseille', NULL, '13000', '1', '0', '0'); 

INSERT INTO `customer` (`id`, `account`, `customer_address`, `email`, `lastname`, `firstname`, `no_pub`) VALUES ('1', '1', '1', '[email protected]', 'Scorcese', 'Martin', '0'), ('2', '2', '2', '[email protected]', 'De Niro', 'Robert', '0'), ('3', '3', NULL, '[email protected]', 'Willis', 'Bruce', '0'); 

INSERT INTO `sf_activities` (`id`, `name`, `asks_for_custom`) VALUES ('1', 'Activity #1', '0'), ('2', 'Activity #2', '0'); 

INSERT INTO `sf_activity_types` (`id`, `name`, `identifier`) VALUES ('1', 'Activity Type #1', 'activity-type-1'), ('2', 'Activity Type #2', 'activity-type-2'); 

INSERT INTO `sf_geo_regions` (`id`, `name`) VALUES ('1', 'Ile-de-France'), ('2', 'Cote d''Azur'); 

INSERT INTO `sf_geo_cities` (`id`, `region_id`, `name`, `slug`, `zipcode`, `insee_code`, `latitude`, `longitude`) VALUES ('1', '1', 'Paris', 'paris', '75001', '1', '0', '0'), ('2', '2', 'Marseille', 'marseille', '13000', '2', '0', '0'); 

INSERT INTO `sf_user_data` (`id`, `user_id`, `main_activity_type_id`, `main_activity_id`) VALUES ('1', '1', '1', '1'), ('2', '3', '2', '2');

使用这个最小量的数据，我可以运行下面的查询，它返回我想要的所有东西。但是，这个查询在我真正的数据库300K +客户和400K +地址

年龄运行

SELECT c.id, c.email, c.firstname, c.lastname, acttypes.name AS activity_type, act.name AS activity, gc.name AS city, gr.name AS region 
FROM customer c 
JOIN account a ON a.id = c.account 
LEFT JOIN sf_user_data ud ON ud.user_id = a.id 
LEFT JOIN sf_activity_types acttypes ON acttypes.id = ud.main_activity_type_id 
LEFT JOIN sf_activities act ON act.id = ud.main_activity_id 
LEFT JOIN address ad ON ad.id = c.customer_address 
LEFT JOIN sf_geo_cities gc ON gc.zipcode = ad.zipcode 
LEFT JOIN sf_geo_regions gr ON gr.id = gc.region_id 
WHERE no_pub = 0

更新＃3：跟踪连接问题

这个查询运行速度快：

SELECT 
    c.id 
    ,c.email 
    ,c.firstname 
    ,c.lastname 
    ,acttypes.name AS activity_type 
    ,act.name AS activity 
    ,ad.zipcode AS address_zipcode 
-- ,gc.name AS city 
-- ,gr.name AS region  
FROM 
    customer c 
JOIN account a ON a.id = c.account 
    LEFT JOIN sf_user_data ud ON ud.user_id = a.id 
    LEFT JOIN sf_activity_types acttypes ON acttypes.id = ud.main_activity_type_id 
    LEFT JOIN sf_activities act ON act.id = ud.main_activity_id 
    LEFT JOIN address ad ON ad.id = c.customer_address 
-- LEFT JOIN sf_geo_cities gc ON gc.zipcode = ad.zipcode 
-- LEFT JOIN sf_geo_regions gr ON gr.id = gc.region_id 
WHERE 
    no_pub = 0

这个查询跑得也快：

SELECT 
    c.id 
    ,c.email 
    ,c.firstname 
    ,c.lastname 
-- ,acttypes.name AS activity_type 
-- ,act.name AS activity 
    ,ad.zipcode AS address_zipcode 
    ,gc.name AS city 
-- ,gr.name AS region  
FROM 
    customer c 
JOIN account a ON a.id = c.account 
-- LEFT JOIN sf_user_data ud ON ud.user_id = a.id 
-- LEFT JOIN sf_activity_types acttypes ON acttypes.id = ud.main_activity_type_id 
-- LEFT JOIN sf_activities act ON act.id = ud.main_activity_id 
    LEFT JOIN address ad ON ad.id = c.customer_address 
    LEFT JOIN sf_geo_cities gc ON gc.zipcode = ad.zipcode 
-- LEFT JOIN sf_geo_regions gr ON gr.id = gc.region_id 
WHERE 
    no_pub = 0

这个查询将永远运行下去：

SELECT 
    c.id 
    ,c.email 
    ,c.firstname 
    ,c.lastname 
    ,acttypes.name AS activity_type 
    ,act.name AS activity 
    ,ad.zipcode AS address_zipcode 
    ,gc.name AS city 
-- ,gr.name AS region  
FROM 
    customer c 
JOIN account a ON a.id = c.account 
    LEFT JOIN sf_user_data ud ON ud.user_id = a.id 
    LEFT JOIN sf_activity_types acttypes ON acttypes.id = ud.main_activity_type_id 
    LEFT JOIN sf_activities act ON act.id = ud.main_activity_id 
    LEFT JOIN address ad ON ad.id = c.customer_address 
    LEFT JOIN sf_geo_cities gc ON gc.zipcode = ad.zipcode 
-- LEFT JOIN sf_geo_regions gr ON gr.id = gc.region_id 
WHERE 
    no_pub = 0

加入的活动都OK，连接上的地址是好的，但要使用所有这些连接在一起不起作用。

来源

2015-07-28 VaN

您是否将索引添加到表中？ – Jens

你有什么指数？ – Kickstart

显示'create table'语法。显示'explain'的输出。 – GhostGambler

正如我的评论中提到的，非常重要的一点是返回多少条记录。一条语句中的记录太多可能会导致问题，如果您分页结果，则一次选择n条记录可能会更好。

要对查询进行疑难解答，请将其加入连接以尝试确定何时性能下降。开始于：

SELECT 
    c.id 
    ,c.email 
    ,c.firstname 
    ,c.lastname 
-- ,acttypes.name AS activity_type 
-- ,act.name AS activity 
-- ,gc.name AS city 
-- ,gr.name AS region  
FROM 
    customer c 
-- JOIN account a ON a.id = c.account 
-- LEFT JOIN sf_user_data ud ON ud.user_id = a.id 
-- LEFT JOIN sf_activity_types acttypes ON acttypes.id = ud.main_activity_type_id 
-- LEFT JOIN sf_activities act ON act.id = ud.main_activity_id 
-- LEFT JOIN address ad ON ad.id = c.customer_address 
-- LEFT JOIN sf_geo_cities gc ON gc.zipcode = ad.zipcode 
-- LEFT JOIN sf_geo_regions gr ON gr.id = gc.region_id 
WHERE 
    no_pub = 0

然后取消注释一次加入，直到您的查询执行得非常慢。分析该查询并查看是否可以使用索引进行改进。然后继续取消注释连接，直到您有完整查询。

来源

2015-07-29 08:22:44 Tobsey

试图限制连接似乎是一个值得的想法。希望能帮助追踪哪些连接导致问题。 – Kickstart

要回答您的评论，有285972名no_pub = 0的客户。我会尝试按照您的方式一次取消注释1，并跟踪性能问题。会回来发布我发现的内容。 – VaN

刚刚更新了我的原始帖子，更新＃3部分。加入活动是好的，加入地址是好的，使用它们都行不通。 – VaN

不能使连接正常工作

回答

相关问题