如何使用多个连接优化慢查询

Question

我的情况:

• 查询搜索大约90,000辆车
• 每次查询都需要很长时间
• 我已经在所有正在加入的字段上都有索引.

我该如何优化它？

这是查询:

SELECT vehicles.make_id,
       vehicles.fuel_id,
       vehicles.body_id,
       vehicles.transmission_id,
       vehicles.colour_id,
       vehicles.mileage,
       vehicles.vehicle_year,
       vehicles.engine_size,
       vehicles.trade_or_private,
       vehicles.doors,
       vehicles.model_id,
       Round(3959 * Acos(Cos(Radians(51.465436)) *
                         Cos(Radians(vehicles.gps_lat)) *
                                           Cos(
                                           Radians(vehicles.gps_lon) - Radians(
                                           -0.296482)) +
                               Sin(
                                      Radians(51.465436)) * Sin(
                               Radians(vehicles.gps_lat)))) AS distance
FROM   vehicles
       INNER JOIN vehicles_makes
         ON vehicles.make_id = vehicles_makes.id
       LEFT JOIN vehicles_models
         ON vehicles.model_id = vehicles_models.id
       LEFT JOIN vehicles_fuel
         ON vehicles.fuel_id = vehicles_fuel.id
       LEFT JOIN vehicles_transmissions
         ON vehicles.transmission_id = vehicles_transmissions.id
       LEFT JOIN vehicles_axles
         ON vehicles.axle_id = vehicles_axles.id
       LEFT JOIN vehicles_sub_years
         ON vehicles.sub_year_id = vehicles_sub_years.id
       INNER JOIN members
         ON vehicles.member_id = members.id
       LEFT JOIN vehicles_categories
         ON vehicles.category_id = vehicles_categories.id
WHERE  vehicles.status = 1
       AND vehicles.date_from < 1330349235
       AND vehicles.date_to > 1330349235
       AND vehicles.type_id = 1
       AND ( vehicles.price >= 0
             AND vehicles.price <= 1000000 )  

这是车辆表架构:

CREATE TABLE IF NOT EXISTS `vehicles` (
  `id` int(11) NOT NULL AUTO_INCREMENT,
  `number_plate` varchar(100) NOT NULL,
  `type_id` int(11) NOT NULL,
  `make_id` int(11) NOT NULL,
  `model_id` int(11) NOT NULL,
  `model_sub_type` varchar(250) NOT NULL,
  `engine_size` decimal(12,1) NOT NULL,
  `vehicle_year` int(11) NOT NULL,
  `sub_year_id` int(11) NOT NULL,
  `mileage` int(11) NOT NULL,
  `fuel_id` int(11) NOT NULL,
  `transmission_id` int(11) NOT NULL,
  `price` decimal(12,2) NOT NULL,
  `trade_or_private` tinyint(4) NOT NULL,
  `postcode` varchar(25) NOT NULL,
  `gps_lat` varchar(50) NOT NULL,
  `gps_lon` varchar(50) NOT NULL,
  `img1` varchar(100) NOT NULL,
  `img2` varchar(100) NOT NULL,
  `img3` varchar(100) NOT NULL,
  `img4` varchar(100) NOT NULL,
  `img5` varchar(100) NOT NULL,
  `img6` varchar(100) NOT NULL,
  `img7` varchar(100) NOT NULL,
  `img8` varchar(100) NOT NULL,
  `img9` varchar(100) NOT NULL,
  `img10` varchar(100) NOT NULL,
  `is_featured` tinyint(4) NOT NULL,
  `body_id` int(11) NOT NULL,
  `colour_id` int(11) NOT NULL,
  `doors` tinyint(4) NOT NULL,
  `axle_id` int(11) NOT NULL,
  `category_id` int(11) NOT NULL,
  `contents` text NOT NULL,
  `date_created` int(11) NOT NULL,
  `date_edited` int(11) NOT NULL,
  `date_from` int(11) NOT NULL,
  `date_to` int(11) NOT NULL,
  `member_id` int(11) NOT NULL,
  `inactive_id` int(11) NOT NULL,
  `status` tinyint(4) NOT NULL,
  PRIMARY KEY (`id`),
  KEY `type_id` (`type_id`),
  KEY `make_id` (`make_id`),
  KEY `model_id` (`model_id`),
  KEY `fuel_id` (`fuel_id`),
  KEY `transmission_id` (`transmission_id`),
  KEY `body_id` (`body_id`),
  KEY `colour_id` (`colour_id`),
  KEY `axle_id` (`axle_id`),
  KEY `category_id` (`category_id`),
  KEY `vehicle_year` (`vehicle_year`),
  KEY `mileage` (`mileage`),
  KEY `status` (`status`),
  KEY `date_from` (`date_from`),
  KEY `date_to` (`date_to`),
  KEY `trade_or_private` (`trade_or_private`),
  KEY `doors` (`doors`),
  KEY `price` (`price`),
  KEY `engine_size` (`engine_size`),
  KEY `sub_year_id` (`sub_year_id`),
  KEY `member_id` (`member_id`),
  KEY `date_created` (`date_created`)
) ENGINE=MyISAM  DEFAULT CHARSET=utf8 AUTO_INCREMENT=136237 ;

解释:

1   SIMPLE  vehicles    ref     type_id,make_id,status,date_from,date_to,price,mem...   type_id     4   const   85695   Using where
1   SIMPLE  members     index   PRIMARY     PRIMARY     4   NULL    3   Using where; Using index; Using join buffer
1   SIMPLE  vehicles_makes  eq_ref  PRIMARY     PRIMARY     4   tvs.vehicles.make_id    1   Using index
1   SIMPLE  vehicles_models     eq_ref  PRIMARY     PRIMARY     4   tvs.vehicles.model_id   1   Using index
1   SIMPLE  vehicles_fuel   eq_ref  PRIMARY     PRIMARY     4   tvs.vehicles.fuel_id    1   Using index
1   SIMPLE  vehicles_transmissions  eq_ref  PRIMARY     PRIMARY     4   tvs.vehicles.transmission_id    1   Using index
1   SIMPLE  vehicles_axles  eq_ref  PRIMARY     PRIMARY     4   tvs.vehicles.axle_id    1   Using index
1   SIMPLE  vehicles_sub_years  eq_ref  PRIMARY     PRIMARY     4   tvs.vehicles.sub_year_id    1   Using index
1   SIMPLE  vehicles_categories     eq_ref  PRIMARY     PRIMARY     4   tvs.vehicles.category_id    1   Using index

Answer 1

改进WHERE子句

您的EXPLAIN显示MySQL只使用一个索引(type_id)来选择与该WHERE子句匹配的行,即使该子句中有多个条件.

为了能够为WHERE子句中的所有条件使用索引,并尽可能快地减小结果集的大小,请在vehicles表的以下列中添加多列索引:

(status, date_from, date_to, type_id, price)

列应按最高基数的顺序排列.

例如,vehicles.date_from可能有更多不同的值status,所以把date_from列放在前面status,如下所示:

(date_from, date_to, price, type_id, status)

这应该减少查询执行的第一部分中返回的行,并且应该在EXPLAIN结果的第一行显示较低的行数.

您还会注意到MySQL将在EXPLAIN结果中使用WHERE的多列索引.如果不是偶然的话,你应该提示或强制多列索引.

删除不必要的JOIN

您似乎没有使用任何连接表中的任何字段,因此请删除连接.这将删除查询的所有其他工作,并将您简化为一个简单的执行计划(EXPLAIN结果中的一行).

每个JOINed表都会导致结果集的每行进行额外的查找.因此,如果WHERE子句从车辆中选择5,000行,因为您有8个连接到车辆,您将有5,000*8 = 40,000个查找.从您的数据库服务器要求很多.