我有以下查询，尽管它的复杂性，但在以下形状中表现良好：
SELECT
`listings`.*,
`auth_agents`.*,
`symbols`.`code` AS `symbol_code`,
`symbols`.`text` AS `symbol_text`,
`symbols`.`position` AS `symbol_position`,
GROUP_CONCAT(DISTINCT IFNULL(`categories_countries`.`translation`, `c`.`name`) ORDER BY CASE WHEN `c`.`category_id` = 106 THEN 1 ELSE `c`.`category_id` END) as `category_names`,
`pv_1`.`value` AS `transaction_type_name`,
`pv_2`.`value` AS `property_type_name`,
`listings_statuses`.`name` AS `status`,
CONCAT(`pv_3`.`value`, 'property/', `listings`.`slug`, '/', `listings`.`listing_id`) AS `url`,
price_range(`listings`.`price_sales_min`, `listings`.`price_sales`, `symbols`.`code`, `symbols`.`position`, `listings`.`listings_price_qualifier_id`) AS `price_sales_range`,
price_range(`listings`.`price_lettings_min`, `listings`.`price_lettings`, `symbols`.`code`, `symbols`.`position`, `listings`.`listings_price_qualifier_id`) AS `price_lettings_range`,
summary(`listings`.`description`, `listings`.`summary`) AS `summary`,
short_title(`categories`.`name`, `categories`.`title`, `pv_1`.`value`, `listings`.`city`, `listings`.`region`, `listings`.`area`) AS `short_title`,
IF(`listings`.`listings_price_qualifier_id` = 2, TRUE, FALSE) AS `POA`,
IF((SELECT `listings_categories`.`listing_id` FROM `listings_categories` WHERE `listings_categories`.`listing_id` = `listings`.`listing_id` AND `listings_categories`.`category_id` = 124 LIMIT 1) IS NOT NULL, TRUE, FALSE) AS `serviced_office`,
GROUP_CONCAT(DISTINCT CONCAT_WS('|', `auth_agents_staff`.`auth_agents_staff_id`, `auth_staff`.`f_name`, `auth_staff`.`l_name`, `auth_staff`.`photo`)) AS `agents_staff`,
(SELECT CONCAT('http://cdn.commercialpeople.com/images/', `listings`.`auth_agent_id`, '/', `listings_media`.`filename`) FROM `listings_media` WHERE `listings_media`.`listing_id` = `listings`.`listing_id` ORDER BY `default` DESC LIMIT 1) AS `image`,
(SELECT COUNT(`listings_media`.`listings_media_id`) FROM `listings_media` WHERE `listings_media`.`listing_id` = `listings`.`listing_id` AND `listings_media`.`listings_media_type_id` = 1) AS `image_count`,
(SELECT COUNT(`listings_media`.`listings_media_id`) FROM `listings_media` WHERE `listings_media`.`listing_id` = `listings`.`listing_id` AND `listings_media`.`listings_media_type_id` = 3) AS `pdf_count`,
(SELECT COUNT(`listings_media`.`listings_media_id`) FROM `listings_media` WHERE `listings_media`.`listing_id` = `listings`.`listing_id` AND `listings_media`.`listings_media_type_id` = 4) AS `floor_plan_count`,
distance(`listings`.`lat`, `listings`.`lng`, 51.5073500, -0.1277600) AS `distance`
FROM `listings`
JOIN `listings_coords` ON `listings_coords`.`listing_id` = `listings`.`listing_id`
JOIN `auth_agents` ON `listings`.`auth_agent_id` = `auth_agents`.`auth_agent_id`
JOIN `branches` USING (`branch_id`)
LEFT JOIN `listings_auth_agents_staff` ON `listings_auth_agents_staff`.`listing_id` = `listings`.`listing_id`
LEFT JOIN `auth_agents_staff` ON `listings_auth_agents_staff`.`listing_id` IS NOT NULL AND `listings_auth_agents_staff`.`auth_agents_staff_id` = `auth_agents_staff`.`auth_agents_staff_id`
LEFT JOIN `auth` AS `auth_staff` ON `listings_auth_agents_staff`.`listing_id` IS NOT NULL AND `auth_agents_staff`.`auth_agents_staff_id` IS NOT NULL AND
`auth_staff`.`auth_id` = `auth_agents_staff`.`auth_id`
JOIN `parameters_values` AS `pv_1`
ON `pv_1`.`parameter_id` = 2 AND `pv_1`.`country_id` = 223 AND `pv_1`.`key` = `listings`.`transaction_type`
JOIN `parameters_values` AS `pv_2`
ON `pv_2`.`parameter_id` = 1 AND `pv_2`.`country_id` = 223 AND `pv_2`.`key` = `listings`.`property_type`
JOIN `parameters_values` AS `pv_3`
ON `pv_3`.`parameter_id` = 5 AND `pv_2`.`country_id` = 223
JOIN `countries` ON `listings`.`country_id` = `countries`.`country_id`
JOIN `countries_symbols` ON `countries`.`country_id` = `countries_symbols`.`country_id`
JOIN `symbols` ON `countries_symbols`.`symbol_id` = `symbols`.`symbol_id`
JOIN `listings_units` ON `listings`.`listings_unit_id` = `listings_units`.`listings_unit_id`
JOIN `listings_units` AS `user_units` ON `user_units`.`listings_unit_id` = 2
JOIN `listings_statuses` ON `listings`.`listings_status_id` = `listings_statuses`.`listings_status_id`
LEFT JOIN `listings_statuses_countries` ON `listings_statuses`.`listings_status_id` = `listings_statuses_countries`.`listings_status_id`
AND `listings_statuses_countries`.`country_id` = '223'
JOIN `listings_categories` ON `listings_categories`.`listing_id` = `listings`.`listing_id`
JOIN `categories` ON `categories`.`category_id` = `listings_categories`.`category_id`
JOIN `listings_categories` AS `lc` ON `lc`.`listing_id` = `listings`.`listing_id`
JOIN `categories` AS `c` ON `c`.`category_id` = `lc`.`category_id`
LEFT JOIN `categories_countries` ON `c`.`category_id` = `categories_countries`.`category_id` AND `categories_countries`.`country_id` = '223'
LEFT JOIN `listings_lettings`
ON (`listings`.`transaction_type` = 2 OR `listings`.`transaction_type` = 3) AND `listings_lettings`.`listing_id` = `listings`.`listing_id`
LEFT JOIN `listings_lettings_rent_frequencies`
ON (`listings`.`transaction_type` = 2 OR `listings`.`transaction_type` = 3) AND `listings_lettings_rent_frequencies`.`listings_lettings_rent_frequency_id` = `listings_lettings`.`listings_lettings_rent_frequency_id`
LEFT JOIN `listings_lettings_rent_frequencies` AS `llrf` ON `llrf`.`listings_lettings_rent_frequency_id` = 2
WHERE `listings`.`active` = 1 AND `listings`.`published_flag` = 1 AND
`listings`.`listings_status_id` = 1 AND
`listings`.`lat` BETWEEN 51.333436956522 AND 51.681263043478 AND
`listings`.`lng` BETWEEN -0.40717687879372 AND 0.15165687879372 AND
st_within(`listings_coords`.`coords`, @poly) AND
IF (`listings`.`transaction_type` = 2 || `listings`.`transaction_type` = 3,
`listings`.`price_lettings` * `listings_lettings_rent_frequencies`.`months` >= `llrf`.`months` * 500,
TRUE
) AND
IF(`listings_units`.`meters` IS NULL, TRUE, `listings`.`max_size` * `listings_units`.`meters` >= 100 * `user_units`.`meters`) AND
`listings`.`country_id` = 223
GROUP BY `listings`.`listing_id`
ORDER BY `listings`.`created_at`
LIMIT 10;
如您所见，第一个查询抓取多边形，然后通过空间函数在多边形搜索中使用该多边形。查询在aprox 0.06sec。
中执行但是，添加任何ORDER BY子句会导致性能急剧下降，最终会在17秒内执行。
现在 - 我已经完成了一些研究，我知道这可能与聚簇索引有关，或者只是添加正确的索引，但是花了几个小时才尝试返回ID＆和然后运行另一个查询来获取数据或者只是删除GROUP BY并删除连接（这似乎最初有效，但当我加入几个表进行价格搜索时出现了另一个性能问题） - 我放弃了
我试图在没有分组的情况下运行查询，然后对结果进行分组，例如：
SELECT * FROM ( *the query* ) AS results GROUP BY listing_id
但我得到了相同的结果。
有没有办法优化查询，所以我可以进行分组和排序？
这是EXPLAIN：
| 1 | PRIMARY | countries | const | PRIMARY | PRIMARY | 4 | const | 1 | Using index; Using temporary; Using filesort |
| 1 | PRIMARY | user_units | const | PRIMARY | PRIMARY | 4 | const | 1 | NULL |
| 1 | PRIMARY | listings_statuses | const | PRIMARY | PRIMARY | 4 | const | 1 | NULL |
| 1 | PRIMARY | listings_statuses_countries | const | PRIMARY,country_id | PRIMARY | 8 | const,const | 1 | Using index |
| 1 | PRIMARY | countries_symbols | ref | PRIMARY,symbol_id | PRIMARY | 4 | const | 1 | Using index |
| 1 | PRIMARY | symbols | eq_ref | PRIMARY | PRIMARY | 4 | cp_staging.countries_symbols.symbol_id | 1 | NULL |
| 1 | PRIMARY | pv_2 | ref | parameter_id,country_id | parameter_id | 8 | const,const | 2 | NULL |
| 1 | PRIMARY | pv_1 | ref | parameter_id,country_id | parameter_id | 8 | const,const | 3 | NULL |
| 1 | PRIMARY | pv_3 | ref | parameter_id | parameter_id | 4 | const | 4 | NULL |
| 1 | PRIMARY | listings | range | SEE BELOW | compound | 20 | NULL | 2594 | Using index condition; Using where; Using join buffer (Block Nested Loop) |
| 1 | PRIMARY | listings_units | eq_ref | PRIMARY | PRIMARY | 4 | cp_staging.listings.listings_unit_id | 1 | Using where |
| 1 | PRIMARY | listings_coords | eq_ref | PRIMARY,coords | PRIMARY | 4 | cp_staging.listings.listing_id | 1 | Using where |
| 1 | PRIMARY | auth_agents | eq_ref | PRIMARY | PRIMARY | 4 | cp_staging.listings.auth_agent_id | 1 | NULL |
| 1 | PRIMARY | branches | eq_ref | PRIMARY | PRIMARY | 4 | cp_staging.listings.branch_id | 1 | Using index |
| 1 | PRIMARY | listings_categories | ref | PRIMARY,listings_categories_category_id_foreign | PRIMARY | 4 | cp_staging.listings.listing_id | 1 | Using index |
| 1 | PRIMARY | lc | ref | PRIMARY,listings_categories_category_id_foreign | PRIMARY | 4 | cp_staging.listings.listing_id | 1 | Using index |
| 1 | PRIMARY | listings_auth_agents_staff | ref | PRIMARY | PRIMARY | 4 | cp_staging.listings.listing_id | 1 | Using index |
| 1 | PRIMARY | categories | eq_ref | PRIMARY | PRIMARY | 4 | cp_staging.listings_categories.category_id | 1 | NULL |
| 1 | PRIMARY | c | eq_ref | PRIMARY | PRIMARY | 4 | cp_staging.lc.category_id | 1 | NULL |
| 1 | PRIMARY | auth_agents_staff | eq_ref | PRIMARY | PRIMARY | 4 | cp_staging.listings_auth_agents_staff.auth_agents_staff_id | 1 | Using where |
| 1 | PRIMARY | auth_staff | eq_ref | PRIMARY | PRIMARY | 4 | cp_staging.auth_agents_staff.auth_id | 1 | Using where |
| 1 | PRIMARY | categories_countries | eq_ref | PRIMARY,categories_countries_country_id_foreign | PRIMARY | 8 | cp_staging.lc.category_id,const | 1 | NULL |
| 1 | PRIMARY | listings_lettings | ref | listings_lettings_listing_id_foreign | listings_lettings_listing_id_foreign | 4 | cp_staging.listings.listing_id | 1 | Using where |
| 1 | PRIMARY | listings_lettings_rent_frequencies | eq_ref | PRIMARY,listings_lettings_rent_frequencies_id_months | PRIMARY | 4 | cp_staging.listings_lettings.listings_lettings_rent_frequency_id | 1 | Using where |
| 1 | PRIMARY | llrf | const | PRIMARY,listings_lettings_rent_frequencies_id_months | PRIMARY | 4 | const | 1 | Using where |
| 5 | DEPENDENT SUBQUERY | listings_media | ref | listings_media_listing_id_foreign,listings_media_listings_media_type_id_foreign | listings_media_listing_id_foreign | 4 | func | 1 | Using where |
| 4 | DEPENDENT SUBQUERY | listings_media | ref | listings_media_listing_id_foreign,listings_media_listings_media_type_id_foreign | listings_media_listing_id_foreign | 4 | func | 1 | Using where |
| 3 | DEPENDENT SUBQUERY | listings_media | ref | listings_media_listing_id_foreign,listings_media_listings_media_type_id_foreign | listings_media_listing_id_foreign | 4 | func | 1 | Using where |
| 2 | DEPENDENT SUBQUERY | listings_categories | eq_ref | PRIMARY,listings_categories_category_id_foreign | PRIMARY | 8 | func,const | 1 | Using index |
listings表的第5列值（已拉出以便可以保留上表的格式）PRIMARY,listings_former_id_unique,listings_price_sales_index,listings_price_sales_min_index,listings_price_lettings_index,listings_price_lettings_min_index,listings_country_id_foreign,listings_agent_id_foreign,listings_listings_status_id_foreign,listings_listings_price_qualifier_id_foreign,listings_listings_unit_id_foreign,listings_listings_tenure_type_id_foreign,agents_staff_id,listings_listings_class_id_foreign_idx,listings_listings_location_type_id_foreign_idx,listings_listings_branch_id_foreign_idx,latlng,listings_city,listings_created_at,listings_country_created_at,listings_transaction_type,listings_listing_id_transaction_type,listings_listings_coords_id,listings_created_at_listing_id,compound
答案 0 :(得分：0)
socket.socket，listings，listings_lettings_rent_frequencies，llrf以外的所有表格。listings_units。如果我们可以让该查询合理地快速运行，那么请执行
listing_ids答案 1 :(得分：0)
我遗漏了所有可选位（也删除了GROUP BY，因为这是不必要的），它几乎归结为：
SET @poly = (SELECT `polygon` FROM locations WHERE location_id = 65);
SELECT
`listings`.`listing_id`
FROM `listings`
JOIN `listings_coords` ON `listings_coords`.`listing_id` = `listings`.`listing_id`
JOIN `listings_units` ON `listings`.`listings_unit_id` = `listings_units`.`listings_unit_id`
JOIN `listings_units` AS `user_units` ON `user_units`.`listings_unit_id` = 2
LEFT JOIN `listings_lettings`
ON (`listings`.`transaction_type` = 2 OR `listings`.`transaction_type` = 3) AND `listings_lettings`.`listing_id` = `listings`.`listing_id`
LEFT JOIN `listings_lettings_rent_frequencies`
ON (`listings`.`transaction_type` = 2 OR `listings`.`transaction_type` = 3) AND `listings_lettings_rent_frequencies`.`listings_lettings_rent_frequency_id` = `listings_lettings`.`listings_lettings_rent_frequency_id`
LEFT JOIN `listings_lettings_rent_frequencies` AS `llrf` ON `llrf`.`listings_lettings_rent_frequency_id` = 2
WHERE
`listings`.`lat` BETWEEN 51.333436956522 AND 51.681263043478 AND
`listings`.`lng` BETWEEN -0.40717687879372 AND 0.15165687879372 AND
st_within(`listings_coords`.`coords`, @poly) AND
(
`listings`.`transaction_type` = 1 OR
`listings`.`price_lettings` * `listings_lettings_rent_frequencies`.`months` >= `llrf`.`months` * 500
)
AND
(
`listings_units`.`meters` IS NULL OR
`listings`.`max_size` * `listings_units`.`meters` >= 100 * `user_units`.`meters`
)
AND
`listings`.`country_id` = 223
ORDER BY `listings`.`created_at`
LIMIT 10;
现在似乎没有ORDER BY子句减慢速度。目前的解释：
+----+-------------+------------------------------------+--------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------+---------+----------------------------------------------------------+------+----------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+------------------------------------+--------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------+---------+----------------------------------------------------------+------+----------------------------------------------------+
| 1 | SIMPLE | user_units | const | PRIMARY | PRIMARY | 4 | const | 1 | Using temporary; Using filesort |
| 1 | SIMPLE | listings | range | PRIMARY,listings_country_id_foreign,listings_listings_unit_id_foreign,latlng,listings_country_created_at,listings_country_units_created_at,listings_transaction_type,listings_listing_id_transaction_type,listings_lat_lng_created_at | latlng | 10 | NULL | 3728 | Using index condition; Using where |
| 1 | SIMPLE | listings_coords | eq_ref | PRIMARY,coords | PRIMARY | 4 | cp.listings.listing_id | 1 | Using where |
| 1 | SIMPLE | listings_lettings | ref | listings_lettings_listing_id_foreign | listings_lettings_listing_id_foreign | 4 | cp.listings.listing_id | 1 | Using where |
| 1 | SIMPLE | listings_lettings_rent_frequencies | eq_ref | PRIMARY | PRIMARY | 4 | cp.listings_lettings.listings_lettings_rent_frequency_id | 1 | Using where |
| 1 | SIMPLE | listings_units | ALL | PRIMARY | NULL | NULL | NULL | 6 | Using where; Using join buffer (Block Nested Loop) |
| 1 | SIMPLE | llrf | const | PRIMARY | PRIMARY | 4 | const | 1 | Using where |
+----+-------------+------------------------------------+--------+---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+--------------------------------------+---------+----------------------------------------------------------+------+----------------------------------------------------+
删除价格和尺寸条件会带来更好的性能，并且无需文件排序即可进行搜索。它可能与糟糕的索引有关，尽管正如所指出的那样 - 我确实有很多这样的索引。上述查询的当前性能是aprox 5s。同样删除st_within函数似乎解决了这个问题（0.047s）。正如你所说 - 我可以轻松地在子查询中执行初始搜索，获得所需的10个ID，并在外部查询中继续使用JOIN。
这是列表表的创建语句：
CREATE TABLE `listings` (
`listing_id` int(10) unsigned NOT NULL AUTO_INCREMENT,
`auth_agent_id` int(10) unsigned NOT NULL,
`country_id` int(10) unsigned NOT NULL,
`branch_id` int(10) unsigned DEFAULT NULL,
`property_type` tinyint(4) NOT NULL,
`listings_status_id` int(10) unsigned NOT NULL,
`listings_price_qualifier_id` int(10) unsigned NOT NULL,
`listings_tenure_type_id` int(10) unsigned DEFAULT NULL,
`listings_class_id` int(10) unsigned DEFAULT NULL,
`listings_location_type_id` int(10) unsigned DEFAULT NULL,
`transaction_type` enum('1','2','3') COLLATE utf8_bin NOT NULL,
`auth_agents_staff_id` int(10) unsigned DEFAULT NULL,
`published_flag` tinyint(1) NOT NULL,
`address_1` char(255) COLLATE utf8_bin DEFAULT NULL,
`address_2` char(255) COLLATE utf8_bin DEFAULT NULL,
`area` char(150) COLLATE utf8_bin DEFAULT NULL,
`city` char(255) COLLATE utf8_bin DEFAULT NULL,
`region` char(255) COLLATE utf8_bin DEFAULT NULL,
`postcode` char(255) COLLATE utf8_bin DEFAULT NULL,
`hide_address` tinyint(1) NOT NULL DEFAULT '0',
`street_view` tinyint(1) NOT NULL DEFAULT '1',
`lat` decimal(10,6) NOT NULL,
`lng` decimal(10,6) NOT NULL,
`price_sales` decimal(14,2) DEFAULT NULL,
`price_sales_min` decimal(10,2) DEFAULT NULL,
`price_lettings` decimal(10,2) DEFAULT NULL,
`price_lettings_min` decimal(10,2) DEFAULT NULL,
`price_per_unit_sales` decimal(9,2) DEFAULT NULL,
`price_per_unit_lettings` decimal(9,2) DEFAULT NULL,
`min_size` decimal(10,2) DEFAULT NULL,
`max_size` decimal(10,2) DEFAULT NULL,
`listings_unit_id` int(10) unsigned NOT NULL,
`summary` text COLLATE utf8_bin,
`description` text COLLATE utf8_bin,
`short_title` varchar(150) COLLATE utf8_bin DEFAULT NULL,
`title` varchar(200) COLLATE utf8_bin DEFAULT NULL,
`slug` varchar(200) COLLATE utf8_bin DEFAULT NULL,
`agent_ref` char(255) COLLATE utf8_bin DEFAULT NULL,
`active` tinyint(1) NOT NULL,
`created_at` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP,
`updated_at` timestamp NOT NULL DEFAULT '0000-00-00 00:00:00' ON UPDATE CURRENT_TIMESTAMP,
`former_id` int(11) DEFAULT NULL,
PRIMARY KEY (`listing_id`),
UNIQUE KEY `listings_transaction_listing_id` (`transaction_type`,`listing_id`),
UNIQUE KEY `listings_former_id_unique` (`former_id`),
KEY `listings_price_sales_index` (`price_sales`),
KEY `listings_price_sales_min_index` (`price_sales_min`),
KEY `listings_price_lettings_index` (`price_lettings`),
KEY `listings_price_lettings_min_index` (`price_lettings_min`),
KEY `listings_country_id_foreign` (`country_id`),
KEY `listings_agent_id_foreign` (`auth_agent_id`),
KEY `listings_listings_status_id_foreign` (`listings_status_id`),
KEY `listings_listings_price_qualifier_id_foreign` (`listings_price_qualifier_id`),
KEY `listings_listings_unit_id_foreign` (`listings_unit_id`),
KEY `listings_listings_tenure_type_id_foreign` (`listings_tenure_type_id`),
KEY `agents_staff_id` (`auth_agents_staff_id`),
KEY `listings_listings_class_id_foreign_idx` (`listings_class_id`),
KEY `listings_listings_location_type_id_foreign_idx` (`listings_location_type_id`),
KEY `listings_listings_branch_id_foreign_idx` (`branch_id`),
KEY `lat_lng_country_id_active_published` (`lat`,`lng`,`country_id`,`active`,`published_flag`),
CONSTRAINT `listings_agent_id_foreign` FOREIGN KEY (`auth_agent_id`) REFERENCES `auth_agents` (`auth_agent_id`),
CONSTRAINT `listings_country_id_foreign` FOREIGN KEY (`country_id`) REFERENCES `countries` (`country_id`),
CONSTRAINT `listings_ibfk_1` FOREIGN KEY (`auth_agents_staff_id`) REFERENCES `agents_staff` (`agents_staff_id`) ON DELETE SET NULL ON UPDATE SET NULL,
CONSTRAINT `listings_listings_branch_id_foreign` FOREIGN KEY (`branch_id`) REFERENCES `branches` (`branch_id`),
CONSTRAINT `listings_listings_class_id_foreign` FOREIGN KEY (`listings_class_id`) REFERENCES `listings_classes` (`listings_class_id`) ON DELETE NO ACTION ON UPDATE NO ACTION,
CONSTRAINT `listings_listings_location_type_id_foreign` FOREIGN KEY (`listings_location_type_id`) REFERENCES `listings_location_types` (`listings_location_type_id`) ON DELETE NO ACTION ON UPDATE NO ACTION,
CONSTRAINT `listings_listings_price_qualifier_id_foreign` FOREIGN KEY (`listings_price_qualifier_id`) REFERENCES `listings_price_qualifiers` (`listings_price_qualifier_id`),
CONSTRAINT `listings_listings_status_id_foreign` FOREIGN KEY (`listings_status_id`) REFERENCES `listings_statuses` (`listings_status_id`),
CONSTRAINT `listings_listings_tenure_type_id_foreign` FOREIGN KEY (`listings_tenure_type_id`) REFERENCES `listings_tenure_types` (`listings_tenure_type_id`),
CONSTRAINT `listings_listings_unit_id_foreign` FOREIGN KEY (`listings_unit_id`) REFERENCES `listings_units` (`listings_unit_id`)
) ENGINE=InnoDB AUTO_INCREMENT=34832 DEFAULT CHARSET=utf8 COLLATE=utf8_bin;