我一直在努力处理以下查询（以及其他一些类似的查询），我觉得我错过了一些东西，或者我使用了错误类型的数据库或其他东西。
该查询用于获取过去 10 年在英国与特定城镇每年的新电影总数和停止放映（关闭）的电影总数。多年来，这些查询也针对许多城镇和县运行。
其他查询做类似的事情，有时UNION ALL在查询的末尾添加 a 以获取打开或关闭的记录年份。
还有一些查询是针对月度数据和季度数据而不是年度数据运行的，还有一些查询只是比较特定季度（例如第三季度）或月份（例如三月）的历史开盘/关盘。
这是将 2012 年英国与伦敦进行比较的查询：
SELECT inc.opening_year as year, inc.number_of_films as opens,
diss.number_of_films as closures, inc.uk_films as uk_opens,
diss.uk_films as uk_closures
FROM
(SELECT film_db.opening_year, uk.number_of_films as uk_films,
COUNT(film_db.id_film_db) as number_of_films
FROM film_db
JOIN postcodes ON id_postcodes = opening_postcode_id
JOIN towns ON id_towns = town_id AND town = 'London'
JOIN (SELECT opening_year, COUNT(film_db.id_film_db) as number_of_films
FROM film_db
WHERE opening_year <= 2012 AND opening_year >= (2012 - 10)
GROUP BY opening_year
) uk ON uk.opening_year = film_db.opening_year
WHERE film_db.opening_year <= 2012 AND film_db.opening_year >= (2012 - 10)
GROUP BY film_db.opening_year
ORDER BY film_db.opening_year DESC
) inc
JOIN
(SELECT film_db.closing_year, uk.number_of_films as uk_films,
COUNT(film_db.id_film_db) as number_of_films
FROM film_db
JOIN postcodes ON id_postcodes = postcode_id
JOIN towns ON id_towns = town_id AND town = 'London'
JOIN (SELECT closing_year, COUNT(film_db.id_film_db) as number_of_films
FROM film_db
WHERE film_db.closing_year <= 2012 AND film_db.closing_year >= (2012 - 10)
GROUP BY film_db.closing_year
) uk ON uk.closing_year = film_db.closing_year
WHERE film_db.closing_year <= 2012 AND film_db.closing_year >= (2012 - 10)
GROUP BY film_db.closing_year
ORDER BY film_db.closing_year DESC
) diss ON diss.closing_year = inc.opening_year
数据库SHOW CREATE TABLE输出如下：
电影数据库：
CREATE TABLE `film_db` (
`id_film_db` int(11) NOT NULL AUTO_INCREMENT,
`film_name` varchar(255) DEFAULT NULL,
`category` varchar(100) DEFAULT NULL,
`status` varchar(50) DEFAULT NULL,
`opening_date` date DEFAULT NULL,
`opening_year` int(4) DEFAULT NULL,
`opening_month` int(2) DEFAULT NULL,
`opening_quarter` int(1) DEFAULT NULL,
`closing_date` date DEFAULT NULL,
`closing_year` int(4) DEFAULT NULL,
`closing_month` int(2) DEFAULT NULL,
`closing_quarter` int(1) DEFAULT NULL,
`datetime` timestamp NULL DEFAULT CURRENT_TIMESTAMP,
`postcode_id` int(4) NOT NULL DEFAULT '0',
`opening_postcode_id` int(4) NOT NULL DEFAULT '0',
PRIMARY KEY (`id_film_db`),
KEY `opening_date` (`opening_date`),
KEY `status` (`status`),
KEY `postcode_id` (`postcode_id`),
KEY `type` (`category`),
KEY `opening_year` (`opening_year`),
KEY `opening_month` (`opening_month`,`opening_year`) USING BTREE,
KEY `opening_quarter` (`opening_quarter`,`opening_year`) USING BTREE,
KEY `closing_year` (`closing_year`),
KEY `closing_month` (`closing_year`,`closing_month`),
KEY `closing_quarter` (`closing_year`,`closing_quarter`),
KEY `closing_date` (`closing_date`),
KEY `opening_closing_date` (`opening_date`,`closing_date`),
KEY `opening_postcode` (`opening_postcode_id`),
FULLTEXT KEY `film_name` (`film_name`)
) ENGINE=MyISAM AUTO_INCREMENT=10649173 DEFAULT CHARSET=utf8
邮编：
CREATE TABLE `postcodes` (
`id_postcodes` int(4) NOT NULL AUTO_INCREMENT,
`postcode` varchar(9) NOT NULL,
`town_id` int(4) NOT NULL,
`lat` float NOT NULL,
`lng` float NOT NULL,
PRIMARY KEY (`id_postcodes`),
UNIQUE KEY `postcode` (`postcode`) USING BTREE,
KEY `town` (`town_id`)
) ENGINE=MyISAM AUTO_INCREMENT=5705 DEFAULT CHARSET=latin1
城市：
CREATE TABLE `towns` (
`id_towns` int(4) NOT NULL AUTO_INCREMENT,
`town` varchar(150) NOT NULL,
`county_id` int(3) NOT NULL,
PRIMARY KEY (`id_towns`),
KEY `county` (`county_id`)
) ENGINE=MyISAM AUTO_INCREMENT=1606 DEFAULT CHARSET=latin1
这是EXPLAIN EXTENDED输出：
1 PRIMARY <derived2> ALL 11 100
1 PRIMARY <derived4> ALL 11 100 Using where; Using join buffer
4 DERIVED <derived5> ALL 11 100 Using where; Using temporary; Using filesort
4 DERIVED film_db ref postcode_id,closing_year,closing_month,closing_quarter closing_year 5 uk.closing_year 2 100 Using where
4 DERIVED postcodes eq_ref PRIMARY,town PRIMARY 4 film_db.postcode_id 1 100
4 DERIVED towns eq_ref PRIMARY PRIMARY 4 postcodes.town_id 1 100 Using where
5 DERIVED film_db ALL closing_year,closing_month,closing_quarter 9895680 47.66 Using where; Using temporary; Using filesort
2 DERIVED <derived3> ALL 11 100 Using where; Using temporary; Using filesort
2 DERIVED film_db ref opening_year,opening_postcode opening_year 5 uk.opening_year 3 100 Using where
2 DERIVED postcodes eq_ref PRIMARY,town PRIMARY 4 film_db.opening_postcode_id 1 100
2 DERIVED towns eq_ref PRIMARY PRIMARY 4 postcodes.town_id 1 100 Using where
3 DERIVED film_db ALL opening_year 9895680 54.53 Using where; Using temporary; Using filesort
如您所见，MySQL 认为对film_db表进行过滤不会产生任何性能差异，因此它不使用任何键。
所以：
我可以改进此查询以更好地使用索引吗？
我可以改进索引以使查询运行得更快吗？
是否应该使用另一种数据库类型（不是 MySQL）来代替这种查询，我最感兴趣的是计算具有复杂条件和连接的条目数？