mysql-在大表上用LEFT JOIN查询确实很慢
作者:互联网
以下查询大约需要12秒钟才能执行.我曾尝试优化,但未能做到.要连接的表相当大(> 8.000.000条记录).
SELECT
p0_.id AS id_0,
p0_.ean AS ean_1,
p0_.brand AS brand_2,
p0_.type AS type_3,
p0_.retail_price AS retail_price_4,
p0_.target_price AS target_price_5,
min(NULLIF(c1_.delivery_price, 0)) AS sclr_6,
COALESCE(((p0_.target_price - min(NULLIF(c1_.delivery_price, 0))) / p0_.target_price * -100), 0) AS sclr_7
FROM product p0_
LEFT JOIN crawl c1_ ON (
c1_.product_ean = p0_.ean AND (
c1_.crawl_date = p0_.last_crawl_date OR
p0_.last_crawl_date IS NULL
)
AND c1_.source_id IN (
SELECT o2_.source_id AS sclr_8
FROM organisation_source o2_
WHERE o2_.organisation_id = 5
)
)
WHERE p0_.organisation_id = 5 GROUP BY p0_.ean
我已经尝试过以许多不同的方式编写查询,但是不幸的是没有给我任何性能上的胜利.如果我在最后一个子查询中删除了子查询,那么它也无济于事.
请参见下面的EXPLAIN语句的输出:
+------+--------------+-------+------+---------------------------------------------------+------------------+---------+------------------------+--------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+------+--------------+-------+------+---------------------------------------------------+------------------+---------+------------------------+--------+-------------+
| 1 | PRIMARY | p0_ | ref | uniqueConstraint,IDX_D34A04AD9E6B1585 | uniqueConstraint | 5 | const | 69 | Using where |
| 1 | PRIMARY | c1_ | ref | IDX_product_ean,IDX_crawl_date | IDX_product_ean | 62 | admin_pricev-p.p0_.ean | 468459 | Using where |
| 2 | MATERIALIZED | o2_ | ref | PRIMARY,IDX_DD91A56E9E6B1585,IDX_DD91A56E953C1C61 | PRIMARY | 4 | const | 1 | Using index |
+------+--------------+-------+------+---------------------------------------------------+------------------+---------+------------------------+--------+-------------+
请参阅下面的产品和抓取表格的CREATE TABLE语句:
CREATE TABLE `product` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`organisation_id` int(11) DEFAULT NULL,
`ean` varchar(20) COLLATE utf8_unicode_ci NOT NULL,
`brand` varchar(50) COLLATE utf8_unicode_ci NOT NULL,
`type` varchar(50) COLLATE utf8_unicode_ci NOT NULL,
`retail_price` decimal(10,2) NOT NULL,
`target_price` decimal(10,2) NOT NULL,
`last_crawl_date` datetime DEFAULT NULL,
PRIMARY KEY (`id`),
UNIQUE KEY `uniqueConstraint` (`organisation_id`,`ean`),
KEY `IDX_D34A04AD9E6B1585` (`organisation_id`),
KEY `IDX_target_price` (`target_price`),
KEY `IDX_ean` (`ean`),
KEY `IDX_type` (`type`),
KEY `IDX_last_crawl_date` (`last_crawl_date`),
CONSTRAINT `FK_D34A04AD9E6B1585` FOREIGN KEY (`organisation_id`) REFERENCES `organisation` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=927 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci
CREATE TABLE `crawl` (
`id` int(11) NOT NULL AUTO_INCREMENT,
`source_id` int(11) DEFAULT NULL,
`store_id` int(11) DEFAULT NULL,
`product_ean` varchar(20) COLLATE utf8_unicode_ci NOT NULL,
`crawl_date` datetime NOT NULL,
`takeaway_price` decimal(10,2) DEFAULT NULL,
`delivery_price` decimal(10,2) DEFAULT NULL,
PRIMARY KEY (`id`),
KEY `IDX_B4E9F1C2953C1C61` (`source_id`),
KEY `IDX_B4E9F1C2B092A811` (`store_id`),
KEY `IDX_product_ean` (`product_ean`),
KEY `IDX_takeaway_price` (`takeaway_price`),
KEY `IDX_crawl_date` (`crawl_date`),
CONSTRAINT `FK_B4E9F1C2953C1C61` FOREIGN KEY (`source_id`) REFERENCES `source` (`id`),
CONSTRAINT `FK_B4E9F1C2B092A811` FOREIGN KEY (`store_id`) REFERENCES `store` (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=8606874 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci
任何人都知道如何提高此查询的性能吗?非常感谢!如果需要更多信息,请告诉我!
解决方法:
您可以将查询简化为:
SELECT . . .
FROM product p0_ LEFT JOIN
crawl c1_
ON c1_.product_ean = p0_.ean AND
c1_.crawl_date = p0_.last_crawl_date AND
EXISTS (SELECT 1
FROM organisation_source o2_
WHERE o2_.organisation_id = 5 AND c1_.source_id = o2_.source_id
)
WHERE p0_.organisation_id = 5
GROUP BY p0_.ean;
p0_.last_crawl_date IS NULL可能是不必要的.即使比较中为NULL,LEFT JOIN也会将所有行保留在第一个表中.您的逻辑匹配第二个表中的所有行(满足其他条件).那可能就是您想要的,但我猜不是.
在MySQL中,存在有时比在存在中更快,这就是为什么我重写了这一部分的原因.
对于此查询,您可以使用以下索引加快搜索速度:product(organisation_id,ean,last_crawl_date),爬网(product_ean,crawl_date,source_id)和organisation_source(source_id,organisation_id).
标签:large-data,performance,left-join,mysql 来源: https://codeday.me/bug/20191118/2031835.html