我试图优化此查询,它会从building_rent_prices和building_weather返回多行,然后将它们分组并计算其字段的平均值。到目前为止,这些表都在一百万行以下,但它需要几秒钟,有谁知道我如何从复合索引优化这个或重写查询?我假设它应该可以是一个100毫秒或更快的查询,但到目前为止似乎它不能
SELECT b.*
, AVG(r.rent)
, AVG(w.high_temp)
FROM buildings b
LEFT
JOIN building_rent_prices r
ON r.building_id = b.building_id
LEFT
JOIN building_weather w
ON w.building_id = b.building_id
WHERE w.date BETWEEN CURDATE() AND CURDATE + INTERVAL 4 DAY
AND r.date BETWEEN CURDATE() AND CURDATE + INTERVAL 10 day
GROUP
BY b.building_id
ORDER
BY AVG(r.rent) / b.square_feet DESC
LIMIT 10;
解释如下:
1 SIMPLE building_rent_prices范围
1 SIMPLE buildings eq_ref
1 SIMPLE building_weather ref
使用where;使用索引;使用临时;使用filesort
使用
使用where;使用索引
我正在处理一些测试数据,这是创建表
CREATE TABLE building(
building_id INT PRIMARY KEY AUTO_INCREMENT,
name VARCHAR(255),
square_feet INT
);
CREATE TABLE building_weather(
building_weather_id INT PRIMARY KEY AUTO_INCREMENT,
building_id INT,
weather_date DATE,
high_temp INT
);
CREATE TABLE building_rates(
building_rate_id INT PRIMARY KEY AUTO_INCREMENT,
building_id INT,
weather_date DATE,
rate double
);
ALTER TABLE building_rates INDEX(building_id);
ALTER TABLE buildings INDEX(building_id);
ALTER TABLE building_weather INDEX(building_id);
这似乎在不到索引的情况下根据DRapp的答案在1秒内工作(我还需要测试它的有效性)
select
B.*,
BRP.avgRent,
BW.avgTemp
from
( select building_id,
AVG( rent ) avgRent
from
building_rent_prices
where
date BETWEEN CURDATE() AND CURDATE() + 10
group by
building_id
order by
building_id ) BRP
JOIN buildings B
on BRP.building_id = B.building_id
left join ( select building_id,
AVG( hi_temp ) avgTemp
from building_weather
where date BETWEEN CURDATE() AND CURDATE() + 10
group by building_id) BW
on BRP.building_id = BW.building_id
GROUP BY BRP.building_id
ORDER BY BRP.avgRent / 1 DESC
LIMIT 10;
答案 0 :(得分:1)
首先,您对基于WEATHER的表的查询仅为4天,RENT PRICES表为10天。由于两者之间没有任何连接关联,因此每个建筑物ID将产生40个记录的笛卡尔结果。这是故意还是仅仅被认定为哎呀......
其次,我会调整查询,如下所示,但我也调整了两个天气和租金价格表以反映相同的日期范围。我首先通过构建和日期查询价格和组的子查询,然后加入到建筑物,然后按建筑物和日期分组的另一个子查询天气。但在这里,我从租金价格子查询加入到建筑物ID和日期的天气子查询,因此它最多将保持1:1的比例。我不知道为什么天气甚至是跨越日期范围的考虑因素。
但是为了帮助索引,我建议以下
Table Index on
buildings (Building_ID) <-- probably already exists as a PK
building_rent_prices (date, building_id, rent)
building_weather (date, building_id, hi_temp)
索引的目的是利用WHERE子句(首先是日期),然后是GROUP BY(建筑物ID),并且是COVERING INDEX(包括租金)。同样地,对于建筑气象表也是出于同样的原因。
select
B.*,
BRP.avgRent,
BW.avgTemp
from
( select building_id,
AVG( rent ) avgRent
from
building_rent_prices
where
date BETWEEN CURDATE() AND CURDATE() + INTERVAL 10 DAY
group by
building_id
order by
building_id ) BRP
JOIN buildings B
on BRP.building_id = B.building_id
left join ( select building_id,
AVG( hi_temp ) avgTemp
from
building_weather
where
date BETWEEN CURDATE() AND CURDATE() + INTERVAL 10 DAY
group by
building_id ) BW
on BRP.building_id = BW.building_id
GROUP BY
BRP.building_id
ORDER BY
BRP.avgRent / B.square_feet DESC
LIMIT 10;
...澄清
我无法保证执行顺序,但实质上是BPR和BW别名的两个(查询),它们将在任何连接发生之前快速完成并执行。如果您想要(在我的示例中)10天与每日加入的平均值,那么我已将“日期”作为组的一个组件删除,因此每个建筑物最多分别返回1个。
现在,以1:1:1的比例加入建筑物表将限制最终结果集中的记录。这应该照顾您对那些日子的平均值的关注。
答案 1 :(得分:1)
不要使用CURDATE + 4:
mysql> select CURDATE(), CURDATE() + 30, CURDATE() + INTERVAL 30 DAY;
+------------+----------------+-----------------------------+
| CURDATE() | CURDATE() + 30 | CURDATE() + INTERVAL 30 DAY |
+------------+----------------+-----------------------------+
| 2015-03-15 | 20150345 | 2015-04-14 |
+------------+----------------+-----------------------------+
将INDEX(building_id)
添加到第二个和第三个表格。
如果那些人没有解决它;回过头来修改查询和架构,我会更深入。
答案 2 :(得分:1)
让我们详细了解一下这个查询。您想要为每个建筑报告两种不同的平均值。您需要在单独的子查询中计算它们。如果你不这样做,你会得到笛卡尔组合爆炸。
一个是平均十一天的租金价格。您可以使用此子查询获取该数据:
SELECT building_id, AVG(rent) rent
FROM building_rent_prices
WHERE date BETWEEN CURDATE() AND CURDATE() + INTERVAL 10 DAY
GROUP BY building_id
此子查询可以由building_rent_prices
上的compound covering index优化,由(date, building_id, rent)
组成。
接下来是平均五天的温度。
SELECT building_id, AVG(high_temp) high_temp
FROM building_weather
WHERE date BETWEEN CURDATE() AND CURDATE() + INTERVAL 4 DAY
GROUP BY building_id
这可以通过覆盖building_weather
上的索引的复合优化,由(date, building_id, high_temp)
组成。
最后,您需要将这两个子查询连接到buildings
表以生成最终结果集。
SELECT buildings.*, a.rent, b.high_temp
FROM buildings
LEFT JOIN (
SELECT building_id, AVG(rent) rent
FROM building_rent_prices
WHERE date BETWEEN CURDATE() AND CURDATE() + INTERVAL 10 DAY
GROUP BY building_id
) AS a ON buildings.building_id = a.building_id
LEFT JOIN (
SELECT building_id, AVG(high_temp) high_temp
FROM building_weather
WHERE date BETWEEN CURDATE() AND CURDATE() + INTERVAL 4 DAY
GROUP BY building_id
) AS b ON buildings.building_id = b.building_id
ORDER BY a.rent / buildings.square_feet DESC
LIMIT 10
一旦优化了两个子查询,这个子查询除building_id
主键外不需要任何其他内容。
总之,要加快此查询,请创建building_rent_prices
和building_weather
查询中提到的两个复合索引。
答案 3 :(得分:0)
对于任何遇到与我类似问题的人来说,解决方案是使用building_id对要加入的每个表进行分组,这样您就可以按平均值加入一对一。如果您不希望结果在所有表中都没有数据,那么使用JOIN而不是LEFT JOIN的Ollie Jones查询是最接近的答案。另外我遇到的主要问题是我忘了在avg(low_temp)列上放置一个索引,所以INDEXES。我从中学到的是,如果你在select中做了一个聚合函数,它就属于你的索引。我添加了low_temp。
building_weather(date,building_id,hi_temp,low_temp)AS由Ollie和DR APP建议
ALTER TABLE building_weather ADD index(date, building_id, hi_temp, low_temp);
SELECT buildings.*, a.rent, b.high_temp, b.low_temp
FROM buildings
JOIN (
SELECT building_id, AVG(rent) rent
FROM building_rent_prices
WHERE date BETWEEN CURDATE() AND CURDATE() + INTERVAL 10 DAY
GROUP BY building_id
) AS a ON buildings.building_id = a.building_id
JOIN (
SELECT building_id, AVG(high_temp) high_temp, AVG(low_temp) low_temp
FROM building_weather
WHERE date BETWEEN CURDATE() AND CURDATE() + INTERVAL 4 DAY
GROUP BY building_id
) AS b ON buildings.building_id = b.building_id
ORDER BY a.rent / buildings.square_feet DESC
LIMIT 10