我正在使用此查询成功运行
select
hash,
SUM(DATE(TIMESTAMP) = CURDATE()) as today,
sum(DATE(TIMESTAMP) between DATE_SUB(CURDATE( ), INTERVAL 7 DAY) and DATE_SUB(CURDATE( ), INTERVAL 1 DAY)) as last_week
from behaviour
group by hash
having last_week > 0 and today > last_week
order by today desc
我正在努力优化它。
我正在尝试这样做,以避免last_week>0
没有运气的条款。我得到了“无效使用群组功能”
select
hash,
SUM(DATE(TIMESTAMP) = CURDATE()) as today,
sum(DATE(TIMESTAMP) between DATE_SUB(CURDATE( ), INTERVAL 7 DAY) and DATE_SUB(CURDATE( ), INTERVAL 1 DAY)) as last_week
from behaviour
where
and (sum(DATE(TIMESTAMP) between DATE_SUB(CURDATE( ), INTERVAL 4 DAY) and DATE_SUB(CURDATE( ), INTERVAL 1 DAY)) > 0)
group by hash
having today > last_week
order by today desc
我该如何优化它?因为在大表中执行大约需要1分钟。
答案 0 :(得分:3)
您希望在进行聚合之前过滤:
select hash,
sum(DATE(TIMESTAMP) = CURDATE()) as today,
sum(DATE(TIMESTAMP) between DATE_SUB(CURDATE( ), INTERVAL 7 DAY) and DATE_SUB(CURDATE( ), INTERVAL 1 DAY)) as last_week
from behaviour
where timestamp >= curdate() - interval 7 day
timestamp < curdate() + interval 1 day
group by hash
having today > last_week and last_week > 0
order by today desc;
这减少了group by
所需的数据量 - 这应该会显着提高性能。您可以使用(timestamp, hash)
上的索引进一步提高效果。
您仍需要having
子句,因为您需要在结果上添加其他过滤器。但是,性能增益来自聚合之前的过滤。