This query pops up in my slow query logs:
SELECT
COUNT(*) AS ord开发者_运维百科ersCount,
SUM(ItemsPrice + COALESCE(extrasPrice, 0.0)) AS totalValue,
SUM(ItemsPrice) AS totalValue,
SUM(std_delivery_charge) AS totalStdDeliveryCharge,
SUM(extra_delivery_charge) AS totalExtraDeliveryCharge,
this_.type AS y5_,
this_.transmissionMethod AS y6_,
this_.extra_delivery AS y7_
FROM orders this_
WHERE this_.deliveryDate BETWEEN '2010-01-01 00:00:00' AND '2010-09-01 00:00:00'
AND this_.status IN(1, 3, 2, 10, 4, 5, 11)
AND this_.senderShop_id = 10017
GROUP BY this_.type, this_.transmissionMethod, this_.extra_delivery
ORDER BY this_.deliveryDate DESC;
The table is InnoDB and has about 880k rows and takes between 9-12 seconds to execute. I tried adding the following index ALTER TABLE orders ADD INDEX _deliverydate_senderShopId_status ( deliveryDate , senderShop_id , status, type, transmissionMethod, extra_delivery);
with no practical gains. Any help and/or suggestion is welcomed
Here is the query execution plan right now:
id select_type table type possible_keys key key_len ref rows filtered Extra 1 SIMPLE this_ ref FKC3DF62E57562BA6F 8 const 139894 100.00 Using where; Using temporary; Using filesort
I took out the possible_keys value out of the text because i think it listed all the indexes in the table. The key used (FKC3DF62E57562BA6F) looks like
Keyname Type Unique Packed Field Cardinality Collation Null Comment FKC3DF62E57562BA6F BTREE No No senderShop_id 4671 A
I'll tell you one thing that you can look at for increasing the speed.
You only generally have NULL
values in the data for either unknown or non-applicable rows. It appears to me that, since you're treating NULL
as 0
anyway, you should think about getting rid of them and making sure that all extrasPrice
values are 0
where they were previously NULL
so that you can get rid of the time penalty of the coalesce
.
In fact, you could go one step further and introduce another column called totalPrice
which you set with an insert/update trigger to the actual value ItemsPrice + extrasPrice
or (ItemsPrice + COALESCE(extrasPrice,0.0)
if you still need nullability of extrasPrice
).
Then, you can simply use:
SELECT
COUNT(*) AS ordersCount,
SUM(totalPrice) AS totalValue,
SUM(ItemsPrice) AS totalValue2,
:
(I'm not sure you should have two output columns with the same name or whether that was a typo, that's going to be, at worst, an error, at best, confusing).
This moves the cost of the calculation to insert/update time rather than select time and amortises that cost over all the selects - most database tables are read far more often than written. The consistency of the data is maintained due to the trigger and the performance should be better, at the cost of some storage requirements.
But, since the vast majority of database questions are "How can I get more speed?" rather than "How can I use less disk?", that's often a good idea.
Another suggestion is to provide a non-composite index on the column that reduces your result set the fastest (high cardinality). In other words, if you store only two weeks worth of data (14 different dates) in your table but 400 different shops, you should have an index on senderShop_id
and make sure your statistics are up to date.
This should cause the DBMS execution engine to whittle down the result set using that key so that subsequent operations are faster.
A composite index on deliveryDate,senderShop_id,...
will not be able to use senderShop_id
to whittle down the results because the key ordering will be senderShop_id
within deliveryDate
.
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