About the system:
-The system has a total of 8 tables
– Users
– Tutor_Details (Tutors are a type of User,Tutor_Details table is linked to Users)
– learning_packs, (stores packs created by tutors)
– learning_packs_tag_relations, (holds tag relations meant for search)
– tutors_tag_relations and tags and
orders (containing purchase details of tutor’s packs),
order_details linked to orders and tutor_details.
For a more clear idea about the tables involved please check the The tables section in the end.
-A tags based search approach is being followed.Tag relations are created when new tutors register and when tutors create packs (this makes tutors and packs searcheable). For details please check the section How tags work in this system? below.
Following is a simpler representation (not the actual) of the more complex query which I am trying to optimize:- I have used statements like explanation of parts in the query
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select
SUM(DISTINCT( t.tag LIKE "%Dictatorship%" )) as key_1_total_matches,
SUM(DISTINCT( t.tag LIKE "%democracy%" )) as key_2_total_matches,
td.*, u.*, count(distinct(od.id_od)), `if (lp.id_lp > 0) then some conditional logic on lp fields else 0 as tutor_popularity`
from Tutor_Details AS td JOIN Users as u on u.id_user = td.id_user
LEFT JOIN Learning_Packs_Tag_Relations AS lptagrels ON td.id_tutor = lptagrels.id_tutor
LEFT JOIN Learning_Packs AS lp ON lptagrels.id_lp = lp.id_lp
LEFT JOIN `some other tables on lp.id_lp - let's call learning pack tables set (including
Learning_Packs table)`
LEFT JOIN Order_Details as od on td.id_tutor = od.id_author LEFT JOIN Orders as o on
od.id_order = o.id_order
LEFT JOIN Tutors_Tag_Relations as ttagrels ON td.id_tutor = ttagrels.id_tutor
JOIN Tags as t on (t.id_tag = ttagrels.id_tag) OR (t.id_tag = lptagrels.id_tag)
where `some condition on Users table's fields`
AND CASE WHEN ((t.id_tag = lptagrels.id_tag) AND (lp.id_lp > 0)) THEN `some
conditions on learning pack tables set` ELSE 1 END
AND CASE WHEN ((t.id_tag = wtagrels.id_tag) AND (wc.id_wc > 0)) THEN `some
conditions on webclasses tables set` ELSE 1 END
AND CASE WHEN (od.id_od>0) THEN od.id_author = td.id_tutor and `some conditions on Orders table's fields` ELSE 1 END
AND ( t.tag LIKE "%Dictatorship%" OR t.tag LIKE "%democracy%")
group by td.id_tutor HAVING key_1_total_matches = 1 AND key_2_total_matches = 1
order by tutor_popularity desc, u.surname asc, u.name asc limit
0,20
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What does the above query do?
- Does AND logic search on the search keywords (2 in this example – “Democracy” and “Dictatorship”).
- Returns only those tutors for which both the keywords are present in the union of the two sets – tutors details and details of all the packs created by a tutor.
To make things clear – Suppose a Tutor name “Sandeepan Nath” has created a pack “My first pack”, then:-
- Searching “Sandeepan Nath” returns Sandeepan Nath.
- Searching “Sandeepan first” returns Sandeepan Nath.
- Searching “Sandeepan second” does not return Sandeepan Nath.
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The problem
The results returned by the above query are correct (AND logic working as per expectation), but the time taken by the query on heavily loaded databases is like 25 seconds as against normal query timings of the order of 0.005 – 0.0002 seconds, which makes it totally unusable.
It is possible that some of the delay is being caused because all the possible fields have not yet been indexed, but I would appreciate a better query as a solution, optimized as much as possible, displaying the same results
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How tags work in this system?
- When a tutor registers, tags are entered and tag relations are created with respect to tutor’s details like name, surname etc.
- When a Tutors create packs, again tags are entered and tag relations are created with respect to pack’s details like pack name, description etc.
- tag relations for tutors stored in tutors_tag_relations and those for packs stored in learning_packs_tag_relations. All individual tags are stored in tags table.
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The tables
Most of the following tables contain many other fields which I have omitted here.
CREATE TABLE IF NOT EXISTS `users` (
`id_user` int(10) unsigned NOT NULL AUTO_INCREMENT,
`name` varchar(100) NOT NULL DEFAULT '',
`surname` varchar(155) NOT NULL DEFAULT '',
PRIMARY KEY (`id_user`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=636 ;
CREATE TABLE IF NOT EXISTS `tutor_details` (
`id_tutor` int(10) NOT NULL AUTO_INCREMENT,
`id_user` int(10) NOT NULL DEFAULT '0',
PRIMARY KEY (`id_tutor`),
KEY `Users_FKIndex1` (`id_user`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1 AUTO_INCREMENT=51 ;
CREATE TABLE IF NOT EXISTS `orders` (
`id_order` int(10) unsigned NOT NULL AUTO_INCREMENT,
PRIMARY KEY (`id_order`),
KEY `Orders_FKIndex1` (`id_user`),
) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=275 ;
ALTER TABLE `orders`
ADD CONSTRAINT `Orders_ibfk_1` FOREIGN KEY (`id_user`) REFERENCES `users`
(`id_user`) ON DELETE NO ACTION ON UPDATE NO ACTION;
CREATE TABLE IF NOT EXISTS `order_details` (
`id_od` int(10) unsigned NOT NULL AUTO_INCREMENT,
`id_order` int(10) unsigned NOT NULL DEFAULT '0',
`id_author` int(10) NOT NULL DEFAULT '0',
PRIMARY KEY (`id_od`),
KEY `Order_Details_FKIndex1` (`id_order`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=284 ;
ALTER TABLE `order_details`
ADD CONSTRAINT `Order_Details_ibfk_1` FOREIGN KEY (`id_order`) REFERENCES `orders`
(`id_order`) ON DELETE NO ACTION ON UPDATE NO ACTION;
CREATE TABLE IF NOT EXISTS `learning_packs` (
`id_lp` int(10) unsigned NOT NULL AUTO_INCREMENT,
`id_author` int(10) unsigned NOT NULL DEFAULT '0',
PRIMARY KEY (`id_lp`),
KEY `Learning_Packs_FKIndex2` (`id_author`),
KEY `id_lp` (`id_lp`)
) ENGINE=InnoDB DEFAULT CHARSET=utf8 AUTO_INCREMENT=23 ;
CREATE TABLE IF NOT EXISTS `tags` (
`id_tag` int(10) unsigned NOT NULL AUTO_INCREMENT,
`tag` varchar(255) DEFAULT NULL,
PRIMARY KEY (`id_tag`),
UNIQUE KEY `tag` (`tag`),
KEY `id_tag` (`id_tag`),
KEY `tag_2` (`tag`),
KEY `tag_3` (`tag`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1 AUTO_INCREMENT=3419 ;
CREATE TABLE IF NOT EXISTS `tutors_tag_relations` (
`id_tag` int(10) unsigned NOT NULL DEFAULT '0',
`id_tutor` int(10) DEFAULT NULL,
KEY `Tutors_Tag_Relations` (`id_tag`),
KEY `id_tutor` (`id_tutor`),
KEY `id_tag` (`id_tag`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1;
ALTER TABLE `tutors_tag_relations`
ADD CONSTRAINT `Tutors_Tag_Relations_ibfk_1` FOREIGN KEY (`id_tag`) REFERENCES
`tags` (`id_tag`) ON DELETE NO ACTION ON UPDATE NO ACTION;
CREATE TABLE IF NOT EXISTS `learning_packs_tag_relations` (
`id_tag` int(10) unsigned NOT NULL DEFAULT '0',
`id_tutor` int(10) DEFAULT NULL,
`id_lp` int(10) unsigned DEFAULT NULL,
KEY `Learning_Packs_Tag_Relations_FKIndex1` (`id_tag`),
KEY `id_lp` (`id_lp`),
KEY `id_tag` (`id_tag`)
) ENGINE=InnoDB DEFAULT CHARSET=latin1;
ALTER TABLE `learning_packs_tag_relations`
ADD CONSTRAINT `Learning_Packs_Tag_Relations_ibfk_1` FOREIGN KEY (`id_tag`)
REFERENCES `tags` (`id_tag`) ON DELETE NO ACTION ON UPDATE NO ACTION;
===================================================================================
Following is the exact query (this includes classes also – tutors can create classes and search terms are matched with classes created by tutors):-
SELECT SUM(DISTINCT( t.tag LIKE "%Dictatorship%" )) AS key_1_total_matches,
SUM(DISTINCT( t.tag LIKE "%democracy%" )) AS key_2_total_matches,
COUNT(DISTINCT( od.id_od )) AS tutor_popularity,
CASE
WHEN ( IF(( wc.id_wc > 0 ), ( wc.wc_api_status = 1
AND wc.wc_type = 0
AND wc.class_date > '2010-06-01 22:00:56'
AND wccp.status = 1
AND ( wccp.country_code = 'IE'
OR wccp.country_code IN ( 'INT' )
) ), 0)
) THEN 1
ELSE 0
END AS 'classes_published',
CASE
WHEN ( IF(( lp.id_lp > 0 ), ( lp.id_status = 1
AND lp.published = 1
AND lpcp.status = 1
AND ( lpcp.country_code = 'IE'
OR lpcp.country_code IN ( 'INT' )
) ), 0)
) THEN 1
ELSE 0
END AS 'packs_published',
td . *,
u . *
FROM tutor_details AS td
JOIN users AS u
ON u.id_user = td.id_user
LEFT JOIN learning_packs_tag_relations AS lptagrels
ON td.id_tutor = lptagrels.id_tutor
LEFT JOIN learning_packs AS lp
ON lptagrels.id_lp = lp.id_lp
LEFT JOIN learning_packs_categories AS lpc
ON lpc.id_lp_cat = lp.id_lp_cat
LEFT JOIN learning_packs_categories AS lpcp
ON lpcp.id_lp_cat = lpc.id_parent
LEFT JOIN learning_pack_content AS lpct
ON ( lp.id_lp = lpct.id_lp )
LEFT JOIN webclasses_tag_relations AS wtagrels
ON td.id_tutor = wtagrels.id_tutor
LEFT JOIN webclasses AS wc
ON wtagrels.id_wc = wc.id_wc
LEFT JOIN learning_packs_categories AS wcc
ON wcc.id_lp_cat = wc.id_wp_cat
LEFT JOIN learning_packs_categories AS wccp
ON wccp.id_lp_cat = wcc.id_parent
LEFT JOIN order_details AS od
ON td.id_tutor = od.id_author
LEFT JOIN orders AS o
ON od.id_order = o.id_order
LEFT JOIN tutors_tag_relations AS ttagrels
ON td.id_tutor = ttagrels.id_tutor
JOIN tags AS t
ON ( t.id_tag = ttagrels.id_tag )
OR ( t.id_tag = lptagrels.id_tag )
OR ( t.id_tag = wtagrels.id_tag )
WHERE ( u.country = 'IE'
OR u.country IN ( 'INT' ) )
AND CASE
WHEN ( ( t.id_tag = lptagrels.id_tag )
AND ( lp.id_lp > 0 ) ) THEN lp.id_status = 1
AND lp.published = 1
AND lpcp.status = 1
AND ( lpcp.country_code = 'IE'
OR lpcp.country_code IN (
'INT'
) )
ELSE 1
END
AND CASE
WHEN ( ( t.id_tag = wtagrels.id_tag )
AND ( wc.id_wc > 0 ) ) THEN wc.wc_api_status = 1
AND wc.wc_type = 0
AND
wc.class_date > '2010-06-01 22:00:56'
AND wccp.status = 1
AND ( wccp.country_code = 'IE'
OR wccp.country_code IN (
'INT'
) )
ELSE 1
END
AND CASE
WHEN ( od.id_od > 0 ) THEN od.id_author = td.id_tutor
AND o.order_status = 'paid'
AND CASE
WHEN ( od.id_wc > 0 ) THEN od.can_attend_class = 1
ELSE 1
END
ELSE 1
END
GROUP BY td.id_tutor
HAVING key_1_total_matches = 1
AND key_2_total_matches = 1
ORDER BY tutor_popularity DESC,
u.surname ASC,
u.name ASC
LIMIT 0, 20
Please note – The provided database structure does not show all the fields and tables as in this query
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The explain query output:-
Please see this screenshot
http://www.test.examvillage.com/Explain_query.jpg
Answering my own question.
The main problem with this approach was that too many tables were joined in a single query. Some of those tables like
Tags(having large number of records – which can in future hold as many as all the English words in the vocabulary) when joined with so many tables cause this multiplication effect which can in no way be countered.The solution is basically to make sure too many joins are not made in a single query. Breaking one large join query into steps, using the results of the one query (involving joins on some of the tables) for the next join query (involving joins on the other tables) reduces the multiplication effect.
I will try to provide better explanation to this later.