SQL: Chaining Joins Efficiency - sql

I have a query in my WordPress plugin like this:
SELECT users.*, U.`meta_value` AS first_name,M.`meta_value` AS last_name
FROM `nwp_users` AS users
LEFT JOIN `nwp_usermeta` U
ON users.`ID`=U.`user_id`
LEFT JOIN `nwp_usermeta` M
ON users.`ID`=M.`user_id`
LEFT JOIN `nwp_usermeta` C
ON users.`ID`=C.`user_id`
WHERE U.meta_key = 'first_name'
AND M.meta_key = 'last_name'
AND C.meta_key = 'nwp_capabilities'
ORDER BY users.`user_login` ASC
LIMIT 0,10
I'm new to using JOIN and I'm wondering how efficient it is to use so many JOIN in one query. Is it better to split it up into multiple queries?
The database schema can be found here.

JOIN usually isn't so bad if the keys are indexed. LEFT JOIN is almost always a performance hit and you should avoid it if possible. The difference is that LEFT JOIN will join all rows in the joined table even if the column you're joining is NULL. While a regular (straight) JOIN just joins the rows that match.
Post your table structure and we can give you a better query.

See this comment:
http://forums.mysql.com/read.php?24,205080,205274#msg-205274
For what it's worth, to find out what MySQL is doing and to see if you have indexed properly, always check the EXPLAIN plan. You do this by putting EXPLAIN before your query (literally add the word EXPLAIN before the query), then run it.
In your query, you have a filter AND C.meta_key = 'nwp_capabilities' which means that all the LEFT JOINs above it can be equally written as INNER JOINs. Because if the LEFT JOINS fail (LEFT OUTER is intended to preserve the results from the left side), the result will 100% be filtered out by the WHERE clause.
So a more optimal query would be
SELECT users.*, U.`meta_value` AS first_name,M.`meta_value` AS last_name
FROM `nwp_users` AS users
JOIN `nwp_usermeta` U
ON users.`ID`=U.`user_id`
JOIN `nwp_usermeta` M
ON users.`ID`=M.`user_id`
JOIN `nwp_usermeta` C
ON users.`ID`=C.`user_id`
WHERE U.meta_key = 'first_name'
AND M.meta_key = 'last_name'
AND C.meta_key = 'nwp_capabilities'
ORDER BY users.`user_login` ASC
LIMIT 0,10
(note: "JOIN" (alone) = "INNER JOIN")

Try explaining the query to see what is going on and if your select if optimized. If you haven't used explain before read some tutorials:
http://www.learn-mysql-tutorial.com/OptimizeQueries.cfm
http://www.databasejournal.com/features/mysql/article.php/1382791/Optimizing-MySQL-Queries-and-Indexes.htm

Related

outer joins models that are not associations

I have the following SQL I want to create with activerecord. My problem is that I am stuck in a logic loop where I can't LEFT OUTER JOIN a table which has yet to be joined, and I can't find my entry point to the join fiasco
in activerecord I am trying to do
AdMsgs.joins("LEFT OUTER JOIN shows ON ad_msgs.user_id = shows.id OR ad_msgs.user_id = shows.b_id ")
.joins("LEFT OUTER JOIN m ON m.user_id = users.id OR m.m_id = shops.id OR m.m_id = shows.b_id")
.joins("LEFT OUTER JOIN users ON ad_msgs.to = users.email OR ad_msgs.user_id = users.id OR users.id = m.user_id")
.where("shows.id = ?", self.id)
.distinct("ad_msgs.id")
the query outputs an error saying it doesn't know what users is on the second join (probably since I haven't joined it yet) but I need to select the m records according the the users
AdMsgs doesn't have an association with neither of the tables.
Is there a way to full outer join these 3 tables and then select the ones relevant (or any better ways?)
use find_by_sql to implement such scenarios.
otherwise as a rule of thumb, if you can't use joins like this Blog.joins(articles: :comments) you are probably doing something bad or use find_by_sql instead.
in a complex case, i'm writing my query in SQL first to verify the logic involved. often times it's trivial to replace one complex query with 2 simple ones (using IN(*ids)).

How can I optimise this slow PostgreSQL query

I have tracked the cause of a slow API endpoint to an SQL query and cannot for the life of me optimise it.
The query is as follows:
SELECT "Views".*, "Show".*, "Episode".*, "User".* FROM "Views"
LEFT OUTER JOIN "Shows" AS "Show" ON "Show"."id" = "Views"."ShowId"
LEFT OUTER JOIN "Episodes" AS "Episode" ON "Episode"."id" = "Views"."EpisodeId"
LEFT OUTER JOIN "Users" AS "User" ON "User"."id" = "Views"."UserId"
WHERE "Show"."tvdb_id" IN (259063,82066,258823,265766,261742,82283,205281,182061,121361)
AND "User"."id"=29;
It takes between 3000-4200ms to complete. The result of an EXPLAIN ANALYZE on the query can be found here: http://explain.depesz.com/s/J9R
EDIT: I have also tried separating the IN() into ORs:
SELECT "Views".*, "Show".*, "Episode".*, "User".* FROM "Views"
LEFT OUTER JOIN "Shows" AS "Show" ON "Show"."id" = "Views"."ShowId"
LEFT OUTER JOIN "Episodes" AS "Episode" ON "Episode"."id" = "Views"."EpisodeId"
LEFT OUTER JOIN "Users" AS "User" ON "User"."id" = "Views"."UserId"
WHERE
"Show"."tvdb_id"=259063 OR
"Show"."tvdb_id"=82066 OR
"Show"."tvdb_id"=258823 OR
"Show"."tvdb_id"=265766 OR
"Show"."tvdb_id"=261742 OR
"Show"."tvdb_id"=82283 OR
"Show"."tvdb_id"=205281 OR
"Show"."tvdb_id"=182061 OR
"Show"."tvdb_id"=121361
AND "User"."id"=29;
I have tried creating indexes on the columns referenced in the LEFT OUTER JOIN but that resulted in marginal gains (if anything). What's interesting is I also tried reducing the WHERE x IN to a single WHERE x = y and this instantly improved the situation, responding instead in 200-300ms. So how would I go about optimizing the IN statement?
Thanks!
Try to make combined index on table Views on fields ShowId, EpisodeId, UserId together.
CREATE INDEX Views_idx ON Views
USING btree (ShowId, EpisodeId, UserId);
ps. explain link is wrong, it's for some other query
Best regards,
nele

Queries that implicit SQL joins can't do?

I've never learned how joins work but just using select and the where clause has been sufficient for all the queries I've done. Are there cases where I can't get the right results using the WHERE clause and I have to use a JOIN? If so, could someone please provide examples? Thanks.
Implicit joins are more than 20 years out-of-date. Why would you even consider writing code with them?
Yes, they can create problems that explicit joins don't have. Speaking about SQL Server, the left and right join implicit syntaxes are not guaranteed to return the correct results. Sometimes, they return a cross join instead of an outer join. This is a bad thing. This was true even back to SQL Server 2000 at least, and they are being phased out, so using them is an all around poor practice.
The other problem with implicit joins is that it is easy to accidentally do a cross join by forgetting one of the where conditions, especially when you are joining too many tables. By using explicit joins, you will get a syntax error if you forget to put in a join condition and a cross join must be explicitly specified as such. Again, this results in queries that return incorrect values or are fixed by using distinct to get rid of the cross join which is inefficient at best.
Moreover, if you have a cross join, the maintenance developer who comes along in a year to make a change doesn't know if it was intended or not when you use implicit joins.
I believe some ORMs also now require explicit joins.
Further, if you are using implied joins because you don't understand how joins operate, chances are high that you are writing code that, in fact, does not return the correct result because you don't know how to evaluate what the correct result would be since you don't understand what a join is meant to do.
If you write SQL code of any flavor, there is no excuse for not thoroughly understanding joins.
Yes. When doing outer joins. You can read this simple article on joins. Joins are not hard to understand at all so you should start learning (and using them where appropriate) right away.
Are there cases where I can't get the right results using the WHERE clause and I have to use a JOIN?
Any time your query involves two or more tables, a join is being used. This link is great for showing the differences in joins with pictures as well as sample result sets.
If the join criteria is in the WHERE clause, then the ANSI-89 JOIN syntax is being used. The reason for the newer JOIN syntax in the ANSI-92 format, is that it made LEFT JOIN more consistent across various databases. For example, Oracle used (+) on the side that was optional while in SQL Server you had to use =*.
Implicit join syntax by default uses Inner joins. It is sometimes possible to modify the implicit join syntax to specify outer joins, but it is vendor dependent in my experience (i know oracle has the (-) and (+) notation, and I believe sqlserver uses *= ). So, I believe your question can be boiled down to understanding the differences between inner and outer joins.
We can look at a simple example for an inner vs outer join using a simple query..........
The implicit INNER join:
select a.*, b.*
from table a, table b
where a.id = b.id;
The above query will bring back ONLY rows where the 'a' row has a matching row in 'b' for it's 'id' field.
The explicit OUTER JOIN:
select * from
table a LEFT OUTER JOIN table b
on a.id = b.id;
The above query will bring back EVERY row in a, whether or not it has a matching row in 'b'. If no match exists for 'b', the 'b' fields will be null.
In this case, if you wanted to bring back EVERY row in 'a' regardless of whether it had a corresponding 'b' row, you would need to use the outer join.
Like I said, depending on your database vendor, you may still be able to use the implicit join syntax and specify an outer join type. However, this ties you to that vendor. Also, any developers not familiar wit that specialized syntax may have difficulty understanding your query.
Any time you want to combine the results of two tables you'll need to join them. Take for example:
Users table:
ID
FirstName
LastName
UserName
Password
and Addresses table:
ID
UserID
AddressType (residential, business, shipping, billing, etc)
Line1
Line2
City
State
Zip
where a single user could have his home AND his business address listed (or a shipping AND a billing address), or no address at all. Using a simple WHERE clause won't fetch a user with no addresses because the addresses are in a different table. In order to fetch a user's addresses now, you'll need to do a join as:
SELECT *
FROM Users
LEFT OUTER JOIN Addresses
ON Users.ID = Addresses.UserID
WHERE Users.UserName = "foo"
See http://www.w3schools.com/Sql/sql_join.asp for a little more in depth definition of the different joins and how they work.
Using Joins :
SELECT a.MainID, b.SubValue AS SubValue1, b.SubDesc AS SubDesc1, c.SubValue AS SubValue2, c.SubDesc AS SubDesc2
FROM MainTable AS a
LEFT JOIN SubValues AS b ON a.MainID = b.MainID AND b.SubTypeID = 1
LEFT JOIN SubValues AS c ON a.MainID = c.MainID AND b.SubTypeID = 2
Off-hand, I can't see a way of getting the same results as that by using a simple WHERE clause to join the tables.
Also, the syntax commonly used in WHERE clauses to do left and right joins (*= and =*) is being phased out,
Oracle supports LEFT JOIN and RIGHT JOIN using their special join operator (+) (and SQL Server used to support *= and =* on join predicates, but no longer does). But a simple FULL JOIN can't be done with implicit joins alone:
SELECT f.title, a.first_name, a.last_name
FROM film f
FULL JOIN film_actor fa ON f.film_id = fa.film_id
FULL JOIN actor a ON fa.actor_id = a.actor_id
This produces all films and their actors including all the films without actor, as well as the actors without films. To emulate this with implicit joins only, you'd need unions.
-- Inner join part
SELECT f.title, a.first_name, a.last_name
FROM film f, film_actor fa, actor a
WHERE f.film_id = fa.film_id
AND fa.actor_id = a.actor_id
-- Left join part
UNION ALL
SELECT f.title, null, null
FROM film f
WHERE NOT EXISTS (
SELECT 1
FROM film_actor fa
WHERE fa.film_id = f.film_id
)
-- Right join part
UNION ALL
SELECT null, a.first_name, a.last_name
FROM actor a
WHERE NOT EXISTS (
SELECT 1
FROM film_actor fa
WHERE fa.actor_id = a.actor_id
)
This will quickly become very inefficient both syntactically as well as from a performance perspective.

Optimizing for an OR in a Join in MySQL

I've got a pretty complex query in MySQL that slows down drastically when one of the joins is done using an OR. How can I speed this up? the relevant join is:
LEFT OUTER JOIN publications p ON p.id = virtual_performances.publication_id
OR p.shoot_id = shoots.id
Removing either condition in the OR decreases the query time from 1.5s to 0.1s. There are already indexes on all the relevant columns I can think of. Any ideas? The columns in use all have indexes on them. Using EXPLAIN I've discovered that once the OR comes into play MySQL ends up not using any of the indexes. Is there a special kind of index I can make that it will use?
This is a common difficulty with MySQL. Using OR baffles the optimizer because it doesn't know how to use an index to find a row where either condition is true.
I'll try to explain: Suppose I ask you to search a telephone book and find every person whose last name is 'Thomas' OR whose first name is 'Thomas'. Even though the telephone book is essentially an index, you don't benefit from it -- you have to search through page by page because it's not sorted by first name.
Keep in mind that in MySQL, any instance of a table in a given query can make use of only one index, even if you have defined multiple indexes in that table. A different query on that same table may use another index if the optimizer reasons that it's more helpful.
One technique people have used to help in situations like your is to do a UNION of two simpler queries that each make use of separate indexes:
SELECT ...
FROM virtual_performances v
JOIN shoots s ON (...)
LEFT OUTER JOIN publications p ON (p.id = v.publication_id)
UNION ALL
SELECT ...
FROM virtual_performances v
JOIN shoots s ON (...)
LEFT OUTER JOIN publications p ON p.shoot_id = s.id;
Make two joins on the same table (adding aliases to separate them) for the two conditions, and see if that is faster.
select ..., coalesce(p1.field, p2.field) as field
from ...
left join publications p1 on p1.id = virtual_performances.publication_id
left join publications p2 on p2.shoot_id = shoots.id
You can also try something like this on for size:
SELECT * FROM tablename WHERE id IN
(SELECT p.id FROM tablename LEFT OUTER JOIN publications p ON p.id IN virtual_performances.publication_id)
OR
p.id IN
(SELECT p.id FROM tablename LEFT OUTER JOIN publications p ON p.shoot_id = shoots.id);
It's a bit messier, and won't be faster in every case, but MySQL is good at selecting from straight data sets, so repeating yourself isn't so bad.

Refactor SQL (workaround RIGHT OUTER JOIN)

Since SQLite does not support RIGHT OUTER JOINS I pose the following challenge (read: invitation to do my work for me):
Refactor this query so it no longer utilises SQLite-unsupported constructs like RIGHT/FULL OUTER JOINs.
SELECT strings.*, translations.text
FROM translations INNER JOIN
language ON translations.language_id = language.id RIGHT OUTER JOIN
strings ON translations.string_id = strings.id
WHERE (language.handle = 'english')
I sense it can be achieved with subqueries or by pivoting the tables and performing a LEFT OUTER JOIN but my attempts have failed; my SQL's not what it used to be.
Here's a query builder outline showing the applicable schema: http://dl.getdropbox.com/u/264612/sql-refactor.PNG
First to crack it gets an e-hug from dekz
The following is untested.
select strings.*, translations.text
from strings left outer join translations
on translations.string_id = strings.id
and translations.language_id = (select id
from language
where language.handle = 'english')
I think this will give you all strings with the matching translation text where a suitable translation exists in English. Is that what you are trying to get?
Intriguing that SQLite allows LEFT OUTER JOINs but not RIGHT OUTER JOINs. Well, since it does allow LEFT OUTER JOINs, you're right, you can just rearrange the join order:
SELECT strings.*, translations.text
FROM strings LEFT OUTER JOIN (
translations INNER JOIN language ON translations.language_id = language.id
) tr ON tr.string_id = strings.id
WHERE (language.handle = 'english')
[EDIT: Applied Blorgbeard's suggestion of naming the joined table to get the query to parse -- hope it works now!]