I met the following MySQL code:
SELECT ServiceFee
FROM Shows
WHERE ID = (SELECT ShowID FROM Orders WHERE ID = ?)
It makes me wonder because the people who wrote this code usually use SQL joins. I would rewrite it
SELECT ServiceFee
FROM Shows
INNER JOIN Orders ON Shows.ID = Orders.ShowID
WHERE Orders.ID = ?
My question: Is there any reason why this code was written with a subquery and whether it is completely safe (producing the same result in all situations) to rewrite it with the join?
Are there any caveats?
"Is there any reason why this code was written with a subquery"
a very long time ago MySQL joins used to be slow
Without a context the two queries don't do the same. If Orders.ID is not unique, the first query might produce an error because the subquery can return multiple rows. If Orders.ID is unique (probably primary key) then there will not be any difference - neither in the result nor in the performance (with newer versions). So in this case it is just a question of preference. Usually i prefer joins. But in your example the subquery solution looks fine and readable. So i wouldn't rewrite it without a reason.
Nope, there are no caveats. As a matter of fact, the INNER JOIN query might run faster
There is a logical reason to prefer a Subquery over a Join:
Between Shows and Orders there's a 1-many relation, when you switch to a join you usually must add a DISTINCT to get rid of the duplicate rows returned.
In your case this is not needed, because you restrict to a single order, but when you remove the WHERE-condition or change it to return multiple rows you will notice that.
Related
For simplicity, assume all relevant fields are NOT NULL.
You can do:
SELECT
table1.this, table2.that, table2.somethingelse
FROM
table1, table2
WHERE
table1.foreignkey = table2.primarykey
AND (some other conditions)
Or else:
SELECT
table1.this, table2.that, table2.somethingelse
FROM
table1 INNER JOIN table2
ON table1.foreignkey = table2.primarykey
WHERE
(some other conditions)
Do these two work on the same way in MySQL?
INNER JOIN is ANSI syntax that you should use.
It is generally considered more readable, especially when you join lots of tables.
It can also be easily replaced with an OUTER JOIN whenever a need arises.
The WHERE syntax is more relational model oriented.
A result of two tables JOINed is a cartesian product of the tables to which a filter is applied which selects only those rows with joining columns matching.
It's easier to see this with the WHERE syntax.
As for your example, in MySQL (and in SQL generally) these two queries are synonyms.
Also, note that MySQL also has a STRAIGHT_JOIN clause.
Using this clause, you can control the JOIN order: which table is scanned in the outer loop and which one is in the inner loop.
You cannot control this in MySQL using WHERE syntax.
Others have pointed out that INNER JOIN helps human readability, and that's a top priority, I agree.
Let me try to explain why the join syntax is more readable.
A basic SELECT query is this:
SELECT stuff
FROM tables
WHERE conditions
The SELECT clause tells us what we're getting back; the FROM clause tells us where we're getting it from, and the WHERE clause tells us which ones we're getting.
JOIN is a statement about the tables, how they are bound together (conceptually, actually, into a single table).
Any query elements that control the tables - where we're getting stuff from - semantically belong to the FROM clause (and of course, that's where JOIN elements go). Putting joining-elements into the WHERE clause conflates the which and the where-from, that's why the JOIN syntax is preferred.
Applying conditional statements in ON / WHERE
Here I have explained the logical query processing steps.
Reference: Inside Microsoft® SQL Server™ 2005 T-SQL Querying
Publisher: Microsoft Press
Pub Date: March 07, 2006
Print ISBN-10: 0-7356-2313-9
Print ISBN-13: 978-0-7356-2313-2
Pages: 640
Inside Microsoft® SQL Server™ 2005 T-SQL Querying
(8) SELECT (9) DISTINCT (11) TOP <top_specification> <select_list>
(1) FROM <left_table>
(3) <join_type> JOIN <right_table>
(2) ON <join_condition>
(4) WHERE <where_condition>
(5) GROUP BY <group_by_list>
(6) WITH {CUBE | ROLLUP}
(7) HAVING <having_condition>
(10) ORDER BY <order_by_list>
The first noticeable aspect of SQL that is different than other programming languages is the order in which the code is processed. In most programming languages, the code is processed in the order in which it is written. In SQL, the first clause that is processed is the FROM clause, while the SELECT clause, which appears first, is processed almost last.
Each step generates a virtual table that is used as the input to the following step. These virtual tables are not available to the caller (client application or outer query). Only the table generated by the final step is returned to the caller. If a certain clause is not specified in a query, the corresponding step is simply skipped.
Brief Description of Logical Query Processing Phases
Don't worry too much if the description of the steps doesn't seem to make much sense for now. These are provided as a reference. Sections that come after the scenario example will cover the steps in much more detail.
FROM: A Cartesian product (cross join) is performed between the first two tables in the FROM clause, and as a result, virtual table VT1 is generated.
ON: The ON filter is applied to VT1. Only rows for which the <join_condition> is TRUE are inserted to VT2.
OUTER (join): If an OUTER JOIN is specified (as opposed to a CROSS JOIN or an INNER JOIN), rows from the preserved table or tables for which a match was not found are added to the rows from VT2 as outer rows, generating VT3. If more than two tables appear in the FROM clause, steps 1 through 3 are applied repeatedly between the result of the last join and the next table in the FROM clause until all tables are processed.
WHERE: The WHERE filter is applied to VT3. Only rows for which the <where_condition> is TRUE are inserted to VT4.
GROUP BY: The rows from VT4 are arranged in groups based on the column list specified in the GROUP BY clause. VT5 is generated.
CUBE | ROLLUP: Supergroups (groups of groups) are added to the rows from VT5, generating VT6.
HAVING: The HAVING filter is applied to VT6. Only groups for which the <having_condition> is TRUE are inserted to VT7.
SELECT: The SELECT list is processed, generating VT8.
DISTINCT: Duplicate rows are removed from VT8. VT9 is generated.
ORDER BY: The rows from VT9 are sorted according to the column list specified in the ORDER BY clause. A cursor is generated (VC10).
TOP: The specified number or percentage of rows is selected from the beginning of VC10. Table VT11 is generated and returned to the caller.
Therefore, (INNER JOIN) ON will filter the data (the data count of VT will be reduced here itself) before applying the WHERE clause. The subsequent join conditions will be executed with filtered data which improves performance. After that, only the WHERE condition will apply filter conditions.
(Applying conditional statements in ON / WHERE will not make much difference in few cases. This depends on how many tables you have joined and the number of rows available in each join tables)
The implicit join ANSI syntax is older, less obvious, and not recommended.
In addition, the relational algebra allows interchangeability of the predicates in the WHERE clause and the INNER JOIN, so even INNER JOIN queries with WHERE clauses can have the predicates rearranged by the optimizer.
I recommend you write the queries in the most readable way possible.
Sometimes this includes making the INNER JOIN relatively "incomplete" and putting some of the criteria in the WHERE simply to make the lists of filtering criteria more easily maintainable.
For example, instead of:
SELECT *
FROM Customers c
INNER JOIN CustomerAccounts ca
ON ca.CustomerID = c.CustomerID
AND c.State = 'NY'
INNER JOIN Accounts a
ON ca.AccountID = a.AccountID
AND a.Status = 1
Write:
SELECT *
FROM Customers c
INNER JOIN CustomerAccounts ca
ON ca.CustomerID = c.CustomerID
INNER JOIN Accounts a
ON ca.AccountID = a.AccountID
WHERE c.State = 'NY'
AND a.Status = 1
But it depends, of course.
Implicit joins (which is what your first query is known as) become much much more confusing, hard to read, and hard to maintain once you need to start adding more tables to your query. Imagine doing that same query and type of join on four or five different tables ... it's a nightmare.
Using an explicit join (your second example) is much more readable and easy to maintain.
I'll also point out that using the older syntax is more subject to error. If you use inner joins without an ON clause, you will get a syntax error. If you use the older syntax and forget one of the join conditions in the where clause, you will get a cross join. The developers often fix this by adding the distinct keyword (rather than fixing the join because they still don't realize the join itself is broken) which may appear to cure the problem but will slow down the query considerably.
Additionally for maintenance if you have a cross join in the old syntax, how will the maintainer know if you meant to have one (there are situations where cross joins are needed) or if it was an accident that should be fixed?
Let me point you to this question to see why the implicit syntax is bad if you use left joins.
Sybase *= to Ansi Standard with 2 different outer tables for same inner table
Plus (personal rant here), the standard using the explicit joins is over 20 years old, which means implicit join syntax has been outdated for those 20 years. Would you write application code using a syntax that has been outdated for 20 years? Why do you want to write database code that is?
The SQL:2003 standard changed some precedence rules so a JOIN statement takes precedence over a "comma" join. This can actually change the results of your query depending on how it is setup. This cause some problems for some people when MySQL 5.0.12 switched to adhering to the standard.
So in your example, your queries would work the same. But if you added a third table:
SELECT ... FROM table1, table2 JOIN table3 ON ... WHERE ...
Prior to MySQL 5.0.12, table1 and table2 would be joined first, then table3. Now (5.0.12 and on), table2 and table3 are joined first, then table1. It doesn't always change the results, but it can and you may not even realize it.
I never use the "comma" syntax anymore, opting for your second example. It's a lot more readable anyway, the JOIN conditions are with the JOINs, not separated into a separate query section.
They have a different human-readable meaning.
However, depending on the query optimizer, they may have the same meaning to the machine.
You should always code to be readable.
That is to say, if this is a built-in relationship, use the explicit join. if you are matching on weakly related data, use the where clause.
I know you're talking about MySQL, but anyway:
In Oracle 9 explicit joins and implicit joins would generate different execution plans. AFAIK that has been solved in Oracle 10+: there's no such difference anymore.
If you are often programming dynamic stored procedures, you will fall in love with your second example (using where). If you have various input parameters and lots of morph mess, then that is the only way. Otherwise, they both will run the same query plan so there is definitely no obvious difference in classic queries.
ANSI join syntax is definitely more portable.
I'm going through an upgrade of Microsoft SQL Server, and I would also mention that the =* and *= syntax for outer joins in SQL Server is not supported (without compatibility mode) for 2005 SQL server and later.
I have two points for the implicit join (The second example):
Tell the database what you want, not what it should do.
You can write all tables in a clear list that is not cluttered by join conditions. Then you can much easier read what tables are all mentioned. The conditions come all in the WHERE part, where they are also all lined up one below the other. Using the JOIN keyword mixes up tables and conditions.
I am trying to select rows from a table which don't have a correspondence in the other table.
For this purpose, I'm currently using LEFT JOIN and WHERE joined_table.any_column IS NULL, but I don't think that's the fastest way.
SELECT * FROM main_table mt LEFT JOIN joined_table jt ON mt.foreign_id=jt.id WHERE jt.id IS NULL
This query works, but as I said, I'm looking for a faster alternative.
Your query is a standard query for this:
SELECT *
FROM main_table mt LEFT JOIN
joined_table jt
ON mt.foreign_id=jt.id
WHERE jt.id IS NULL;
You can try this as well:
SELECT mt.*
FROM main_table mt
WHERE not exists (select 1 from joined_table jt where mt.foreign_id = jt.id);
In some versions of MySQL, it might produce a better execution plan.
In my experience with MSSQL the syntax used (usually) produces the exact same query plan as the WHERE NOT EXISTS() syntax, however this is mysql, so I can't be sure about performance!!
That said, I'm a much bigger fan of using the WHERE NOT EXISTS() syntax for the following reasons :
it's easier to read. If you speak a bit of English anyone can deduce the meaning of the query
it's more foolproof, I've seen people test for NULL on a NULL-able field
it can't have side effects like 'doubled-records' due to the JOIN. If the referenced field is unique there is no problem, but again I've seen situations where people chose 'insufficient keys' causing the main-table to get multiple hits against the joined table... and off course they solved it again using DISTINCT (aarrgg!!! =)
As for performance, make sure to have a (unique) index on the referenced field(s) and if possible put a FK-relationship between both tables. Query-wise I doubt you can squeeze much more out of it.
My 2 cents.
The query that you are running is usually the fastest option, just make sure that you have an index forh both mt.foreign_id and jt.id.
You mentioned that this query is more complex, so it might be possible that the problem is in another part of the query. You should check the execution plan to see what is wrong and fix it.
I built the following query using this MySQL doc page that I found through this StackOverflow question.
It gives me what I wanted: one record for each personkey, and the maximum (most recent) matchkey that that person has participated in.
but I don't understand the purpose of the "s1" and "s2," nor do I understand the construction used in the FROM line (and because I don't know what it's called, it's been difficult to search on it.) What is actually going on in this query?
SELECT personforeignkey, matchforeignkey
FROM peoplematchesheroes s1
WHERE matchforeignkey = (SELECT MAX(s2.matchforeignkey)
FROM peoplematchesheroes s2
WHERE s1.personforeignkey = s2.personforeignkey)
Note: I understand that this query is inefficient, but I want to understand the correlated-subquery construction before I try to optimize.
s1 and s2 are table aliases, in this case both for the same table 'peoplematchesheroes'. s1 is used as the alias for the outer query, and s2 for the inner correlated subquery.
It's not necessary to use a table alias for a correlated subquery, but in your case, since your inner query is also referring to the same table as the outer query, you need to alias them. Think of it as a resolution of scope, because otherwise it would be impossible to tell which 'personforeignkey' field you are referring to- the one from the table correlated subquery or from the outer one.
Hope this makes sense.
I have followed the tutorial over at tizag for the MAX() mysql function and have written the query below, which does exactly what I need. The only trouble is I need to JOIN it to two more tables so I can work with all the rows I need.
$query = "SELECT idproducts, MAX(date) FROM results GROUP BY idproducts ORDER BY MAX(date) DESC";
I have this query below, which has the JOIN I need and works:
$query = ("SELECT *
FROM operators
JOIN products
ON operators.idoperators = products.idoperator JOIN results
ON products.idProducts = results.idproducts
ORDER BY drawndate DESC
LIMIT 20");
Could someone show me how to merge the top query with the JOIN element from my second query? I am new to php and mysql, this being my first adventure into a computer language I have read and tried real hard to get those two queries to work, but I am at a brick wall. I cannot work out how to add the JOIN element to the first query :(
Could some kind person take pity on a newb and help me?
Try this query.
SELECT
*
FROM
operators
JOIN products
ON operators.idoperators = products.idoperator
JOIN
(
SELECT
idproducts,
MAX(date)
FROM results
GROUP BY idproducts
) AS t
ON products.idproducts = t.idproducts
ORDER BY drawndate DESC
LIMIT 20
JOINs function somewhat independently of aggregation functions, they just change the intermediate result-set upon which the aggregate functions operate. I like to point to the way the MySQL documentation is written, which hints uses the term 'table_reference' in the SELECT syntax, and expands on what that means in JOIN syntax. Basically, any simple query which has a table specified can simply expand that table to a complete JOIN clause and the query will operate the same basic way, just with a modified intermediate result-set.
I say "intermediate result-set" to hint at the mindset which helped me understand JOINS and aggregation. Understanding the order in which MySQL builds your final result is critical to knowing how to reliably get the results you want. Generally, it starts by looking at the first row of the first table you specify after 'FROM', and decides if it might match by looking at 'WHERE' clauses. If it is not immediately discardable, it attempts to JOIN that row to the first JOIN specified, and repeats the "will this be discarded by WHERE?". This repeats for all JOINs, which either add rows to your results set, or remove them, or leaves just the one, as appropriate for your JOINs, WHEREs and data. This process builds what I am referring to when I say "intermediate result-set". Somewhere between starting and finishing your complete query, MySQL has in it's memory a potentially massive table-like structure of data which it built using the process I just described. Only then does it begin to aggregate (GROUP) the results according to your criteria.
So for your query, it depends on what specifically you are going for (not entirely clear in OP). If you simply want the MAX(date) from the second query, you can simply add that expression to the SELECT clause and then add an aggregation spec to the end:
SELECT *, MAX(date)
FROM operators
...
GROUP BY idproducts
ORDER BY ...
Alternatively, you can add the JOIN section of the second query to the first.
I came across writing the query in differnt ways like shown below
Type-I
SELECT JS.JobseekerID
, JS.FirstName
, JS.LastName
, JS.Currency
, JS.AccountRegDate
, JS.LastUpdated
, JS.NoticePeriod
, JS.Availability
, C.CountryName
, S.SalaryAmount
, DD.DisciplineName
, DT.DegreeLevel
FROM Jobseekers JS
INNER
JOIN Countries C
ON JS.CountryID = C.CountryID
INNER
JOIN SalaryBracket S
ON JS.MinSalaryID = S.SalaryID
INNER
JOIN DegreeDisciplines DD
ON JS.DegreeDisciplineID = DD.DisciplineID
INNER
JOIN DegreeType DT
ON JS.DegreeTypeID = DT.DegreeTypeID
WHERE
JS.ShowCV = 'Yes'
Type-II
SELECT JS.JobseekerID
, JS.FirstName
, JS.LastName
, JS.Currency
, JS.AccountRegDate
, JS.LastUpdated
, JS.NoticePeriod
, JS.Availability
, C.CountryName
, S.SalaryAmount
, DD.DisciplineName
, DT.DegreeLevel
FROM Jobseekers JS, Countries C, SalaryBracket S, DegreeDisciplines DD
, DegreeType DT
WHERE
JS.CountryID = C.CountryID
AND JS.MinSalaryID = S.SalaryID
AND JS.DegreeDisciplineID = DD.DisciplineID
AND JS.DegreeTypeID = DT.DegreeTypeID
AND JS.ShowCV = 'Yes'
I am using Mysql database
Both works really well, But I am wondering
which is best practice to use all time for any situation?
Performance wise which is better one?(Say the database as a millions records)
Any advantages of one over the other?
Is there any tool where I can check which is better query?
Thanks in advance
1- It's a no brainer, use the Type I
2- The type II join are also called 'implicit join', whereas the type I are called 'explicit join'. With modern DBMS, you will not have any performance problem with normal query. But I think with some big complex multi join query, the DBMS could have issue with the implicit join. Using explicit join only could improve your explain plan, so faster result !
3- So performance could be an issue, but most important maybe, the readability is improve for further maintenance. Explicit join explain exactly what you want to join on what field, whereas implicit join doesn't show if you make a join or a filter. The Where clause is for filter, not for join !
And a big big point for explicit join : outer join are really annoying with implicit join. It is so hard to read when you want multiple join with outer join that explicit join are THE solution.
4- Execution plan are what you need (See the doc)
Some duplicates :
Explicit vs implicit SQL joins
SQL join: where clause vs. on clause
INNER JOIN ON vs WHERE clause
in the most code i've seen, those querys are done like your Type-II - but i think Type-I is better because of readability (and more logic - a join is a join, so you should write it as a join (althoug the second one is just another writing style for inner joins)).
in performance, there shouldn't be a difference (if there is one, i think the Type-I would be a bit faster).
Look at "Explain"-syntax
http://dev.mysql.com/doc/refman/5.1/en/explain.html
My suggestion.
Update all your tables with some amount of records. Access the MySQL console and run SQL both command one by one. You can see the time execution time in the console.
For the two queries you mentioned (each with only inner joins) any modern database's query optimizer should produce exactly the same query plan, and thus the same performance.
For MySQL, if you prefix the query with EXPLAIN, it will spit out information about the query plan (instead of running the query). If the information from both queries is the same, them the query plan is the same, and the performance will be identical. From the MySQL Reference Manual:
EXPLAIN returns a row of information
for each table used in the SELECT
statement. The tables are listed in
the output in the order that MySQL
would read them while processing the
query. MySQL resolves all joins using
a nested-loop join method. This means
that MySQL reads a row from the first
table, and then finds a matching row
in the second table, the third table,
and so on. When all tables are
processed, MySQL outputs the selected
columns and backtracks through the
table list until a table is found for
which there are more matching rows.
The next row is read from this table
and the process continues with the
next table.
When the EXTENDED keyword is used,
EXPLAIN produces extra information
that can be viewed by issuing a SHOW
WARNINGS statement following the
EXPLAIN statement. This information
displays how the optimizer qualifies
table and column names in the SELECT
statement, what the SELECT looks like
after the application of rewriting and
optimization rules, and possibly other
notes about the optimization process.
As to which syntax is better? That's up to you, but once you move beyond inner joins to outer joins, you'll need to use the newer syntax, since there's no standard for describing outer joins using the older implicit join syntax.