[sql] INNER JOIN ON vs WHERE clause

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?

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.

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.

Applying conditional statements in ON / WHERE

Here I have explained the logical query processing steps.

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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.

1. 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.

2. ON: The ON filter is applied to VT1. Only rows for which the <join_condition> is TRUE are inserted to VT2.

3. 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.

4. WHERE: The WHERE filter is applied to VT3. Only rows for which the <where_condition> is TRUE are inserted to VT4.

5. GROUP BY: The rows from VT4 are arranged in groups based on the column list specified in the GROUP BY clause. VT5 is generated.

6. CUBE | ROLLUP: Supergroups (groups of groups) are added to the rows from VT5, generating VT6.

7. HAVING: The HAVING filter is applied to VT6. Only groups for which the <having_condition> is TRUE are inserted to VT7.

8. SELECT: The SELECT list is processed, generating VT8.

9. DISTINCT: Duplicate rows are removed from VT8. VT9 is generated.

10. ORDER BY: The rows from VT9 are sorted according to the column list specified in the ORDER BY clause. A cursor is generated (VC10).

11. TOP: The specified number or percentage of rows is selected from the beginning of VC10. Table VT11 is generated and returned to the caller.

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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)

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.

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.

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?

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):

1. Tell the database what you want, not what it should do.
2. 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.

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.

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.