INNER JOIN vs multiple table names in "FROM" [duplicate]

This question already has answers here: Closed 11 years ago.

Possible Duplicate:

INNER JOIN versus WHERE clause — any difference?

What is the difference between an INNER JOIN query and an implicit join query (i.e. listing multiple tables after the FROM keyword)?

For example, given the following two tables:

CREATE TABLE Statuses(
  id INT PRIMARY KEY,
  description VARCHAR(50)
);
INSERT INTO Statuses VALUES (1, 'status');

CREATE TAB开发者_高级运维LE Documents(
  id INT PRIMARY KEY,
  statusId INT REFERENCES Statuses(id)
);
INSERT INTO Documents VALUES (9, 1);

What is the difference between the below two SQL queries?

From the testing I've done, they return the same result. Do they do the same thing? Are there situations where they will return different result sets?

-- Using implicit join (listing multiple tables)
SELECT s.description
FROM Documents d, Statuses s
WHERE d.statusId = s.id
      AND d.id = 9;

-- Using INNER JOIN
SELECT s.description
FROM Documents d
INNER JOIN Statuses s ON d.statusId = s.id
WHERE d.id = 9;

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There is no reason to ever use an implicit join (the one with the commas). Yes for inner joins it will return the same results. However, it is subject to inadvertent cross joins especially in complex queries and it is harder for maintenance because the left/right outer join syntax (deprecated in SQL Server, where it doesn't work correctly right now anyway) differs from vendor to vendor. Since you shouldn't mix implicit and explict joins in the same query (you can get wrong results), needing to change something to a left join means rewriting the entire query.

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If you do it the first way, people under the age of 30 will probably chuckle at you, but as long as you're doing an inner join, they produce the same result and the optimizer will generate the same execution plan (at least as far as I've ever been able to tell).

This does of course presume that the where clause in the first query is how you would be joining in the second query.

This will probably get closed as a duplicate, btw.

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The nice part of the second method is that it helps separates the join condition (on ...) from the filter condition (where ...). This can help make the intent of the query more readable.

The join condition will typically be more descriptive of the structure of the database and the relation between the tables. e.g., the salary table is related to the employee table by the EmployeeID column, and queries involving those two tables will probably always join on that column.

The filter condition is more descriptive of the specific task being performed by the query. If the query is FindRichPeople, the where clause might be "where salaries.Salary > 1000000"... thats describing the task at hand, not the database structure.

Note that the SQL compiler doesn't see it that way... if it decides that it will be faster to cross join and then filter the results, it will cross join and filter the results. It doesn't care what is in the ON clause and whats in the WHERE clause. But, that typically wont happen if the on clause matches a foreign key or joins to a primary key or indexed column. As far as operating correctly, they are identical; as far as writing readable, maintainable code, the second way is probably a little better.

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there is no difference as far as I know is the second one with the inner join the new way to write such statements and the first one the old method.

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The first one does a Cartesian product on all record within those two tables then filters by the where clause.

The second only joins on records that meet the requirements of your ON clause.

EDIT: As others have indicated, the optimization engine will take care of an attempt on a Cartesian product and will result in the same query more or less.

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A bit same. Can help you out.

• Left join vs multiple tables in SQL (a)
• Left join vs multiple tables in SQL (b)

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In the example you've given, the queries are equivalent; if you're using SQL Server, run the query and display the actual exection plan to see what the server's doing internally.