Using Outer Joins. Inner joins return rows only when there is at least one row from both tables that matches the join condition.
Inner joins eliminate the rows that do not match with a row from the other table. Outer joins, however, return all rows from at least one of the tables or views mentioned in the FROM clause, as long as those rows meet any WHERE or HAVING search conditions. Using Inner Joins. An inner join is a join in which the values in the columns being joined are compared using a comparison operator.
In the ISO standard, inner joins can be specified in either the FROM or WHERE clause. This is the only type of join that ISO supports in the WHERE clause. Inner joins specified in the WHERE clause are known as old-style inner joins. The following Transact-SQL query is an example of an inner join: Using Self-Joins. A table can be joined to itself in a self-join.
Use a self-join when you want to create a result set that joins records in a table with other records in the same table. To list a table two times in the same query, you must provide a table alias for at least one of instance of the table name. This table alias helps the query processor determine whether columns should present data from the right or left version of the table.
Using Cross Joins. A cross join that does not have a WHERE clause produces the Cartesian product of the tables involved in the join.
The size of a Cartesian product result set is the number of rows in the first table multiplied by the number of rows in the second table. The following example shows a Transact-SQL cross join. USE AdventureWorks2008R2; GO SELECT p.BusinessEntityID, t.Name AS Territory FROM Sales.SalesPerson p CROSS JOIN Sales.SalesTerritory t ORDER BY p.BusinessEntityID; The result set contains 170 rows (SalesPerson has 17 rows and SalesTerritory has 10; 17 multiplied by 10 equals 170). CROSS APPLY Explained. My first introduction to the APPLY operator was using the DMVs.
For quite a while after first being introduced, I didn’t understand it or see a use for it. While it is undeniable that it is has some required uses when dealing with table valued functions, it’s other uses evaded me for a while. Luckily, I started seeing some code that used it outside of table valued functions. It finally struck me that it could be used as a replacement for correlated sub queries and derived tables.
That’s what we’ll discuss today. I never liked correlated subqueries because it always seemed like adding full blown queries in the select list was confusing and improper. SELECT SalesOrderID = soh.SalesOrderID ,OrderDate = soh.OrderDate ,MaxUnitPrice = (SELECT MAX(sod.UnitPrice) FROM Sales.SalesOrderDetail sod WHERE soh.SalesOrderID = sod.SalesOrderID)FROM AdventureWorks.Sales.SalesOrderHeader AS soh It always seemed to me that these operations should go below the FROM clause. We have this: Join Hints (Transact-SQL) Join hints specify that the query optimizer enforce a join strategy between two tables in SQL Server 2012.
For general information about joins and join syntax, see FROM (Transact-SQL). Applies to: Transact-SQL Syntax Conventions <join_hint> ::= { LOOP | HASH | MERGE | REMOTE } Me talking out loud » Blog Archive » “Getting” Joins. NOTE: I highly recommend people read the Coding Horror extension of my post.
I wrote this up as a quick and dirty cheat for a friend. Coding Horror actually takes his time with the subject and gives it a better explanation. I was asked to post this after explaining it to someone on IRC. If you have tried to understand how joins work and constantly get confused about what join to use, you just need to keep a simple picture in mind ( I like pictures). I will be explaining joins by referencing a Venn diagram. We will start with just an empty diagram: A Visual Explanation of SQL Joins. I love the concept, though, so let's see if we can make it work.
Assume we have the following two tables. Table A is on the left, and Table B is on the right. We'll populate them with four records each. id name id name -- ---- -- ---- 1 Pirate 1 Rutabaga 2 Monkey 2 Pirate 3 Ninja 3 Darth Vader 4 Spaghetti 4 Ninja Let's join these tables by the name field in a few different ways and see if we can get a conceptual match to those nifty Venn diagrams. There's also a cartesian product or cross join, which as far as I can tell, can't be expressed as a Venn diagram: SELECT * FROM TableA CROSS JOIN TableB This joins "everything to everything", resulting in 4 x 4 = 16 rows, far more than we had in the original sets.