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Table alias names
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This query uses the AS clause to create a table alias name for each table involved in the query. Creating an alias name can simplify your queries and mean less typing instead of having to type HumanResources.Employee every time the table is referenced, the alias name, E , can be used.
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Outer joins return rows with matching data as well as rows with nonmatching data. There are three types of outer joins available to Transact-SQL developers: left outer joins, right outer joins, and full outer joins. A left outer join returns all the rows from the left table in the join, whether or not there are any matching rows in the right table. For any matching rows in the right table, the data for those rows will be returned. For nonmatching rows, the columns in the right table will return NULL. Consider the following query:
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SELECT * FROM HumanResources.Employee AS E LEFT OUTER JOIN HumanResources.EmployeeAddress AS EA ON E.EmployeeId = EA.EmployeeId
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Lesson 1: Querying Data
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This query will return one row for every employee in the Employee table. For each row of the Employee table, if a corresponding row exists in the EmployeeAddress table, the data from that table will also be returned. However, if for a row of the Employee table no corresponding row exists in EmployeeAddress, the row from the Employee table will still be returned, with NULL values for each column that would have been returned from the EmployeeAddress table. A right outer join is similar to a left outer join except that all rows from the right table will be returned, instead of rows from the left table. The following query is, therefore, identical to the query listed previously:
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SELECT * FROM HumanResources.EmployeeAddress AS EA RIGHT OUTER JOIN HumanResources.Employee AS E ON E.EmployeeId = EA.EmployeeId
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The final outer join type is the full outer join, which returns all rows from both tables, whether or not matching rows exist. Where matching rows do exist, the rows will be joined. Where matching rows do not exist, NULL values will be returned for whichever table does not contain corresponding values. Generally speaking, inner joins are the most common join type you ll use when working with SQL Server. You should use inner joins whenever you are querying two tables and know that both tables have matching data or would not want to return missing data. For instance, assume that you have an Employee table and an EmployeePhoneNumber table. The EmployeePhoneNumber table might or might not contain a phone number for each employee. If you want to return a list of employees and their phone numbers and not return employees without phone numbers, use an inner join. You use outer joins whenever you need to return nonmatching data. In the example of the Employee and EmployeePhoneNumber tables, you probably want a full list of employees including those without phone numbers. In that case, you use an outer join instead of an inner join.
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Determining the Columns to Return
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Just as it s important to limit the tables your queries use, it s also important when writing a query to return only the columns absolutely necessary to satisfy the request. Returning extra unnecessary columns in a query can have a surprisingly negative effect on query performance.
5
Working with Transact-SQL
The performance impact of choosing extra columns is related to two factors: network utilization and indexing. From a network standpoint, bringing back extra data with each query means that your network might have to do a lot more work than necessary to get the data to the client. The smaller the amount of data you send across the network, the faster the transmission will go. By returning only necessary columns and not returning additional columns just in case, you will preserve bandwidth. The other cause of performance problems is index utilization. In many cases, SQL Server can use nonclustered indexes to satisfy queries that use only a subset of the columns from a table. This is called index covering. If you add additional columns to a query, the query might no longer be covered by the index, and therefore performance will decrease. For more information about indexing, see 4, Creating Indexes.
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