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In this chapter s opening paragraphs, I mentioned that there might be cases in which you need logical temporary tables that is, only virtual materialization of interim sets, as opposed to physical materialization in temporary tables and table variables . Table expressions give you this capability . These include derived tables, CTEs, views, and inline table-valued UDFs . Here I ll point out the scenarios in which these are preferable to other temporary objects and provide an example . You should use table expressions in cases where you need a temporary object mainly for simplification for example, when developing a solution in a modular approach, a step at a time . Also, use table expressions when you need to access the temporary object only once or a very small number of times and you don t need to index interim result sets . SQL Server doesn t physically materialize a table expression . The optimizer merges the outer query with the inner one, and it generates one plan for the query accessing the underlying tables directly . So I m mainly talking about simplification, and I show such examples

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How do you insert a customer without an order (By the way, can you see the incompleteness problem )

CAST(SUBSTRING(binstr, 23, 8) AS DATETIME) AS RequiredDate FROM (SELECT EmployeeID, MAX(CAST(OrderDate AS BINARY(8)) + CAST(OrderID AS BINARY(4)) + CAST(CustomerID AS BINARY(10)) + CAST(RequiredDate AS BINARY(8))) AS binstr FROM dbo.Orders GROUP BY EmployeeID) AS D;

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throughout the book . But even beyond simplification, in some cases you will be able to improve performance of solutions by using table expressions . There might be cases where the optimizer will generate a better plan for your query compared to alternative queries . In terms of scope and visibility, derived tables and CTEs are available only to the current statement, whereas views and inline UDFs are available globally to users that have permissions to access them . As an example of using a table expression to solve a problem, suppose you want to return from the Sales .Orders table in the InsideTSQL2008 database, the row with the highest orderid for each employee . Here s a solution that uses a CTE:

If item Ba is renamed, how do you perform an update You can easily miss some row you should update. This occurs because of redundancy.

How do you calculate the total quantity of bananas This is the problem with a nonscalar column. The Items column is a collection.

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USE InsideTSQL2008; WITH EmpMax AS ( SELECT empid, MAX(orderid) AS maxoid FROM Sales.Orders GROUP BY empid ) SELECT O.orderid, O.empid, O.custid, O.orderdate FROM Sales.Orders AS O JOIN EmpMax AS EM ON O.orderid = EM.maxoid;

The derived table D contains the maximum concatenated string for each employee. Notice that each value was converted to the appropriate fixed-size string before concatenation based on its datatype (DATETIME8 bytes, INT4 bytes, and so on).

The rst normal form (1NF) says that a table is in rst normal form if all columns are atomic. No multivalued columns are allowed. Note that the 1NF de nition simply states that a table must represent a relation. Decomposition has to start with the Items column. You need a single row per item in an order, and every atomic piece of data of a single item (ProductId, ProductName, Quantity) must get its own column. However, after the decomposition, you get multiple rows for a single order. OrderId by itself cannot be the key anymore. The new key is composed of the OrderId and ProductId columns. If you allow multiple products on a single order for example, each time with a different discount you would not be able to use the ProductId as a part of the key. You would probably add ItemId attribute and use it as a part of the new key. A decomposed table in 1NF would look like Table 3-2.

This generates the following output:

TABLE 3-2

orderid ----------11077 11073 11063 11076 11043 11045 11074 11075 11058 empid ----------1 2 3 4 5 6 7 8 9 custid ----------65 58 37 9 74 10 73 68 6 orderdate ----------------------2008-05-06 00:00:00.000 2008-05-05 00:00:00.000 2008-04-30 00:00:00.000 2008-05-06 00:00:00.000 2008-04-22 00:00:00.000 2008-04-23 00:00:00.000 2008-05-06 00:00:00.000 2008-05-06 00:00:00.000 2008-04-29 00:00:00.000

1 1 2 3 3 1 1 1 2 2 Company ABC Company ABC Company ABC XYZ XYZ 2008-10-22 2008-10-22 2008-10-24 2008-09-15 2008-09-15

When converting numbers to binary strings, only nonnegative values will preserve their original sort behavior. As for character strings, converting them to binary values makes them use similar sort behavior to a binary sort order.

Before I start with 2NF, let me point out one common misconception with 1NF. You ll often read about repeating group of columns. Take, for example, the Employees table design shown in Figure 3-11.

Table 7-1 contains a summary of the functionality and behavior of the different object types . Note that I don t include global temporary tables because typically you use those for different purposes than the other types of temporary objects . You might find this table handy as a reference when you need to choose the appropriate temporary object type for a given task .

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