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To demonstrate the use of these functions, run the code in Listing 6-2 .

Support for cursors in T-SQL hasn t changed for quite a few versions of SQL Server now . I ll assume that you have sufficient technical knowledge of the various cursor types and know the syntax for declaring and using them . If you don t, you can find a lot of information about cursors in SQL Server Books Online . My focus is to explain the differences between cursor-based and set-based solutions to querying problems, and to present the cases in which using cursors does make sense . So why should you avoid using cursors for the most part Cursors conflict with the main premise of the relational model . Using cursors, you apply procedural logic and iterate through individual rows, as opposed to applying set-based logic, where you handle whole sets of rows . With cursors, you end up writing a lot of code with iterations, where you mainly focus on how to deal with data . When you apply set-based logic, you typically write substantially less code, as you focus on what you want and not how to get it .

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You need to be able to recognize the cases in which a problem is procedural/iterative in nature where you truly need to process one row at a time In these cases, you should consider using a cursor For example, suppose you need to invoke a stored procedure for each row in a table, using column values as arguments If the procedure s logic can be written as a table-valued function, you can use the APPLY operator in a query to invoke the function for each row of the table But if the procedure s logic cannot be written as a table-valued function, using a cursor to invoke the procedure for each row of the table is a viable option Cursors also have a lot of overhead involved with the row-by-row manipulation and are typically substantially slower than set-based code I demonstrate the use of set-based solutions throughout the book .

You need to be able to measure and estimate the cursor overhead and identify the few scenarios where cursors will yield better performance than set-based code In some cases, data distribution will determine whether a cursor or a set-based solution will yield better performance Cursors have another very important aspect they can request and assume ordered data as input, whereas queries can accept only a relational input, which by definition cannot assume a particular order This difference is important in identifying scenarios in which cursors might actually be faster such as problems that can benefit from ordered access to the data An example of such a problem is running aggregations The I/O cost involved with the cursor activity plus the cursor overhead might end up being lower than a set-based solution that performs substantially more I/O .

Session Bean (BugAccessor)

ANSI recognizes the practical need for calculations that are based on some logical order and provides some standards for addressing this need In the ANSI SQL standard you can find several query constructs that rely on logical ordering for example, the OVER(ORDER BY ) clause, which includes the calculation order for ranking and aggregate functions, or the SEARCH clause defined with recursive CTEs, which determines the order of traversal of trees Note, however, that supporting a calculation based on logical ordering doesn t contradict the relational model The model deals with relations (sets) and operations on relations Both the input and the output of operations or calculations must be sets As long as this rule is preserved, having operations or calculations that use logical ordering as part of their definition is not a contradiction with the model .

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