A batch is one or several SQL Server commands that are dispatched and executed together. Because every batch sent from the client to the server requires handshaking between the two, sending a batch instead of sending separate commands can prove to be more efficient. Even a batch that doesn't return a result set (for example, a single INSERT statement) requires at least an acknowledgment that the command was processed and offers a status code for its level of success. At the server, the batch must be received, queued for execution, and so on.

Although commands are grouped and dispatched together for execution, each command is distinct from the others. Let's look at an example. Suppose you need to execute 150 INSERT statements. Executing all 150 statements in one batch requires the processing overhead to be incurred once rather than 150 times. In one real-world situation, an application that took 5 to 6 seconds to complete 150 individual INSERT statements was changed so that all 150 statements were sent as one batch. The processing time decreased to well under 0.5 second, more than a tenfold improvement. And this was on a LAN, not on a slow network like a WAN or the Internet, where the improvement would have been even more pronounced. (Try running an application with 150 batches to insert 150 rows over the Internet, and you'll be really sorry!)

Using a batch is a huge win. By using the Transact-SQL constructs that were presented in Chapter 9, such as conditional logic and looping, you can often perform sophisticated operations within a single batch and eliminate the need to carry on an extensive conversation between the client and the server. Those operations can also be saved on the server as a stored procedure, which allows them to execute even more efficiently . Using batches and stored procedures to minimize client/server conversations is crucial for achieving high-performing applications. And now that more applications are being deployed on slower networks ”such as WANs, the Internet, and dial-up systems ”instead of on LANs only, using batches and stored procedures is crucial.

Every SELECT statement (except for those used for assigning a value to a variable) generates a result set. Even a SELECT statement that finds zero rows returns a result set that describes the columns selected. Every time the server sends a result set back to the client application, it must send metadata as well as the actual data. The metadata describes the result set to the client. You can think of metadata in this way: "Here's a result set with eight columns. The first column is named last_name and is of type char(30) . The second column is ...."

Obviously, then, executing a single SELECT statement with a WHERE clause formulated to find (in one fell swoop) all 247 rows that meet your criteria is much more efficient than separately executing 247 SELECT statements that each return one row of data. In the former case, one result set is returned. In the latter case, 247 result sets are returned ”the performance difference is striking.

Using batches might seem like an obvious necessity, yet many programmers still write applications that perform poorly because they don't use batches. The problem is especially common for developers who have worked on ISAM or similar sequential files doing row-at-a-time processing. Unlike ISAM, SQL Server works best with sets of data, not individual rows of data, so that you can minimize conversations between the server and the client application.

There's actually a middle ground between using one SELECT statement that returns all your rows and using an individual batch to return each row. Batches can contain multiple statements, each one returning its own metadata, so the ideal solution is to minimize your total number of statements. Multiple SELECTs within a single batch are still better than having each statement in its own batch, because each batch has the overhead of handshaking between the client and server.

Following is a simple batch, issued from Query Analyzer. Even though three unrelated operations are being performed, we can package them in a single batch to conserve bandwidth:

 INSERT authors VALUES (etc.) SELECT * FROM authors UPDATE publishers SET pub_id= (etc.) GO 

All the statements within a single batch are parsed as a unit. This means that if you have a syntax error in any of the statements, none of the statements will execute. For example, consider this batch of two statements, which we can try to execute from Query Analyzer:

 SELECT * FROM sales SELECT * FOM titleauthor GO 

When you execute this batch, you'll get the following error:

 Server: Msg 170, Level 15, State 1 Line 2: Incorrect syntax near 'fom'. 

Even though the first SELECT statement is perfectly legal, because of the error in the second statement, no data is returned. If we separated this into two different batches, the first one would return a result set and the second one would return an error.

Now suppose that instead of mistyping the keyword FROM as FOM , we had mistyped the name of the table:

 SELECT * FROM sales SELECT * FROM titleautor GO 

SQL Server 7 introduces delayed name resolution, in which object names aren't resolved until execution time. Earlier versions of SQL Server resolved names at compile time, so the above batch would return an "Invalid Object Name" error, and nothing would be executed. In this example, SQL Server 7 returns the data from the first SELECT, followed by the error message below.

 Server: Msg 208, Level 16, State 1 Invalid object name 'titleautor'. 

However, if we had mistyped the object name in the first statement, execution of the batch would stop when the error was encountered . No data would be returned by any subsequent valid queries.

Normally when using Query Analyzer, everything in the query window is considered a single batch and is sent to SQL Server for parsing, compiling, and execution when you click the green EXECUTE button. However, Query Analyzer provides two ways around this. First, it allows you to highlight just a section of code in the query window so that when you click the EXECUTE button, only the highlighted text is sent as a batch to SQL Server. Alternatively, you can include the keyword GO between your queries.

If you use either of the text-based query tools ( osql or isql ), there's no green EXECUTE button to click. When using those tools, you must type GO on a line by itself to indicate that everything you've typed up to that point is a batch. The tool ( osql or isql ) will then send that batch to SQL Server for processing.

GO isn't an SQL command. It's the end-of-batch signal understood only by certain client tools. It's interpreted by the client to mean that everything since the last GO should be sent to the server for execution. SQL Server never sees the GO command and has no idea what it means. With a custom application, a batch is executed with a single SQLExecute from ODBC (or dbsqlexec from DB-Library).

If you include the GO command in your query window in Query Analyzer, Query Analyzer will break up your statement into the indicated batches behind the scenes. Each batch (as marked by the GO command) will be sent individually to SQL Server.

A collection of batches that we frequently want to execute together is sometimes called a script . Most of the client tools allow us a mechanism for loading a script that we've saved to a text file and for executing it. In Query Analyzer, we can use the File/ Open command to load a script. From the command-line osql or isql programs, we can specify the /i flag followed by a filename to indicate that the SQL Server batches to execute should come from the specified file.

The fact that the client tool processes GO and not SQL Server can lead to some unexpected behavior. Suppose you have a script containing several batches. During your testing, you want to comment out a couple of the batches, to ignore them for the time being. Your commented script might then look something like this:

 SELECT * FROM authors /*  GO SELECT * FROM sales GO SELECT * FROM publishers GO  */ SELECT * FROM titles GO 

The intention here was to comment out the SELECT from the sales and publishers tables and to run the SELECT from authors and titles as a single batch. However, if you run this script from Query Analyzer, you'll find that you get exactly the opposite behavior! That is, you'll see the data from the sales and publishers tables, but not from authors or titles. If you look at this script from the perspective of the client tool, the behavior makes sense. The tool doesn't try to interpret any of your SQL statements; it just breaks the statements into batches to be sent to SQL Server. A batch is marked by a GO command at the beginning of a line. So, the above script contains four batches.

The first batch (everything before the first GO) is:

 SELECT * FROM authors /* 

SQL Server generates an error message because there's an open comment with no corresponding close comment.

The second and third batches are:

 SELECT * FROM sales 


 SELECT * FROM publishers 

Both of these batches are perfectly legal, and SQL Server can process them and return results.

The fourth batch is:

 */ SELECT * FROM titles 

SQL Server also generates an error for this last one, because it has a close comment without an open comment marker, and no data will be returned.

If you want to comment out statements within a script that can contain the end-of-batch GO command, you should use the alternative comment marker ”the double dash ”in front of every GO. Your script would then look like this:

 SELECT * FROM authors /*  --GO SELECT * FROM sales --GO SELECT * FROM publishers --GO  */ SELECT * FROM titles GO 

With this revised script, the client tool won't recognize the GO as the end-of-batch marker, because it's not the first thing on a line. The client will consider this script to be one single batch and send it to SQL Server as such. SQL Server will then ignore everything between the open comment (/*) and the close comment (*/) and execute only the SELECT statements from authors and titles .

Inside Microsoft SQL Server 7.0
Inside Microsoft SQL Server 7.0 (Mps)
ISBN: 0735605173
EAN: 2147483647
Year: 1999
Pages: 144 © 2008-2017.
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