Apress.Expert.Oracle.Database.Architecture.9i.and.10g.Programming.Techniques.and.Solutions.Sep.2005

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CHAPTER 5 ■ ORACLE PROCESSES 167 Of course, a big reason to use shared server is when you have no choice. Many advanced connection features require the use of shared server. If you want to use Oracle Net connection pooling, you must use shared server. If you want to use database link concentration between databases, then you must use shared server for those connections. ■Note If you are already using a connection pooling feature in your application (e.g., you are using the J2EE connection pool), and you have sized your connection pool appropriately, using shared server will only be a performance inhibitor. You already sized your connection pool to cater for the number of concurrent connections that you will get at any point in time—you want each of those connections to be a direct dedicated server connection. Otherwise, you just have a connection pooling feature connecting to yet another connection pooling feature. Potential Benefits of Shared Server So, what are the benefits of shared server, bearing in mind that you have to be somewhat careful about the transaction types you let use it? Shared server does three things for us mainly: it reduces the number of operating system processes/threads, it artificially limits the degree of concurrency, and it reduces the memory needed on the system. We’ll discuss these points in more detail in the sections that follow. Reduces the Number of Operating System Processes/Threads On a system with thousands of users, the operating system may quickly become overwhelmed when trying to manage thousands of processes. In a typical system, only a fraction of the thousands of users are concurrently active at any point in time. For example, I’ve worked on systems recently with 5,000 concurrent users. At any one point in time, at most 50 were active. This system would work effectively with 50 shared server processes, reducing the number of processes the operating system has to manage by two orders of magnitude (100 times). The operating system can now, to a large degree, avoid context switching. Artificially Limits the Degree of Concurrency Speaking as a person who has been involved in lots of benchmarks, the benefits of this are obvious to me. When running benchmarks, people frequently ask to run as many users as possible until the system breaks. One of the outputs of these benchmarks is always a chart that shows the number of concurrent users versus the number of transactions (see Figure 5-3).
168 CHAPTER 5 ■ ORACLE PROCESSES Figure 5-3. Concurrent users vs. transactions per second Initially, as you add concurrent users, the number of transactions increases. At some point, however, adding additional users does not increase the number of transactions you can perform per second—the graph tends to drop off. The throughput has peaked and now response time starts to increase (you are doing the same number of transactions per second, but the end users are observing slower response times). As you continue adding users, you will find that the throughput will actually start to decline. The concurrent user count before this drop-off is the maximum degree of concurrency you want to allow on the system. Beyond this point, the system becomes flooded and queues begin forming to perform work. Much like a backup at a tollbooth, the system can no longer keep up. Not only does response time rise dramatically at this point, but throughput from the system may fall as well as the overhead of simply context switching and sharing resources between too many consumers takes additional resources itself. If we limit the maximum concurrency to the point right before this drop, we can sustain maximum throughput and minimize the increase in response time for most users. Shared server allows us to limit the maximum degree of concurrency on our system to this number. An analogy for this process could be a simple door. The width of the door and the width of people limit the maximum people per minute throughput. At low “load,” there is no problem; however, as more people approach, some forced waiting occurs (CPU time slice). If a lot of people want to get through the door, we get the fallback effect—there are so many saying “after you” and false starts that the throughput falls. Everybody gets delayed getting through. Using a queue means the throughput increases, some people get through the door almost as fast as if there was no queue, while others (the ones put at the end of the queue) experience the greatest delay and might fret that “this was a bad idea.” But when you measure how fast
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Expert Oracle Database Architecture
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Contents Foreword . . . . . . . . .
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■CONTENTS v Block Buffer Cache .
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■CONTENTS vii ■CHAPTER 9 Redo a
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■CONTENTS ix ■CHAPTER 12 Dataty
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Foreword “THINK.” In 1914, Thom
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About the Technical Reviewers ■JO
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Introduction The inspiration for th
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