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IT-SC book: Advanced CORBA Programming with C++
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22 Performance, Scalability, and Maintainability
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221 Overview
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In this chapter we bring the book to a close with a light discussion of design techniques that can help make your CORBA applications perform well and be more scalable, maintainable, and portable Section 223 discusses overhead due to remote method invocation and explains how you can reduce it In Section 224 we review the techniques described in earlier chapters for optimizing server applications Following that, Section 225 briefly presents federation as a solution to distributing process load Finally, Section 226 describes an approach for isolating your application code from your CORBA-related code to achieve better portability and separation of concerns
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222 Introduction
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By now you probably realize that CORBA does not present you with a cookbook approach to building distributed systems You cannot simply throw together a handful of interfaces, implement them, and expect to have a distributed application To be sure, CORBA makes it easy to create a client-server application in a short time However, if you want to build something that scales to large numbers of objects and at the same time performs well, you must plan ahead This chapter presents a few of the design techniques you have at your disposal for building applications that scale and perform well without sacrificing maintainability of your code This discussion is by no means complete CORBA applies to such a variety of distributed systems applications that we cannot hope to cover the topic extensively here Instead, we present a few design techniques that are likely to be useful for many kinds of applications Of course, you must use your own judgment as to whether these techniques apply to your situation Typically, the goals of scalability, performance, and maintainability are in conflict For example, better performance often implies coding or design techniques that result in source code that compromises maintainability Similarly, increased scalability often implies a reduction in performance Steering the correct path through these trade-offs is the hallmark of design excellence, and a cookbook approach is unlikely to lead to the best possible solution However, the techniques we present here should help to get you started along the correct path and provide a source of ideas you can modify as the situation demands
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223 Reducing Messaging Overhead
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IT-SC book: Advanced CORBA Programming with C++
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The similarity of IDL to C++ class definitions makes it easy to approach IDL interface design the same way you would approach C++ class design This similarity is both a boon and a bane Because IDL is so similar to C++ in both syntax and semantics, most programmers quickly feel at home with the language and can begin to develop applications with only a small learning curve However, pretending that IDL design is the same as C++ class design is likely to get you into trouble Even though CORBA makes it easy to ignore details of distribution and networking, this does not mean that you can pretend that distribution and networking do not exist It is easy to forget that sending a message to a remote object is several orders of magnitude slower than sending a message to a local object Naive IDL design therefore can easily result in systems that work but are unacceptably slow 2231 Basic IIOP Performance Limitations To get at least a basic idea of the fundamental performance parameters within which you must create your design, you must know the cost of sending remote messages This cost is determined by two factors: latency and marshaling rate Call latency is the minimum cost of sending any message at all, whereas the marshaling rate determines the cost of sending and receiving parameter and return values depending on their size
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Call Latency
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The cheapest message you can send is one that has no parameters and does not return a result:
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interface Cheap { oneway void fast_operation(); };
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The number of fast_operation invocations that your ORB can deliver per time interval sets a fundamental design limit: you cannot hope to meet your performance goals if your design requires more messages to be sent per time interval than your ORB can deliver Unfortunately, the only real way to find out what your ORB is capable of is to create benchmarks The cost of call dispatch varies considerably among environments and depends on a large number of variables, such as the underlying network technology, the CPU speed, the operating system, the efficiency of your TCP/IP implementation, your compiler, and the efficiency of the ORB run time itself To give you a rough idea of the state of current technology, general-purpose ORBs have call dispatch times of between 05 msec and 5 msec In other words, depending on your ORB implementation, you can expect a maximum call rate of 200 to 2,000 operation invocations per second (We obtained these figures by running a client and a server on different machines connected by an otherwise unused 10 Mb Ethernet; client and server were running on typical UNIX workstations and were implemented using a number of commercial general-purpose
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