how to generate barcode in asp.net using c# 5-1. IMPLEMENTING A UNIVERSAL WEB SERVICE ARCHITECTURE in Font

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CHAPTER 5 5-1. IMPLEMENTING A UNIVERSAL WEB SERVICE ARCHITECTURE
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their limits, especially in the context of Internet-based applications. You could use objectoriented databases, but they haven t caught on for one reason or another the reality is that most data is stored in relational databases. With REST-based Web services, you want to encapsulate the logic on the server and expose a set of URLs that represent Web service operations.
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Recipe Summary
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This recipe illustrated how to build universal Web services using REST-based techniques. Remember the following points: You should treat Web services as components and only implement the functionality necessary. As the example illustrates, you don t need to componentize the Web service. That doesn t mean that componentization is not necessary, nor does it mean that you should ignore good object-oriented design principles. It does mean that you don t always need to componentize, and you should consider the Web service boundary as part of your componentization. Only create code components when it makes sense. The aim is to componentize your application using Web services. Your Web service will be a success based on its interface and the usability of the interface, not on the code behind the interface. For example, if you need a fast response time, write code that is fast, even if that means using arrays instead of linked lists and so on. Using classes instead of components doesn t mean that you cannot configure the behavior of your Web service. For example, you don t have to hard-code the URLs used to define the Web service. Configurability and componentization are two orthogonal issues. When defining the Web service, focus on the URLs and the data that the URLs accept and generate.
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CHAPTER
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6-1. Implementing Web Services for Large or Slow Data Sets
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n the context of an Ajax and REST application, Web services that expose large data sets or slow data sets deserve special attention because of the requirement that the resulting solution be as efficient as possible. This recipe covers the following aspects of implementing a Web service that exposes large data sets or slow data sets: Understanding the context of what a large or slow data set application is Outlining the overall architecture of the solution Determining how an application should be architected in coding terms
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Problem
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You want to create Web services that expose large data sets or data sets that take a long time to generate.
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Theory
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Many developers experience the need to show a huge number of records to end users. The first reaction of most developers to this issue is, No, it can t be done. Yet when you look at the Google and Yahoo! search engines, you see that it can be done. This recipe sets out to solve such a problem specifically, how to display 64,000 records in a Web browser. Please note that the solution for a large data set or slow data set Web service is very specialized and should not be used as a general solution. The added complexity of the solution makes it impractical for use in every application. Web services that are a single request and response are simple and require no management of state or callbacks. In this recipe s solution, state and callbacks are required. Efficiency is one of the requirements of this solution, but remember that efficiency is relative, and the solution will be as efficient as possible for the context. The simplest illustration of the problem of large data sets that take a long time to generate is a search, as shown in Figure 6-1.
CHAPTER 6 6-1. IMPLEMENTING WEB SERVICES FOR LARGE OR SLOW DATA SETS
Figure 6-1. Yahoo! search results for the phrase really big search As you know, in any search engine, you enter a term or phrase in a text box, click the Search button, and the relevant HTML pages are returned for the term or phrase you typed in. Whether the search engine presents useful results is not the point of this solution. What is relevant is the fact that a search was executed that resulted in an HTML page displaying 10 results per page of the roughly 175,000,000 available results. The HTML search result page looks good, and the search took only 0.13 seconds. The search speed should amaze users, but I tend to be cynical. I am sure that the 0.13 seconds is not a lie, but the question is, what does the 0.13 seconds measure Is the 0.13 seconds a measure of having found the search terms in 175,000,000 pages I doubt it, because if this were the case, it would mean each page was found in 0.00000000074286 seconds, or each page was found in two clock cycles of a 3GHz CPU. These statistics should make anybody wary of the results found, even if parallel processes were involved. So if the statistics are very approximate to the point of being irrelevant, what is actually going on The search engine is solving the problem of large or slow data sets using an illusion. The illusion is that the search engine is presenting you with the information in a fast manner, even though you are seeing only an extremely small sliver of the total information. It is not difficult for a search engine to search its indices and return 10 results of a huge data set. As the 10 results are generated and returned as a single HTML page, the second and third batches of results are being generated. I would even hazard a guess that Yahoo! generates a result list of 100 found links. I guess that it is probably a result set of 100 elements because at the bottom of the page there are 10 page links of search results. Multiply 10 and 10, and you get 100 links. What is very interesting is how Yahoo! allows you to retrieve the result set. Consider the URL generated by the query:
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