掌握LINQ：高效使用与进阶指南

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"Think in LINQ" 这本书名为《Think in LINQ》，主要关注如何有效地使用C#中的语言集成查询（Language Integrated Query，简称LINQ）技术。作者希望通过书中的实例，展示LINQ的强大功能，让读者能深入理解并熟练运用LINQ，而不仅仅是了解其基础知识。书中涵盖了一系列主题，旨在帮助读者提升在实际开发中使用LINQ的能力。 1. **思考函数式编程**：第一章介绍了函数式编程的概念，这是理解和使用LINQ的基础。LINQ深受函数式编程的影响，学习如何用函数式思维方式处理问题，可以更好地利用LINQ的特性。 2. **序列生成**：第二章讨论了如何使用LINQ创建和操作各种数据序列。这包括从基本集合、数组和列表到更复杂的序列结构，以及如何通过查询表达式生成这些序列。 3. **文本处理**：第三章深入讲解了使用LINQ对文本进行操作的方法，包括字符串分割、查找、替换和模式匹配等常见任务，使开发者能高效地处理文本数据。 4. **使用LINQ进行重构**：第四章探讨了如何使用LINQ来改进代码结构，提高代码的可读性和可维护性。这里会展示如何将传统循环和条件语句转换为更简洁的LINQ查询。 5. **更多LINQ用法**：第五章进一步扩展了LINQ的应用，介绍了一些高级特性和扩展方法，比如聚合、分组和窗口函数，帮助开发者掌握更复杂的查询需求。 6. **创建领域特定语言**：第六章讲解如何利用LINQ构建特定领域的查询语言，这有助于创建更加定制化的数据处理解决方案。 7. **静态代码分析**：第七章关注使用LINQ进行静态代码分析，通过查询代码结构来发现潜在的错误和优化机会。 8. **探索性数据分析**：第八章介绍了如何利用LINQ处理和分析数据，特别是在进行初步的数据探索和统计分析时的应用。 9. **与文件系统的交互**：第九章讲解如何使用LINQ操作文件系统，如读取、写入和搜索文件，以及处理目录结构。 10. **精简LINQ提示**：附录A提供了关于优化和更高效使用LINQ的一些建议和技巧，帮助开发者提高效率。 11. **使用Rx.NET驯服流数据**：附录B介绍了Reactive Extensions (Rx.NET)，这是一种处理异步数据流的库，可以结合LINQ使用，处理实时或定时数据源。 12. **索引**：书末提供了详细的索引，方便读者查找特定主题。通过对这些章节的学习，读者将能够更全面地理解LINQ的工作原理，从而在实际项目中充分发挥其潜力，避免滥用或误解这项强大的工具。

Chapter 2 ■ SerieS Generation

How It Works

This example uses a lookup table to find out the percentile. The keys in the lookup table hold the number, and the

values are all those numbers that are smaller than that number. Later the code finds the percent of these values

against the total number of items. That yields the percentile for the particular number represented by the key.

2-5. Math and Statistics: Finding the Dominator in an Array

A dominator is an element in an array that repeats in more than 50 percent of the array positions.

Problem

Assume you have the following array: {3, 4, 3, 2, 3, -1, 3, 3}. There are eight elements, and 3 appears in five of those.

So in this case the dominator is 3. The problem is to use LINQ to find the dominator in an array.

Solution

The first algorithm that comes to mind to find a dominator has to loop through the array twice and thus has quadratic

time complexity, but you can improve the efficiency by using a lookup. Listing 2-6 shows the solution.

Listing 2-6. Finding the array dominator

int[] array = { 3, 4, 3, 2, 3, -1, 3, 3};

array.ToLookup (a => a).First (a => a.Count() >

array.Length/2).Key.Dump("Dominator");

Figure 2-7. Student rank derived from percentile

Chapter 2 ■ SerieS Generation

When you run this query in LINQPad, you will see the output shown in Figure 2-9. The Key column shows

the face value of various bills, while the Value column shows the number of those bills required to add up to the

target value.

How It Works

The algorithm to find the minimum number of currency bills required is recursive. It is a continuous division of the

value by the largest currency value that results in an integer greater than or equal to 1, repeated against the remainder

until the value of the amount diminishes to zero.

amount/c (amount divided by c) calculates the number of currency bills required with value c. The remaining

amount is the remainder, as calculated by amount % c.

The data is stored as a currency and currency count pair in the C# dictionary map. Each dictionary key is a

currency bill face value, and the value is the number of such currency bills required to total the given amount, using

the minimum number of currency bills. Thus, any nonzero value in the map is what you should look for. The LINQ

query map.Where (m => m.Value!=0) does just that. And that’s about it!

LINQPad has a cool feature that sums up the values in the Value column. In this case, that summation is 8.

That means it will require a minimum of eight currency bills to make 2,548.

The first call to OrderByDescending() makes sure that you start with the highest available currency value.

2-7. Math and Statistics: Finding Moving Averages

Finding a moving average is a problem that often arises in time series analysis, where it’s used to smooth out local

fluctuations. A moving average is just what it says—an average that “moves.” In other words, it is the average of all

elements that fall within a moving window of a predefined size. For example, suppose you have the numbers 1, 2, 3, 4,

and the window size is 2. In that case, there are three moving averages: the average of 1 and 2, the average of 2 and 3,

and the average of 3 and 4.

Problem

Create a program that finds the moving average of given window size.

Figure 2-9. Output of the minimum currency bill count query

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