robertyuzj的博客

Python Cookbook（第3版）中文版》介绍了Python应用在各个领域中的一些使用技巧和方法，其主题涵盖了数据结构和算法，字符串和文本，数字、日期和时间，迭代器和生成器，文件和I/O，数据编码与处理，函数，类与对象，元编程，模块和包，网络和Web编程，并发，实用脚本和系统管理，测试、调试以及异常，C语言扩展等。 本书覆盖了Python应用中的很多常见问题，并提出了通用的解决方案。

TensorFlow-ML-cookbook

tensorflow指南

2015年11月9日，Google发布人工智能系统TensorFlow并宣布开源，同日，极客学院组织在线TensorFlow中文文档翻译。 机器学习作为人工智能的一种类型，可以让软件根据大量的数据来对未来的情况进行阐述或预判。如今，领先的科技巨头无不在机器学习下予以极大投入。Facebook、苹果、微软，甚至国内的百度。Google 自然也在其中。「TensorFlow」是 Google 多年以来内部的机器学习系统。如今，Google 正在将此系统成为开源系统，并将此系统的参数公布给业界工程师、学者和拥有大量编程能力的技术人员

master docker

目前最好的docker中文教程

Kubernetes权威指南：从Docker到Kubernetes实践全接触（第2版） PDF扫描版，是2016年10月出版的，基于Kubernetes1.3版本讲的，比第一版讲的要更细，内容更全面。增强介绍了1.0后的新功能，新资源

Cassandra 权威指南英文第二版，完整版哦，针对 Cassandra 3.0 版

第一本的docker书

fast spark processing with spark 2

In Expert Hadoop® Administration, leading Hadoop administrator Sam R. Alapati brings together authoritative knowledge for creating, configuring, securing, managing, and optimizing production Hadoop clusters in any environment. Drawing on his experience with large-scale Hadoop administration, Alapati integrates action-oriented advice with carefully researched explanations of both problems and solutions. He covers an unmatched range of topics and offers an unparalleled collection of realistic examples. Alapati demystifies complex Hadoop environments, helping you understand exactly what happens behind the scenes when you administer your cluster. You’ll gain unprecedented insight as you walk through building clusters from scratch and configuring high availability, performance, security, encryption, and other key attributes. The high-value administration skills you learn here will be indispensable no matter what Hadoop distribution you use or what Hadoop applications you run. Understand Hadoop’s architecture from an administrator’s standpoint Create simple and fully distributed clusters Run MapReduce and Spark applications in a Hadoop cluster Manage and protect Hadoop data and high availability Work with HDFS commands, file permissions, and storage management Move data, and use YARN to allocate resources and schedule jobs Manage job workflows with Oozie and Hue Secure, monitor, log, and optimize Hadoop Benchmark and troubleshoot Hadoop Table of Contents Part I: Introduction to Hadoop—Architecture and Hadoop Clusters Chapter 1 Introduction to Hadoop and Its Environment Chapter 2 An Introduction to the Architecture of Hadoop Chapter 3 Creating and Configuring a Simple Hadoop Cluster Chapter 4 Planning for and Creating a Fully Distributed Cluster Part II: Hadoop Application Frameworks Chapter 5 Running Applications in a Cluster—The MapReduce Framework (and Hive and Pig) Chapter 6 Running Applications in a Cluster—The Spark Framework Chapter 7 Running Spark Applications Part III: Managing and Protecting Hadoop Data and High Availability Chapter 8 The Role of the NameNode and How HDFS Works Chapter 9 HDFS Commands, HDFS Permissions and HDFS Storage Chapter 10 Data Protection, File Formats and Accessing HDFS Chapter 11 NameNode Operations, High Availability and Federation Part IV: Moving Data, Allocating Resources, Scheduling Jobs and Security Chapter 12 Moving Data Into and Out of Hadoop Chapter 13 Resource Allocation in a Hadoop Cluster Chapter 14 Working with Oozie to Manage Job Workflows Chapter 15 Securing Hadoop Part V: Monitoring, Optimization and Troubleshooting Chapter 16 Managing Jobs, Using Hue and Performing Routine Tasks Chapter 17 Monitoring, Metrics and Hadoop Logging Chapter 18 Tuning the Cluster Resources, Optimizing MapReduce Jobs and Benchmarking Chapter 19 Configuring and Tuning Apache Spark on YARN Chapter 20 Optimizing Spark Applications Chapter 21 Troubleshooting Hadoop—A Sampler Chapter 22 Installing VirtualBox and Linux and Cloning the Virtual Machines

这是一本实用手册，四位作者均是Cloudera公司的数据科学家，他们联袂展示了利用Spark进行大规模数据分析的若干模式，而且每个模式都自成一体。他们将Spark、统计学方法和真实数据集结合起来，通过实例向读者讲述了怎样解决分析型问题。 　　本书首先介绍了Spark及其生态系统，接着详细介绍了将分类、协同过滤及异常检查等常用技术应用于基因学、安全和金融领域的若干模式。如果你对机器学习和统计学有基本的了解，并且会用Java、Python或Scala编程，这些模式将有助于你开发自己的数据应用。

If you’re familiar with Gradle’s basics elements—possibly through the author’s previous O’Reilly book, Building and Testing with Gradle—(also available free on this site) this more advanced guide provides the recipes, techniques, and syntax to help you master this build automation tool. With clear, concise explanations and lots of ready-to-use code examples, you’ll explore four discrete areas of Gradle functionality: file operations, custom Gradle plugins, build lifecycle hooks, and dependency management. Learn how to use Gradle’s rich set of APIs and Groovy-based Domain Specific Language to customize build software that actually conforms to your product. By using the techniques in this book, you’ll be able to write domain-specific builds that support every other line of code your team creates. Gradle Book Cover •Examine Gradle’s file API, including copy tasks, pattern matching, content filtering, and the FileCollection interface •Understand the process for building and packaging a custom Gradle plug-in •Manage build complexity with hook methods and Gradle’s rule feature •Learn how Gradle handles dependency management natively and through customization

Key Features This book is based on the latest 2.0 version of Apache Spark and 2.7 version of Hadoop integrated with most commonly used tools. Learn all Spark stack components including latest topics such as DataFrames, DataSets, GraphFrames, Structured Streaming, DataFrame based ML Pipelines and SparkR. Integrations with frameworks such as HDFS, YARN and tools such as Jupyter, Zeppelin, NiFi, Mahout, HBase Spark Connector, GraphFrames, H2O and Hivemall. Book Description Big Data Analytics book aims at providing the fundamentals of Apache Spark and Hadoop. All Spark components – Spark Core, Spark SQL, DataFrames, Data sets, Conventional Streaming, Structured Streaming, MLlib, Graphx and Hadoop core components – HDFS, MapReduce and Yarn are explored in greater depth with implementation examples on Spark + Hadoop clusters. It is moving away from MapReduce to Spark. So, advantages of Spark over MapReduce are explained at great depth to reap benefits of in-memory speeds. DataFrames API, Data Sources API and new Data set API are explained for building Big Data analytical applications. Real-time data analytics using Spark Streaming with Apache Kafka and HBase is covered to help building streaming applications. New Structured streaming concept is explained with an IOT (Internet of Things) use case. Machine learning techniques are covered using MLLib, ML Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get started with web based notebooks such as Jupyter, Apache Zeppelin and data flow tool Apache NiFi to analyze and visualize data. What you will learn Find out and implement the tools and techniques of big data analytics using Spark on Hadoop clusters with wide variety of tools used with Spark and Hadoop Understand all the Hadoop and Spark ecosystem components Get to know all the Spark components: Spark Core, Spark SQL, DataFrames, DataSets, Conventional and Structured Streaming, MLLib, ML Pipelines and Graphx See batch and real-time data analytics using Spark Core, Spark SQL, and Conventional and Structured Streaming Get to grips with data science and machine learning using MLLib, ML Pipelines, H2O, Hivemall, Graphx, SparkR and Hivemall. About the Author Venkat Ankam has over 18 years of IT experience and over 5 years in big data technologies, working with customers to design and develop scalable big data applications. Having worked with multiple clients globally, he has tremendous experience in big data analytics using Hadoop and Spark. He is a Cloudera Certified Hadoop Developer and Administrator and also a Databricks Certified Spark Developer. He is the founder and presenter of a few Hadoop and Spark meetup groups globally and loves to share knowledge with the community. Venkat has delivered hundreds of trainings, presentations, and white papers in the big data sphere. While this is his first attempt at writing a book, many more books are in the pipeline. Table of Contents Chapter 1: Big Data Analytics at a 10,000-Foot View Chapter 2: Getting Started with Apache Hadoop and Apache Spark Chapter 3: Deep Dive into Apache Spark Chapter 4: Big Data Analytics with Spark SQL, DataFrames, and Datasets Chapter 5: Real-Time Analytics with Spark Streaming and Structured Streaming Chapter 6: Notebooks and Dataflows with Spark and Hadoop Chapter 7: Machine Learning with Spark and Hadoop Chapter 8: Building Recommendation Systems with Spark and Mahout Chapter 9: Graph Analytics with GraphX Chapter 10: Interactive Analytics with SparkR

Kafka: The Definitive Guide 预览版

SMACK(Spark, Mesos, Akka, Cassandra, Kafka) 这本书讲解了大数据的一种技术架构选型：SMACK涉及的方方面面

Concurrency is everywhere. With the rise of multicore processors in the consumer market, the need for concurrent programming has overwhelmed the developer world. Where it once served to express asynchrony in programs and computer systems, and was largely an academic discipline, concurrent programming is now a pervasive methodology in software development. As a result, advanced concurrency frameworks and libraries are sprouting at an amazing rate. Recent years have witnessed a renaissance in the field of concurrent computing

Scala in Depth is a unique new book designed to help you integrate Scala effectively into your development process. By presenting the emerging best practices and designs from the Scala community, it guides you through dozens of powerful techniques example by example.

《JUnit实战(第2版)》从认识JUnit、不同的测试策略、JUnit与构建过程、JUnit扩展4个方面，由浅入深、由易到难地对JUnit展开了系统的讲解，包括探索JUnit的核心、软件测试原则、测试覆盖率与开发、使用stub进行粗粒度测试、使用mock objects进行测试、容器内测试、从Ant中运行JUnit测试、从Maven2中运行JUnit测试、持续集成工具、表示层的测试、Ajax测试、使用Cactus进行服务器端的Java测试、测试JSF应用程序、测试OSGi组件、测试数据库访问、测试基于JPA的应用程序、JUnit的其他用法等内容。

Building distributed applications is difficult enough without having to coordinate the actions that make them work. This practical guide shows how Apache ZooKeeper helps you manage distributed systems, so you can focus mainly on application logic. Even with ZooKeeper, implementing coordination tasks is not trivial, but this book provides good practices to give you a head start, and points out caveats that developers and administrators alike need to watch for along the way. In three separate sections, ZooKeeper contributors Flavio Junqueira and Benjamin Reed introduce the principles of distributed systems, provide ZooKeeper programming techniques, and include the information you need to administer this service.

golang 1.10 最新windows安装包 The most exciting part of this release for many people will probably be that the go tool now does automatic caching of build & test results. Of course, one of the hundreds of smaller changes may be your favorite.

proto buffer 最新官方全平台包 proto buffer 最新官方全平台包 proto buffer 最新官方全平台包

作者：汪晓明 授权发布 书籍简介：以太坊是一个全新开放的区块链平台，它允许任何人在平台中建立和使用通过区块链技术运行的去中心化应用。就像比特币一样，以太坊不受任何人控制，也不归任何人所有——它是一个开放源代码项目，由全球范围内的很多人共同创建。和比特币协议有所不同的是，以太坊的设计十分灵活，极具适应性。在以太坊平台上创立新的应用十分简便，随着Homestead的发布，任何人都可以安全地使用该平台上 的应用。

微服务设计模式 英文版 1 Escaping monolithic hell 2 Decomposition strategies 3 Inter-process communication in a microservice architecture 4 Managing transactions with sagas 5 Designing business logic in a micros ervice architecture 6 Developing business logic withevent sourcing 7 Implementing queries in a microservice architecture 8 External API patterns 9 Testing microservices 10 Microservices in production 11 Refactoring to microservices

PART 1: GETTING STARTED WITH KAFKA STREAMS 1 Welcome to Kafka Streams 2 Kafka Quickly PART 2: KAFKA STREAMS DEVELOPMENT 3 Developing Kafka Streams 4 Streams and State 5 The KTable API 6 The Processor

Mastering Bitcoin 2017年 第二版 PDF格式　 比特幣技術核心， 比特幣參考實現方案， 電子錢包， 比特幣交易和網絡協議 區块鏈的應用等等。

This book is intended to be a comprehensive guide to understanding and designing Reactive systems. Therefore, it includes not only an annotated version of the Reactive Manifesto, but also the reasoning that led to its inception. The main part of the book is a selection of design patterns that implement many facets of Reactive system design, with pointers toward deeper literature resources for further study. While the presented patterns form a cohesive whole, the list is not exhaustive—it cannot be—but the included background knowledge will enable the reader to identify, distill, and curate new patterns as the need arises.

Learning Concurrent Programming in Scala, 2nd Edition 最新版 pdf格式。全面介绍了并行原理。 Concurrent and parallel programming have progressed from niche disciplines, of interest only to kernel programming and high-performance computing, to something that every competent programmer must know. As parallel and distributed computing systems are now the norm, most applications are concurrent, be it for increasing the performance or for handling asynchronous events.

Microservice Patterns 的第一章

Build robust, highly scalable reactive web applications with Ratpack, the lightweight JVM framework. With this practical guide, you’ll discover how asynchronous applications differ from more traditional thread-per-request systems—and how you can reap the benefits of complex non-blocking through an API that makes the effort easy to understand and adopt. Author Dan Woods—a member of the Ratpack core team—provides a progressively in-depth tour of Ratpack and its capabilities, from basic concepts to tools and strategies to help you construct fast, test-driven applications in a semantic and expressive way. Ideal for Java web developers familiar with Grails or Spring, this book is applicable to all versions of Ratpack 1.x. Configure your applications and servers to accommodate the cloud Use Ratpack testing structures on both new and legacy applications Add advanced capabilities, such as component binding, with modules Explore Ratpack’s static content generation and serving mechanisms Provide a guaranteed execution order to asynchronous processing Model data and the data access layer to build high-performance, data-driven applications Work with reactive and functional programming strategies Use distribution techniques that support continuous delivery and other deployment tactics Table of Contents Chapter 1. Welcome to Ratpack Chapter 2. Getting Started Chapter 3. Testing Ratpack Applications Chapter 4. Application Configuration Chapter 5. Ratpack Modules Chapter 6. Serving Web Assets Chapter 7. Asynchronous Programming, Promises, and Executions Chapter 8. Data-Driven Web Applications Chapter 9. Ratpack and Spring Boot Chapter 10. Reactive Programming in Ratpack Chapter 11. Sessions and Security Chapter 12. Application Security Chapter 13. Going to Production

Master Wireshark to solve real-world security problems If you don’t already use Wireshark for a wide range of information security tasks, you will after this book. Mature and powerful, Wireshark is commonly used to find root cause of challenging network issues. This book extends that power to information security professionals, complete with a downloadable, virtual lab environment. Wireshark for Security Professionals covers both offensive and defensive concepts that can be applied to essentially any InfoSec role. Whether into network security, malware analysis, intrusion detection, or penetration testing, this book demonstrates Wireshark through relevant and useful examples. Master Wireshark through both lab scenarios and exercises. Early in the book, a virtual lab environment is provided for the purpose of getting hands-on experience with Wireshark. Wireshark is combined with two popular platforms: Kali, the security-focused Linux distribution, and the Metasploit Framework, the open-source framework for security testing. Lab-based virtual systems generate network traffic for analysis, investigation and demonstration. In addition to following along with the labs you will be challenged with end-of-chapter exercises to expand on covered material. Lastly, this book explores Wireshark with Lua, the light-weight programming language. Lua allows you to extend and customize Wireshark’s features for your needs as a security professional. Lua source code is available both in the book and online. Lua code and lab source code are available online through GitHub, which the book also introduces. The book’s final two chapters greatly draw on Lua and TShark, the command-line interface of Wireshark. By the end of the book you will gain the following: Master the basics of Wireshark Explore the virtual w4sp-lab environment that mimics a real-world network Gain experience using the Debian-based Kali OS among other systems Understand the technical details behind network attacks Execute exploitation and grasp offensive and defensive activities, exploring them through Wireshark Employ Lua to extend Wireshark features and create useful scripts To sum up, the book content, labs and online material, coupled with many referenced sources of PCAP traces, together present a dynamic and robust manual for information security professionals seeking to leverage Wireshark. Table of Contents Chapter 1 Introducing Wireshark Chapter 2 Setting Up the Lab Chapter 3 The Fundamentals Chapter 4 Capturing Packets Chapter 5 Diagnosing Attacks Chapter 6 Offensive Wireshark Chapter 7 Decrypting TLS, Capturing USB, Keyloggers, and Network Graphing Chapter 8 Scripting with Lua

该书用了千页的篇幅讲述了五大板块的内容。其中第一篇就由证明到数据型讲述了数学分析的基本内容，该篇幅为计算机科学的开发者们提供了宝贵的推理和逻辑演绎能力。随后在第二篇「结构」中，该书以数论开始讲述，首先就重点介绍了数论的主题整数集的性能，并由此衍生到计算机科学最基础的结构图论（Graphs）或者说是网络（networks）。在随后的两章节中，该书又向我们介绍了计算理论和概率论，这一部分在我们构建机器学习模型时十分重要和有效。 在该书中，作者在第四章着重介绍了对机器学习算法有重要作用的概率论，其中从概率论那一部分的目录和简介可以看出来作者主要讲述了基本的概率定义和数字特征与假设检验基础，随后由这些基本概率论的定义引出了统计学模型，包括中心极限定理，切比雪夫不等式和马尔可夫理论等重要内容。而这些统计学概念和模型却又正好是机器学习的方法基础。下面让我们一起来看看该书的章节目录： I 数学分析（Proofs） 简介（Introduction） 0.1 参考文献（References） 1 什么是证明？（What is a Proof?） 1.1 命题（Propositions） 1.2 谓词（Predicates） 1.3 公理化方法（The Axiomatic Method） 1.4 我们的公理（Our Axioms） 1.5 证明命题的含义（Proving an Implication） 1.6 证明「有且仅有」（Proving an「If and Only If」） 1.7 案例证明（Proof by Cases） 1.8 反证法（Proof by Contradiction） 1.9 证明的实战演练（Good Proofs in Practice） 1.10 参考文献（References） 2 良序原则（The Well Ordering Principle） 2.1 良序证明（Well Ordering Proofs） 2.2 良序证明模式（Template for Well Ordering Proofs） 2.3 素数因子分解（Factoring into Primes） 2.4 良序集合（Well Ordered Sets） 3 逻辑公式（Logical Formulas） 3.1 命题中的命题（Propositions from Propositions） 3.2 计算机程序中的命题逻辑（Propositional Logic in Computer Programs） 3.3 等价性和有效性（Equivalence and Validity） 3.4 命题的代数（The Algebra of Propositions） 3.5 SAT 问题（The SAT Problem） 3.6 谓词公式（Predicate Formulas） 3.7 参考文献（References） 4 数学上的数据类型（Mathematical Data Types） 4.1 集合（Sets） 4.2 序列（Sequences） 4.3 函数（Functions） 4.4 二元关系（Binary Relations） 4.5 有限基数（Finite Cardinality） 5 简介（Induction） 5.1 一般归纳法（Ordinary Induction） 5.2 强归纳法（Strong Induction） 5.3 强归纳法、一般归纳法和良序法（Strong Induction vs. Induction vs. Well Ordering） 6 状态机（State Machines） 6.1 状态和转换（States and Transitions） 6.2 不变量原则（The Invariant Principle） 6.3 部分正确性和终止（Partial Correctness & Termination） 6.4 稳定婚姻问题（The Stable Marriage Problem） 7 递归数据型（Recursive Data Types） 7.1 递归定义和结构归纳法（Recursive Definitions and Structural Induction） 7.2 Matched Brackets 字符串（Strings of Matched Brackets） 7.3 非负整数递归函数（Recursive Functions on Nonnegative Integers） 7.4 算术表达式（Arithmetic Expressions） 7.5 递归数据型在计算机科学中的简介（Induction in Computer Science） 8 无限集（Infinite Sets） 8.1 无限基数集（Infinite Cardinality） 8.2 停止问题（The Halting Problem） 8.3 集合的逻辑（The Logic of Sets） 8.4 这些真的有效吗？（Does All This Really Work?） II 结构（Structures） Introduction 9 数论（Number Theory） 9.1 可分性（Divisibility） 9.2 最大公约数（The Greatest Common Divisor） 9.3 神秘的素数（Prime Mysteries） 9.4 算术的基本定理（The Fundamental Theorem of Arithmetic） 9.5 Alan Turing 9.6 模运算（Modular Arithmetic） 9.7 余数运算（Remainder Arithmetic） 9.8 Turing's Code (Version 2.0) 9.9 乘法逆运算和消除（Multiplicative Inverses and Cancelling） 9.10 欧拉定理（Euler's Theorem） 9.11 RSA 公钥加密（RSA Public Key Encryption） 9.12 SAT 与它有什么关系？（What has SAT got to do with it?） 9.13 参考文献（References） 10 有向图和部分排序（Directed graphs & Partial Orders） 10.1 顶点度（Vertex Degrees） 10.2 步长与路径（Walks and Paths） 10.3 临近矩阵（Adjacency Matrices） 10.4 Walk Relations 10.5 有向非循环图标和时序（Directed Acyclic Graphs & Scheduling） 10.6 局部排序（Partial Orders） 10.7 通过集合遏制表征局部排序（Representing Partial Orders by Set Containment） 10.8 线性排序（Linear Orders） 10.9 乘积排序（Product Orders） 10.10 等价关系（Equivalence Relations） 10.11 关系属性总结（Summary of Relational Properties） 11 通信网络（Communication Networks） 11.1 路由（Routing） 11.2 Routing Measures） 11.3 网络设计（Network Designs） 12 简单图（Simple Graphs） 12.1 Vertex Adjacency and Degrees） 12.2 美国性别人口统计（Sexual Demographics in America） 12.3 一些常见的图（Some Common Graphs） 12.4 同构（Isomorphism） 12.5 二部图&匹配（Bipartite Graphs & Matchings） 12.6 Coloring 12.7 Simple Walks 12.8 连接（Connectivity） 12.9 森林和树（Forests & Trees） 12.10 References 13 平面图（Planar Graphs） 13.1 在平面中绘制图（Drawing Graphs in the Plane） 13.2 平面图的定义（Definitions of Planar Graphs） 13.3 欧拉公式（Euler's Formula） 13.4 在平面图中限定边的数量（Bounding the Number of Edges in a Planar Graph） 13.5 Returning to K5 and K3;3 13.6 Coloring Planar Graphs 13.7 Classifying Polyhedra 13.8 平面图的另一种特征化（Another Characterization for Planar Graphs） III 计数（Counting） Introduction 14 逼近求和（Sums and Asymptotics） 14.1 养老金的价值（The Value of an Annuity） 14.2 幂级数求和 Sums of Powers） 14.3 逼近求和（Approximating Sums） 14.4 Hanging Out Over the Edge） 14.5 乘积（Products） 14.6 Double Trouble 14.7 渐进的符号表示（Asymptotic Notation） 15 基数法则（Cardinality Rules） 15.1 由计算另一项计算该项（Counting One Thing by Counting Another） 15.2 计算序列（Counting Sequences） 15.3 广义乘积法则（The Generalized Product Rule） 15.4 除法法则（The Division Rule） 15.5 子集计算（Counting Subsets） 15.6 重复序列（Sequences with Repetitions） 15.7 Counting Practice: Poker Hands 15.8 鸽巢原理（The Pigeonhole Principle） 15.9 包含与排斥（Inclusion-Exclusion） 15.10 组合证明（Combinatorial Proofs） 15.11 References 16 母函数（Generating Functions） 16.1 无穷级数（Infinite Series） 16.2 使用母函数进行计数（Counting with Generating Functions） 16.3 部分分式（Partial Fractions） 16.4 求解线性递归（Solving Linear Recurrences） 16.5 形式幂级数（Formal Power Series） 16.6 References IV 概率论（Probability） Introduction 17 事件和概率空间（Events and Probability Spaces） 17.1 Let's Make a Deal 17.2 四步法（The Four Step Method） 17.3 Strange Dice 17.4 生日原则（The Birthday Principle） 17.5 集合论和概率论（Set Theory and Probability） 17.6 References 18 条件概率（Conditional Probability） 18.1 Monty Hall Confusion 18.2 定义和符号（Definition and Notation） 18.3 条件概率的四步法（The Four-Step Method for Conditional Probability） 18.4 为什么树状图如此有效（Why Tree Diagrams Work） 18.5 全概法则（The Law of Total Probability） 18.6 辛普森悖论（Simpson's Paradox） 18.7 独立性（Independence） 18.8 相互独立性（Mutual Independence） 18.9 概率与置信度（Probability versus Confidence） 19 随机变量（Random Variables） 19.1 随机样本（Random Variable Examples） 19.2 独立性（Independence） 19.3 分布函数（Distribution Functions） 19.4 期望（Great Expectations） 19.5 线性期望（Linearity of Expectation） 20 平均偏差（Deviation from the Mean） 20.1 马尔可夫定理（Markov‘s Theorem） 20.2 切比雪夫定理（Chebyshev's Theorem） 20.3 方差的性质（Properties of Variance） 20.4 随机样本估计（Estimation by Random Sampling） 20.5 估计置信度（Confidence in an Estimation） 20.6 随机变量加和（Sums of Random Variables） 20.7 Really Great Expectations 21 随机步（Random Walks） 21.1 Gambler’s Ruin 21.2 图表中的随机步（Random Walks on Graphs） V Recurrences Introduction 22 Recurrences 22.1 The Towers of Hanoi 22.2 Merge Sort 22.3 Linear Recurrences 22.4 Divide-and-Conquer Recurrences 22.5 A Feel for Recurrences 参考书目（Bibliography） 符号词汇表（Glossary of Symbols） 索引（Index）

Maven权威指南是一本关于Apache Maven的书。完整版的Maven权威指南，包括了其他版本缺失的12,13,15,17,18章以及附录，目录书签更加详细。 Copyright 1. Creative Commons BY-ND-NC Foreword: Beta 0.16 Preface 1. How to Use this Book 2. Your Feedback 3. Font Conventions 4. Maven Writing Conventions 5. Acknowledgements 1. 介绍 Apache Maven 1.1. Maven... 它是什么? 1.2. 约定优于配置（Convention Over Configuration） 1.3. 一个一般的接口 1.4. 基于Maven插件的全局性重用 1.5. 一个“项目”的概念模型 1.6. Maven是Ant的另一种选择么？ 1.7. 比较Maven和Ant 1.8. 总结 2. 安装和运行Maven 2.1. 验证你的Java安装 2.2. 下载Maven 2.3. 安装Maven 2.3.1. 在Mac OSX上安装Maven 2.3.2. 在Microsoft Windows上安装Maven 2.3.3. 在Linux上安装Maven 2.3.4. 在FreeBSD或OpenBSD上安装Maven 2.4. 验证Maven安装 2.5. Maven安装细节 2.5.1. 用户相关配置和仓库 2.5.2. 升级Maven 2.6. 获得Maven帮助 2.7. 使用Maven Help插件 2.7.1. 描述一个Maven插件 2.8. 关于Apache软件许可证 I. Maven实战 3. 一个简单的Maven项目 3.1. 简介 3.1.1. 下载本章的例子 3.2. 创建一个简单的项目 3.3. 构建一个简单的项目 3.4. 简单的项目对象模型 (Project Object Model) 3.5. 核心概念 3.5.1. Maven插件和目标 (Plugins and Goals) 3.5.2. Maven生命周期 (Lifecycle) 3.5.3. Maven坐标 (Coordinates) 3.5.4. Maven仓库(Repositories) 3.5.5. Maven依赖管理 (Dependency Management) 3.5.6. 站点生成和报告 (Site Generation and Reporting) 3.6. 小结 4. 定制一个Maven项目 4.1. 介绍 4.1.1. 下载本章样例 4.2. 定义Simple Weather项目 4.2.1. Yahoo! Weather RSS 4.3. 创建Simple Weather项目 4.4. 定制项目信息 4.5. 添加新的依赖 4.6. Simple Weather源码 4.7. 添加资源 4.8. 运行Simple Weather项目 4.8.1. Maven Exec 插件 4.8.2. 浏览你的项目依赖 4.9. 编写单元测试 4.10. 添加测试范围依赖 4.11. 添加单元测试资源 4.12. 执行单元测试 4.12.1. 忽略测试失败 4.12.2. 跳过单元测试 4.13. 构建一个打包好的命令行应用程序 5. 一个简单的Web应用 5.1. 介绍 5.1.1. 下载本章样例 5.2. 定义这个简单的Web应用 5.3. 创建这个简单的Web应用 5.4. 配置Jetty插件 5.5. 添加一个简单的Servlet 5.6. 添加J2EE依赖 5.7. 小结 6. 一个多模块项目 6.1. 简介 6.1.1. 下载本章样例 6.2. simple-parent 项目 6.3. simple-weather 模块 6.4. simple-webapp 模块 6.5. 构建这个多模块项目 6.6. 运行Web应用 7. 多模块企业级项目 7.1. 简介 7.1.1. 下载本章样例 7.1.2. 多模块企业级项目 7.1.3. 本例中所用的技术 7.2. simple-parent项目 7.3. simple-model模块 7.4. simple-weather模块 7.5. simple-persist模块 7.6. simple-webapp模块 7.7. 运行这个Web应用 7.8. simple-command模块 7.9. 运行这个命令行程序 7.10. 小结 7.10.1. 编写接口项目程序 8. 优化和重构POM 8.1. 简介 8.2. POM清理 8.3. 优化依赖 8.4. 优化插件 8.5. 使用Maven Dependency插件进行优化 8.6. 最终的POM 8.7. 小结 II. Maven Reference 9. 项目对象模型 9.1. 简介 9.2. POM 9.2.1. 超级POM 9.2.2. 最简单的POM 9.2.3. 有效POM 9.2.4. 真正的POM 9.3. POM语法 9.3.1. 项目版本 9.3.1.1. 版本构建号 9.3.1.2. SNAPSHOT版本 9.3.1.3. LATEST 和 RELEASE 版本 9.3.2. 属性引用 9.4. 项目依赖 9.4.1. 依赖范围 9.4.2. 可选依赖 9.4.3. 依赖版本界限 9.4.4. 传递性依赖 9.4.4.1. 传递性依赖和范围 9.4.5. 冲突解决 9.4.6. 依赖管理 9.5. 项目关系 9.5.1. 坐标详解 9.5.2. 多模块项目 9.5.3. 项目继承 9.6. POM最佳实践 9.6.1. 依赖归类 9.6.2. 多模块 vs. 继承 9.6.2.1. 简单项目 9.6.2.2. 多模块企业级项目 9.6.2.3. 原型父项目 10. 构建生命周期 10.1. 简介 10.1.1. 清理生命周期 (clean) 10.1.2. 默认生命周期 (default) 10.1.3. 站点生命周期 (site) 10.2. 打包相关生命周期 10.2.1. JAR 10.2.2. POM 10.2.3. Maven Plugin 10.2.4. EJB 10.2.5. WAR 10.2.6. EAR 10.2.7. 其它打包类型 10.3. 通用生命周期目标 10.3.1. Process Resources 10.3.2. Compile 10.3.3. Process Test Resources 10.3.4. Test Compile 10.3.5. Test 10.3.6. Install 10.3.7. Deploy 11. 构建Profile 11.1. Profile是用来做什么的? 11.1.1. 什么是构建可移植性 11.1.1.1. 不可移植构建 11.1.1.2. 环境可移植性 11.1.1.3. 组织（内部）可移植性 11.1.1.4. 广泛（全局）可移植性 11.1.2. 选择一个适当级别的可移植性 11.2. 通过Maven Profiles实现可移植性 11.2.1. 覆盖一个项目对象模型 11.3. 激活Profile 11.3.1. 激活配置 11.3.2. 通过属性缺失激活 11.4. 外部Profile 11.5. Settings Profile 11.5.1. 全局Settings Profile 11.6. 列出活动的Profile 11.7. 提示和技巧 11.7.1. 常见的环境 11.7.2. 安全保护 11.7.3. 平台分类器 11.8. 小结 12. Maven套件 12.1. 简介 12.2. Assembly基础 12.2.1. 预定义的套件描述符 12.2.2. 构建一个套件Building an Assembly 12.2.3. 套件作为依赖 12.2.4. 通过套件依赖组装套件 12.3. 套件描述符概述 12.4. 套件描述符 12.4.1. 套件描述符中的属性引用 12.4.2. 必须的套件信息 12.5. 控制一个套件的内容 12.5.1. Files 元素 12.5.2. FileSets 元素 12.5.3. fileSets的默认排除模式 12.5.4. dependencySets 元素 12.5.4.1. 自定义依赖输出目录 12.5.4.2. 依赖输出位置的属性插值 12.5.4.3. Including and Excluding Dependencies by Scope 12.5.4.4. Fine Tuning: Dependency Includes and Excludes 12.5.4.5. Transitive Dependencies, Project Attachments, and Project Artifacts 12.5.4.6. Advanced Unpacking Options 12.5.4.7. Summarizing Dependency Sets 12.5.5. moduleSets 部分 12.5.5.1. Module Selection 12.5.5.2. Sources Section 12.5.5.3. Interpolation of outputDirectoryMapping in moduleSets 12.5.5.4. Binaries section 12.5.5.5. moduleSets, Parent POMs and the binaries Section 12.5.6. Repositories Section 12.5.7. Managing the Assembly’s Root Directory 12.5.8. componentDescriptors and containerDescriptorHandlers 12.6. Best Practices 12.6.1. Standard, Reusable Assembly Descriptors 12.6.2. Distribution (Aggregating) Assemblies 12.7. Summary 13. 属性和资源过滤 13.1. 简介 13.2. Maven属性 13.2.1. Maven项目的属性 13.2.2. Maven的Settings属性 13.2.3. 环境变量属性 13.2.4. Java系统属性 13.2.5. 用户定义的属性 13.3. 资源过滤 14. Maven和Eclipse: m2eclipse 14.1. 简介 14.2. m2eclipse 14.3. 安装 m2eclipse 插件 14.3.1. 安装前提条件 14.3.1.1. 安装 Subclipse 14.3.1.2. 安装 Mylyn 14.3.1.3. 安装 AspectJ Tools Platform (AJDT) 14.3.1.4. 安装 Web Tools Platform (WTP) 14.3.2. 安装 m2eclipse 14.4. 开启 Maven 控制台 14.5. 创建一个 Maven 项目 14.5.1. 从 SCM 签出一个 Maven 项目 14.5.2. 用Maven Archetype创建一个Maven项目 14.5.3. 创建一个 Maven 模块 14.6. 创建一个Maven POM文件 14.7. 导入Maven项目 14.7.1. 导入一个Maven项目 14.7.2. 具体化一个Maven项目 14.8. 运行Maven构建 14.9. 使用Maven进行工作 14.9.1. 添加及更新依赖或插件 14.9.2. 创建一个Maven模块 14.9.3. 下载源码 14.9.4. 打开项目页面 14.9.5. 解析依赖 14.10. 使用Maven仓库进行工作 14.10.1. 搜索 Maven 构件和 Java 类 14.10.2. 为Maven仓库编制索引 14.11. 使用基于表单的POM编辑器 14.12. 在m2eclipse中分析项目依赖 14.13. Maven 选项 14.14. 小结 15. 站点生成 15.1. 简介 15.2. 使用Maven构建项目站点 15.3. 自定义站点描述符 15.3.1. 自定义页面顶端图片 15.3.2. 自定义导航菜单 15.4. 站点目录结构 15.5. 编写项目文档 15.5.1. APT样例 15.5.2. FML样例 15.6. 部署你的项目web站点 15.6.1. 配置服务器认证 15.6.2. 配置文件和目录模式 15.7. 自定义站点外观 15.7.1. 自定义站点CSS 15.7.2. 创建自定义的站点模板 15.7.3. 可重用的web站点皮肤 15.7.4. 创建自定义的主题CSS 15.7.5. 在皮肤中自定义站点模板 15.8. 提示与技巧 15.8.1. 给HEAD嵌入XHTML 15.8.2. 在你站点logo下添加链接 15.8.3. 为你的站点添加导航链接 15.8.4. 添加项目版本 15.8.5. 修改发布日期格式和位置 15.8.6. 使用Doxia宏 16. 仓库管理器 16.1. 简介 16.1.1. Nexus历史 16.2. 安装Nexus 16.2.1. 从Sonatype下载Nexus 16.2.2. 安装Nexus 16.2.3. 运行Nexus 16.2.4. 安装后检查单 16.2.5. 为RedHat/Fedora/CentOS设置启动脚本 16.2.6. 升级Nexus版本 16.3. 使用Nexus 16.3.1. 浏览仓库 16.3.2. 浏览组 16.3.3. 搜索构件 16.3.4. 浏览系统RSS源 16.3.5. 浏览日志文件和配置 16.3.6. 更改你的密码 16.4. 配置Maven使用Nexus 16.4.1. 使用Nexus中央代理仓库 16.4.2. 使用Nexus作为快照仓库 16.4.3. 为缺少的依赖添加仓库 16.4.4. 添加一个新的仓库 16.4.5. 添加一个仓库至一个组 16.5. 配置Nexus 16.5.. 定制服务器配置 16.5.2. 管理仓库 16.5.3. 管理组 16.5.4. 管理路由 16.5.5. 网络配置 16.6. 维护仓库 16.7. 部署构件至Nexus 16.7.1. 部署发布版 16.7.2. 部署快照版 16.7.3. 部署第三方构件 17. 编写插件 17.1. 简介 17.2. Maven编程 17.2.1. 什么是反转控制？ 17.2.2. Plexus简介 17.2.3. 为什么使用Plexus? 17.2.4. 什么是插件？ 17.3. 插件描述符 17.3.1. 顶层插件描述符元素 17.3.2. Mojo��置 17.3.3. 插件依赖 17.4. 编写自定义插件 17.4.1. 创建一个插件项目 17.4.2. 一个简单的Java Mojo 17.4.3. 配置插件前缀 17.4.4. 插件中的日志 17.4.5. Mojo类注解 17.4.6. 当Mojo失败的时候 17.5. Mojo参数 17.5.1. 为Mojo参数提供值 17.5.2. 多值的Mojo参数 17.5.3. 依赖于一个Plexus组件 17.5.4. Mojo参数注解 17.6. 插件和Maven生命周期 17.6.1. 执行平行的生命周期 17.6.2. 创建自定义的生命周期 17.6.3. 覆盖默认生命周期 18. Writing Plugins in Alternative Languages 18.1. Writing Plugins in Ant 18.2. Creating an Ant Plugin 18.3. Writing Plugins in JRuby 18.3.1. Creating a JRuby Plugin 18.3.2. Ruby Mojo Implementations 18.3.3. Logging from a Ruby Mojo 18.3.4. Raising a MojoError 18.3.5. Referencing Plexus Components from JRuby 18.4. Writing Plugins in Groovy 18.4.1. Creating a Groovy Plugin A. 附录: Settings细节 A.1. 简介 A.2. Settings细节 A.2.1. 简单值 A.2.2. 服务器（Servers） A.2.3. 镜像（Mirrors） A.2.4. 代理（Proxies） A.2.5. Profiles A.2.6. 激活（Activation） A.2.7. 属性（Properties） A.2.8. 仓库（Repositories） A.2.9. 插件仓库 A.2.10. 激活的Profile B. Appendix: Sun Specification Alternatives List of Figures List of Examples

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