基于hadoop2.7.2，scala2.11的sparklinux软件包，解压到指定目录后即可使用，实测可行

hadoop-eclipse开发插件，此jar所支持的是hadoop-1.2.1，请下载该插件后放置于Eclipse\plugins目录下，然后重启eclipse即可。

该jar包是属于大数据hadoop使用的些jar包，可以在编写代码的时候导入工程中 该jar包是属于大数据hadoop使用的些jar包，可以在编写代码的时候导入工程中

人工智能-hadoop

基于Hadoop大数据平台对某网站的外卖订单数据进行分析，分析结果进行可视化展示

Title: Hadoop in Practice, 2nd Edition Author: Alex Holmes Length: 512 pages Edition: 2 Language: English Publisher: Manning Publications Publication Date: 2014-10-12 ISBN-10: 1617292222 ISBN-13: 9781617292224 Summary Hadoop in Practice, Second Edition provides over 100 tested, instantly useful techniques that will help you conquer big data, using Hadoop. This revised new edition covers changes and new features in the Hadoop core architecture, including MapReduce 2. Brand new chapters cover YARN and integrating Kafka, Impala, and Spark SQL with Hadoop. You'll also get new and updated techniques for Flume, Sqoop, and Mahout, all of which have seen major new versions recently. In short, this is the most practical, up-to-date coverage of Hadoop available anywhere. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Book It's always a good time to upgrade your Hadoop skills! Hadoop in Practice, Second Edition provides a collection of 104 tested, instantly useful techniques for analyzing real-time streams, moving data securely, machine learning, managing large-scale clusters, and taming big data using Hadoop. This completely revised edition covers changes and new features in Hadoop core, including MapReduce 2 and YARN. You'll pick up hands-on best practices for integrating Spark, Kafka, and Impala with Hadoop, and get new and updated techniques for the latest versions of Flume, Sqoop, and Mahout. In short, this is the most practical, up-to-date coverage of Hadoop available. Readers need to know a programming language like Java and have basic familiarity with Hadoop. What's Inside Thoroughly updated for Hadoop 2 How to write YARN applications Integrate real-time technologies like Storm, Impala, and Spark Predictive analytics using Mahout and RR Readers need to know a programming language like Java and have basic familiarity with Hadoop. About the Author Alex Holmes works on tough big-data problems. He is a software engineer, author, speaker, and blogger specializing in large-scale Hadoop projects. Table of Contents Part 1: Background and fundamentals Chapter 1: Hadoop in a heartbeat Chapter 2: Introduction to YARN Part 2: Data logistics Chapter 3: Data serialization— working with text and beyond Chapter 4: Organizing and optimizing data in HDFS Chapter 5: Moving data into and out of Hadoop Part 3: Big data patterns Chapter 6: Applying MapReduce patterns to big data Chapter 7: Utilizing data structures and algorithms at scale Chapter 8: Tuning, debugging, and testing Part 4: Beyond MapReduce Chapter 9: SQL on Hadoop Chapter 10: Writing a YARN application Appendix: Installing Hadoop and friends

jar包引入命令：mvn install:install-file -DgroupId=com.cloudera -DartifactId=ImpalaJDBC41 -Dversion=2.6.3 -Dpackaging=jar -Dfile=./ImpalaJDBC41-2.6.3.jar DgroupId: pom.xml配置中groupId的值 DartifactId: pom.xml配置中artifactId的值 Dversion: 版本号 Dpackaging: 文件类型 Dfile: 文件路径

计算机毕业设计Python+Spark游戏推荐系统 游戏可视化 游戏爬虫 游戏用户画像系统 游戏大屏可视化 游戏数据分析 游戏情感分析 神经网络混合CF推荐算法 大数据毕业设计 大数据毕设

提出了一款基于Hadoop的并行数据分析系统―――PDM.该系统拥有大量以MapReduce为计算框架的并行数据分析算法,不仅包括传统的ETL、数据挖掘、数据统计和文本分析算法,还引入了基于图理论的SNA(社会网络分析)算法.详细阐述了并行多元线性回归算法和“多源最短路径”算法的原理和实现,其中,提出的“消息传递模型”能有效解决MapReduce难以处理邻接矩阵的问题;介绍了基于电信数据的典型应用,如采用并行k均值和决策树算法实现的“套餐推荐”,利用并行PageRank算法实现的“营销关键点发现”等;最后

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