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Lynda – Hadoop Fundamentals

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Lynda - Hadoop Fundamentals

475MB | Duration: 4h 48m | Video: AVC (.mp4) 1280x720 15fps | Audio: AAC 48KHz 2ch

Genre: eLearning | Level: Intermediate | Language: English

Hadoop is indispensible when it comes to processing big data—as necessary to understanding your information as servers are to storing it. This course is your introduction to Hadoop, its file system (HDFS), its processing engine (MapReduce), and its many libraries and programming tools. Developer and big-data consultant Lynn Langit shows how to set up a Hadoop development environment, run and optimize MapReduce jobs, code basic queries with Hive and Pig, and build workflows to schedule jobs. Plus, get a sneak peek at some up-and-coming libraries like Impala and the lightning-fast Spark.

Topics include:

* Understanding Hadoop core components: HDFS and MapReduce
* Setting up your Hadoop development environment
* Working with the Hadoop file system
* Running and tracking Hadoop jobs
* Tuning MapReduce
* Understanding Hive and HBase
* Exploring Pig tools
* Building workflows
* Using other libraries, such as Impala, Mahout, and Storm
* Understanding Spark
* Visualizing Hadoop output
Lynda - Hadoop Fundamentals

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  1. Lynda - Hadoop基础教程 Hadoop在处理你信息的时候就像你的服务器存储它们一样是不可或缺的。本教程会向你介绍Hadoop,其稳健系统、其处理引擎以及其类库和编程工具。开发者和打数据咨询师Lynn Langit会将借如何建立Hadoop开发环境,运行和优化MapReduce工作,利用Hive和Pig进行基本的查询,以及建立计划工作的开发流程。另外,还会对一些常用的类库,如Impala和轻量级的Spark作一简介。 主要内容:了解Hadoop核心组件;建立Hadoop开发环境;处理Hadoop文件系统;运行和跟踪Hadoop任务;调试MapReduce;了解Hive和HBase;了解Pig工具;开发工作流程;使用类库,如Impala,Mahout和Storm;理解Spark;可视化Hadoop输出结果。
    wilde(特殊组-翻译)2年前 (2015-01-22)