Hadoop 英文视频教程

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    过年回来发现竟然成功申请了hadoop版主了，我刚开始准备学习集群方面的东西，目前学Linux。

   下面是我收集的一些hadoop英文视频，免费给大家下载，就当见面礼好了，嘿嘿。

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关键词：Hadoop 视频教程 Had Linux 见面礼 视频教程

SQL on Hadoop – Analyzing Big Data with Hive

百度网盘下载地址：
http://pan.baidu.com/s/1pJ80qd9

密码：7li1

This course will teach you the Hive query language and how to apply it to solve common Big Data problems. This includes an introduction to distributed computing, Hadoop, and MapReduce fundamentals and the latest features released with Hive 0.11. From developer to analyst, this course tackles a few big questions about big data: Why does this technology exist and why do I need it? How can I get the best out of it utilizing something familiar like SQL and how does this all fit together in an ever-evolving eco-system? This course will introduce the concepts of distributed computing, Hadoop and MapReduce and then goes into great detail into Apache Hive which is an SQL-like query language that can be used with Hadoop and NoSQL databases like HBase and Cassandra. The course presents some challenges you might experience solving real production problems and how Hive makes that task easier to accomplish.

│ sql-hadoop-analyzing-big-data-hive.zip
│
├───01. Introduction to Hadoop
│ 01. Introduction.wmv
│ 02. Motivation for Hadoop.wmv
│ 03. Distributed Computing Challenges.wmv
│ 04. Hadoop File System (HDFS).wmv
│ 05. MapReduce.wmv
│ 06. Word Count Example.wmv
│ 07. Demo Basic Hadoop Commands and Environment Setup.wmv
│ 08. Summary.wmv
│
├───02. Introduction to Hive
│ 01. Introduction.wmv
│ 02. O£Hive Motivation.wmv
│ 03. Hive Architecture.wmv
│ 04. Hive Principles – Schema on Read.wmv
│ 05. Hive Principles – The Hive Warehouse.wmv
│ 06. Hive Query Language Basics – SELECT and Sub Queries.wmv
│ 07. Creating Databases and Tables with HiveQL.wmv
│ 08. Demo Working with Hive Tables and Loading Data into Warehouse.wmv
│ 09. Loading Data – Hive Managed and External Tables.wmv
│ 10. Demo External Tables and Create Table Alternatives.wmv
│ 11. Summary.wmv
│
├───03. Hive Query Language
│ 01. Introduction.wmv
│ 02. Data Types.wmv
│ 03. Type Conversions.wmv
│ 04. Managed Partitioned Tables.wmv
│ 05. External Partitioned Tables.wmv
│ 06. Demo Table Partitioning.wmv
│ 07. Multi Inserts and Dynamic Partition Inserts.wmv
│ 08. Demo Loading Data Use Case.wmv
│ 09. Data Retrieval – Group By and Functions.wmv
│ 10. Sorting and Controlling Data Flow.wmv
│ 11. The CLI and Variable Substitution.wmv
│ 12. Summary.wmv
│
├───04. Advanced HiveQL
│ 01. Introduction.wmv
│ 02. Bucketing.wmv
│ 03. Bucket and Block Sampling.wmv
│ 04. Joins.wmv
│ 05. Joins in Depth and Join Optimizations.wmv
│ 06. Map-side Joins for Bucketed Tables.wmv
│ 07. Distributed Cache.wmv
│ 08. UDTFs, Explode and Lateral View.wmv
│ 09. Demo Extending Hive – Creating Your own UDF.wmv
│ 10. Demo Extending Hive – Compiling and Testing Custom UDF.wmv
│ 11. Extending Hive – Custom UDF Recap.wmv
│ 12. Demo Hive Initialization File.wmv
│ 13. Accessing The Distributed Cache.wmv
│ 14. Hadoop Streaming and Transform().wmv
│ 15. Windowing and Analytics Functions.wmv
│ 16. Demo Putting it All Together Using Transform.wmv
│ 17. Demo Analytics Functions.wmv
│ 18. Demo Ranking Functions.wmv
│ 19. Summary.wmv
│
└───05. Storage and The Eco-System
01. Create Table Statement – File Formats and SerDes.wmv
02. HCatalog.wmv
03. Sqoop.wmv
04. DistCP.wmv
05. Hadoop Eco-System Projects.wmv
06. References and Resources.wmv
07. Summary.wmv

CBT Nuggets – Apache Hadoop

百度网盘：http://pan.baidu.com/s/1hqKPO36
密码：dv8u


The data revolution is upon us and Hadoop is THE leading Big Data platform. Fortune 500 companies are using it for storing and analyzing extremely large datasets, while other companies are realizing its potential and preparing their budgets for future Big Data positions. It’s the elephant in Big Data’s room
Recommended skills:
Familiarity with Ubuntu Linux
Recommended equipment:
Ubuntu Linux 12.04 LTS operating system
Related certifications:
None
Related job functions:
Big Data architects
Big Data administrators
Big Data developers
IT professionals
This series will get you up to speed on Big Data and Hadoop. Topics include how to install, configure and manage a single and multi-node Hadoop cluster, configure and manage HDFS, write MapReduce jobs and work with many of the projects around Hadoop such as Pig, Hive, HBase, Sqoop, and Zookeeper. Topics also include configuring Hadoop in the cloud and troubleshooting a multi-node Hadoop cluster.
(1/20) Hadoop Series Introduction
(2/20) Hadoop Technology Stack
(3/20) Hadoop Distributed File System (HDFS)
(4/20) Introduction to MapReduce
(5/20) Installing Apache Hadoop (Single Node)
(6/20) Installing Apache Hadoop (Multi Node)
(7/20) Troubleshooting, Administering and Optimizing Hadoop
(8/20) Managing HDFS
(9/20) MapReduce Development
(10/20) Introduction to Pig
(11/20) Developing with Pig
(12/20) Introduction to Hive
(13/20) Developing with Hive
(14/20) Introduction to HBase
(15/20) Developing with HBase
(16/20) Introduction to Zookeeper
(17/20) Introduction to Sqoop
(18/20) Local Hadoop: Cloudera CDH VM
(19/20) Cloud Hadoop: Amazon EMR
(20/20) Cloud Hadoop: Microsoft HDInsight

Live Lessons – Hadoop Fundamentals

百度网网盘：http://pan.baidu.com/s/1gdJ5WUf
密码：dc65

Live Lessons – Hadoop Fundamentals
WEB-Rip | AVC1 @ 1.5 Mbit/s | 1280×720 | AAC Stereo @ 128 Kbit/s 48 KHz | 4+ Hours | 2.14 GB
Genre: Hadoop Fundamentals | Language: English4+ Hours of Video Instruction
Apache Hadoop is a freely available open source tool-set that enables big data analysis. This Hadoop Fundamentals LiveLessons tutorial demonstrates the core components of Hadoop including Hadoop Distriuted File Systems (HDFS) and MapReduce. In addition, the tutorial demonstrates how to use Hadoop at several levels including the native Java interface, C++ pipes, and the universal streaming program interface. Examples of how to use high level tools include the Pig scripting language and the Hive “SQL like” interface. Finally, the steps for installing Hadoop on a desktop virtual machine, in a Cloud environment, and on a local stand-alone cluster are presented. Topics covered in this tutorial apply to Apache Hadoop versions 1 and 2 (i.e., MR2 or Yarn).
Douglas Eadline, PhD, began his career as a practitioner and a chronicler of the Linux Cluster HPC revolution and now documents big data analytics. Starting with the first Beowulf How To document, Dr. Eadline has written hundreds of articles, white papers, and instructional documents covering virtually all aspects of HPC computing. Prior to starting and editing the popular ClusterMonkey.net web site in 2005, he served as Editor­in­chief for ClusterWorld Magazine, and was Senior HPC Editor for Linux Magazine. Currently, he is a consultant to the HPC industry and writes a monthly column in HPC Admin Magazine. Both clients and readers have recognized Dr. Eadline’s ability to present a “technological value proposition” in a clear and accurate style. He has practical hands on experience in many aspects of HPC including, hardware and software design, benchmarking, storage, GPU, cloud, and parallel computing.
Lesson 1, “Background Concepts,” covers important Hadoop and Big Data fundamentals. You learn Hadoop history and design principles along with the
introduction to the MapReduce paradigm and the components of the Hadoop ecosystem will be introduced.
Lesson 2, “Running Hadoop on a Desktop or Laptop,” shows you how to create a real Hadoop working installation in a virtual Linux sandbox. All software is freely available, can be easily installed to a desktop or laptop computer, and can be used for many of the examples in this tutorial.
Lesson 3, “The Hadoop Distributed File System” introduces you to the distributed storage system of Hadoop. In this lesson, you learn HDFS design basics, how to perform basic file operations, and how to use HDFS in programs.
Lesson 4, “Hadoop MapReduce,” presents Hadoop MapReduce in more detail using simple command line examples. You also learn how to run a Java MapReduce application on a Hadoop cluster and then learn each step of the full Hadoop MapReduce process.
Lesson 5, “Hadoop Examples,” teaches you how to write MapReduce programs in almost any language using the Streaming and Pipes interface. You also learn how to run a “grep” like Hadoop application and use some basic debugging techniques.
Lesson 6, “Higher Level Tools,” shows you how to use Pig and Hive, two high level Hadoop applications. Each lesson teaches you the various execution modes and commands needed to use the tools.
Lesson 7, “Setting Up Hadoop in the Cloud,” demonstrates the simple steps needed to start a Hadoop Cluster in the cloud using a tool called Whirr.



Lesson 8, “Setting Up Hadoop on a Local Cluster,” teaches you how to install Hadoop on a basic four node cluster. You will learn the steps needed to configure, install, start, test, and monitor a fully functional Hadoop cluster.
LiveLessons Video Training series publishes hundreds of hands-on, expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. This professional and personal technology video series features world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, IBM Press, Pearson IT Certification, Prentice Hall, Sams, and Que. Topics include: IT Certification, Programming, Web Development, Mobile Development, Home & Office Technologies, Business & Management, and more.

Apache Hadoop Yarn (video Training)Live Lessons – Hadoop Fundamentals

百度网盘：http://pan.baidu.com/s/1nt5gC1z
密码：i9mb

Live Lessons – Hadoop Fundamentals
WEB-Rip | AVC1 @ 1.5 Mbit/s | 1280×720 | AAC Stereo @ 128 Kbit/s 48 KHz | 4+ Hours | 2.14 GB
Genre: Hadoop Fundamentals | Language: English4+ Hours of Video Instruction
Apache Hadoop is a freely available open source tool-set that enables big data analysis. This Hadoop Fundamentals LiveLessons tutorial demonstrates the core components of Hadoop including Hadoop Distriuted File Systems (HDFS) and MapReduce. In addition, the tutorial demonstrates how to use Hadoop at several levels including the native Java interface, C++ pipes, and the universal streaming program interface. Examples of how to use high level tools include the Pig scripting language and the Hive “SQL like” interface. Finally, the steps for installing Hadoop on a desktop virtual machine, in a Cloud environment, and on a local stand-alone cluster are presented. Topics covered in this tutorial apply to Apache Hadoop versions 1 and 2 (i.e., MR2 or Yarn).
Douglas Eadline, PhD, began his career as a practitioner and a chronicler of the Linux Cluster HPC revolution and now documents big data analytics. Starting with the first Beowulf How To document, Dr. Eadline has written hundreds of articles, white papers, and instructional documents covering virtually all aspects of HPC computing. Prior to starting and editing the popular ClusterMonkey.net web site in 2005, he served as Editor­in­chief for ClusterWorld Magazine, and was Senior HPC Editor for Linux Magazine. Currently, he is a consultant to the HPC industry and writes a monthly column in HPC Admin Magazine. Both clients and readers have recognized Dr. Eadline’s ability to present a “technological value proposition” in a clear and accurate style. He has practical hands on experience in many aspects of HPC including, hardware and software design, benchmarking, storage, GPU, cloud, and parallel computing.
Lesson 1, “Background Concepts,” covers important Hadoop and Big Data fundamentals. You learn Hadoop history and design principles along with the
introduction to the MapReduce paradigm and the components of the Hadoop ecosystem will be introduced.
Lesson 2, “Running Hadoop on a Desktop or Laptop,” shows you how to create a real Hadoop working installation in a virtual Linux sandbox. All software is freely available, can be easily installed to a desktop or laptop computer, and can be used for many of the examples in this tutorial.
Lesson 3, “The Hadoop Distributed File System” introduces you to the distributed storage system of Hadoop. In this lesson, you learn HDFS design basics, how to perform basic file operations, and how to use HDFS in programs.
Lesson 4, “Hadoop MapReduce,” presents Hadoop MapReduce in more detail using simple command line examples. You also learn how to run a Java MapReduce application on a Hadoop cluster and then learn each step of the full Hadoop MapReduce process.
Lesson 5, “Hadoop Examples,” teaches you how to write MapReduce programs in almost any language using the Streaming and Pipes interface. You also learn how to run a “grep” like Hadoop application and use some basic debugging techniques.
Lesson 6, “Higher Level Tools,” shows you how to use Pig and Hive, two high level Hadoop applications. Each lesson teaches you the various execution modes and commands needed to use the tools.
Lesson 7, “Setting Up Hadoop in the Cloud,” demonstrates the simple steps needed to start a Hadoop Cluster in the cloud using a tool called Whirr.



Lesson 8, “Setting Up Hadoop on a Local Cluster,” teaches you how to install Hadoop on a basic four node cluster. You will learn the steps needed to configure, install, start, test, and monitor a fully functional Hadoop cluster.
LiveLessons Video Training series publishes hundreds of hands-on, expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. This professional and personal technology video series features world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, IBM Press, Pearson IT Certification, Prentice Hall, Sams, and Que. Topics include: IT Certification, Programming, Web Development, Mobile Development, Home & Office Technologies, Business & Management, and more.

好东西，共同学习，共同建设Hadoop版块！

谢谢分享

好东西，谢谢分享