hadoop2.x Big Data Platform V3 Video Tutorial | HADOOP2 Video Tutorial

Course Outline:

1th Week Hadoop Ecosystem Overview and version evolution

Provides an overview of the Hadoop ecosystem and its version evolution history, and gives recommendations for Hadoop version selection.

2nd Week HDFS 2.0 principle, characteristics and basic architecture

Introduces the principle and architecture of HDFS 2.0 and compares it with HDFS 1.0. Introduces the new features of HDFs 2.0, including snapshots, caches, heterogeneous storage architectures, and more

3rd Week Yarn Application scenario, basic architecture and resource scheduling

This paper introduces what yarn is, its basic principle and architecture, and analyzes its scheduling strategy.

4th Week MapReduce 2.0 Fundamentals and Architecture

Introduces the basic principle and architecture of computational framework MapReduce

5th Week MapReduce 2.0 Programming practice (involving multilingual programming)

How to write a mapreduce program in Java, C + +, PHP and other languages

6th Week HBase Application scenario, principle and basic architecture

Introducing HBase scenarios, principles, and architectures

7th Week HBase Programming practice (involving multi-language programming)

Hands-on how to write HBase client programs in Java, C + +, Python, and other languages.

8th Week HBase Case analysis

This paper introduces several typical cases of hbase, including internet application case and bank application case.

9th Week Zookeeper deployment and typical applications

Describe what zookeeper is and what it is in the Hadoop ecosystem

10th Week Hadoop Data warehousing system Flume and Sqoop

Describes how to use flume and Sqoop to import data from external streaming data (such as site logs, user behavior data, etc.), relational databases (such as MySQL, Oracle, etc.) into Hadoop for analysis and mining

11th Week data Analysis System hive and pig application and comparison

Describes how to use hive and pig to analyze massive amounts of data in Hadoop

12th Week Data Mining Toolkit Mahout

Describes how to use data mining and machine learning algorithms provided by Mahout for massive data mining

13th Week Workflow Engine Oozie and Azkaban application

Describes how to use Oozie and Azkaban to manage and dispatch mapreduce jobs, pig/hive jobs, etc.

14th Week Two comprehensive cases: Log analysis system and machine learning platform

This paper introduces two typical internet application cases, and further insights into the application scenarios of each system in the Hadoop ecosystem and how to solve practical problems.

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hadoop2.x Big Data Platform V3 Video Tutorial | HADOOP2 Video Tutorial