Big Data Hadoop
- Big data is a collection of large datasets that cannot be processed using traditional computing techniques.
- It is not a single technique or a tool, rather it has become a complete subject, which involves various tools, technqiues and framework
Syllabus
- ARCHITECTURE:
- Introduction to Big Data / Hadoop
- Understanding of Eco-System Build
- Understanding Cluster Setup Activities
- HIVE Architecture
- PIG Architecture
- Introduction to NoSql
- Understanding Linux & Hadoop Basic Commands.
- HBASE Architecture
- Understanding of Cloudera Manager and HUE
- ADMINISTRATOR:
- Introduction to Big Data / Hadoop
- Understanding Cluster
- Best Practices for Cluster Setup
- How MapReduce Works
- Install Pseudcluster
- Install Multi node cluster
- Configuration
- Setup cluster on Cloud - EC2
- Tools
- Metadata & Data Backups
- File system check (fsck)
- Backing Up NN
- HADOOP DEVELOPER:
- Introduction to Big Data / Hadoop
- Understanding Cluster
- Developing MapReduce Application
- How MapReduce Works
- MapReduce Types
- MapReduce Formats
- MapReduce Features
- HIVE Basics
- HIVE UDF's
- PIG Basic's
- PIG UDF's
- Introduction to NoSql
- Introduction to HBASE
- Zookeeper
- Oozie
- Usecases
- Exam
- HADOOP DATA ANALYTICS:
- Java Refresher Session-MR Introduction
- Working With Hive-E-Commerce Use Case
- Working With Pig-Financial Uses Case
- Twitter Use Case-Sentimental Analysis
- MR Optimization
- Custom Combiner, Custom Partitioner And Distributed Cache
- NEW DEVELOPMENTS:
- Introduction to Yarn
- Overview of BI Tools.
- Overview of Platform
- Overview of Cloudera Manager
- HADOOP DATA INGESTION:
- Data Ingestion Using Scoop And Flume
- From Source To HDFS
- Deriving Insights From Log Files, Unstructured Data And DBMS
- Installation And Understanding Of Scoop And Flume
- Understanding Architecture And Installation of Hbase
- Meeting Zookeeeper, HRegionServer
- PROJECT USE CASES:
- Entertainment Use Case
- Twitter Use Case
- Health Care Use Case
- E-Commerce Use Case
- Bio-Informatics Use Case
- Course Objectives:
After completing the course successfully, participants should be able to:
- Explain the need for Big Data, and list its applications.
- Demonstrate the mastery of HDFS concepts and MapReduce framework
- Use Sqoop and Flume tload data intHadoop File System
- Run queries using Pig, and Hive
- Install and configure HBase
- Discuss and differentiate various commercial distributions of Big Data like Cloudera and Hortonworks
- Differentiate between Hadoop 1.0 and hadoop 2.0
For More Information
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