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We do provide online training on Hadoop Developer by Industry experts.
Email: Nitesh@unitedglobalsoft.com
Contact: +91-8099902123
Course Description
Hadoop Big Data Training course helps you learn the core techniques and concepts of Big Data and
Hadoop ecosystem. It equips you with in-depth knowledge of writing codes using MapReduce
framework and managing large data sets with HBase. The topics covered in this course mainly includes-
Hive, Pig and setup of Hadoop Cluster.
Course Outcomes
Understand Big Data and Hadoop ecosystem
Work with Hadoop Distributed File System (HDFS)
Write MapReduce programs and implementing HBase
Write Hive and Pig scripts
Pre-requisites
You should have knowledge of programming in C++ or Java or any other Object Oriented
Programming language
1. Introduction
A. Distributed computing
B. Cloud Computing
C. Data Past, Present and Future
D. Computing Past, Present and Future
E. Hadoop
F. NoSQL
2. Understanding Hadoop Stack
A. MapReduce
B. NoSQL
C. CAP Theorem
D. Databases: Key Value, Document,
E. Graph
F. HBase and Cassandra
G. Hive and Pig
H. HDFS
3. Understanding Data
A. Data collection and generation
B. Data Storage
C. Data Retrieval
D. Random Access vs. Sequential Access
E. Disk is the new Tape – The Return of
F. sequential access to data
4. Hands on Hadoop
A. Hadoop Setup Single Node
B. Cluster Nodes
C. HDFS File System
D. HBase Setup
E. HBase Shell
5. Hands on to Data
A. Working on Twitter Data
B. Importing data into HBase
C. Querying using HBase CLI
D. Understanding data organization
E. Hbase Internals
F. Exercise: Solving various query using
G. scan and get
6. Introduction to HBase
A. Unlearning SQL
B. Learning NoSQL
C. Creating Table
D. Understanding Column Families
E. Unlearning Entity Relation
F. Learning Column Value & Key Pair
G. Unlearning Index & Query
H. Learning Scan and Scan Only
7. Introduction to Hive
8. Introduction to Pig
9. Looking Data as large sparse matrix
10. Applying BI on large data
11. Exercise: Working with Twitter data
12. Exercise: Working with Facebook data
13. Exercise: Working with LinkedIn data

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Hadoop Online Training - call +91-8099902123

  • 1. We do provide online training on Hadoop Developer by Industry experts. Email: Nitesh@unitedglobalsoft.com Contact: +91-8099902123 Course Description Hadoop Big Data Training course helps you learn the core techniques and concepts of Big Data and Hadoop ecosystem. It equips you with in-depth knowledge of writing codes using MapReduce framework and managing large data sets with HBase. The topics covered in this course mainly includes- Hive, Pig and setup of Hadoop Cluster. Course Outcomes Understand Big Data and Hadoop ecosystem Work with Hadoop Distributed File System (HDFS) Write MapReduce programs and implementing HBase Write Hive and Pig scripts Pre-requisites You should have knowledge of programming in C++ or Java or any other Object Oriented Programming language 1. Introduction A. Distributed computing B. Cloud Computing C. Data Past, Present and Future D. Computing Past, Present and Future E. Hadoop F. NoSQL 2. Understanding Hadoop Stack A. MapReduce B. NoSQL C. CAP Theorem D. Databases: Key Value, Document, E. Graph F. HBase and Cassandra G. Hive and Pig
  • 2. H. HDFS 3. Understanding Data A. Data collection and generation B. Data Storage C. Data Retrieval D. Random Access vs. Sequential Access E. Disk is the new Tape – The Return of F. sequential access to data 4. Hands on Hadoop A. Hadoop Setup Single Node B. Cluster Nodes C. HDFS File System D. HBase Setup E. HBase Shell 5. Hands on to Data A. Working on Twitter Data B. Importing data into HBase C. Querying using HBase CLI D. Understanding data organization E. Hbase Internals F. Exercise: Solving various query using G. scan and get 6. Introduction to HBase A. Unlearning SQL B. Learning NoSQL C. Creating Table D. Understanding Column Families E. Unlearning Entity Relation F. Learning Column Value & Key Pair G. Unlearning Index & Query H. Learning Scan and Scan Only 7. Introduction to Hive 8. Introduction to Pig 9. Looking Data as large sparse matrix 10. Applying BI on large data
  • 3. 11. Exercise: Working with Twitter data 12. Exercise: Working with Facebook data 13. Exercise: Working with LinkedIn data