You can attend 1st 2 sessions for free. once you like the classes then you can go for registration.
or full course details please visit our website www.hadooponlinetraining.net
Duration for course is 30 days or 45 hours and special care will be taken. It is a one to one training with hands on experience.
* Resume preparation and Interview assistance will be provided.
For any further details please contact
INDIA: +91-9052666559
USA: +1-6786933475
visit www.hadooponlinetraining.net
please mail us all queries to info@magnifictraining.com
1. HADOOP online training from real
time experts @ Magnific training
Contact : +91-9052666559
HADOOP
2. • CONTACT US:
• Call :
• india +91-9052666559
• USA:+1-6786933475
• Mail :info@magnifictraining.com
• Visit : www.hadooponlinetraining.net
3. • 1. Introduction
• Distributed computing
• Cloud Computing
• Data Past, Present and Future
• Computing Past, Present and Future
• Hadoop
• NoSQL
4. • 2. Understanding Hadoop Stack
• MapReduce
• NoSQL
• CAP Theorem
• Databases: Key Value, Document,
• Graph
• HBase and Cassandra
• Hive and Pig
• HDFS
5. • 3. Understanding Data
• Data collection and generation
• Data Storage
• Data Retrieval
• Random Access vs. Sequential Access
• Disk is the new Tape – The Return of
• sequential access to data
6. • 4. Hands on Hadoop
• Hadoop Setup Single Node
• Cluster Nodes
• HDFS File System
• HBase Setup
• HBase Shell
7. • 5. Hands on to Data
• Working on Twitter Data
• Importing data into HBase
• Querying using HBase CLI
• Understanding data organization
• Hbase Internals
• Exercise: Solving various query using
• scan and get
8. • 6. Introduction to HBase
• Unlearning SQL
• Learning NoSQL
• Creating Table
• Understanding Column Families
• Unlearning Entity Relation
• Learning Column Value & Key Pair
• Unlearning Index & Query
• Learning Scan and Scan Only
9. • 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