Hadoop Training

For Attending Big Data Training Session

Upcoming Batch
March/April 2016

Call us : 480-823-3203
email : training@windsorconsulting.net

Training Details

  • Duration

5 weekends

  • Location

At your convenience thru in-person/Online

  • Course

Big Data Hadoop Traininge
Job oriented course

  • Faculty

Expert from the Industry. Working in a leading institution

  • Cost

In Person - $899 and Webex - $375. $350 discount for the first 5 registration. There are referral discounts, please contact us for more information. Registration fee will be $50 and it is refundable before the first session if customer decline to continue.

Premium Training in hadoop

Are you convinced of the power and potential of Big Data and predictive analytics, but still doubtful on what it can do for you, it is the right time to learn about it.The course below will take you to full length in providing you the power of Big Data. Big Data can help you understand how others perceive your products so that you can adapt them, or your marketing. Analysis of unstructured social media text allows you to uncover the sentiments of your customers !!

Benefits of Hadoop/Data Scientist Program

  • Hadoop is storing and processing very large amount of enterprise data.
  • Apache Hadoop to build powerful applications to analyze Big Data
  • Companies are going towards digital and currently it is a revolution everywhere. There are tens and thousands of job is coming up.
  • Giants such as Google, Yahoo, Apple, eBay, Facebook, ORACLE, IBM, Microsoft, Linkedin and Amazon looking for Hadoop professionals.
  • Researchers predicts that Big Data revenue market will grow at 35% a year and it might hit $35 billion by end of 2016

Curriculum

Introduction: (Day #1)

  • Why Big Data and Evolution of Hadoop
  • What is Hadoop
    • HDFS
    • YARN
    • Map Reduce/Tez
  • HDFS Master-Slave Architecture
    • Namenode
    • Datanode
    • Secondary Namenode
  • Map reduce Master-Slave Architecture
    • Job Tracker
    • Task Tracker
    • YARN Components
  • Benefits of Hadoop
  • Hadoop Ecosystem and other Evolving technologies
  • Realtime Hadoop Cluster architecture
  • Hadoop Use Cases

HDFS: (Day #2)

  • Why Big Data and Evolution of Hadoop
  • What is Hadoop
  • Benefits of Hadoop
  • Hadoop Ecosystem and other Evolving technologies
  • Anatomy of File Read and File Write operations in HDFS
  • DistCp
  • Hadoop Archive filesystem(HAR)
  • Compression in HDFS
  • Serialization in Hadoop

Map Reduce: (Day 3)

  • Map Reduce Evolution and Architecture
  • Anatomy of Mapreduce
    • Mapper
    • Reducer
    • Partitioner
    • Combiner
  • Different modes of running Mapreduce program
  • Shuffle & Sort
  • Decomposing a problem into Mapreduce work flow

Resource Management in Hadoop (Day 4)

  • Classic Mapreduce vs YARN
  • Advantages of YARN
  • Multi Tenancy in YARN
  • How failures are handled in YARN
  • Different schedulers (Fair Scheduler vs Capacity Scheduler)
  • REST API in Capacity Scheduler

Pig: (Day 5 & Day 6)

  • Why Pig and Evolution of Pig
  • Pig Grunt
  • Pig Latin
  • UDFs in Pig
  • Processing Data in Pig
  • Hands On
  • Parallelism in Pig
  • Parameter Substitution in Pig
  • Advanced topics in Pig
  • Hands on Use case with Pig

Hive: (Day 7 & 8)

  • Why Hive and Evolution of Hive
  • Difference between RDBMS & Hive
  • HiveQL
  • Different types of Tables in Hive
  • Partitions and Buckets
  • Storage Formats in Hive
  • Playing with data in Hive
  • MetaData - Altering and Dropping tables in Hive
  • UDFs and UDAFs in Hive
  • Hive running on Tez
  • Hands on use case with Hive

Other Ecosystems in Hive: (Day 9 and Conclusion)

  • Hbase overview
  • Impala overview
  • Spark overview
  • Zookeeper overview
  • Flume Overview
  • Sqoop overview
  • Interview preparation

Map Reduce for Java Developers (Day 10)

  • InputFormat, OutputFormat
  • Counters
  • Advance Mapreduce
    • Joins - Mapside Joins
    • Reduce side Joins
    • Sorting
  • Hands on Map Reduce programming
    • Packaging the jar
    • Launching the job
    • Web UI
    • Debugging the Job
    • Hadoop logs
  • Tuning tips for Mapreduce
  • Project- Hands on

Curriculum

Work on a Real time Project on Big Data Analytics and gain Hands on Project Experience.