Thursday 4 October 2012

Hadoop Developer Course Content Details


Introduction
The Motivation for Hadoop
·         Problems with traditional large-scale systems
·         Requirements for a new approach
Hadoop: Basic Concepts
·         An Overview of Hadoop
·         The Hadoop Distributed File System
·         Hands-On Exercise
·         How MapReduce Works
·         Hands-On Exercise
·         Anatomy of a Hadoop Cluster
·         Other Hadoop Ecosystem Components
Writing a MapReduce Program
·         The MapReduce Flow
·         Examining a Sample MapReduce Program
·         Basic MapReduce API Concepts
·         The Driver Code
·         The Mapper
·         The Reducer
·         Hadoop’s Streaming API
·         Using Eclipse for Rapid Development
·         Hands-on exercise
·         The New MapReduce API
Delving Deeper Into The Hadoop API
·         More about ToolRunner
·         Testing with MRUnit
·         Reducing Intermediate Data With Combiners
·         The configure and close methods for Map/Reduce Setup and Teardown
·         Writing Partitioners for Better Load Balancing
·         Hands-On Exercise
·         Directly Accessing HDFS
·         Using the Distributed Cache
·         Hands-On Exercise
Common MapReduce Algorithms
·         Sorting and Searching
·         Indexing
·         Machine Learning With Mahout
·         Term Frequency – Inverse Document Frequency
·         Word Co-Occurrence
·         Hands-On Exercise
Usining HBase
·         What is HBase?
·         HBase Architecture
·         HBase API
·         Managing large data sets with HBase
·         Using HBase in Hadoop applications
·         Hands-on exercise
Using Hive and Pig
·         Hive Basics
·         Pig Basics
·         Hands-on exercise
Practical Development Tips and Techniques
·         Debugging MapReduce Code
·         Using LocalJobRunner Mode For Easier Debugging
·         Retrieving Job Information with Counters
·         Logging
·         Splittable File Formats
·         Determining the Optimal Number of Reducers
·         Map-Only MapReduce Jobs
·         Hands-On Exercise

More Advanced MapReduce Programming
·         Custom Writables and WritableComparables
·         Saving Binary Data using SequenceFiles and Avro Files
·         Creating InputFormats and OutputFormats
·         Hands-On Exercise
Joining Data Sets in MapReduce
·         Map-Side Joins
·         The Secondary Sort
·         Reduce-Side Joins 


7 comments:

  1. With Cloudera's funding of 900 M $ , Hadoop as a platform is going to be very popular in enterprises. There is certainly going to be a dearth of talent. We have been doing live classes on Hadoop and solving the talent crunch. More at http://www.venturesity.com/course/big-data-course-mapreduce-and-hadoop-training-online-hadoop-training

    ReplyDelete
  2. Good source of information on hadoop and Map R. We always rely on this blog other than our regular hadoop online training classes.

    ReplyDelete
  3. Thanks for your valuable post ofHadoop Online Training is very informaive and useful for who wants to learn about Hadoop

    Visit :http://www.trainingbees.com/

    ReplyDelete
  4. here your said about everything is well performance one. keep do update more infomation.
    hadoop training chennai

    ReplyDelete