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Marathahalli Colony, Bangalore

Course ID: 16224

Marathahalli Colony, Bangalore

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About the Course

Hi All,

We are providing classroom training on Hadoop Bigdata in marathahalli, Bangalore.

If any one interested please contact us.

Topics Covered

BigData : Hadoop ?Complete Package
A) Big Data ? Motivation & Basics.
B) Hadoop Administration ? Architecture, Setups, Manipulation & Maintenances ??? (with Prerequisites -Linux).
C) Hadoop Development ? a) MapReduce (Basics) b)Real World MapReduce (Advance) ?..(with Prerequisites ?Java).
D) Corporate Technologies ? Hive, Pig, HBase, Oozie, Flume, Sqoop, Zookeeper, Mahout ??(with Prerequisites ?SQL).
E) Cloud Computing ? Concepts & Deploying hadoop on cloud (AWS- EC2, S3, EMR, & others as per requirement of Project).
F) Beyond Hadoop ? Strom, Sparks, Mesos?..etc & future scope of Hadoop with these coming technologies.

A) Big Data
? What is big data?
? Challenges in big data
? Challenges in traditional Applications
? New Requirement
? Introducing Hadoop
? Brief History of Hadoop
? Features of Hadoop
? Overview of Hadoop Ecosystem
? Overview of MapReduce

B) Hadoop Administration
1) Linux ? Basic architecture, important commands, file permission and ownership, administration, communication, pipe etc.

2) Setup Single (pseudo-node) Cluster
? Important Directories,
? Configuring HDFS & Important Configuration Properties.

3) Interacting with HDFS.
? Common Example Operations
? HDFS Command Reference
? DFSAdmin Command Reference
? Using HDFS For MapReduce
? HDFS Web Interface
? And how to Setup Multi-node Cluster.
? Hands?on Exercises and Assignment.

4) Additional HDFS Tasks
? Rebalancing Blocks
? Copying Large Sets of Files
? Decommissioning Nodes
? Verifying File System Health
? Rack Awareness
? Cluster Configuration
o Small Clusters: 2-10 Nodes
o Medium Clusters: 10-40 Nodes
o Large Clusters: Multiple Racks
? Performance Monitoring
o Ganglia
o Nagios
? Hands-on Exercises and Assignment.

C) Hadoop Development
1) MapReduce -1
? Java - basic Oops concepts, Serialization, I/O, Collection, Sorts ..etc.
? Configure eclipse environment for Mapreduce development & run first Program.
? Hands-on Exercises and Assignment.
2) MapReduce -2
? Explanation of first program in details describing Mapper, Reducer, Driver.
? MapReduce Algorithms and whole process flow ? map, partition, sort, shuffle, reduce.
? Related terms ? Input formats, Input Splits, Speculative Execution..etc
? Other related Algorithm ? Combiner, Partitioner.
? Hands-on Exercises and Assignment.
3) MapReduce -3
? Discussion and solution of various program and their use cases in real world.
? Local Runner and Usage of Tool runners.
? Setup/Cleanup method in mapper/reducer.
? Passing the parameters to mapper and reducer.
? Searching Algorithm.
? Distributed cache.
? Hands-on Exercises and Assignment.
4) Real World MapReduce -1 (Advance)
? Create custom keys and values.
? Create custom partitioner.
? Write custom input format.
? Hands-on Exercises and Assignment.
5) Real World MapReduce -2
? Implementing Custom comparator.
? Secondary sorting.
? Relational Manipulation ? map-side & reduce-side joins.
? Real-World Data mining.
? Hands-on exercises and Assignment.

D) Corporate Technologies
1) SQL, HBase & other Components.
? Introduction to Sqoop, Hive, Pig, Oozie, Flume, Mahout? their use cases and installation.
? Introduction to HBase, Architecture, Map Reduce Integration, Different Client API ?Feature and Administration.
? Hands-on exercises and Assignment.
2) Hive
? Understanding Hive, Architecture, Physical Model, DataTypes.
? Hive QL ?DDL, DML, Other Operations.
? Understanding Tables in Hive, Partitioning, Indexes, Bucketing, Joining Tables, Data Load?etc
? Hands-on Exercises and Assignment.
3) Pig
? Understanding Pig, Different Mode and Data Model
? Advance Pig Latin, Evaluation and Filter Functions..etc.
? Real time use cases.
? When to use pig and when to use hive.
? Hands-on Exercises and Assignment.
4) Cloud Computing
? Introduction, Options and how to use.
? AWS(Amazon Web Services)- Registration and AMI setup.
? Create multimode cluster using S3, EC2..and run MapReduce, pig and hive program.

F) Beyond Hadoop
? Current world scenario and near future expectations.
? Strom, Sparks, Mesos?..etc & future scope of Hadoop with these coming technologies.
? Job exploration.

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About the Trainer

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