Big data hadoop admin

Big data describes a holistic information management strategy that includes and integrates
many new types of data and data management alongside traditional data.

TO BE THE BEST LEARN FROM THE BEST

Courses Overview

Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Hadoop Cluster- Single and Multi node, Hadoop 2.x, Flume, Sqoop, Map-Reduce, PIG, Hive, Hbase, Zookeeper, Oozie etc. will be covered in the course. This course is designed for professionals aspiring to make a career in Big Data Analytics using Hadoop Framework. Software Professionals, Analytics Professionals, ETL developers, Project Managers, Testing Professionals are the key beneficiaries of this course. Other professionals who are looking forward to acquire a solid foundation of Hadoop Architecture can also opt for this course.

BIG DATA THE ACTUAL REASON FOR HADOOP

Understanding Big data
Collecting and cleaning data
Traditional approach for processing and its challenges
Big data vs Hadoop

AN INTRODUCTION TO HADOOP

Hadoop overview
Hadoop components
Hadoop distributions
Getting started
What is HDFS
What is Map Reduce
Hadoop stack
Hands On Hadoop setup and basic operations

HDFS

HDFS explained
High availability
Federation
Architecture
File system Shell
Hands On
Hands On

MAP REDUCE

Map Reduce flow
Hello World
Map Reduce API concepts
Mapper
Reducer
Other components combiner, partitioner, shuffle/sort
Hadoop 1.x vs 2.x
Hadoop streaming API
Hands on with Eclipse

YARN

Architecture
Scheduler
Resource Manager (RM)
RM HA
YARN commands
Hands On with YARN applications

INTEGRATING HADOOP INTO THE WORKFLOW

RDBMS interaction using Sqoop
Workflow management using Oozie
Back office jobs with Zookeeper
Hands On with actual data sets

DATA MINING

Unstructured data using PIG
Structured data mining using hive
Hands On with actual data sets

HBASE

Problem with SQL Database
Introduction to NOSQL
Hands On Exercises
Introduction to HBASE
Column Families
Delving deeper into HBASE
HBASE Architecture
HBASE Hands-On Exercises

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

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

JOINING DATA SETS IN MAPREDUCE

Map-Side Joins
The Secondary Sort
Reduce-Side Joins
Hands-On Exercise

Project Training

Internship Training Live Project Training Corporate Training Industrial Training Summer Training Digital marketing Big Data

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