Learn how to use Hadoop from beginner level to advanced techniques which is taught by experienced working professionals. With our Hadoop Training in Chennai you’ll learn concepts in expert level with practical manner. GREENS TECHNOLOGYS provides best Hadoop Training in Chennai as class room with placements. We designed this Hadoop Training from beginner level to advanced level and project based training with helps everyone to be ready for industry practices. Anyone who completes our Hadoop Training in Chennai will become a master in Hadoop with hands-on workouts and projects. Our Hadoop trainers are well experienced and certified working professionals with more experience in real time projects.
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Awarded as the Best Hadoop Training Center in Chennai - We Guarantee Your Hadoop Training Success in Chennai
Bigdata and Hadoop Training in Chennai for developers, data analysts and administrators delivered by certified and highly experienced trainers with extensive real-world end-to-end experience. We are the best BigData and Hadoop Developer Training institute in Chennai.
Learn Hadoop, MapReduce and BigData from Scratch. A Complete Hands on training to Learn and Master the Popular Big Data Technologies with many Real World Business Use Cases.
Greens Technology Apache Hadoop training in Chennai is the expert source for Apache Hadoop training and certification. We offer public and private Hadoop courses for developers and administrators with certification for IT professionals involved in Apache Hadoop projects using Hadoop, Pig, Hive, Sqoop, HBase, Mahout, HCatalog, Flume, Cassandra, MongoDB, Redis, Solr, Lucene, Oozie, many other NoSQL Databases, and Open Source Projects.
Get SQL, Java and Linux Course free with our Hadoop Training in Chennai !
About Instructor: - Srikanth is a Professional Instructor & Software Architect with an exceptional history and experience of approx 11 years in leading IT projects involving complex functional as well as non-functional requirements.
Srikanth has got Hadoop Instructor accreditations from Cloudera. Srikanth worked in various domains including Big Data, eCommerce, Insurance and Location Intelligence.
Srikanth has strong background in Designing, Architecture of Enterprise applications, Java, Spring, HDFS, Map Reduce, Pig, Hive, Impala, Hadoop Administration, Google Search Appliance, Demandware eCommerce Platform, Google Analytics, Maven, Enterprise Architect, Social Integration via OAuth etc. Srikanth is actively involved in imparting trainings on various technologies including Google Search Appliance, HDFS, HBase, NoSQL, MapReduce, Hive, Pig, Impala, Java, Software Craftsmanship etc.
Srikanth has a strong expertise working on IaaS, PaaS and SaaS based environments. He has been consulting several CMM 5 organizations on best practice implementation, coding standard implementation, improve programming efficiency and code coverage, and implement automation testing and continuous integration processes.
Some of the automation tool, Srikanth has been working & consulting on includes: Cruise Control, Jenkins, Hudson. Among the collaboration software, Srikanth has an extensive experience with JIRA, both development and administration.
Srikanth has got excellent exposure in developing external web applications having highly demanding non-functional requirements like Security, Performance, Usability etc.
Srikanth has positive attitude, Solution oriented approach, Constant and Fast Learner
Srikanth is a graduate of Landmark education which imparts Transformative learning
Talk to the Trainer @ +91-89399 15577
What is Hadoop?
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Hadoop is the data platform chosen by many because it provides high performance – especially if you replace MapReduce in the Hadoop stack with the Apache Spark data processing engine.
Hadoop has evolved into a user-friendly data management system. Different implementations have done their part to optimize Hadoop’s manageability through different administrative tools.
Look for a distribution that has intuitive administrative tools that assist in management, troubleshooting, job placement and monitoring.
Certified Apache Big data & Hadoop Developer training in Chennai
This course is designed for clearing Cloudera Certified Developer for Apache Hadoop (CCDH). At the end of the course there will be a quiz and project assignments once you complete them you will be awarded with Greens Technology Course Completion certificate.
This course is designed for clearing Cloudera Certified Administrator for Apache Hadoop (CCAH). At the end of the course there will be a quiz and project assignments once you complete them you will be awarded with Greens Technology Course Completion certificate.
About Hadoop Training Course in Chennai
This Combo course comprises of Hadoop Developer, Analyst, Administration & Testing.
This Combo course comes with a great discount!! Hurry up and avail the offer!!
Here are the topics covered in this course:-
Introduction to Hadoop and its Ecosystem, Map Reduce and HDFS, Deep Dive in Map Reduce and Yarn, Deep Dive in Pig, Deep Dive in Hive, Introduction to Hbase architecture, Hadoop Cluster Setup and Running Map Reduce Jobs, Major Project – Putting it all together and Connecting Dots, Advance Mapreduce, Impala, ETL Connectivity with Hadoop Ecosystem, Hadoop Cluster Configuration, Hadoop Administration and Maintenance, Hadoop Monitoring and Troubleshooting, Hadoop Multi Node Cluster Setup and Running Map Reduce Jobs on Amazon Ec2, High Availability Federation, Yarn and Security, Advance Oozie, Advance flume, Advance hue, Advance Impala, Advance zookeeper.
Hands on Exercise:
End to end POC using Yarn or Hadoop 2.0
Learning Objectives:
Programming in YARN (MRv2) latest version of Hadoop Release 2.0
Implementation of HBase, MapReduce Integration, Advanced Usage and Advanced Indexing.
Learn to work with Hadoop Distributed File System (HDFS)
Implement Multi node cluster using 3-4 instances of Amazon ec2.
Ability to design and develop applications involving large data using Hadoop eco system.
Differentiate between new as well as old APIs for Hadoop
Understand how YARN engages in managing compute resources into clusters
Setting up Hadoop infrastructure with single and multi node cluster on Amazon ec2 (CDH4).
Know best practices of using Hadoop in enterprise world
ETL tool connectivity with Hadoop, real time case studies etc.
Detailed hands on with Impala for real time queries on Hadoop.
Writing Hive and Pig Scripts and working with Sqoop.
Implementation of HBase, MapReduce Integration, Advanced Usage and Advanced Indexing.
Work on a Real Life Project on Big Data Analytics and gain Hands on Project Experience.
Implement linked-in algorithms – Identification of Shortest path for 1st level or 2nd level connection using Map Reduce.
Play with Datasets – Twitter data set for sentiment analysis, whether dataset, Loan Data set.
Guidance and Quiz to prepare for Professional Certification exams like – Cloudera, etc.
Ability to design and develop applications involving large data using Hadoop eco system.
Optimize Hadoop cluster for the best performance based on specific job requirements
Monitor a Hadoop cluster and execute routine administration procedures
Deal with Hadoop component failures and recoveries
Get familiar with related Hadoop projects: Hbase, Hive and Pig
Last but not the least, the Hadoop online tutorial program prepares programmers for better career opportunities in the world of Big Data.
Pre-Requisites:
Some prior experience any Programming Language would be good. Basic commands knowledge of UNIX, sql scripting. Prior knowledge of Apache Hadoop is not required.
Recommended Audience:
Professionals aspiring to make a career in Big Data Analytics using Hadoop Framework
Java Developers / Architects, BI /ETL/DW Professionals or SAS Professionals/Architects
Why Go for Hadoop Training in Chennai Greens Technology's?
Hadoop is a combination of online running applications on a very huge scale built of commodity hardware. Hadoop is uncluttered source software which is handled by the Apache Software Foundation and it’s very helpful in storing and handling huge amounts of data inexpensively and professionally. Basically Hadoop collects huge packets of data and classifies this data using MapReduce.
If you are looking for Hadoop Jobs and you are a Hadoop professional then there are a lot of jobs about Hadoop and related technologies. There are many companies like Google, Yahoo, Apple, Hortonworks, eBay, Facebook, ORACLE, IBM, Microsoft, and CISCO which are looking for skilled professionals having experience in this field and are capable of managing the Big Data in their companies. If you are a professional of Hadoop then you could be one of them. These companies such as Google, Facebook, and ORACLE etc are looking for the Hadoop Professionals at different levels such as database Administrators, Hadoop Professionals having complete operational skills, Hadoop engineers & also senior Hadoop engineers, big data Engineers, Hadoop developers and also Java Engineers (DSE Team).
Research of IDC shows that the Big Data market revenue’s will grow at 31.7 percent a year and it will hit the $23.8 billion mark in 2016. According to the latest research by market the Hadoop and Big Data world widely is expected to growth about 13.9$ billion by 2017.
Companies Using Hadoop:
Amazon Web Services, IBM, Hortonworks, Cloudera, Intel, Microsoft, Pivotal, Twitter, Salesforce, AT&T Stumbleupon, Ebay, Yahoo, Facebook, Hulu etc.
Career Opportunities after Hadoop course:
Google trends tell exponential growth of Jobs in Hadoop. Check Top Job websites for Hadoop Jobs:
Best Hadoop Training Course in Chennai
In this Hadoop Training course in Chennai, you will Learn how to use Hadoop from beginner level to advanced techniques which is taught by experienced working professionals. With our Hadoop Training in Chennai you’ll learn concepts in expert level with practical manner.
Big Data &Hadoop Certification Course from Hadoop Training Chennai will help you to:
Get certified on “Big Data and Hadoop”
Master the concepts of Hadoop framework and its deployment in a cluster environment
Process around 3.5 Billion Data points spanning across 8 Data sets with a high level of efficiency
Understand Hadoop Architecture by understanding Hadoop Distribution File System operations principles (vHDFS 1.0 & vHDFS 2.0)
Understand advance concepts of parallel processing in MapReduce1.0 (or MRv1) & MapReduce2.0 (or MRv2)
Learn to write complex Map Reduce programs in both MRv1 & MRv2 (Yarn)
Learn high-level scripting frameworks Pig & Hive and perform data analytics using high level scripting language under Pig & Hive
Have a good understanding of Ecosystem and its advance components like Flume, Apache Oozie workflow scheduler etc.
Understand advance concepts Hadoop 2.0 : Hbase, Zookeeper and Sqoop
Get hands-on experience in different configurations of Hadoop cluster, its optimization & troubleshooting
Get a chance to work on 2 Real time Industry based Projects
Hadoop Training Course Details
Learn how to use Hadoop from beginner level to advanced techniques which is taught by experienced working professionals. With our Hadoop Training in Chennai you’ll learn concepts in expert level with practical manner. Become a Hadoop Expert by mastering MapReduce, Yarn, Pig, Hive, HBase, Oozie, Flume and Sqoop while working on industry based Use-cases and Projects.
INTRODUCTION TO BIG DATA - HADOOP
BigData(What,Why,Who) - 3++Vs-Overviews of Hadoop EcoSystem - Role of Hadoop in Big data - overviews of other Big Data System -
Who is using Hadoop - Hadoop integrations into Exiting Software Products - Current Scenario in Hadoop Ecosystem - Installation - Configuration - UseCases of Hadoop(HealthCare,Retail,teecom)
HDFS
Concepts - Architecture - Data Flow(File Read,File Write) - Fault Tolerance - Shell Commands - Java Base API - Data Flow
Archives - coherency - Data Integrity - Role of Secondary NameNode
MAPREDUCE
Theory - Data Flow (Map-shuffle-Reduce) - MapRed vs MapReduce APIs - Programming[Mapper,Reducer, Combiner, Partitioner] - Writable- InputFormat - Outputformat- Streaming API using python - Inherent Failure Handing using Speculative Execution - Magic of Shuffle phase - FileFormats - Sequence Files
ADVANCE MAPREDUCE PROGRAMMING
Counter(Built IN and Custom) - Custom Input Format - Distributed Cache - Joins(MapSide,FReduceSide) - Sorting - Perfomance Tuning-GenericOptionsParser - ToolRunner - Debugging(LocalJobRunner)
ADMINISTRATION
Multi Node Cluster Setup using AWS Cloud Machines - Hardware Considerations - Software Considerations - Commands(fsck,job,dfsadmin)-Schedulers in job Tracker - RackAwareness Policy - Balancing - NameNode Failure and Recovery - commissioning and Decommissioning a Node - Compression Codecs
HBASE
Introduction to NoSQL - CAP Theorem - Classification of NoSQL - Hbase and RDBMS - HBASE and HDFS - Architecture(Read Path,Write Path,Compactions,Splits) - Installation - Configuration - Role of Zookeeper - HBase Shell - Java Based APIs(Scan,Get,Other advanced APIs) - Introduction to Filter - RowKey Design - Map reduce Integration-performance Tuning - What's New in HBase0.98 - Backup and Disaster Recovery - Hands On
Architecture- Installation - Hive vs Pig-Pig Latin syntax - Data Types - Functions(Eval,Load/Store,String,DateTime) - joins - PigServer - Macros - UDFs -performance - Troubleshooting - Commonly Used Functions
SQOOP
Architecture - Installation,commands(Import,Hive-Import,Eval,Hbase Import,Import All tables,Export)-Connectors
to Existing DBs and DW
FLUME
Why Flume?-Architecture,Configuration(Agents), Source(Exec-Avro-NetCat), Channels(File,Memory,JDBC,HBase), Sinks(Logger, Avro, HDFS, Hbase, FileRoll), Contextual Routing(Interceptors, Channel Selectors)-Introduction to other aggregation frameworks
OOZIE
Architecture, Installation, Workflow,Coordinator, Action(Mapreduce,Hive,Pig,Sqoop)-Introduction to Bundle - Mail Notifications
HADOOP 2.0
Limitations in Hadoop-1.0-HDFS Federation-High Availability in HDFS-HDFS Snapshots-Other Improvements in HDFS2-Introduction to YARN aka MR2-Limitations in MR1-Architecture of YARN-MapReduce Job Flow in YARN-Introduction to Stinger Initiative and Tez-BackWard Compatibility for Hadoop 1.X
SOLR
Introduction to Information Retrieval - common usecases- Introduction to Solr and Lucene - Installation - Concepts(Cores,Schema,Documents,fields,
Inverted Index)- Configuration - CRUD Operation requests and responses - Java Based APIs - Introduction to SolrCloud
Developing Solutions Using Apache Hadoop
The Developing Solutions using Apache Hadoop training course is designed for developers who want to better understand how to create Apache Hadoop solutions. The course consists of 50% hands-on lab exercises and 50% presentation material.
After successfully completing this training course each student will receive one free voucher for the Hadoop Certified Developer exam.
Topics Covered
The process of taking a Hadoop project from conception to completion
Big Data Defined and How Hadoop makes Big Data more valuable
MapReduce training: Including how to write a MapReduce program using the Hadoop API
HDFS training: Including effective loading and processing of data with CLI and API
Pig, Hive and Hcatalog: how to accomplish Data movement and processing with higher level languages
Over 15 hands-on training exercises using HDFS, Pig, Hive, HBase, key MapReduce components and features (e.g. mapper, reducer, combiner, partitioner and streaming) and more
Intended Audience
Java is preferred, but experience in other programming languages such as PHP,C,C+ is sufficient
Course Duration
The Apache Hadoop Developer class is a four-day course spanning 26 total hours
There are approximately 13 hours each of hands-on labs and presentations
Sorting files using Hadoop Configuration API discussion
Emulating “grep” for searching inside a file in Hadoop
Chain Mapping API discussion
Job Dependency API discussion and Hands on
Input Format API discussion and hands on
Input Split API discussion and hands on
Custom Data type creation in Hadoop
Developing Apache Hadoop Applications in Java
This 30hrs hands-on training course takes a deep-dive into developing Java MapReduce applications for Big Data deployed on the Hadoop Distributed File System (HDFS). Students who attend this course will learn how to harness the power of Apache Hadoop™ and MapReduce to manipulate, analyze and perform computations on their Big Data.
Prerequisites
This course assumes students have experience developing Java applications and using a Java IDE. Labs are completed using the Eclipse IDE and Maven.
Target Audience
Experienced Java developers responsible for developing MapReduce applications and performing analysis of Big Data stored on Apache Hadoop.
Course Objectives
At the completion of the course, student will be enabled to perform the following:
Write a Java MapReduce application using Eclipse and Maven
Develop a Combiner to perform map aggregation
Customize input and output formats of a MapReduce job
Compute mathematical computations on your Big Data files
Use best practices to optimize MapReduce jobs
Create JUnit tests for a MapReduce job
Discover trends in your Big Data
Define an Oozie workflow
Access Apache HBase™ data from a Java MapReduce job
Write custom, user-defined functions for Apache Pig™ and Apache™ Hive
Lab Content
Students will work through the following exercises using Eclipse, Maven and the Hortonworks Data Platform:
Configuring a Hadoop ™ Development Environment
Word Count
Distributed Grep
Inverted Index
Using a Combiner
Computing an Average
Writing a Custom Partitioner
Using a TotalOrderPartitioner
Custom Sorting
Writing a Custom InputFormat
Customizing Output
Simple Moving Average
Using Data Compression
Defining a RawComparator
A Map-Side Join
Using a Bloom Filter
Unit Testing
Defining an Oozie Workflow
Term Frequency–Inverse Document Frequency (TF-IDF)
Accessing HBase from Java MapReduce
Writing a User-Defined Pig Function
Writing a User-Defined Hive Function
Administering Apache Hadoop
This three-day Apache Hadoop training course is designed for administrators who deploy and manage Apache Hadoop clusters. This course will walk you through installation, provisioning and ongoing resource management within a Hadoop cluster. You will leave with a valuable set of best practices that have been developed over years of working with Hadoop in production so that you can optimize your Hadoop clusters.
We’ll work through the full lifecycle of an Apache Hadoop deployment using realistic hands-on lab experiments. You’ll learn from our experience over the past six years of working with some of the largest Hadoop clusters in the world.
The Hadoop Administration course spans three days and provides a solid foundation for management of your Hadoop clusters. A full outline is below.
Objectives
In this course you will learn the best practices for Apache Hadoop administration as experienced by the developers and architects of core Apache Hadoop.
How to size and deploy a cluster
How to deploy a cluster for the first time
How to perform ongoing maintenance to nodes in the cluster
How to balance and performance tune a cluster
How to integrate status and health checks into your existing monitoring tools (single plane of glass)
How to recover form a NameNode or DataNode failure
How to implement a high available solution
Best practices for deploying Hadoop clusters
Audience
This course is designed for IT administrators and operators with at least basic knowledge of Linux. Existing knowledge of Hadoop is not required.
Course Outline
Day 1: Deployment: Sizing, deployment and provisioning
Introduction to Hadoop
Best Practices for Hadoop Cluster Hardware and Software
Basic Hadoop Operations
Installing Hadoop using HMC and Ambari
Benchmarking Hadoop
Creating a multi-user environment in Hadoop
Understanding logs and directory structures in Hadoop
Day 2: Management: Management, monitoring and high availability
Understanding configuration files
Monitoring the cluster with Nagios and Ganglia
Understanding dfsadmin and mradmin
Understanding Schedulers in Apache Hadoop
Data Integrity with Apache Hadoop
Using Rack Topology
Day 3: Maintenance
Commissioning and Decommissioning nodes
NameNode Back up and Recovery
Hadoop Security
Copying Cluster Data
Hadoop Archive
Upgrading Hadoop
Hadoop Ecosystem
Oozie Administration
Hcatalog and Hive Administration
About Hadoop Testing Training Course in Chennai
This Hadoop Testing Training in Chennai is to make you enable to learn and understand to test and rectify errors from Hadoop projects performance. This Hadoop Testing Training Course in Chennai will enable you to learn about Hadoop Software, Hadoop Architecture, HDFS, Mapreduce Jobs, Hive, PIG, POC and lab exercise.
Learning Objectives:
Setting up Hadoop infrastructure with single and multi node cluster on Amazon ec2 (CDH4).
Writing Hive and Pig Scripts and working with Sqoop.
Work on a Real Life Project on Big Data Testing and gain Hands on Project Experience.
Guidance and Quiz to prepare for Professional Certification exams like – Cloudera, etc.
Ability to design and test Hadoop applications involving large data using MRUnit testing Framework.
Recommended Audience:
This course is recommended for:
QA Professionals aspiring to make a career in Big Data Analytics using Hadoop Framework.
System Administrators and Support Engineers who will test Hadoop works
Pre-Requisites:
Basic knowledge of QA
Basic knowledge of Unix, sql scripting
Prior knowledge of Apache Hadoop is not required
Why Go for Hadoop Testing Training?
Hadoop is a combination of online running applications on a very huge scale built of commodity hardware. Hadoop is uncluttered source software which is handled by the Apache Software Foundation and it’s very helpful in storing and handling huge amounts of data inexpensively and professionally. Basically Hadoop collects huge packets of data and classifies this data using MapReduce.
If you are looking for Hadoop Jobs and you are a Hadoop professional then there are a lot of jobs about Hadoop and related technologies. There are many companies like Google, Yahoo, Apple, Hortonworks, eBay, Facebook, ORACLE, IBM, Microsoft, and CISCO which are looking for skilled professionals having experience in this field and are capable of managing the Big Data in their companies. If you are a professional of Hadoop then you could be one of them. These companies such as Google, Facebook, and ORACLE etc are looking for the Hadoop Professionals at different levels such as database Administrators, Hadoop Professionals having complete operational skills, Hadoop engineers & also senior Hadoop engineers, big data Engineers, Hadoop developers and also Java Engineers (DSE Team).
Research of IDC shows that the Big Data market revenue’s will grow at 31.7 percent a year and it will hit the $23.8 billion mark in 2016. According to the latest research by market the Hadoop and Big Data world widely is expected to growth about 13.9$ billion by 2017.
Hadoop QA Professional: Hadoop QA professional is a person who tests and rectifies glitches in Hadoop and its Data base system.
Companies Using Hadoop:
Amazon Web Services, IBM, Hortonworks, Cloudera, Intel, Microsoft, Pivotal, Twitter, Salesforce, AT&T Stumbleupon, Ebay, Yahoo, Facebook, Hulu etc.
About Hadoop Analyst Training in Chennai
Hadoop Data Analyst Training: Using Pig, Hive, and Impala with Hadoop. This Hadoop Analyst Hands-On Training course in Chennai from Greens Technology, focusing on Apache Pig, Apache Hive, and Cloudera Impala, will teach you to access, manipulate, and analyze massive data sets in your Hadoop cluster. Using SQL and a simple scripting language you will learn how to perform ETL tasks and gain valuable insight from your data.
Introduction
Hadoop Fundamentals
Introduction to Pig
Basic Data Analysis with Pig
Processing Complex Data with Pig
Multi-Dataset Operations with Pig
Pig Troubleshooting and Optimization
Introduction to Impala and Hive
Querying with Impala and Hive
Data Management
Data Storage and Performance
Relational Data Analysis With Impala and Hive
Working with Impala
Analyzing Text and Complex Data with Hive
Hive Optimization
Extending Hive
Choosing the Best Tool for the Job
Conclusion
Developing Solutions for Apache Hadoop on Windows
Students will learn to develop applications and analyze big data stored in Apache Hadoop running on Microsoft Windows. Students will learn the details of the Hadoop Distributed File System (HDFS ™) architecture and MapReduce framework, as well as learn how to develop applications on Hadoop® using tools like C#, Pig , Hive, HCatalog, Sqoop, Oozie and Microsoft Excel.
Duration
4 days
Prerequisites
Students should have programming experience, preferably with Visual Studio and SQL, as well as familiarity with the Windows Server operating system. No prior Hadoop knowledge is required.
Target Audience
.NET Developers and Data Analysts responsible for developing applications and performing analysis on big data using the Hortonworks Data Platform for Windows.
Course Objectives
At the completion of the course students will be able to:
Explain the various tools and frameworks in the Hadoop ecosystem
Recognize use cases for HDP for Windows and Big Data
Explain the architecture of the Hadoop Distributed File System (HDFS)
Transfer data between HDFS and Microsoft SQL Server using Sqoop
Explain the architecture of MapReduce
Run a MapReduce job on Hadoop
Use Hadoop streaming
Use the Microsoft .NET API for Hadoop to write a C# MapReduce job
Recognize use cases for Pig
Write a Pig script to explore and transform data in HDFS
Define advanced Pig relations
Use Pig to apply structure to unstructured Big Data
Join large datasets using Pig
Invoke a Pig User-Defined Function
Write a Hive query using Hive QL
Understand how Hive tables are defined and implemented
Use Hive to run SQL-like queries to perform data analysis
Explain the uses and purpose of HCatalog
Use an HCatalog schema within a Pig script
Explain the purpose of the Hive ODBC driver
Connect Microsoft Excel to HDFS using Hive ODBC
Import Hive query results into Excel
Explain the usages of Oozie
Write and execute an Oozie workflow
Lab Content
Students will work through the following lab exercises using the Hortonworks Data Platform for Windows:
Access HDFS using the HDFS commands
Import SQL Server data into HDFS using Sqoop
Export HDFS data from HDFS into SQL Server using Sqoop
Run a MapReduce Job
Monitor a MapReduce Job
Develop a .NET MapReduce application in C#
Explore data using Pig
Split and join datasets using Pig
Transform unstructured for use with Hive
Analyze Big Data with Hive
Understanding MapReduce with Hive
Joining datasets with Hive
Use HCatalog with Pig
Use Hive ODBC with Microsoft Excel
Define an Oozie Workflow
What is Apache Hadoop?
Hadoop is an open source project from Apache that has evolved rapidly into a major technology movement. It has emerged as the best way to handle massive amounts of data, including not only structured data but also complex, unstructured data as well. Its popularity is due in part to its ability to store, analyze and access large amounts of data, quickly and cost effectively across clusters of commodity hardware.
Apache Hadoop is not actually a single product but instead a collection of several components including the following:
MapReduce – A framework for writing applications that processes large amounts of structured and unstructured data in parallel across large clusters of machines in a very reliable and fault-tolerant manner.
Hadoop Distributed File System (HDFS) – A reliable and distributed Java-based file system that allows large volumes of data to be stored and rapidly accessed across large clusters of commodity servers.
Hive – Built on the MapReduce framework, Hive is a data warehouse that enables easy data summarization and ad-hoc queries via an SQL-like interface for large datasets stored in HDFS.
Pig – A platform for processing and analyzing large data sets. Pig consists on a high-level language (Pig Latin) for expressing data analysis programs paired with the MapReduce framework for processing these programs.
HBase – A column-oriented NoSQL data storage system that provides random real-time read/write access to big data for user applications.
ZooKeeper – A highly available system for coordinating distributed processes. Distributed applications use ZooKeeper to store and mediate updates to important configuration information.
Ambari – An open source installation lifecycle management, administration and monitoring system for Apache Hadoop clusters.
HCatalog – A table and metadata management service that provides a centralized way for data processing systems to understand the structure and location of the data stored within Apache Hadoop.
Apache Hadoop is generally not a direct replacement for enterprise data warehouses, data marts and other data stores that are commonly used to manage structured or transactional data. Instead, it is used to augment enterprise data architectures by providing an efficient and cost-effective means for storing, processing, managing and analyzing the ever-increasing volumes of semi-structured or un-structured data being produced daily.
Apache Hadoop can be useful across a range of use cases spanning virtually every vertical industry. It is becoming popular anywhere that you need to store, process, and analyze large volumes of data. Examples include digital marketing automation, fraud detection and prevention, social network and relationship analysis, predictive modeling for new drugs, retail in-store behavior analysis, and mobile device location-based marketing.
Apache Hadoop is widely deployed at including many of the world’s leading Internet and social networking businesses. At Yahoo!, Apache Hadoop is literally behind every click, processing and analyzing petabytes of data to better detect spam, predicting user interests, target ads and determine ad effectiveness. Many of the key architects and Apache Hadoop committers from Yahoo! founded Hortonworks to further accelerate development and adoption and assist organizations achieve similar business value.
Cloudera Certification Assistance will be Provided!!
As a recent Hadoop graduate, I feel more prepared to begin creating Hadoop applications. I would strongly recommend the Greens Technology training programs to anyone looking to optimize Apache Hadoop deployments for technical and business success.
" I was very impressed with the depth and completeness of Hadoop training in Chennai. First of all thanks to all Greens Technologies team for providing such a unique and comprehensive platform for learning HADOOP in a simple and interesting manner. the coursework is prepared in simple, easy to understand but effective and having a proper rhythm †i.e step by step learning its a nice course of Greens Technologies and I liked a lot being a part of this course Greens Technologies really helped me understand Hadoop's capabilities so that I can make better technology choices relative to our Big Data opportunity going forward. "
My greetings to Hadoop God Srikanth of Greens temple.As a hadoop Pilgrim i have gained power of hadoop.I know what iam before entering to this holy place and now i know i have acquired magic power of hadoop.With your blessings iam going to enter in to programming world.I wish there was some way of showing my gratitude for all what you have done for me....Loving You...... UrsForever
Greens Technologys Overall Reviews
Greens Technologys Overall Reviews4.9
out of 5
based on 17 ratings.
17 user reviews.
"""I think this is the best hadoop training course in chennai I have taken so far..Well I am still in the process of learning new things but for me this learning process has become so easy only after I joined this course in greens technologies..as Srikanth is very organized and up to the point.. he knows what he is teaching and makes his point very clear by explaining numerous times. I would definitely recommend anyone who has any passion for hadoop.." ""
As a recent Hadoop graduate, I feel more prepared to begin creating Hadoop applications. I would strongly recommend the Greens Technology training programs to anyone looking to optimize Apache Hadoop deployments for technical and business success. 
" I was very impressed with the depth and completeness of Hadoop training in Chennai. First of all thanks to all Greens Technologies team for providing such a unique and comprehensive platform for learning HADOOP in a simple and interesting manner. the coursework is prepared in simple, easy to understand but effective and having a proper rhythm †i.e step by step learning its a nice course of Greens Technologies and I liked a lot being a part of this course Greens Technologies really helped me understand Hadoop's capabilities so that I can make better technology choices relative to our Big Data opportunity going forward. "
My greetings to Hadoop God Srikanth of Greens temple.As a hadoop Pilgrim i have gained power of hadoop.I know what iam before entering to this holy place and now i know i have acquired magic power of hadoop.With your blessings iam going to enter in to programming world.I wish there was some way of showing my gratitude for all what you have done for me....Loving You...... UrsForever
"""I think this is the best hadoop training course in chennai I have taken so far..Well I am still in the process of learning new things but for me this learning process has become so easy only after I joined this course in greens technologies..as Srikanth is very organized and up to the point.. he knows what he is teaching and makes his point very clear by explaining numerous times. I would definitely recommend anyone who has any passion for hadoop.." ""