Big Data Training in Chennai


Learn Big Data and Hadoop from the Best Big Data Training Institute in Chennai with the most experienced and Cloudera certified expert trainers in the field. Greens Technology provides Big Data training in Chennai to professionals and corporates on Hadoop 2.7, Yarn, MapReduce, HDFS, Pig, Impala, HBase, Flume, Apache Spark and prepares you for Cloudera’s CCA175 Big data certification.

Rated as No 1 Big Data and Hadoop training institute in Chennai for certification and Assured Placements. Our Job Oriented Big Data and Hadoop training in chennai courses are taught by experienced certified professionals with extensive real-world experience. All our Best Big Data and Hadoop training in Chennai focuses on practical than theory model.


About The Trainer

- Karthik is an experienced statistician and data miner with more than 10+ years of experience using R, Python and SAS and a passion for building analytical solutions. He is a M.S. in Quantitative Economics and Applied Mathematics graduate who has analytics experience working with companies like Capital One, Walmart, ICICI Lombard etc.

Karthik is a lead Data Scientist at Citi Bank. As a Certified Predictive Modeler, Statistical Business Analyst, and Certified Advanced Programmer, Karthik is passionate about sharing his knowledge on how data science can support data-driven business decisions.



Flexible Timings / Weekend classes Available.

Talk to the Trainer @ +91-8939915577

Big Data and Hadoop Training courses in Chennai


  • Big Data and Hadoop Certification Training
  • Hadoop Project based Training
  • Apache Spark Certification Training
  • Hadoop Administration
  • NoSQL Databases for Big Data
  • CCA175 - Cloudera Spark and Hadoop Developer Certification
  • Hadoop Interview Preparation - Questions and Answers

The Big Data Hadoop Certification course is designed to give you in-depth knowledge of the Big Data framework using Hadoop and Spark, including HDFS, YARN, and MapReduce. You will learn to use Pig, Hive, and Impala to process and analyze large datasets stored in the HDFS, and use Sqoop and Flume for data ingestion with our big data training.

You will master real-time data processing using Spark, including functional programming in Spark, implementing Spark applications, understanding parallel processing in Spark, and using Spark RDD optimization techniques. With our big data course, you will also learn the various interactive algorithms in Spark and use Spark SQL for creating, transforming, and querying data forms.

As a part of the big data course, you will be required to execute real-life industry-based projects using CloudLab in the domains of banking, telecommunication, social media, insurance, and e-commerce. This Big Data Hadoop training course will prepare you for the Cloudera CCA175 big data certification.


Hadoop Training Training courses content


  • 1 About Hadoop Training
  • 2 Hadoop Training Course Prerequisites
  • 3 Hardware and Software Requirements
  • 4 Hadoop Training Course Duration
  • 5 Hadoop Course Content


  • Hadoop Training Course Prerequisites


    • Basic Unix Commands
    • Core Java (OOPS Concepts, Collections , Exceptions ) — For Map-Reduce Programming
    • SQL Query knowledge – For Hive Queries

    Hardware and Software Requirements


    • Any Linux flavor OS (Ex: Ubuntu/Cent OS/Fedora/RedHat Linux) with 4 GB RAM (minimum), 100 GB HDD
    • Java 1.6+
    • Open-SSH server & client
    • MYSQL Database
    • Eclipse IDE
    • VMWare (To use Linux OS along with Windows OS)

    Hadoop Training Course Duration


    • 70 Hours, daily 1:30 Hours

    Hadoop Course Content


    Introduction to Hadoop


    • High Availability
    • Scaling
    • Advantages and Challenges

    Introduction to Big Data


    • What is Big data
    • Big Data opportunities
    • Big Data Challenges
    • Characteristics of Big data

    Introduction to Hadoop


    • Hadoop Distributed File System
    • Comparing Hadoop & SQL.
    • Industries using Hadoop.
    • Data Locality.
    • Hadoop Architecture.
    • Map Reduce & HDFS.
    • Using the Hadoop single node image (Clone).

    The Hadoop Distributed File System (HDFS)


    • HDFS Design & Concepts
    • Blocks, Name nodes and Data nodes
    • HDFS High-Availability and HDFS Federation.
    • Hadoop DFS The Command-Line Interface
    • Basic File System Operations
    • Anatomy of File Read
    • Anatomy of File Write
    • Block Placement Policy and Modes
    • More detailed explanation about Configuration files.
    • Metadata, FS image, Edit log, Secondary Name Node and Safe Mode.
    • How to add New Data Node dynamically.
    • How to decommission a Data Node dynamically (Without stopping cluster).
    • FSCK Utility. (Block report).
    • How to override default configuration at system level and Programming level.
    • HDFS Federation.
    • ZOOKEEPER Leader Election Algorithm.
    • Exercise and small use case on HDFS.

    Map Reduce


    • Functional Programming Basics.
    • Map and Reduce Basics
    • How Map Reduce Works
    • Anatomy of a Map Reduce Job Run
    • Legacy Architecture ->Job Submission, Job Initialization, Task Assignment, Task Execution, Progress and Status Updates
    • Job Completion, Failures
    • Shuffling and Sorting
    • Splits, Record reader, Partition, Types of partitions & Combiner
    • Optimization Techniques -> Speculative Execution, JVM Reuse and No. Slots.
    • Types of Schedulers and Counters.
    • Comparisons between Old and New API at code and Architecture Level.
    • Getting the data from RDBMS into HDFS using Custom data types.
    • Distributed Cache and Hadoop Streaming (Python, Ruby and R).
    • YARN.
    • Sequential Files and Map Files.
    • Enabling Compression Codec’s.
    • Map side Join with distributed Cache.
    • Types of I/O Formats: Multiple outputs, NLINEinputformat.
    • Handling small files using CombineFileInputFormat.

    Map/Reduce Programming – Java Programming


    • Hands on “Word Count” in Map/Reduce in standalone and Pseudo distribution Mode.
    • Sorting files using Hadoop Configuration API discussion
    • Emulating “grep” for searching inside a file in Hadoop
    • DBInput Format
    • Job Dependency API discussion
    • Input Format API discussion
    • Input Split API discussion
    • Custom Data type creation in Hadoop.

    NOSQL


    • ACID in RDBMS and BASE in NoSQL.
    • CAP Theorem and Types of Consistency.
    • Types of NoSQL Databases in detail.
    • Columnar Databases in Detail (HBASE and CASSANDRA).
    • TTL, Bloom Filters and Compensation.

    HBase


    • HBase Installation
    • HBase concepts
    • HBase Data Model and Comparison between RDBMS and NOSQL.
    • Master & Region Servers.
    • HBase Operations (DDL and DML) through Shell and Programming and HBase Architecture.
    • Catalog Tables.
    • Block Cache and sharding.
    • SPLITS.
    • DATA Modeling (Sequential, Salted, Promoted and Random Keys).
    • JAVA API’s and Rest Interface.
    • Client Side Buffering and Process 1 million records using Client side Buffering.
    • HBASE Counters.
    • Enabling Replication and HBASE RAW Scans.
    • HBASE Filters.
    • Bulk Loading and Coprocessors (Endpoints and Observers with programs).
    • Real world use case consisting of HDFS,MR and HBASE.

    Hive


    • Installation
    • Introduction and Architecture.
    • Hive Services, Hive Shell, Hive Server and Hive Web Interface (HWI)
    • Meta store
    • Hive QL
    • OLTP vs. OLAP
    • Working with Tables.
    • Primitive data types and complex data types.
    • Working with Partitions.
    • User Defined Functions
    • Hive Bucketed Tables and Sampling.
    • External partitioned tables, Map the data to the partition in the table, Writing the output of one query to another table, Multiple inserts
    • Dynamic Partition
    • Differences between ORDER BY, DISTRIBUTE BY and SORT BY.
    • Bucketing and Sorted Bucketing with Dynamic partition.
    • RC File.
    • INDEXES and VIEWS.
    • MAPSIDE JOINS.
    • Compression on hive tables and Migrating Hive tables.
    • Dynamic substation of Hive and Different ways of running Hive
    • How to enable Update in HIVE.
    • Log Analysis on Hive.
    • Access HBASE tables using Hive.
    • Hands on Exercises

    Pig


    • Installation
    • Execution Types
    • Grunt Shell
    • Pig Latin
    • Data Processing
    • Schema on read
    • Primitive data types and complex data types.
    • Tuple schema, BAG Schema and MAP Schema.
    • Loading and Storing
    • Filtering
    • Grouping & Joining
    • Debugging commands (Illustrate and Explain).
    • Validations in PIG.
    • Type casting in PIG.
    • Working with Functions
    • User Defined Functions
    • Types of JOINS in pig and Replicated Join in detail.
    • SPLITS and Multiquery execution.
    • Error Handling, FLATTEN and ORDER BY.
    • Parameter Substitution.
    • Nested For Each.
    • User Defined Functions, Dynamic Invokers and Macros.
    • How to access HBASE using PIG.
    • How to Load and Write JSON DATA using PIG.
    • Piggy Bank.
    • Hands on Exercises

    SQOOP


    • Installation
    • Import Data.(Full table, Only Subset, Target Directory, protecting Password, file format other than CSV,Compressing,Control Parallelism, All tables Import)
    • Incremental Import(Import only New data, Last Imported data, storing Password in Metastore, Sharing Metastore between Sqoop Clients)
    • Free Form Query Import
    • Export data to RDBMS,HIVE and HBASE
    • Hands on Exercises.

    HCATALOG.


    • Installation.
    • Introduction to HCATALOG.
    • About Hcatalog with PIG,HIVE and MR.
    • Hands on Exercises.

    FLUME


    • Installation
    • Introduction to Flume
    • Flume Agents: Sources, Channels and Sinks
    • Log User information using Java program in to HDFS using LOG4J and Avro Source
    • Log User information using Java program in to HDFS using Tail Source
    • Log User information using Java program in to HBASE using LOG4J and Avro Source
    • Log User information using Java program in to HBASE using Tail Source
    • Flume Commands
    • Use case of Flume: Flume the data from twitter in to HDFS and HBASE. Do some analysis using HIVE and PIG

    More Ecosystems


    • HUE.(Hortonworks and Cloudera).

    Oozie


    • Workflow (Action, Start, Action, End, Kill, Join and Fork), Schedulers, Coordinators and Bundles.
    • Workflow to show how to schedule Sqoop Job, Hive, MR and PIG.
    • Real world Use case which will find the top websites used by users of certain ages and will be scheduled to run for every one hour.
    • Zoo Keeper
    • HBASE Integration with HIVE and PIG.
    • Phoenix
    • Proof of concept (POC).

    SPARK


    • Overview
    • Linking with Spark
    • Initializing Spark
    • Using the Shell
    • Resilient Distributed Datasets (RDDs)
    • Parallelized Collections
    • External Datasets
    • RDD Operations
    • Basics, Passing Functions to Spark
    • Working with Key-Value Pairs
    • Transformations
    • Actions
    • RDD Persistence
    • Which Storage Level to Choose?
    • Removing Data
    • Shared Variables
    • Broadcast Variables
    • Accumulators
    • Deploying to a Cluster
    • Unit Testing
    • Migrating from pre-1.0 Versions of Spark
    • Where to Go from Here

Big Data Hadoop Certification Training


Big Data Hadoop training will enable you to master the concepts of the Hadoop framework and its deployment in a cluster environment. You will learn to:

Understand the different components of Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark with this Hadoop course.

  • Understand Hadoop Distributed File System (HDFS) and YARN architecture, and learn how to work with them for storage and resource management
  • Understand MapReduce and its characteristics and assimilate advanced MapReduce concepts
  • Ingest data using Sqoop and Flume
  • Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
  • Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
  • Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
  • Understand and work with HBase, its architecture and data storage, and learn the difference between HBase and RDBMS
  • Gain a working knowledge of Pig and its components
  • Do functional programming in Spark, and implement and build Spark applications
  • Understand resilient distribution datasets (RDD) in detail
  • Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
  • Understand the common use cases of Spark and various interactive algorithms
  • Learn Spark SQL, creating, transforming, and querying data frames
  • Prepare for Cloudera CCA175 Big Data certification



Who should take this Spark and Scala Certification course?


  • Software Engineers looking to upgrade Big Data skills
  • Data Engineers and ETL Developers
  • Data Scientists and Analytics Professionals
  • Graduates looking to make a career in Big Data

What are the Prerequisites for this course?


There are no prerequisites for taking up this course. Basic knowledge of database, SQL and query language can help.


Why take Big Data and Scala training course?


  • Big Data is an open source computing framework up to 100 times faster than Mapreduce
  • Spark is alternative form of data processing unique in batch processing and streaming
  • This is a comprehensive course for advanced implementation of Scala
  • Prepare yourself for cloudera Hadoop Developer and Spark Professional Certification
  • Get professional credibility to your resume so you get hired faster with high salary

Course advisor


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Named by Onalytica as one of the three most influential people in Big Data, Also an author for a number of leading Big Data and Data Science websites, including Datafloq, Data Science Central, and The Guardian. She also regularly speaks at renowned events.


What is a Big Data?


Big Data™ is a fast and general engine for large-scale data processing.
Speed Run programs up to 100x faster than Hadoop MapReduce in memory, or 10x faster on disk.
Ease of Use Write applications quickly in Java, Scala, Python, R.
Generality Combine SQL, streaming, and complex analytics.
Runs Everywhere Spark runs on Hadoop, Mesos, standalone, or in the cloud. It can access diverse data sources including HDFS, Cassandra, HBase, and S3.


Spark runs on Hadoop, Mesos, standalone, or in the cloud. It can access diverse data sources including HDFS, Cassandra, HBase, and S3. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, or on Apache Mesos.


Typical job duties for Big Data developer


  • Install, configure and maintain enterprise hadoop environment.
  • Loading data from different datasets and deciding on which file format is efficient for a task. Hadoop developers source large volumes of data from diverse data platforms into Hadoop platform.
  • Understanding the requirements of input to output transformations.
  • Hadoop developers spend lot of time in cleaning data as per business requirements using streaming API’s or user defined functions.
  • Defining Hadoop Job Flows.
  • Build distributed, reliable and scalable data pipelines to ingest and process data in real-time. Hadoop developer deals with fetching impression streams, transaction behaviours, clickstream data and other unstructured data.
  • Managing Hadoop jobs using scheduler.
  • Reviewing and managing hadoop log files.
  • Design and implement column family schemas of Hive and HBase within HDFS.
  • Assign schemas and create Hive tables.
  • Managing and deploying HBase clusters.
  • Develop efficient pig and hive scripts with joins on datasets using various techniques.
  • Assess the quality of datasets for a hadoop data lake.
  • Apply different HDFS formats and structure like Parquet, Avro, etc. to speed up analytics.
  • Build new hadoop clusters
  • Maintain the privacy and security of hadoop clusters.
  • Fine tune hadoop applications for high performance and throughput.
  • Troubleshoot and debug any hadoop ecosystem run time issues.


5 Reasons to Learn Big Data in Greens Technologys


Positioning yourself for a career in big data data scientists could be a smart move. You’ll have plenty of job opportunities, plus it’s a chance to work in the technology field with room for experimentation and creativity. So what’s your strategy?

1) Learn Big Data to have Increased Access to Big Data
2) Learn Big Data to Make Use of Existing Big Data Investments
3) Learn Big Data to pace up with Growing Enterprise Adoption
4) Learn Big Data as 2016 is set to witness an increasing demand for Spark Developers
5) Learn Big Data to make big money

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Big Data training in Chennai Reviews


Greens Technology Reviews given by our students already completed the training with us. Please give your feedback as well if you are a student.


Big Data training in Chennai Reviews from our Students


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Dear Karthik! This e-mail is to say BIG THANK YOU..for all teaching you done in our Big Data training sessions. I GOT JOB as Big Data Developer after almost 2 months of struggle here in Chennai. I must Thank you for such a good and rocking lessons. to tell you frankly you made me to like/love/crazy about R though i have no idea about it before joining your classes." This is my first job in IT after my studies and i am a bit tensed how things will be after joining in the company. your suggestions are more helpful for me to get on well in the company as good developer.



Best Big Data Certification Training Syllabus


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I attended the Base R and Advanced Big Data course class room sessions. The outline of the each course were well prepared and presented using latest video technology. The instructor is very talented and expert on Analytics concepts both theoretically and practically. I would highly recommend this institute to any one who wants to learn Big Data ." I joined "Greens Technology" because of their proven expertise in R practical training. Here, I learnt the Magic of Big Data . The constant and personal interaction with the Trainer, Live Projects, Certification Training and Study material are the best part. The trainers are extremely proficient in their knowledge and understanding of the topics. The instructors I had were both skillful and possessed the knowledge required to present the material to the classes. The R Certification training program has provided me with the necessary skill sets to prepare me for the corporate world. "Greens Technology" is the stepping stone to my success in the IT world. The money invested is well worth the reward. On my personal experience I recommend "Greens Technology" heart fully as the best training institute for IT Business Intelligence education. Thank you "Greens Technology" for helping me achieve my dream of becoming an Big Data Certified Professional.



Best Big Data Training center in Chennai


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"The course delivery certainly is much better than what I expected. I am glad that I decided to choose Greens Technology for the Big Data course. Wonderful learning experience and I like the way classes are organized and good support staff. Greens Technology provides quality learning experience within affordable price. Also thanks to my educator Dinesh , his teaching inspires and motivates to learn..


Best Big Data Training and Placement In Chennai


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"Friends I am from Manual testing background having 6+ years experienced. I planned to Move into R Business Intelligence (BI) . I Came to know about Greens technologies and Sai who is working in CTS . They Really helped me to clear the interview. Thanks to Sai Sir. Knowledgeable Presenters, Professional Materials, Excellent Support" what else can a person ask for when acquiring a new skill or knowledge to enhance their career. Greens Technology true to its name is the place to gather,garner and garden the knowledge for all around the globe. My Best wishes to Greens Technology team for their upcoming bright future in E-Learning sector.


R Training Venue:

Are you located in any of these areas - Adyar, Mylapore, Nandanam, Nanganallur, Nungambakkam, OMR, Pallikaranai, Perungudi, Ambattur, Aminjikarai, Adambakkam, Anna Nagar, Anna Salai, Ashok Nagar, Besant Nagar, Choolaimedu, Chromepet, Medavakkam, Porur, Saidapet, Sholinganallur, St. Thomas Mount, T. Nagar, Tambaram, Teynampet, Thiruvanmiyur, Thoraipakkam,Vadapalani, Velachery, Egmore, Ekkattuthangal, Guindy, K.K.Nagar, Kilpauk, Kodambakkam, Madipakkam, Villivakkam, Virugambakkam and West Mambalam.

Our Adyar office is just few kilometre away from your location. If you need the best R training in Chennai, driving couple of extra kilometres is worth it!



Big Data Related Training Courses in Chennai




Testimonials
best R training center in chennai "The best thing about Greens Technologys Hadoop classes is that, it uses real examples in class. This gives a deeper understanding of the material as against me just looking at slides.
Karthik! I am really delighted about the Hadoop course and i am surprised to see the depth of your knowledge in all aspects of the bigdata. I see that many architects with over 15+ yrs experience doesn't have the knowledge that you have. I really enjoyed your sessions, definitely look forward to learn more from you in the future. Thanks again."

R training chennai ""Dear Karthik, R training has been outstanding. You have covered every aspect of the R which would boost the confidence of the attendee to dive into greater depths and face the interviews subsequently. I feel confident after attending the R course. I am sure you would be providing us your valuable high level guidence in our initial realtime project . Each of your session is a eye opener and it is a great joy to attend your R training. Thanks and Kindest Regards ""

R training classes in chennai "I thought I knew R until I took this course. My company sent me here against my will. It was definitely worth and I found out how many things I was doing wrong. Karthik is awesome. but i got a lot inspired by you. I will keep in touch and will always try to learn from you as much as I can. Thanks once again Karthik"

Greens Technologys Overall Reviews


Greens Technologys Overall Reviews 5 out of 5 based on 12,468 ratings. 12,468 user reviews.
R training chennai """I think this is the best R course 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..as Sajin 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 Cloud.." ""


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