770+ Hadoop Training in Bangalore

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    Hadoop Training is specifically designed to help candidates in developing their skills associated to the big data and hadoop modules. This course will help candidates in understanding about the implementation of hadoop framework. With this training, one can master concepts such as Yarn, MapReduce, HDFS, Pig, Flume, Spark etc.

    Hadoop Training in Bangalore as on Apr 26, 2018

    1. DVS Technologies, Marathahalli Colony

      146 Reviews 9.1 Sulekha Score
      +91 80 48066750
      Hadoop Training, Big data & Hadoop training
      We leverage our state-of-the art training room facilities and more than a decade of domain experience and expertise to provide niche technology training services. We have trained and certified over 1000 IT professionals in Big data Technologies like Hadoop, Map Reduce, Hive, Pig, Hbase, Sqoop, Flume, Oozie, Zookeeper, Spark etc.,
    2. +91 80 48100596
      Hadoop Training, Big data & Hadoop training

      Our dedicated Trainer/Consultants have extensive, successful corporate experience in successfully delivering effective business solutions.

    3. Sgraph Infotech, Marathahalli

      56 Reviews 4.9 Sulekha Score
      +91 80 43691201
      Hadoop Training, Informatica training

      3rd Floor, Outer Ring Road, Marathahalli, Bangalore - 560037

    4. +91 80 43691648
      Hadoop Training, Informatica training

      No. 4, 2nd Floor, Sathyam Arcade, 1st Phase, BTM Layout 2nd Stage, BTM Layout, Bangalore - 560076 Get Directions

    5. Bigdatahub Org, Bellandur

      5.9 Sulekha Score
      +91 80 43691676
      Hadoop Training, Big data & Hadoop training

      Muthanna Gupta Building ,No. #19, 3rd Floor, Outer Ring Road, Bellandur, Bangalore - 560103 Get Directions

    6. +91 80 48031744
      Hadoop Training, Informatica training

      No.3, Ground Floor, VRKH Building, Vivekananda Layout, Marathahalli, Bangalore - 560037 Get Directions

    7. Redcoin Technologies, Marathahalli

      3 Reviews 5.0 Sulekha Score
      +91 80 43691696
      Hadoop Training, Business intelligence & analytics training

      Krishna Towers ,No. 14, 1st Floor, Off Outer Ring Road, Bridge Marathahalli, Marathahalli, Bangalore - 560037 Get Directions

    8. Aptech Computer Education, Malleswaram

      23 Reviews 4.5 Sulekha Score
      +91 80 48032584
      Hadoop Training, Big data & Hadoop training

      Sai Sharan Heights ,No. 78, 2nd Floor, 15th Cross Street, Margosa Road, Malleswaram, Bangalore - 560003

    9. AM Tech Services, Marathahalli

      13 Reviews 5.6 Sulekha Score
      +91 80 43691902
      Hadoop Training, Big data & Hadoop training

      Sigma Arcade Building ,Unit No.8, 9, 1st Floor, Hal Main Road, Marathahalli, Bangalore - 560037 Get Directions

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    10 Reviews of Hadoop Training in Bangalore as on Apr 26, 2018

    Average Rating (5) - 28 reviews
    1. 26th April, 2018

      Glad to share my experience with this institute, I was joined in this institute for Big data & Hadoop training. I paid total 16000 for Coaching fees, and course duration was 2 months & I'm attending daily classes. The faculty was well experienced and friendly. They explained the subjects in an understandable way. I'm glad to join in this institute.

    2. 15th April, 2018

      I have completed my big data hadoop training from vss innovative technology last month. Trainer was highly experienced and helpful

    3. 13th April, 2018

      Hi, I have attended Hadoop course in besant technologies and it was a great learning experience . Rahul sir taught us from the scratch as I was new to the linux systems and we did real time projects The timing was also flexible and I could attend easily.Best Hadoop Training institute in Bangalore.

    4. 14th March, 2018

      They cover maximum topics of Hadoop eco system and tutor here make it more easy to understand, they clear each n every doubt with practical example..best one for hadoop and spark.

    5. 9th March, 2018

      Best place to learn bigdata technologies

    6. 9th March, 2018

      It good experience to get training from DVS for freshers as well as experienced level. we can get re-sessions when we miss and can be used time for pratice with good facality after classes.

    7. 9th March, 2018

      Best place to learn Bigdata Hadoop . Provided a good environment for practicing also . Good motivation from trainer's . I got more practical knowledge &lot of exposure.

    8. 5th March, 2018

      This the Best Place to learn all Big data concepts like Hadoop,Spark with Real time experienced Trainers.

    9. 27th February, 2018

      i joined for hadoop course and trainer here has superb knowledge, provided practical classes with real life examples datasets . my rating is 5/5

    10. 12th February, 2018

      It’s tremondous service and easily get info about in knowing things using this site

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    • Hadoop Training in Bangalore – Common FAQs

      • Who should opt for this course?

        This course is best suited for:

        • Candidates working as system administrators
        • Professionals working as programming developers
        • Big Data Hadoop developers are inclined to learning more about analytics and administration
        • Data warehousing experts and business intelligence professionals
        • Graduates or fresher’s who have passion towards big data technology
      • What are the pre-requisites for this training?

        There are no specific pre-requisites for this training. But there following skills will be extremely beneficial to candidates:

        • Basic knowledge in UNIX
        • Basic concepts associated to SQL
        • Basic programming knowledge in Java
      • What are the learning outcomes of this training?

        The learning outcomes of this training are as follows:

        • Learning about the fundamentals of Hadoop 2.7 and YARN
        • Understanding how to setup pseudo node and multi node cluster
        • Learning about Spark SQL, Dataframe, RDD and Mlib
        • In depth knowledge in accordance to Hadoop administration activities - cluster management and monitoring, troubleshooting and administration
        • Understanding how to configure Kerberos on Hadoop cluster
        • Learning how to configure ETL tools such as Pentaho and learning work with MapReduce, Hive and Pig
      • Do institutes provide placement assistance after the completion of the training?

        Most of the institutes provide placement assistance for their candidates after the completion of the course. However, just confirm with the institution once prior to joining.

      • Do I need a programming background to learn Hadoop?

        A candidate without a programming background can opt for this training. However, basic coding skills in JAVA and Linux can be beneficial. This knowledge will help candidates in learning about Hadoop faster.

      • What are the benefits of taking up classroom training?

        The benefits of class room training are as follows:

        • Training from experienced trainers
        • Access to state of the art labs
        • Access to the latest material and syllabus
        • Training in accordance to the latest trends in Hadoop
        • Mock tests and interview preparation
        • Training with real life case studies and projects
      • What are the type of projects that I will be working on for this training?

        Projects that focus on MapReduce, Hive and Sqoop

        • Learning how to write a MapReduce program
        • Deploying Apache Pig
        • Learning to work with Hive

        A project to help with Hadoop YARN using real life case studies

        • Appending data
        • Using Sqoop commands
        • End to End flow of transaction data
        • Data processing using MapReduce

        Projects for partitioning tables in Hive

        • Manual and dynamic partitioning
        • Bucketing

        Multinode cluster setup project

        • Running Hadoop multi node
        • Deploying MapReduce on Hadoop cluster
      • What is the duration of this course?

        The duration of this course is as follows:

        Regular Classes

        • Course Duration: 10 weeks
        • Batch Duration: 2 hours/class
        • Class Schedule: Monday to Friday

        Weekend Classes

        • Course Duration: 12 weekends
        • Batch Duration: 3+ hours/class
        • Class Schedule: Saturday and Sundayu=

        Fast track Classes

        • Course Duration: 2 weeks
        • Batch Duration: 5+ hours/class
        • Class Schedule: Daily classes

      Course Syllabus

      Installing Hadoop

      • Hadoop Cluster Architecture
      • Production Cluster Setup
      • Cluster modes
      • Shell commands in Hadoop
      • Configuration files for Hadoop
      • Single node cluster for cloudera
      • Hive and Pig
      • Sqoop
      • Flame
      • Scala and Spark

      Introduction to Big Data Hadoop

      • What is Big data and Hadoop
      • Hadoop Ecosystem - Map Reduce and HDFS
      • Hadoop Distributed file system - Replication, Name node, Block size and high availability
      • YARN - Resource and Node Manager
      • Replicating Data
      • Determining block size
      • Namenode and datanode


      • Introduction to Hadoop Hive
      • Architecture of Hive
      • Hive vs PIG and RDBMS
      • Hive Query Language
      • Creating database and table
      • Types of Hive Tables
      • Hcatalog
      • Storing Hive results
      • Hive partitioning
      • Hive Buckets
      • Hive table partitioning

      Advanced Hive and Impala

      • Indexing in hive
      • Map side join
      • Complex data types
      • Hive user defined functions
      • Introduction to impala
      • Hive vs Impala
      • Architecture of Impala
      • Working with hive queries


      • Introduction to Apache Pig
      • Features of Pig
      • Data types and schema in Hive
      • Pig Functions
      • Hive bags
      • Tuples
      • Fields
      • Working with Pig in Mapreduce

      Flume, Sqoop & HBase

      • Introduction to Apache Sqoop
      • Imports and exports
      • Improving Sqoop performance
      • Limitations of Sqoop
      • Flume architecture
      • HBase
      • CAP Theorem
      • Generating sequence number with flume

      Spark applications and Scala

      • Apache spark applications and Scala
      • Studying scala
      • Need for scala
      • Object orientied programming concepts
      • Scala code execution
      • Classes in Scala - Getters, setters, constructors, extending objects
      • Overriding methods
      • Functional programming
      • Anonymous functions
      • Bobsrockets package
      • Mutable and immutable collections

      Spark Framework

      • Apache spark introduction
      • Features
      • Comparing spark with hadoop
      • Spark components
      • HDFS and spark
      • Importance of Scala and RDD
      • Spark and RDD
      • Spark transformations
      • Data loading
      • MapReduce comparison
      • Key value pair
      • RDD deployment with HDFS

      Data Frames and Spark SQL

      • Spark SQL in detail
      • Significannce of SQL in Spark
      • JSON support
      • XML data
      • Parquet files
      • Hive context creation
      • Data frame to hive reading of JDBC
      • Data Frames in Spark
      • Working with CSV files
      • JDBC tables
      • Data frame to JDBC
      • Shared variable
      • Accumalators
      • Query and data frames
      • Hive on spark as execution engine

      Machine learning with spark

      • Algorithm types
      • Iterative algorithm in spark
      • Spark graph processing
      • K-means and machine learning
      • Variables in Spark
      • Accumulators

      Spark streaming

      • Introduction to spark streaming
      • Architecture of spark streaming
      • Spark streaming program
      • Processing data
      • Dstream
      • Sliding window operations
      • Advanced data sources

      Hadoop administration

      • Hadoop cluster setup
      • MapReduce and Hadoop cluster
      • MapReduce Code
      • Cloudera Manager Setup
      • Cluster configuration
      • Hadoop configuration file
      • Parameters and values for configuration
      • HDFS parameters
      • MapReduce parameters
      • Hadoop environment setup
      • Data node directory structure
      • File system image
      • Checkpoint procedure

      ETL connectivity with Hadoop

      • How ETL tools work
      • ETL and data warehousing
      • End to End ETL poc

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