APACHE HADOOP TRAINING & ONLINE CERTIFICATION COURSES

“Data is a precious thing and will last longer than the systems themselves.”

- Tim Berners-Lee (father of the World wide Web)

Course Features

  • Online / Instructor Led training
  • Placement Assistance
  • Free study materials
  • Full lifetime access
  • Assignments
  • Certificate of Completion
 
     

Tools Covered

  • Data Extraction Tool- Talend, Pentaho
  • Data Storing Tool- Hive, Sqoop, MongoDB
  • Data Mining Tool- Oracle
  • Data Analyzing Tool- HBase, Pig
  • Data integration Tool- Zookeeper

Career Jobs

Hadoop architect, Hadoop Admin, Hadoop developer, Big data analyst, Big data software engineer, Big data architect, Data engineer, Data scientist, ETL developer

Average Pay for Entry level

$1,20,000 – $1,70,000 per year  

APACHE HADOOP TRAINING & ONLINE CERTIFICATION COURSES

Training Providers

join us for apache hadoop training with free course materials

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apache hadoop training is having good demand in the market, our hadoop faculty is very much experienced, he had 13+ yrs real-time hands-on experienced and highly qualified and dedicated.what is hadoop?hadoop is a free, java-based programming framework that supports the processing of large data sets in a distributed computing environment. it is part of the apache project sponsored by the apache sof..

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Pre-requisites

Basics knowledge of Hadoop, Knowledge in data analytics.

About Course

Apache Hadoop is an open source framework used in distributed computing environment sponsored by apache software foundations. It allows to store and process data across clusters using simple programming models. Hadoop framework includes four major modules. First one is Hadoop common, containing libraries and utilities necessary for other Hadoop modules. Secondly, Hadoop distributed file system (HDFS) that provides high throughput access to application data. Hadoop yarn framework for job scheduling and managing cluster resource is the third thing. The final module is Hadoop mapreduce, a programming model for large data sets. To know in detail about the four major modules, engage yourself in apache hadoop online training classes containing advanced topics.

Concentrate on Hadoop courses and advantages and work with real time projects. Hadoop framework allows clients to rapidly create and check distributed systems. Hadoop is designed in such a way that it can handle failures at the application layer. Hadoop continues to work without interruption even the servers are added or removed from the clusters. It is compatible on all the platforms. Find training classes to learn beginner courses to advance modules with certification. Study major topics like hdfs, mapreduce and yarn from professionals in USA. Enroll Benchfolks to join training classes taught by leading trainers in USA. We serve your demanding needs by allowing you to find top apache hadoop training providers.

Apache Hadoop course contents

Learn apache Hadoop with courses including introduction to the course, HDFS, Mapreduce, installing apache Hadoop in single node and multinode, managing HDFS, troubleshooting and optimizing Hadoop, introduction to pig, hive and hbase and other advanced modules. Store, retrieve and analyze large data sets with knowledge in apache Hadoop latest courses. When you consider the Hadoop ecosystem, the entire apache Hadoop platform consists of number of related projects like apache pig, hive, hbase and others. View details of courses via Benchfolks and book training sessions.

Benchfolks has more number of Hadoop specialists registered, who provide certification training in all parts of USA. Get real time experience by working with live projects. Most of the trainers here provide placement opportunities for those who got certification in apache Hadoop. Take online training to learn apache Hadoop with the comfort of staying in your own place. Gain apache hadoop certification with clear understanding of all the major concepts. We care about your career and provide you a chance to get hands on training on apache Hadoop.

Benchfolks has list of trainers with professional approach towards the training. We gain individual attention by providing a pathway for enthusiasts to enter Hadoop career. Choose flexible batch schedule to attend training sessions on your time. Choose trainers from below who provide unique structured courses in an easy understanding way. Get practical demonstrations from best trainers of US signed up with us. Start with the short-term training courses offered by industry specialists of apache Hadoop applications. Know that Hadoop lead the industry by helping large business in numerous ways. Learn apache Hadoop courses and become a certified expert and get high pay apache Hadoop jobs.

Curriculum for this Course

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  • Hadoop Introduction
  • What is Hadoop? Why Hadoop?
  • Hadoop History?
  • HDFS, MapReduce, PIG, Hive, SQOOP, HBASE, OOZIE, Flume, Zookeeper and so on…
  • What is the scope of Hadoop?

Introduction of HDFS

  •         HDFS Design
  •         HDFS role in Hadoop
  •         Features of HDFS
  •         Daemons of Hadoop and its functionality
  •         Name Node
  •         Secondary Name Node
  •         Job Tracker
  •         Data Node
  •         Task Tracker
      • Anatomy of File Wright
      • Anatomy of File Read
      • Network Topology
  •         Nodes
  •         Racks
  •         Data Center
      • Parallel Copying using DistCp
      • Basic Configuration for HDFS
      • Data Organization
  •         Blocks and
  •         Replication
      • Rack Awareness
      • Heartbeat Signal
      • How to Store the Data into HDFS
      • How to Read the Data from HDFS
      • Accessing HDFS (Introduction of Basic UNIX commands)
      • CLI commands

The introduction of MapReduce.

  •         MapReduce Architecture
  •         Data flow in MapReduce
      • Splits
      • Mapper
      • Portioning
      • Sort and shuffle
      • Combiner
      • Reducer
  •         Understand Difference Between Block and InputSplit
  •         Role of RecordReader
  •         Basic Configuration of MapReduce
  •         MapReduce life cycle
      • Driver Code
      • Mapper
      • and Reducer
  •         How MapReduce Works
  •         Writing and Executing the Basic MapReduce Program using Java
  •         Submission & Initialization of MapReduce Job.
  •         File Input/Output Formats in MapReduce Jobs
      • Text Input Format
      • Key Value Input Format
      • Sequence File Input Format
      • NLine Input Format
  •         Joins
      • Map-side Joins
      • Reducer-side Joins
  •         Word Count Example
  •         Partition MapReduce Program
  •         Side Data Distribution
      • Distributed Cache (with Program)
  •         Counters (with Program)
      • Types of Counters
      • Task Counters
      • Job Counters
      • User Defined Counters
      • Propagation of Counters

·         Job Scheduling

  •         Introduction to Apache PIG
  •         Introduction to PIG Data Flow Engine
  •         MapReduce vs. PIG in detail
  •         When should PIG use?
  •         Data Types in PIG
  •         Basic PIG programming
  •         Modes of Execution in PIG
      • Local Mode and
      • MapReduce Mode
  •         Execution Mechanisms
      • Grunt Shell
      • Script
      • Embedded
  •         Operators/Transformations in PIG
  •         PIG UDF’s with Program
  •         Word Count Example in PIG
  •         The difference between the Map

·         Reduce and PIG

  •         Introduction tSQOOP
  •         Use of SQOOP
  •         Connect tmySql database
  •         SQOOP commands
      • Import
      • Export
      • Eval
      • Codegen etc…
  •         Joins in SQOOP
  •         Export to MySQL

·         Export to HBase

  • Introduction to HIVE
  • HIVE Meta Store
  • HIVE Architecture
  • Tables in HIVE
      • Managed Tables
      • External Tables
  • Hive Data Types
      • Primitive Types
      • Complex Types
  • Partition
  • Joins in HIVE
  • HIVE UDF’s and UADF’s with Programs
  • Word Count Example
  • Introduction tHBASE
  • Basic Configurations of HBASE
  • Fundamentals of HBase
  • What is NoSQL?
  • HBase Data Model
      • Table and Row
      • Column Family and Column Qualifier
      • Cell and its Versioning
  • Categories of NoSQL Data Bases
      • Key-Value Database
      • Document Database
      • Column Family Database
  • HBASE Architecture
      • HMaster
      • Region Servers
      • Regions
      • MemStore
      • Store
  • SQL vs. NOSQL
  • How HBASE is differed from RDBMS
  • HDFS vs. HBase
  • Client-side buffering or bulk uploads
  • HBase Designing Tables
  • HBase Operations
      • Get
      • Scan
      • Put
      • Delete
  • What is MongoDB?
  • Where to Use?
  • Configuration On Windows
  • Inserting the data into MongoDB?
  • Reading the MongoDB data.
  • Downloading and installing the Ubuntu12.x
  • Installing Java
  • Installing Hadoop
  • Creating Cluster
  • Increasing Decreasing the Cluster size
  • Monitoring the Cluster Health
  • Starting and Stopping the Nodes
  • Introduction Zookeeper
  • Data Modal
  •  Operations
  • Introduction to OOZIE
  • Use of OOZIE
  • Where to use?
  • Introduction to Flume
  • Uses of Flume
  • Flume Architecture
  • Flume Master
  • Flume Collectors
  • Flume Agents

Jobs and Placements

Get ready for the corporate world. Take up training from the listed training companies here, and they will ensure offer you placement assistance at the end of the course. Advance your career and become an IT professional now. Take role as Hadoop architect, Hadoop Admin, Hadoop developer, Big data analyst, Big data software engineer, Big data architect, Data engineer, Data scientist and ETL developer and become a master in this field.

Sample Interview Q&A

  1. What is Apache Hadoop?

    Hadoop emerged as a solution to the “Big Data” problems. It is a part of the Apache project sponsored by the Apache Software Foundation (ASF)

    2. What are the main components of a Hadoop Application?

    Core components of a Hadoop application are-
    1) Hadoop Common
    2) HDFS
    3) Hadoop MapReduce
    4) YARN

    3. What is HDFS?

    Hadoop Distributed File Systems (HDFS) is one of the core components of Hadoop framework. It is a distributed file system for Hadoop. It runs on top of existing file system

    4. What are the daemons of HDFS?

    NameNode
    DataNode
    Secondary NameNode.

    5.What is MapReduce?

    MapReduce is a programming model for processing on the distributed datasets on the clusters of a computer.

FAQ

The training will be a combination of theoretical and practical on each topic. The trainers will be providing live exposure on projects and give assignments to test your skill sets.

Yes, the trainer will provide you support for any clarification you need in a job.

We have 2 modes of training. Classroom Training & Online training.

All of our online courses are live instructor-led online courses. You will have the ability to interact directly with the trainer and the training is one on one too through an easy-to-use web conferencing tool like GoToMeeting etc.

The course is non-transferable to anyone else other than the person whose details are given while enrolling once the student has started

Yes, you will receive student guides from the trainers.

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