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Big Data Hadoop Training Certificate Course in Delhi

EagletFly’s big data hadoop training in Delhi  is planned by Hadoop industry specialists, and it incorporates in-depth information on Big Data and Hadoop Ecosystem devices such as HDFS, YARN, MapReduce, Hive, Pig, HBase, Spark, Oozie, Flume, and Sqoop.

About Big Data Hadoop Training in Delhi NCR

The Big Data Hadoop Training Certification program Patel Nagar, New Delhi  is created to give you an in-depth insight into the Big Data structure using Hadoop and Spark, including HDFS, YARN, and MapReduce. You will see to use Pig, Hive, and Impala to process and examine huge datasets deposited in the HDFS, and apply Sqoop and Flume for data ingestion with our big data foundation.

During this instructor-led Hadoop Training, you will be operating on real-life application use cases in Retail, Social Media, Aviation, Tourism, and Finance region using our Cloud Lab.

In the course of Big data training in Delhi ( At Patel Nagar Center), you will understand real-time data processing using Spark, including operative programming in Spark, executing Spark applications, empathetic parallel processing in Spark, and handling Spark RDD optimization methods. With our big data course, you will also study several interactive algorithms in Spark and use Spark SQL for building, remodeling, and questioning data forms.

As a part of our Big Data learning program, you will be required to execute real-life, industry-based designs using CloudLab in the realms of business, telecommunication, social media, security, and e-commerce.  This Big Data Hadoop training program in Patel Nagar Delhi will make you fit for big data certifications.

Big Data Skills for Professional Benefits

The range of big data and analytics is a compelling one, modifying rapidly as technology grows over time. Those experts who take the lead and shine in big data and analytics are well-positioned to maintain speed with developments in the technology area and fill expanding job openings.

Job Opportunities for Big Data Trained Professionals

The fields that need Big Data Hadoop trained professionals include:

  • IT experts
  • Data scientists
  • Data technicians
  • Data analysts
  • Project administrators
  • Program directors

Big Data & Hadoop Training Course Frequently Asked Question

Hadoop is a software framework for storing and processing Big Data. It is an open-source tool build on java platform and focuses on improved performance in terms of data processing on clusters of commodity hardware. Hadoop comprises of multiple concepts and modules like HDFS, Map-Reduce, HBase, PIG, HIVE, SQOOP and ZOOKEEPER to perform the easy and fast processing of huge data. Hadoop conceptually different from Relational databases and can process the high volume, high velocity and high variety of data to generate value. This hadoop training in Delhi will help your career and learning path in future.

 

IT/ ITES, Business Intelligence, Database experts/ computer science (or any other circuit categories) alumni who are not just looking for general Hadoop training for a developer position, but desire Big Data Analytics certification based on effective Hadoop-Spark and Cloud Computing skills.

Software Engineers, who are into ETL/Programming and exploring for great job opportunities in Hadoop.

All the managers who want to implement latest technologies in their organization to meet current & upcoming challenges of data management.

You can turn yourself into a certified professional via a professional Hadoop Training Institute in Noida, Gurgaon, Ghaziabad, and Delhi NCR. We offer Hadoop Classes in Delhi, Gurgaon, Ghaziabad, and Delhi NCR at most affordable prices.

The demand for Big Data analytics is expanding across the world and this powerful extension model renders into a great possibility for all the IT Experts. Employing autorities always look for approved Big Data Hadoop specialists. Our Big Data & Hadoop Certification Training assists you to seize this chance and stimulate your career. Our Big Data Hadoop Course can be shadowed by experts as well as freshers. It is extremely suited for:

  • Bachelors looking to make a career in Big Data Field
  • Data Engineers
  • Software Engineers
  • Software Developers, Project Administrators
  • ETL and Data Warehousing Experts
  • Senior IT Professionals
  • Data Analysts & Business Intelligence Professionals
  • DBAs and DB specialists
  • Mainframe professionals
  • Testing experts

For seeking a career in Data Science, understanding of Big Data, Apache Hadoop & Hadoop means are significant. Hadoop practitioners are amidst the highest paid IT professionals today with wages reaching around $97K, and their market interest is increasing quickly.

EagletFly has prepared a variety of teaching plans depending on current need and time. This program is designed in such a way that it gives complete education within a short period of time and conserves money and precious time for people. It can be very effective for people who are working currently. Our training staffs believe in forming a newcomer from the bottom and shaping them into an expert.

We carry many forms of training and include test, mock tasks and practical problem solving lessons. At the completion of the program, applicants are granted Big Data Certification. This is the most comprehensive Big Data Hadoop coaching along with Spark and Cloud in Delhi NCR( Patel Nagar), with the versatility of serving the big data online education through self-paced videos.

Prerequisites for learning Hadoop include hands-on experience in one programing language and good analytical skills to grasp and apply the concepts in Hadoop.

The training ís delivered by highly qualified and certified instructors with relevant industry experience. And feel very proud while telling you, Mapping Minds is one of the well-established Hadoop training institutes in Delhi that provides best Hadoop training in Delhi.

We will provide 2 data sets to work on real live Big Data & Hadoop projects.

Yes, you can learn Hadoop without being from a software background. We provide complimentary courses in Python and Linux so that you can brush up on your programming skills. This will help you in learning Hadoop technologies better and faster.

Yes, if you missed any Big Data class you will get back within 15 days.

We support multiple payment options online /offline. Choose an option that suits you the most to pay your course fee.

The course will be a combination of theoretical and practical sections on each topic. We also provide exposure to our live projects.

Fees for Big Data & Hadoop training course is Rs. 22,500 includes GST

3 months Including  hadoop Live Project Training sessions.

Big Data & Hadoop Training Content

Big data features and challenges
• 3Vs for Big Data
• Problems with traditional large-scale systems
• Why Hadoop? & Hadoop fundamental concepts
• Hadoop vs RDBMS vs No-SQL
• History of Hadoop with Hadoopable problems
• Hadoop distributed file system (HDFS)
• Limitation of Hadoop

Hadoop Version – 2.x & 1.x
• Distributions of Hadoop (Cloudera, Hortonworks)
• Architecture of Hadoop
• Rack awareness and topology
• Cluster storage daemons Name Node
• Secondary Node
• Data Nodes
• YARN Responsibilities
• Resource Manager
• Job History Server
• Node Manager
• Application Manager
• Application Master

  1. Name Node availability
    • Architecture of HA
    • Implementation of HA
    • Apache Zookeeper service
  2. Quorum Journal
    • Active Name Node and Standby Name Node
    • Zookeeper Fail Over controller
    • Quorum Journal Manager
    • Quorum Journal Node(s)

  3.  Namespace federation (NFS)
    • Namespace information
    • Zookeeper fail over controller

• Installation of Linux (Red Hat)
• Basic Linux configurations
• Basic Linux commands
• Password less ssh
• IP address and hostname
• Firewall and selinux
• Yum and creating yum repository
• NTP configurations

• Installation Prerequisites
• General planning considerations
• Choosing the right hardware
• Network considerations
• Configuring nodes
• Planning for cluster management

• Choosing deployment types
• Setting up multi-nodes
• Setting up Cloudera yum repository
• Installation for Cloudera Manager
• Installing multi-node Hadoop (Cloudera) environment
• Specifying the Hadoop configuration
• Performing Initial HDFS configuration
• Performing Initial YARN and Map Reduce configuration
• Hadoop logging & cluster monitoring

• Access HDFS using command line
• Hadoop fs
• Hadoop HDFS admin
• Access Cloudera Manager (Admin)
• Access HUE (Developer)

• Add and remove services
• Configuring HDFS properties like Block size
• Setting up zookeeper on multi node
• Configuring Hadoop operating system
• (YARN) & Map-Reduce
• Configuring schedulers
• Hadoop logging & monitoring
• Advanced configuration parameters
• Configuring Hadoop ports
• Explicitly including and excluding hosts

• Checking HDFS status
• Copying Data between clusters
• Adding and removing cluster nodes
• Rebalancing the cluster
• Cluster upgrading

• Overview of sandBox
• Different flavours (Virtual Box / VMware) of sandBox
• Installation of sandbox

• Introduction of HUE
• Getting started with HUE
• Deployment of jobs
• Functional execution of Hive/HBase
• Design of work-flow using job designer
• Data transfer in Sqoop
• Start working with sandBox

Hadoop developer/admin commands using shell
• NameNode & Secondary Name Node commands
• HDFs dfsadmin and file system shell commands
• Hadoop Name Node / Data Node directory structure
• HDFS permissions model
• Map-Reduce job deployment
• Oozie workflow design
• Different components jobs design

• Introduction to map reduce
• Architecture of map reduce
• Understanding the concept of mappers & reducers
• Anatomy of map reduce program
• Phases of a map reduce progam
• Data-types in hadoop map reduce
• Driver, mapper and reducer classes
• Input split and record reader
• Input format and output format in hadoop
• Concepts of combiner and partitioner
• Running and monitoring mapreduce jobs
• Writing your own map reduce job using map reduce API
• Different interview questions raised for map reduce

• Scala Introduction
• Scala versus Java
• Scala basics
• Scala Data types
• Scala packages
• Variable Declarations
• Variable Type Inference
• Control Structures
• Interactive Scala – Scala shell
• Writing Scala Scripts – Compiling the Scala Programs
• Defining Functions in Scala
• Different IDEs for Scala

Motivation for spark
• Spark vs Map Reduce Processing
• Architecture of Spark
• Spark Shell introduction
• Creating Spark Context
• File operations in Spark Shell
• Spark Project with SBT in Eclipse
• Caching in Spark
• Real time Examples of Spark
• Concepts of combiner and partitioner
• Running and monitoring mapreduce jobs
• Writing your own map reduce job using map reduce AP
• Resilient Distributed Dataset (RDDS)
• Introduction of RDDs
• Features of RDDs
• Creating RDDs
• Creating RDDs referencing an external dataset
• Creating RDDs using text files
• Creating RDDs using other hadoop input formats
• RDD operations & transformations
• Features of RDD persistence
• Storage levels Of RDD persistence
• Choosing the correct RDD persistence storage level
• Invoking the Spark shell
• Creating the Spark contex• basic operations on files in Spark shell RDD
• Demo-build a Spark Python project
• Build a Spark Java project
• Shared variables broadcast & accumulators
• Double RDD methods
• Pair RDD methods Join
• Pair RDD methods Others
• General RDD methods
• Transformations in RDD
• Actions in RDD
• Key Value pair RDD in Python
• Reading text & sequence file from HDFS
• Using groupby operation
• Python application performing group by operation 

• Introduction to Spark SQL
• The SQL Context
• Hive vs Spark SQL
• Spark SQL
• support for Text Files, Parquet and JSON files
• Data Frames
• Real time Examples of Spark SQL

• Introduction to Spark Streaming
• Architecture of Spark Streaming
• Spark Streaming vs Flume
• Introduction to Kafka
• Spark streaming Integration with Kafka overview
• Real time examples of Spark Streaming and Kafka

• Introduction to Machine Learning
• Vector Class in Mlib
• Spark Mlib Algorithms introduction
• Classification and Regression Algorithms
• Naïve Bayes Classification Algorithms
• Decision Trees Algorithm Overview

• Problems with No-SQL
• database
• Introduction & installation Hive
• Hive schema and data storage
• Data types & introduction to SQL
• Hive-SQL: DML & DDL
• Hive-SQL: views & indexes
• Explain and use the various Hive file formats
• Use Hive to run SQL-like queries to perform data analysis
• Use Hive to join data sets using a variety of techniques
• Map-side joins and Sort-Merge-Bucket joins

• Installation of Sqoop
• Ingesting data from external (DB) sources with Sqoop
• Ingesting data from/to relational databases with Sqoop
• Integration of Sqoop and Hive
• Best practices for importing data

• Oozie introduction
• Oozie architecture
• Oozie Configuration Files
• Oozie Job Submission
• Workflow.xml
• Coordinator.xml
• job.coordinator.properties

• Flume introduction
• Flume Architecture
• Flume Master , Flume Collector and Flume Agent
• Flume Time Use Case using Apache Flume

1: What is Kafka – An Introduction
• What is Apache Kafka
• Components and use cases of Kafka
• Implementing Kafka on a single node
• Installing spark as a standalone & cluster environment
2: Multi Broker Kafka Implementation
• Learning about the distributed Kafka terminology
• Deploying multi node Kafka with independent Zookeeper
• Adding replication in Kafka
• Working with Partitioning and Brokers
• Understanding Kafka consumers
• Kafka Writes terminology
• Various failure handling scenarios in Kafka

• Multi node cluster setup in Kafka
• Various administration commands
• Leadership balancing and partition rebalancing
• Graceful shutdown of kafka Brokers and tasks
• Working with the Partition Reassignment Tool
• Cluster expending & Assigning Custom Partition
• Removing of a Broker and improving Replication Factor

• Connecting Kafka using PyKafka
• Writing your own Kafka Producers and Consumers
• Writing a random JSON Producer
• Writing a Consumer to read the messages from a topic
• Writing and working with a File Reader Producer
• Writing a Consumer to store topics data into a file

Join Big Data Course- Join Big Job Opportunity

EagletFly provides job oriented Big Data Hadoop Training in Delhi. Our Instructor-led Classroom program is popular among professionals in Big Data Industry. Join our popular big data & hadoop course in Central Delhi.

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