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    Hadoop Training

    BY
    Mindmajix Technologies

    Learn the fundamental concept and functionalities of big data using Hadoop, as well as Spark, Yarn, Pig, Hive, and MongoDB.

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    Mode

    Online

    Quick Facts

    particular details
    Medium of instructions English
    Mode of learning Self study, Virtual Classroom
    Mode of Delivery Video and Text Based
    Frequency of Classes Weekdays, Weekends

    Course overview

    Hadoop Training online certification is offered by MindMajix Technologies which is designed to help individuals gain an in-depth understanding of all Big Data and Hadoop tools topics, from the fundamentals to advanced level methods. Hadoop Training online course is available in two formats: self-paced videos in which applicants can learn at their own pace using e-learning materials, or live mode in which the teacher conducts online class through Zoom or Google Meet.

    The online Hadoop Training classes include 40 hours of comprehensive HD video lectures on big data and Hadoop topics such as Hadoop architecture, Hadoop MapReduce frameworks, and more analytical tools such as Hive, Pig, Sqoop, Flume, MongoDB, Apache Spark, and others. Candidates will also receive hands-on experience by participating in two real-time industry-based projects related to this curriculum.

    The highlights

    • Certificate of completion
    • Certification oriented curriculum
    • Lifetime self-paced video access
    • Flexible schedule
    • Project use cases
    • 40 hours session
    • Quizzes & Mocks
    • Free demo on request
    • One-on-one doubt resolution
    • 100% money-back guarantee 
    • 24/7 lifetime assistance

    Program offerings

    • Certificate of completion
    • Certification oriented curriculum
    • Lifetime self-paced video access
    • Flexible schedule
    • Project use cases
    • 40 hours session
    • Quizzes & mocks
    • Free demo on request
    • One-on-one doubt resolution
    • 100% money-back guarantee

    Course and certificate fees

    certificate availability

    Yes

    certificate providing authority

    Mindmajix Technologies

    What you will learn

    Knowledge of big data Knowledge of mongodb

    After completing the Hadoop Training certification course, candidates will comprehend the core principles of big data. Candidates will learn about the essential Hadoop features and will get the opportunity to explore the Hadoop ecosystem for big data analytics. Candidates will explore the analytic capabilities of Apache Spark, YARN, Hive, Flume, Sqoop, and MongoDB. Candidates will also be introduced to the Hadoop MapReduce frameworks.

    The syllabus

    Understanding Bigdata and Hadoop

    • Introduction to Big Data
    • Limitations and Solutions of existing Data Analytics Architecture
    • Introduction to Hadoop
    • Hadoop Features
    • Hadoop Ecosystem
    • Hadoop 2.x core components
    • Hadoop Storage: HDFS
    • Hadoop Processing: MapReduce Framework
    • Hadoop Different Distributions.

    YARN

    • YARN (Yet another Resource Negotiator) – Next Gen.
    • Map Reduce
    • What is YARN?
    • Difference between Map Reduce & amp; YARN
    • YARN Architecture
    • Resource Manager Application Master Node Manager.

    Hadoop Architecture and HDFS

    • Hadoop 2.x Cluster Architecture - Federation and High Availability
    • A Typical Production Hadoop Cluster
    • Hadoop Cluster Modes
    • Common Hadoop Shell Commands
    • Single node cluster and Multi node cluster set up Hadoop Administration

    Hadoop Mapreduce Frameworks

    • MapReduce Use Cases
    • Why MapReduce 
    • Hadoop 2.x MapReduce Architecture
    • Hadoop 2.x MapReduce Components 
    • YARN MR Application Execution Flow
    • YARN Workflow
    • Demo on MapReduce
    • Input Splits
    • Relation between Input Splits and HDFS Blocks 
    • MapReduce: Combiner & Partitioner
    • Sequence Input Format
    • Xml file Parsing using MapReduce

    Pig

    • Introduction to Pig
    • MapReduce Vs Pig
    • Pig Use Cases
    • Programming Structure in Pig
    • Pig Running Modes
    • Pig components
    • Pig Execution
    • Pig Latin Program
    • Data Models inPig
    • Pig Data Types
    • Shell and Utility Commands
    • Pig Latin: Relational Operators
    • Group Operator
    • COGROUP Operator
    • Joins and COGROUP
    • Union
    • Diagnostic Operators
    • Specialized joins in Pig
    • Built In Functions (Eval Function, Load and StoreFunctions, Math function, String Function, Date Function, Pig UDF, Piggybank,Parameter Substitution (PIG macros and Pig Parameter substitution)

    Hive

    • Hive Background
    • Hive Use Case
    • About Hive
    • Hive Vs Pig
    • Hive Architecture and Components
    • Metastore in Hive
    • Limitations of Hive
    • Comparison with Traditional Database
    • Hive Data Types and Data Models
    • Partitions and Buckets
    • Hive Tables(Managed Tables and External Tables)
    • Importing Data 
    • Querying Data
    • Managing Outputs
    • Hive Script
    • Hive UDF
    • Retail use case in Hive

    Advanced Hive and HBase

    • Hive QL: Joining Tables
    • Dynamic Partitioning
    • Hive Indexes and views Hive query optimizers
    • Hive: Thrift Server
    • User Defined Functions
    • HBase: Introduction to NoSQL Databases and HBase
    • HBase v/s RDBMS
    • HBase Components
    • HBase Architecture
    • Run Modes & Configuration
    • HBase Cluster Deployment

    Advanced HBase

    • HBase Data Model
    • HBase Shell
    • Data Loading Techniques
    • ZooKeeper Data Model
    • Zookeeper Service
    • Zookeeper 
    • Demos on Bulk Loading
    • Getting and Inserting Data
    • Filters in HBase

    Sqoop

    • Sqoop Architecture 
    • Sqoop Installation 
    • Sqoop Commands(Import, Hive-Import, EVal, Hbase Import, Import All tables,Export) 
    • Connectors to Existing DBs and DW 
    • Hands on Exercise

    Flume

    • Flume Introduction
    • Flume Architecture
    • Flume Master
    • Flume Collector and Flume Agent
    • Flume Configurations
    • Real Time Use Case using Apache Flume

    MongoDB (As part of NoSQL Databases)

    • Need of NoSQL Databases
    • Relational VS Non-Relational Databases
    • Introduction to MongoDB
    • Features of MongoDB
    • Installation of MongoDB
    • Mongo DB Basic operations
    • REAL Time Use Cases on Hadoop &
    • MongoDB Use Case

    Spark

    • Introduction to Apache Spark 
    • Role of Spark in Big data 
    • Who is using Spark 
    • Installation of SparkShell and StandAlone Cluster 
    • Configuration 
    • RDD Operations (Transformations and actions)

    Hadoop Project

    • A demo project using all the components of the above topics

    Practice Test & Interview Questions

    Instructors

    Mr Ankith
    Instructor
    Mindmajix Technologies

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