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Course Duration

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  • MapReduce is a licit programming model and an associated implementation for processing and initiating big data sets with a parallel, distributed algorithm on a cluster. In fact, you will find these specific applications scripting applications that can process huge amounts of data across the clusters of in-expensive nodes. Hadoop MapReduce is the processing part of Apache Hadoop. It is also referred as the heart of Hadoop.
  • It is the most preferred data distilling application. Huge establishments like Amazon, Yahoo, Zuventus, etc. are utilizing the MapReduce platform for high volume data processing. In the present scenario, it is one of the most demanding courses in Big Data Hadoop field, and acquiring its accreditation will help you to uplift your career in various ways. And regarding it’s training Croma Campus would be the appropriate place for you.
  • Things you will learn:
    • Here, you will find a wide range of courses belonging from different industries. 

      Along with training, here, you will be able to acquire its prerequisites as well. 

      Our trainers will also give you the flexibility to acquire training via online/offline medium both. 

      We will also assure you 100% placement. 

  • Here, you will receive a detailed sort of training concerning several instances. Along with theoretical training, you will also be given practical training respectively.

MapReduce Certification Training

About-Us-Course

  • Croma Campus is immensely popular because of its exceptional offerings like high-quality training, placement offers. Moreover, it also makes you aware of its latest trends.
    • By enrolling in our certification program, you will get the opportunity to have a strong base knowledge concerning this subject. 

      In fact, our trainers will thoroughly guide you to the main concepts of MapReduce and Big Data, and their implementations. 

      Further, you will be explained the detailed information regarding the MapReduce framework. 

      You will also receive sessions regarding executing non-Java programs. 

      Moreover, utilization of HDFS will also get cleared.

  • By acquiring this valuable accreditation, you will get a decent salary structure right from the beginning.
    • Post acquiring its minute details, you will always stand out differently from your peers. 

      You will receive immense respect from your colleagues, and senior officials. 

      Well, at the beginning your salary package will be around- 2,71,000-3,71,000 respectively, which is eventually good for starters.

      With time and experience, your salary bracket will eventually get increased. 

      Moreover, you will also end up acquiring a higher place in your direction. 

  • Big Data Hadoop is one of the leading fields and has a bright scope ahead as well. Choosing this direction will only give you ample opportunities to acquire the latest facts and features concerning this technology.
    • By acquiring this important accreditation, you will be able to work as a Hadoop Administrator, Hadoop Developer, Machine Learning Engineer, Big Data Architect, and Big Data Consultant respectively. 

      There are different sorts of certifications as well. And our trainers will briefly tell you about that accreditation in detail. 

      By obtaining this accreditation along with higher-level certifications, you will be able to secure a much higher place in an organization. 

      You will also get the chance to lead the team and make business-driven decisions for your company. 

      Moreover, you will also get the opportunity to learn new things. 

  • There are several valid reasons to acquire this accreditation, and one of the significant ones is its high demand, and scope in the coming years.
    • It's quite a cost-effective way. 

      By learning its details, and features, you will be able to secure your applications with a different aspect. 

      Furthermore, you will be able to implement parallel processing respectively. 

      This specific technology is quite easy to handle, and with its simple structure, you will be able to execute your tasks smoothly. 

      By obtaining this accreditation in hand, you will be able to sustain yourself in this field in the long run. 

  • A MapReduce Programmer has to execute a lot of things. If you also aspire to turn into a good MapReduce Programmer, then you should know its duties beforehand.
    • You will have to execute the dataset across Mapper, and Reducer. 

      Your job role will also comprise of executing tasks on the slave node. 

      In fact, you will also have to handle Hadoop Distributed File System effectively. 

      Furthermore, you will also have to solve job requests from the clients. 

      In a way, you will have to understand the functioning of its numerous elements to come up with effective results respectively. 

  • Today many firms are always looking for MapReduce experts that can help them utilize the power of this magnificent programming model/ framework. This is why firms that use this framework for data processing don’t hesitate to give a decent amount of money to MapReduce experts who can help them use this framework without any difficulty.
  • Top hiring companies for MapReduce professionals:
    • Impetus, Capgemini, TCS, Accenture, etc., are the top-most companies hiring skilled candidates. 

      Moreover, by graduating from our institution, you will be able to get settled in this direction easily. 

      In fact, you will end up grabbing a good decent salary package as well. 

      Here, you will also get the chance to obtain hidden facts concerning this subject. 

      Your every query will also get solved. 

      You will imbibe some latest trends, and features as well. 

  • Once you complete the MapReduce certification training program, you will become proficient in working with this phenomenal software framework/programming model. Furthermore, you will get a MapReduce training completion certificate. This will help you stand out from the rest of the candidates in front of recruiters and help you quickly get a job as a MapReduce expert/programmer in a good company.
  • Advantages of getting certification:
    • You will find our every accreditation being extensively acknowledged in the industry. 

      Apart from technical courses, here at Croma Campus, you will get 140+ courses belonging to different sections. 

      Here, our trainers will not only impart information but will enhance your communication skills as well. 

      Our trainers will also make you aware of its relevant higher-level accreditation also. 

      By obtaining this certification, you will see positive growth in your career graph. 

Why you should choose MapReduce Programmer certification?

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Plenary for MapReduce Certification Training

TrackWeek DaysWeekendsFast Track
Course Duration 40-45 Days 7 Weekends 8 Days
Hours 1 Hrs. Per Day 2 Hrs. Per Day 6+ Hrs. Per Day
Training ModeClassroom/OnlineClassroom/OnlineClassroom/Online
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CURRICULUM & PROJECTS

MapReduce Certification Training

  • Master various popular Hadoop Frameworks and make yourself stand out in the IT and the Big Data space.
  • List of Popular Hadoop Frameworks covered in the course:
    • Apache PIG Framework

      Apache Spark with Scala Framework

      Apache HIVE Framework

      Apache SQOOP Framework

      Apache Hbase Framework

      Apache Flume Framework

      Apache Drill Framework

      Apache Kafka Framework

      Apache Storm Framework

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  • Pig is a high-level platform for creating MapReduce programs used with Hadoop. The language for this platform is called Pig Latin. In this course we will go through the PIG data flow platform and the language used by PIG tool.
  • Things you will learn:
    • Introduction

      PIG Architecture

      Data Models, Operators, and Streaming in PIG

      Functions in PIG

      Advanced Concepts in PIG

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  • Introduction
    • Big Data Overview

      Apache Hadoop Overview

      Hadoop Distribution File System

      Hadoop MapReduce Overview

      Introduction to PIG

      Prerequisites for Apache PIG

      Exploring use cases for PIG

      History of Apache PIG

      Why you need PIG

      Significance of PIG

      PIG over MapReduce

      When PIG suits the most

      When to avoid PIG

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  • PIG Architecture
    • PIG Latin Language

      Running PIG in Different Modes

      PIG Architecture

      GRUNT Shell

      PIG Latin Statements

      Running Pig Scripts

      Utility Commands

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  • Data Models, Operators, and Streaming in PIG
    • PIG Data Model- Scalar Data type

      PIG Data Model - Complex Data Type

      Arithmetic Operators

      Comparison Operators

      Cast Operators

      Type Construction Operator

      Relational Operators

      Loading and Storing Operators

      Filtering Operators

      Filtering Operators-Pig Streaming with Python

      Grouping and Joining Operators-

      Sorting Operator

      Combining and Splitting Operators

      Diagnostic Operators

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  • Functions in PIG
    • Eval Functions

      Load and Store Functions

      Tuple and Bag Functions

      String Functions

      Math Function

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  • Advanced Concepts in PIG
    • File compression in PIG

      Intermediate Compression

      Pig Unit Testing

      Embedded PIG in JAVA

      Pig Macros

      Import Macros

      Parameter Substitutions

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  • Things you will learn:
    • Introduction

      Scala

      Using Resilient Distributed Datasets

      Spark SQL, Data Frames, and Data Sets

      Running Spark on a cluster

      Machine Learning with Spark ML

      Spark Streaming

      Graph X

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  • Introduction
    • Big Data Overview

      Apache Hadoop Overview

      Hadoop Distribution File System

      Hadoop MapReduce Overview

      Introduction to IntelliJ and Scala

      Installing IntelliJ and Scala

      Apache Spark Overview

      What’s new in Apache Spark 3

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  • Using Resilient Distributed Datasets
    • Scala Basics

      Flow control in Scala

      Functions in Scala

      Data Structures in Scala

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  • Using Resilient Distributed Datasets
    • The Resilient Distributed Dataset

      Ratings Histogram Example

      Key / Value RDD's, and the Average Friends by Age example

      Filtering RDD's, and the Minimum Temperature by Location Example

      Check Your Results and Implementation Against Mine

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  • Spark SQL, Data Frames, and Data Sets
    • Introduction to Spark SQL

      What are Data Frames

      What are Data Sets

      Item-Based Collaborative Filtering in Spark, cache (), and persist ()

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  • Running Spark on a cluster
    • What is a Cluster

      Cluster management in Hadoop

      Introducing Amazing Elastic MapReduce

      Partitioning Concepts

      Troubleshooting and managing dependencies

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  • Machine Learning with Spark ML
    • Introducing MLLib

      Using MLLib

      Linear Regression with MLLib

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  • Spark Streaming
    • Spark Streaming

      The DStream API for Spark Streaming

      Structured Streaming

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  • Graph X
    • What is Graph X

      About Pregel

      Breadth-First-Search with Pregel

      Using Pregel API with Spark API

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  • Things you will learn:
    • Introduction

      Installing and Configuring HIVE

      Working on HIVE

      HIVE Implementation

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  • Introduction
    • Big Data Overview

      Hadoop Overview

      What is a Hadoop Framework

      Types of Hadoop Frameworks

      What is Hive

      Motivation Behind the Tool

      Hive use cases

      Hive Architecture

      Different Modes of HIVE

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  • Installing and Configuring HIVE
    • Downloading, installing, and configuring HIVE

      Hive Shell Commands

      Different configuration properties in HIVE

      Beeswax

      Installing and configuring MySQL Database

      Installing Hive Server

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  • Working on HIVE
    • Databases in Hive

      Datatypes in Hive

      Schema on Read

      Schema on Write

      Download Datasets

      Internal Tables

      External Tables

      Partition in HIVE

      Bucketing in HIVE

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  • HIVE Implementation
    • Hive in Real Time Projects

      Auditing in Hive

      Troubleshooting Infra issues in Hive

      Troubleshooting User issues in Hive

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  • Things you will learn:
    • Hadoop Overview

      Sqoop Overview

      Sqoop Import

      Sqoop Export

      Career Guidance and Roadmap

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  • Hadoop Overview
    • Course overview

      Big Data Overview

      Hadoop Overview

      HDFS

      YARN Cluster Overview

      Cluster Setup on Google Cloud

      Environment Update

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  • Sqoop Overvi
    • Sqoop Introduction

      Why Sqoop

      Sqoop Features

      Flume vs Sqoop

      Sqoop Architecture & Working

      Sqoop Commands.

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  • Sqoop Import
    • Managing Target Directories

      Working with Parquet File Format

      Working with Avro File Format

      Working with Different Compressions

      Conditional Imports

      Split-by and Boundary Queries

      Field delimiters

      Incremental Appends

      Sqoop Hive Import

      Sqoop List Tables/Database

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  • Sqoop Export
    • Export from HDFS to MySQL

      Export from Hive to MySQL

      Export Avro Compressed to MySQL

      Sqoop with Airflow

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  • Career Guidance and Roadmap
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  • Things you will learn:
    • Hadoop Overview

      No SQL Databases HBase

      Administration in HBASE

      Troubleshooting in HBASE

      Tuning in HBASE

      Apache HBase Operations Continuity

      Apache HBASE Ecosystem

      Career Guidance and Roadmap

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  • Hadoop Overview
    • Course overview

      Big Data Overview

      Hadoop Overview

      HDFS

      Hadoop Ecosystem

      What is a Hadoop Framework

      Types of Hadoop frameworks

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  • No SQL Databases HBase
    • NoSQL Databases HBase

      NoSQL Introduction

      HBase Overview

      HBase Architecture

      Data Model

      Connecting to HBase

      HBase Shell

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  • Administration in HBASE
    • Introduction

      Learn and Understand HBase Fault Tolerance

      Hardware Recommendations

      Software Recommendations

      HBase Deployment at Scale

      Installation with Cloudera Manager

      Basic Static Configuration

      Rolling Restarts and Upgrades

      Interacting with HBase

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  • Troubleshooting in HBASE
    • Introduction

      Troubleshooting Distributed Clusters

      Learn How to Use the HBase UI

      Learn How to Use the Metrics

      Learn How to Use the Logs

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  • Tuning in HBASE
    • Introduction

      Generating Load & Load Test Tool

      Generating With YCSB

      Region Tuning

      Table Storage Tuning

      Memory Tuning

      Tuning with Failures

      Tuning for Modern Hardware

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  • Apache HBase Operations Continuity
    • Introduction

      Corruption: hbck

      Corruption: Other Tools

      Security

      Security Demo

      Snapshots

      Import, Export and Copy Table

      Cluster Replication

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  • Apache HBASE Ecosystem
    • Introduction

      Hue

      HBase With Apache Phoenix’

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  • Career Guidance and Roadmap
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  • Things you will learn:
    • Apache Flume Overview

      Setting up Agents

      Configuring A Multi Agent Flow

      Flume Sinks

      Flume Channels

      Flume Sink Processors

      Flume Interceptors

      Security

      Career Guidance and Roadmap

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  • Overview
    • Course overview

      Big Data Overview

      Hadoop Overview

      HDFS

      Hadoop Ecosystem

      What is a Hadoop Framework

      Types of Hadoop frameworks

      Flume Overview

      Architecture

      Data flow mode

      Reliability and Recoverability

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  • Setting up Agents
    • Setting up an individual agent

      Configuring individual components

      Wiring the pieces together

      Data ingestion

      Executing Commands

      Network streams

      Setting Multi-Agent Flow

      Consolidation

      Multiplexing the flow

      Configuration

      Defining the flow

      Configuring individual components

      Adding multiple flows in an agent

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  • Configuring A Multi Agent Flow
    • Fan out flow

      Flume Sources

      Avro Source, Exec Source

      NetCat Source

      Sequence Generator Source

      Syslog Sources

      Syslog TCP Source

      Syslog UDP Source

      Legacy Sources

      Avro Legacy Source

      Thrift Legacy Source

      Custom Source

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  • Flume Sinks
    • HDFS Sink

      Logger Sink

      Avro Sink

      IRC Sink

      File Roll Sink

      Null Sink

      HbaseSinks

      HbaseSink

      AsyncHBaseSink

      Custom Sink

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  • Flume Channels
    • Memory Channel

      JDBC Channel

      Recoverable Memory Channel

      File Channel, Pseudo Transaction Channel

      Custom Channel

      Flume Channel Selectors

      Replicating Channel Selector

      Multiplexing Channel Selector

      Custom Channel Selector

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  • Flume Sink Processors
    • Default Sink Processor

      Failover Sink Processor

      Load balancing Sink Processor

      Custom Sink Processor

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  • Flume Interceptors
    • Timestamp Interceptor

      Host Interceptor

      Flume Properties

      Property

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  • Security
    • Monitoring

      Troubleshooting

      Handling agent failures

      Compatibility

      HDFS

      AVRO

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  • Career Guidance and Roadmap
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  • Things you will learn:
    • Apache Drill Overview

      Installing & Configuring Drill

      Querying Simple Delimited Data

      Configuration Options

      Understanding Data Types and Functions in Drill

      Working with Dates and Times in Drill

      Analyzing Nested Data with Drill

      Other Data Types

      Connecting Multiple Data Sources and programming languages

      Career Guidance and Roadmap

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  • Overview
    • Course overview

      Big Data Overview

      Hadoop Overview

      HDFS

      Hadoop Ecosystem

      What is a Hadoop Framework

      Types of Hadoop frameworks

      Drill Overview

      What does Drill do

      How does Drill work

      Kinds of data which can be queried with Drill

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  • Installing & Configuring Drill
    • Comparison of embedded and distributed modes

      Introducing and configuring workspaces

      Demonstrate Drill’s various interfaces

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  • Querying Simple Delimited Data
    • SQL fundamentals

      Querying a simple CSV file

      Arrays in Drill

      Accessing columns in Arrays

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  • Configuration Options
    • Extracting headers from csv files

      Changing delimiter characters

      Specifying options in a query

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  • Understanding Data Types and Functions in Drill
    • Overview of Drill Data Types

      Converting Strings to Numeric Data Types

      Complex Conversions

      Windowing functions

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  • Working with Dates and Times in Drill
    • Understanding dates and times in Drill

      Converting strings to dates

      Reformatting dates

      Intervals and date/time arithmetic in Drill

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  • Analyzing Nested Data with Drill
    • Issues querying nested data with Drill

      Maps and Arrays in Drill

      Querying deeply nested data in Drill

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  • Other Data Types
    • Log files

      HTTPD

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+ More Lessons

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FAQ's

It basically counts the words in each document (map phase), while in the reduce phase it accumulates the data as per the document spanning the entire gathering. Eventually, during the map phase, the input data is divided into splits for analysis by map tasks executing in parallel across the Hadoop framework.

NameNode in Hadoop refers to the "node", where Hadoop stores all the file location information in HDFS (Hadoop Distributed File System) securely. If you want to acquire its detailed analysis, then you should get started with its professional course.

Yes, it's pretty much in demand, and in the coming years as well, it will remain consistently in use. So, if you possess your interest in this line, then you should acquire its accreditation, and make a career out of it.

Yes, we will provide you with the study material. In fact, you can also use our LMS portal and get extra notes, and class recordings as well.

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