Prerequisites for Big data certification

Before you start proceeding with this tutorial, we will assume that you have some prior exposure to Core Java, database concepts, and Linux operating system flavors.

Syllabus for big data certification in Bangalore

Module 1: Hadoop Architecture

Learning Objective: In this module, you will understand what is Big Data, What are its limitations of the existing solutions for Big Data problem; How Hadoop solves the Big Data problem, What are the common Hadoop ecosystem components, Hadoop Architecture, HDFS and Map Reduce Framework, and Anatomy of File Write and Read.

Topics,

Hadoop Cluster Architecture

Hadoop Cluster Mods

Multi-Node Hadoop Cluster

A Typical Production Hadoop Cluster

Map Reduce Job execution

Common Hadoop Shell Commands

Data Loading Technique: Hadoop Copy Commands

Hadoop Project: Data Loading

Hadoop Cluster Architecture

Module 2: Hadoop Cluster Configuration and Data Loading

Learning Objective: In this module, you will learn the Hadoop Cluster Architecture and Setup, Important Configuration in Hadoop Cluster and Data Loading Techniques.

Topics,

Hadoop 2.x Cluster Architecture

Federation and High Availability Architecture

Federation and High Availability Architecture Typical Production Hadoop Cluster

Hadoop Cluster Modes

Common Hadoop Shell Commands

Hadoop 2.x Configuration Files

Single Node Cluster & Multi-Node Cluster set up

Basic Hadoop Administration

Module 3: Hadoop Multiple node cluster and Architecture

Learning Objective: This module will help you understand multiple Hadoop server roles such as Name node & Data node, and Map Reduce data processing. You will also understand the Hadoop 1.0 cluster setup and configuration, steps in setting up Hadoop Clients using Hadoop 1.0, and important Hadoop configuration files and parameters.

Topics,

Hadoop Installation and Initial Configuration

Deploying Hadoop in the fully-distributed mode

Deploying a multi-node Hadoop cluster

Installing Hadoop Clients

Hadoop server roles and their usage

Rack Awareness

Anatomy of Write and Read

Replication Pipeline

Data Processing

Module 4: Backup, Monitoring, Recovery, and Maintenance

Learning Objective: In this module, you will understand all the regular Cluster Administration tasks such as adding and removing data nodes, name node recovery, configuring backup and recovery in Hadoop, Diagnosing the node failure in the cluster, Hadoop upgrade, etc.

Topics,

Setting up Hadoop Backup

White list and Blacklist data nodes in the cluster

Setup quotas, upgrade Hadoop cluster

Copy data across clusters using distcp

Diagnostics and Recovery

Cluster Maintenance

Configure rack awareness

Module 5: Flume (Dataset and Analysis)

Learning Objective: Flume is a standard, simple, robust, flexible, and extensible tool for data ingestion from various data producers (webservers) into Hadoop.

Topics,

What is Flume?

Why Flume

Importing Data using Flume

Twitter Data Analysis using hive

Module 6: PIG (Analytics using Pig) & PIG LATIN

Learning Objective: In this module, we will learn about analytics with PIG. About Pig Latin scripting, complex data type, different cases to work with PIG. Execution environments, operation & transformation.

Topics,

Execution Types

Grunt Shell

Pig Latin

Data Processing

Schema on reading Primitive data types and complex data types and complex data types

Tuples Schema

Tuples Schema BAG Schema and MAP Schema

Loading and storing

Validations in PIG, Typecasting in PIG

Filtering, Grouping & Joining, Debugging commands (Illustrate and Explain)

Working with function

Working with function Types of JOINS in pig and Replicated join in detail

SPLITS and Multi query execution

Error Handling

FLATTEN and ORDER BY parameter

Nested for each

How to LOAD and WRITE JSON data from PIG

Piggy Bank

Hands-on exercise

Module 7: Sqoop (Real-world dataset and analysis)

Learning Objective: This module will cover Import & Export Data from RDBMS (MySql, Oracle) to HDFS & Vice Versa

Topics,

What is Sqoop

Why Sqoop

Importing and exporting data using sqoop

Provisioning Hive Metastore

Populating HBase tables

SqoopConnectors

What are the features of the scoop

Multiple cases with HBase using client

What are the performance benchmarks in our cluster for the scoop

Module 8: HBase and Zookeeper

Learning Objectives: This module will cover advance HBase concepts. You will also learn what Zookeeper is all about, how I help in monitoring a cluster, why HBase uses zookerper and how to build an application with zookeeper.

Topics,

The Zookeeper Service: Data Model

Operations

Implementations

Consistency

Sessions

States

Module 9: Hadoop 2.0, YARN, MRv2

Learning Objective: in this module, you will understand the newly added features in Hadoop 2.0, namely MRv2, Name node High Availability, HDFS Federation, and support for Windows, etc.

Topics,

Hadoop 2.0 New Feature: Name Node High Availability

HDFS Federation

MRv2

YARN

Running MRv1 in YARN

Upgrade your existing MRv1 to MRv2

Module 10: Map-Reduce Basics and Implementation

This module, will work on Map-Reduce Framework. How Map Reduce implements on Data which is stored in HDFS. Know about input split, input format & output format. Overall Map Reduce process & different stages to process the data.

Topics

Map Reduce Concepts

Mapper Reducer

Driver

Record Reader

Input Split (Input Format (Input Split and Records, Text Input, Binary Input, Multiple Input

Overview of InputFileFormat

Hadoop Project: Map-Reduce Programming

Module 11: Hive and HiveQL

In this module, we will discuss a data warehouse package that analysis structure data. About Hive installation and loading data. Storing Data in different tables.

Topics,

Hive Services and Hive Shell

Hive Server and Hive Web Interface (HWI)

Meta Store

Hive QL

OLTP vs. OLAP

Working with Tables

Primitive data types and complex data types

Working with Partitions

User-Defined Functions

Hive Bucketed Table and Sampling

External partitioned tables, Map the data to the partition in the table

Writing the output of one query to another table, multiple inserts

Differences between ORDER BY, DISTRIBUTE BY and SORT BY

Bucketing and Sorted Bucketing with Dynamic

RC File, ORC, SerDe: Regex

MAPSIDE JOINS

INDEXES and VIEWS

Compression on Hive table and Migrating Hive Table

How to enable update in HIVE

Log Analysis on Hive

Access HBase tables using Hive

Hands-on Exercise

Module 12: Oozie

Learning Objective: Apache Oozie is the tool in which all sorts of programs can be pipelined in the desired order to work in Hadoop’s distributed environment. Oozie also provides a mechanism to run the job at a given schedule.

Topics:

What is Oozie?

Architecture

Kinds of Oozie Jobs

Configuration Oozie Workflow

Developing & Running an Oozie Workflow (Map Reduce, Hive, Pig, Sqoop)

Kinds of Nodes

Module 13: Spark

Learning Objectives: This module includes Apache Spark Architecture, How to use Spark with Scala and How to deploy Spark projects to the cloud Machine Learning with Spark. Spark is a unique framework for big data analytics which gives one unique integrated API by developers for the purpose of data scientists and analysts to perform separate tasks.

Topics,

Spark Introduction

Architecture

Functional Programming

Collections

Spark Streaming

Spark SQL

Spark MLLib

Certification Course For Big Data In Bangalore

Get Ready To Learn From The Best

We are providing the most comprehensive big data certification course for all. If you are a tech enthusiast, you would be delighted to join our program as you will be able to get the right knowledge about your skills as we have courses for novice and advanced learners. If you are looking for a place that will help you hone your skills to becoming a Big Data developer, join our platform and be the best version.

Professional Guidance

Our course has been designed by professionals who have more than 10 years of experience. With the knowledge that you get from, of course, you will be able to ace at your work and rise to the top.

How Does The Training Work?

You will be able to interact with the professional trainers on one on one basis. We understand that everyone can’t attend the class at the same time; that is why we have created flexible timings. We keep our students always in mind when creating the course, and that is why you will find that this is the most effective plan. Without the program, you are not only getting the classes but also free access to our YouTube channel dedicated to our learners. I shall also enjoy access to our LMS platform.

Don’t Wait Any Longer

As we all know, the early bird catches the worm, enroll with us asap. Get the benefits of our certification course and see the changes for yourself. You will surely not get a better platform.

What are you waiting for Step into the Nearest Hub of Our corporate Offices are Today and Get the Free Demo Section with us? Doesn’t Just Dream about the Big Data Developer Achieve Your Dreams with our best Big Data Training institute in Bangalore.