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Hadoop Spark Training Institutes in Bangalore

Best Hadoop Spark Training in Bangalore

Hadoop Spark Training in Marathahalli & Best Hadoop Spark Training Institutes in Bangalore

Best Hadoop Spark training institute Ecare technologies in Marathahalli, Bangalore, provides real-time and placement oriented Hadoop Spark training in Bangalore. Ecare technologies provide the Best Hadoop Spark training courses in Bangalore. Ecare Hadoop Spark training course content is designed from basics to advanced levels. We have a team of Hadoop Spark experts who are working professionals with hands-on real-time Hadoop Spark projects knowledge, which will give students an edge over other Training Institutes. Hadoop Spark training course content is designed to get the placement in major MNC companies in Bangalore as soon as you complete the Hadoop Spark training course.

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Our Hadoop Spark training courses help to students to get placement immediately after course completion. Our practical, real-time Hadoop Spark project scenarios training helps to work on Hadoop Spark projects. Our Hadoop Spark training program helps every student to achieve their goal in Hadoop Spark career.

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Hadoop Spark Training In Bangalore, Ecare technologies provide regular training classes, Morning Batches, Evening Batches, weekend training classes and fast-track training classes for Hadoop Spark. Ecaretechnologies provides online and Corporate training classes for Hadoop Spark.


Hadoop Spark Training Syllabus in Bangalore

Big Data and Hadoop

1.            What is Big Data?

2.            5 Vs of Big Data

3.            Big Data Architecture, Technologies, Challenge and Big Data Requirements

4.            Big Data Distributed Computing and Complexity

5.            Hadoop

6.            Map Reduce Framework

7.            Hadoop Ecosystem

Big Data and Hadoop Introduction

1.            What is Big Data and Hadoop?

2.            Challenges of Big Data

3.            Traditional approach Vs Hadoop

4.            Hadoop Architecture

5.            Distributed Model

6.            Block structure File System

7.            Technologies supporting Big Data

8.            Replication

9.            Fault Tolerance

10.          Why Hadoop?

11.          Hadoop Eco-System

12.          Use cases of Hadoop

13.          Fundamental Design Principles of Hadoop

14.          Comparison of Hadoop Vs RDBMS

Understand Hadoop Cluster Architecture

1.            Hadoop Cluster and Architecture

2.            5 Daemons

3.            Hands-On Exercise

4.            Typical Workflow

5.            Hands-On Exercise

6.            Writing Files to HDFS

7.            Hands-On Exercise

8.            Reading Files from HDFS

9.            Hands-On Exercise

10.          Rack Awareness

11.          Before Map Reduce

Map Reduce Concepts

1.            Map Reduce Concepts

2.            What is Map Reduce?

3.            Why Map Reduce?

4.            Map Reduce in real world  and Map Reduce Flow

5.            What is Mapper,  Reducer, and Shuffling?

6.            Word Count Problem

7.            Hands-On Exercise

8.            Distributed Word Count Flow and Solution

9.            Log Processing and Map Reduce

10.          Hands-On Exercise

Advanced Map Reduce Concepts

1.            What is Combiner?

2.            What is Partitioner?

3.            What is Counter?

4.            InputFormats/Output Formats

5.            Map Join using MR

6.            Reduce Join using MR

7.            MR Distributed Cache

8.            Using sequence files & images with MR

9.            Planning for Cluster & Hadoop 2.0 Yarn

10.          Configuration of Hadoop

11.          Choosing Right Hadoop Hardware and Software?

12.          Hadoop Log Files?

Hadoop 2.0 and YARN

1.            Hadoop 1.0 Challenges

2.            NN Scalability, SPOF, and HA

3.            Job Tracker Challenges

4.            Hadoop 2.0 New Features

5.            Hadoop 2.0 Cluster Architecture & Federation

6.            Hadoop 2.0 HA

7.            Yarn & Hadoop Ecosystem

8.            Yarn MR Application Flow

PIG

1.            Introduction to Pig

2.            What Is Pig?

3.            Pigâ??s Features & Pig Use Cases

4.            Interacting with Pig

5.            Basic Data Analysis with Pig

6.            Pig Latin Syntax

7.            Loading Data

8.            Simple Data Types

9.            Field Definitions

10.          Data Output

11.          Viewing the Schema

12.          Filtering and Sorting Data

13.          Commonly-Used Functions

14.          Pig for ETL Processing

15.          Processing Complex Data with Pig

16.          Storage Formats

17.          Complex/Nested Data Types

18.          Hands-On Exercise

19.          Grouping

20.          Built-in Functions for Complex Data

21.          Iterating Grouped Data

22.          Multi-Dataset Operations with Pig

23.          Techniques for Combining Data Sets

24.          Joining Data Sets in Pig

25.          Splitting Data Sets

HIVE

1.            Hive Fundamentals and Architecture

2.            Loading and Querying Data in Hive

3.            Hive Architecture and Installation

4.            Comparison with Traditional Database

5.            HiveQL: Data Types, Operators and Functions

6.            Hive Tables, Managed Tables and External Tables

Hadoop Developer Training Outline

 Introduction to Hadoop

 

o             Hadoop Distributed File System

o             Hadoop Architecture

o             MapReduce & HDFS Hadoop Eco Systems

o             Introduction to Pig

o             Introduction to Hive

o             Introduction to HBase

o             Other eco system Map Hadoop Developer

o             Moving the Data into Hadoop

o             Moving The Data out from Hadoop

o             Reading and Writing the files in HDFS using java program

o             The Hadoop Java API for MapReduce o Mapper Class o Reducer Class o Driver Class

o             Writing Basic MapReduce Program In java

o             Understanding the MapReduce Internal Components

o             Hbase MapReduce Program

o             Hive Overview

o             Working with Hive

o             Pig Overview

o             Working with Pig

o             Sqoop Overview

o             Moving the Data from RDBMS to Hadoop

o             Moving the Data from RDBMS to Hbase

o             Moving the Data from RDBMS to Hive

o             Flume Overview

o             Moving The Data from Web server Into Hadoop

o             Real Time Example in Hadoop

o             Apache Log viewer Analysis

 Hadoop Admin Training Outline

o             Big Data Overview

o             Introduction In Hadoop and Hadoop Related Eco System.

o             Choosing Hardware For Hadoop Cluster nodes

o             Apache Hadoop Installation o Standalone Mode o Pseudo Distributed Mode o Fully Distributed Mode

o             Installing Hadoop Eco System and Integrate With Hadoop

o             Zookeeper Installation o Hbase Installation o Hive Installation o Pig Installation o Sqoop Installation o Installing Mahout

o             Horton Works Installation

o             Cloudera Installation

o             Hadoop Commands usage

o             Import the data in HDFS

o             Sample Hadoop Examples (Word count program and Population problem)

o             Monitoring The Hadoop Cluster o Monitoring Hadoop Cluster with Ganglia o Monitoring Hadoop Cluster with Nagios o Monitoring Hadoop Cluster with JMX

o             Hadoop Configuration management Tool

o             Hadoop Benchmarking


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Hadoop Spark Training trainer Profile & Placement

  • More than 10 Years of experience in Hadoop Spark Training
  • Has worked on multiple realtime Hadoop Spark Training
  • Working in a top MNC company in Bangalore
  • Trained 2000+ Students so far in Hadoop Spark Training.
  • Strong Theoretical & Practical Knowledge
  • Certified Professionals


Hadoop Spark Training Placement in Bangalore

  • More than 2000+ students Trained in Hadoop Spark Training
  • 92% percent Placement Record
  • 1000+ Interviews Organized

Hadoop Spark Training batch size in Bangalore


Regular Batch ( Morning, Day time & Evening)

  • Seats Available : 8 (maximum)

Hadoop Spark Training Weekend Training Batch( Saturday, Sunday & Holidays)

  • Seats Available : 8 (maximum)

Hadoop Spark Training Fast Track batch

  • Seats Available : 5 (maximum)

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Hadoop Spark Training in Bangalore - Marathahalli
Ecare Technologies

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based on 6284 ratings.