What is Apache Hadoop ?


Are you having a problem with processing extensive data? Why not go for the Apache Hadoop course!!

This course is for amateur software engineers or businessmen who might want to comprehend the instruments used to fight and examine ample information. Apache Hadoop preparing will assist candidates with understanding the capacity of the executives, Hadoop filesystem, creation, and the board of Hadoop bunch. Students can make this course as their career option as it helps a lot with data information.

Apache Hadoop  Eligibility Criteria


Candidate should meet the following basic criteria for the above mentioned course:

  • Basic knowledge of Linux Administration, Java Programming and Hadoop administration
  • Prior Knowledge of Apache Interest in data management and analysis, including cloud systems and technology.

Apache Hadoop Course Syllabus


Before enrolling into the course, students must have a brief idea on the syllabus. Below mentioned are some of the important topics that are covered in the entire course.

MODULE I – HADOOP BASICS


7 VIDEOS WHICH CONSIST OF

  1. Hadoop Stack Basics
  2. The Apache Framework: Basic Modules
  3. Hadoop Distributed File System (HDFS)
  4. The Hadoop “Zoo”
  5. Hadoop Ecosystem Major Components
  6. Exploring the Cloudera VM: Hands-On Part 1
  7. Exploring the Cloudera VM: Hands-On Part 2

4 READINGS

  1. Apache Hadoop Ecosystem
  2. Lesson 1 Slides (PDF)
  3. Hardware & Software Requirements
  4. Lesson 2 Slides – Cloudera VM Tour

1 PRACTICE EXERCISE

  1. Basic Hadoop Stack

MODULE II – INTRODUCTION TO HADOOP STACK


10 VIDEOS

  1. Overview of the Hadoop Stack
  2. The Hadoop Distributed File System (HDFS) and HDFS
  3. MapReduce Framework and YARN
  4. The Hadoop Execution Environment
  5. YARN, Tez, and Spark
  6. Hadoop Resource Scheduling
  7. Hadoop-Based Applications
  8. Introduction to Apache Pig
  9. Introduction to Apache HIVE
  10. Introduction to Apache HBASE

6 READINGS

  1. Hadoop Basics – Lesson 1 Slides
  2. Lesson 2: Hadoop Execution Environment – Slides
  3. Lesson 3: Hadoop-based Applications Overview – All Slides
  4. Command list for Applications Slide
  5. Tips to handle service connection errors
  6. References for Application

3 PRACTICE EXERCISE

  1. Overview of Hadoop Stack
  2. Hadoop Execution Environment
  3. Hadoop Applications

MODULE III – INTRODUCTION TO HADOOP DISTRIBUTED FILE SYSTEM


9 VIDEOS

  1. Overview of HDFS Architecture
  2. The HDFS Performance Envelope
  3. Read/Write Processes in HDFS
  4. HDFS Tuning Parameters
  5. HDFS Performance and Robustness
  6. Overview of HDFS Access, APIs, and Applications
  7. HDFS Commands
  8. Native Java API for HDFS
  9. REST API for HDFS

5 READINGS

  1. Lesson 1: Introduction to HDFS – Slides
  2. HDFS references
  3. Lesson 2: HDFS Performance and Tuning – Slides
  4. HDFS Access, APIs
  5. Lesson 3: HDFS Access, APIs, Applications – Slides

3 PRACTICE EXERCISES

  1. HDFS Architecture
  2. HDFS performance, tuning, and robustness
  3. Accessing HDFS

MODULE IV – INTRODUCTION TO MAP/ REDUCE


9 VIDEOS

  1. Introduction to Map/Reduce
  2. The Map/Reduce Framework
  3. A MapReduce Example: Wordcount in detail
  4. MapReduce: Intro to Examples and Principles
  5. MapReduce Example: Trending Wordcount
  6. MapReduce Example: Joining Data
  7. MapReduce Example: Vector Multiplication
  8. Computational Costs of Vector Multiplication
  9. MapReduce Summary

3 READINGS

  1. Lesson 1: Introduction to MapReduce – Slides.
  2. A note on debugging map/reduce programs.
  3. Lesson 2: MapReduce Examples and Principles – Slides

1 PRACTICE EXERCISE

  1. Lesson 1 Review

MODULE V – SPARK


10 VIDEOS

  1. Introduction to Apache Spark
  2. Architecture of Spark
  3. Resilient Distributed Datasets
  4. Spark Transformations
  5. Wide Transformations
  6. Directed Acyclic Graph (DAG) Scheduler
  7. Actions in Spark
  8. Memory Caching in Spark
  9. Broadcast Variables
  10. Accumulators

4 READINGS

  1. Setup PySpark on the Cloudera VM
  2. Lesson 1: Intro to Apache Spark – Slides
  3. Lesson 2: RDD and Transformations – Slides
  4. Lesson 3: Scheduling, Actions, Caching – Slides

3 PRACTICE PAPERS

  1. Spark Lesson 1
  2. Spark Lesson 2
  3. Spark Lesson 3

Top Recruiters for Apache Hadoop  


Getting placed in a good company is like a dream come true for every student. Some of the major recruiters who are hiring students from Apache Hadoop are;

  1. Air India
  2. Airtel
  3. BAJAJ Allianz
  4. HCL
  5. Infosys 
  6. Indian Oil
  7. Wipro
  8. Nestle
  9.  Intel
  10. HP 

Colleges/Institute offering Apache Hadoop Courses in India


Below mentioned are some of the colleges and Institutions offering Apache Hadoop courses;or improving your enlisting approach.

American Management and Technology College, Jaro Education.
Total Fees: 39,385 INR | 6 months | Apply Now
Aptech Computer Education, West Mumbai
Total Fees: INR 16,500 | 3 months | Apply Now
Mapping Minds, Delhi
Total Fees: INR 25,000 | 15 weeks | Apply Now
Indian Institute of Hardware Technology Ltd (IIHT), Kalkaji, Delhi
Total Fees: 30,000 INR | 3 months | Apply Now
Manipal Global Academy of Data Science, Bangalore
Total Fees: 15,220 INR | 3 months | Apply Now