Hadoop Developer In Real World

BY
Udemy

Become certified Hadoop developers by learning the functionalities and concepts associated with Apache Hadoop.

Mode

Online

Fees

₹ 7900

Quick Facts

particular details
Medium of instructions English
Mode of learning Self study
Mode of Delivery Video and Text Based

Course overview

The creation and coding of Hadoop applications is the responsibility of Hadoop developers. An open-source framework called Hadoop is used to store and manage big data applications that are run inside of cluster architectures. In essence, a Hadoop developer develops applications to maintain and manage big data for a business. Hadoop Developer In Real World online certification is developed by Hadoop In Real World - Expert Big Data Consultants and is offered by Udemy.

Hadoop Developer In Real World online course involves more than 20.5 hours of extensive learning materials along with 4 articles and 88 downloadable resources which are aimed at the participants who want to acquire the knowledge of the concepts involved with Hadoop and big data to become certified in Hadoop developers. Hadoop Developer In Real World online training covers topics like data analysis, cloud computing, and Cloudera manager and discusses the functionalities of various big data technologies including Flume, Sqoop, YARN, Kafka, AWS, Pig, Hive, and more.

The highlights

  • Certificate of completion
  • Self-paced course
  • 20.5 hours of pre-recorded video content
  • 4 articles 
  • 88 downloadable resources

Program offerings

  • Online course
  • Learning resources
  • 30-day money-back guarantee
  • Unlimited access
  • Accessible on mobile devices and tv

Course and certificate fees

Fees information
₹ 7,900
certificate availability

Yes

certificate providing authority

Udemy

What you will learn

Knowledge of cloud computing Knowledge of kafka Knowledge of big data Knowledge of aws technology

After completing the Hadoop Developer In Real World certification course, participants will acquire a solid understanding of the principles of Hadoop for dealing with big data for data analysis and cloud computing activities. In this Hadoop developer certification, participants will explore the functionalities of various big data tools like Kafka, Flume, Sqoop, Pig, Hive, MapReduce, and YARN as well as will acquire an understanding of the features of cloud services like AWS for configuring Hadoop clusters. In this Hadoop developer course, participants will learn about concepts involved with Cloudera manager, HDFS, Hadoop architecture, HA configuration, single point of failures, join statements, nodes, AVRO, and SequenceFile.

The syllabus

Thank You and Let's Get Started

  • Course Structure
  • Tools & Setup (Windows)
  • Tools & Setup (Linux)

Introduction To Big Data

  • What is Big Data?
  • Understanding Big Data Problem
  • History of Hadoop
  • Test your understanding of Big Data

HDFS

  • HDFS - Why Another Filesystem?
  • Blocks
  • Working With HDFS
  • HDFS - Read & Write
  • HDFS - Read & Write (Program)
  • Test your understanding of HDFS
  • HDFS Assignment

MapReduce

  • Introduction to MapReduce
  • Dissecting MapReduce Components
  • Dissecting MapReduce Program (Part 1)
  • Dissecting MapReduce Program (Part 2)
  • Combiner
  • Counters
  • Facebook - Mutual Friends
  • New York Times - Time Machine
  • Test your understanding of MapReduce
  • MapReduce Assignment

Apache Pig

  • Introduction to Apache Pig
  • Loading & Projecting Datasets
  • Solving a Problem
  • Complex Types
  • Pig Latin - Joins
  • Million Song Dataset (Part 1)
  • Million Song Dataset (Part 2)
  • Page Ranking (Part 1)
  • Page Ranking (Part 2)
  • Page Ranking (Part 3)
  • Test your understanding of Apache Pig
  • Apache Pig Assignment

Apache Hive

  • Introduction to Apache Hive
  • Dissect a Hive Table
  • Loading Hive Tables
  • Simple Selects
  • Managed Table vs. External Table
  • Order By vs. Sort By vs. Cluster By
  • Partitions
  • Buckets
  • Hive QL - Joins
  • Twitter (Part 1)
  • Twitter (Part 2)
  • Test your understanding of Apache Hive
  • Apache Hive Assignment

Hive Window and Analytical Functions

  • Introduction to Hive Window and Analytical functions
  • Kickstarter campaign duplicates and top campaigns
  • Kickstarter campaign bands and user sessions

Architechture

  • HDFS Architechture
  • Secondary Namenode
  • Highly Available Hadoop
  • MRv1 Architechture
  • YARN
  • Test your understanding of Hadoop Architechture

Cluster Setup

  • Vendors & Hosting
  • Cluster Setup (Part 1)
  • Cluster Setup (Part 2)
  • Cluster Setup (Part 3)
  • Amazon EMR
  • Test your understanding of Cluster Setup

Hadoop Administrator In Real World (Preview)

  • Cloudera Manager - Introduction
  • Cloudera Manager - Installation

File Formats

  • Compression
  • Sequence File
  • AVRO
  • File Formats - Pig
  • File Formats - Hive
  • Introduction to RCFile
  • Working with RCFile
  • Introduction to ORC
  • Working with ORC
  • Parquet - Another Columnar Format
  • Avro Schema and It's Importance
  • Schema Evolution in Avro (Part 1)
  • Schema Evolution in Avro (Part 2)
  • Test your understanding of File Formats

Troubleshooting and Optimizations

  • Exploring Logs
  • MRUnit
  • MapReduce Tuning
  • Pig Join Optimizations (Part 1)
  • Pig Join Optimizations (Part 2)
  • Hive Join Optimizations
  • Test your understanding of Troubleshooting & Optimizations

Apache Sqoop

  • Sqoop Imports
  • Sqoop - File Formats
  • Jobs & Incremental Imports
  • Hive - Exports

Apache Flume

  • Introduction to Flume
  • Replication
  • Consolidation & Mutliplexing
  • Streaming Twitter with Flume

Kafka

  • Kafka - The Why & the What?
  • Kafka Concepts
  • Tolerating Failures - Producers & Consumers
  • Tolerating Failures - Brokers
  • Kafka Installation
  • Experiments with Kafka
  • Streaming Meetup with Kafka (Part-1)
  • Streaming Meetup with Kafka (Part-2)
  • Writing production ready Kafka application
  • Schema management with Kafka Schema Registry
  • Schema evolution with Kafka Schema Registry

Bonus

  • Preparing For Hadoop Interviews

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