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Apache Druid for Data Engineers (Hands-On)

person icon Bigdata Engineer

4.4

Apache Druid for Data Engineers (Hands-On)

Learn everything about Apache Druid a modern real-time analytics database.

updated on icon Updated on Jul, 2024

language icon Language - English

person icon Bigdata Engineer

category icon Databases,Big Data

Lectures -43

Resources -3

Duration -2 hours

4.4

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Course Description

Druid is a high-performance, real-time analytics database that delivers sub-second queries on streaming and batch data at scale and under load.

Apache Druid is a real-time analytics database designed for fast slice-and-dice analytics ("OLAP" queries) on large data sets. Most often, Druid powers use cases where real-time ingestion, fast query performance, and high uptime are important.

Druid is commonly used as the database backend for GUIs of analytical applications, or for highly-concurrent APIs that need fast aggregations. Druid works best with event-oriented data.


One of the most valuable technology skills is the ability to Real-time analytics databases handle analytics on large amounts of data by optimizing resources to enable compute-heavy workloads, and this course is specifically designed to bring you up to speed on one of the best technologies for this task, Apache Duid! The top technology companies like Google, Facebook, Netflix, Airbnb, Amazon, NASA, and more are all using Apache Druid!


Apache Druid Essentials: Unleashing Real-time Analytics and Scalable Data Exploration

Unlock the potential of real-time analytics and scalable data exploration with our comprehensive Apache Druid Essentials course. In this dynamic program, participants will delve into the world of Apache Druid, an open-source, high-performance analytics database designed for fast query response and seamless scalability.


Key Learning Objectives:

  • Introduction to Course

  • Real-time Analytics Databases

  • What is Apache Druid?

  • Key Features of Druid

  • Technology

  • Use cases

  • When to use Druid

  • When not to use Druid

  • List of Company using Apache Druid

  • Installation of Apache Druid

  • Start up Druid services

  • Open the web console

  • Load data

  • Query data

  • Overview of the Druid Web Console

  • Architecture of Druid

  • Druid Servers

  • External Dependencies

  • Storage Design

  • Datasources and Segments

  • Segment Identifiers

  • Segments

  • Introduction to Segments

  • Segment File Structure

  • Data Loading in Druid

  • Load Data from Local Files

  • Load Data from URI

  • Load Data from Kafka (Prerequisite Introduction to Kafka)

  • Installing Single Node Kafka Cluster

  • Change the following to avoid Zookeeper Issue conflict

  • Load Data from Kafka 

  • Query Data Explain Plan

  • Aggregate data with rollup

  • Frequently Asked Questions


Goals

  • Understanding of basic architecture of Apache Druid
  • Installing and Configuring Apache Druid
  • Apache Druid Design, Ingestion, Data management, Querying
  • Frequently asked Questions

Prerequisites

  • Basic knowledge of SQL is appreciated but if you don't have any knowledge on Database management its fine.
  • Linux as Operating System Required
  • 8 GB RAM is required
Apache Druid for Data Engineers (Hands-On)

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction
9 Lectures
  • play icon Introduction to Course 08:57 08:57
  • play icon Real-time Analytics Databases 01:21 01:21
  • play icon What is Apache Druid? 02:15 02:15
  • play icon Key Features of Druid 05:18 05:18
  • play icon Technology 09:57 09:57
  • play icon Use cases 10:32 10:32
  • play icon When to use Druid 02:01 02:01
  • play icon When not to use Druid 01:21 01:21
  • play icon List of Company using Apache Druid 03:44 03:44
Installation of Apache Druid
7 Lectures
Tutorialspoint
Architecture of Druid
5 Lectures
Tutorialspoint
Storage Design
2 Lectures
Tutorialspoint
Segments
2 Lectures
Tutorialspoint
Data Loading in Druid
9 Lectures
Tutorialspoint
Frequently Asked Questions
9 Lectures
Tutorialspoint

Instructor Details

Bigdata Engineer

Bigdata Engineer

I am Solution Architect with 12+ year’s of experience in Banking, Telecommunication and Financial Services industry across a diverse range of roles in Credit Card, Payments, Data Warehouse and Data Center programmes

My role as Bigdata and Cloud Architect to work as part of Bigdata team to provide Software Solution.

Responsibilities includes,

- Support all Hadoop related issues
- Benchmark existing systems, Analyse existing system challenges/bottlenecks and Propose right solutions to eliminate them based on various Big Data technologies
- Analyse and Define pros and cons of various technologies and platforms
- Define use cases, solutions and recommendations
- Define Big Data strategy
- Perform detailed analysis of business problems and technical environments
- Define pragmatic Big Data solution based on customer requirements analysis
- Define pragmatic Big Data Cluster recommendations
- Educate customers on various Big Data technologies to help them understand pros and cons of Big Data
- Data Governance
- Build Tools to improve developer productivity and implement standard practices

I am sure the knowledge in these courses can give you extra power to win in life.

All the best!!

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