Elasticsearch 6 and Elastic Stack - In Depth and Hands On!

4.4 (2279)
MOOC
Payment
Learning paid
Language
English
Duration
8 hours course
Course by Udemy
What will you learn?
Install and configure Elasticsearch 6 on a cluster
Create search indices and mappings
Search full-text and structured data in several different ways
Import data into Elasticsearch using several different techniques
Integrate Elasticsearch with other systems, such as Spark, Kafka, relational databases, S3, and more
Aggregate structured data using buckets and metrics
Use Logstash and the "ELK stack" to import streaming log data into Elasticsearch
Use Filebeats and the Elastic Stack to import streaming data at scale
Analyze and visualize data in Elasticsearch using Kibana
Manage operations on production Elasticsearch clusters
Use cloud-based solutions including Amazon's Elasticsearch Service and Elastic Cloud
About the course

NOTE: A NEW VERSION OF THIS COURSE FOR ELASTICSEARCH 7 IS AVAILABLE. You should only enroll in this if you need to learn Elasticsearch 6 specifically. If that's you, read on!

Elasticsearch is a powerful tool not only for powering search on big websites, but also for analyzing big data sets in a matter of milliseconds! It's an increasingly popular technology, and a valuable skill to have in today's job market. This comprehensive course covers it all, from installation to operations, with 60 lectures including 8 hours of video.

We'll cover setting up search indices on an Elasticsearch 6 cluster (if you need Elasticsearch 5 - we have another course on that), and querying that data in many different ways. Fuzzy searches, partial matches, search-as-you-type, pagination, sorting - you name it. And it's not just theory, every lesson has hands-on examples where you'll practice each skill using a virtual machine running Elasticsearch on your own PC.

We cover, in depth, the often-overlooked problem of importing data into an Elasticsearch index. Whether it's via raw RESTful queries, scripts using Elasticsearch API's, or integration with other "big data" systems like Spark and Kafka - you'll see many ways to get Elasticsearch started from large, existing data sets at scale. We'll also stream data into Elasticsearch using Logstash and Filebeat - commonly referred to as the "ELK Stack" (Elasticsearch / Logstash / Kibana) or the "Elastic Stack".

Elasticsearch isn't just for search anymore - it has powerful aggregation capabilities for structured data. We'll bucket and analyze data using Elasticsearch, and visualize it using the Elastic Stack's web UI, Kibana.

You'll learn how to manage operations on your Elastic Stack, using X-Pack to monitor your cluster's health, and how to perform operational tasks like scaling up your cluster, and doing rolling restarts. We'll also spin up Elasticsearch clusters in the cloud using Amazon Elasticsearch Service and the Elastic Cloud.

Elasticsearch is positioning itself to be a much faster alternative to Hadoop, Spark, and Flink for many common data analysis requirements. It's an important tool to understand, and it's easy to use! Dive in with me and I'll show you what it's all about.

Program
Installing and Understanding Elasticsearch
We'll cover the main components of the Elastic Stack and take a look at Elasticsearch's architecture and main concepts. And, we'll actually install Elasticsearch on your own PC and see if it works!
Udemy 101: Getting the Most From This Course
Installing Elasticsearch [Step by Step]
We'll talk about why Elasticsearch is important and what you can expect from this course. Then, we'll install a virtual Ubuntu machine right on your own desktop PC, install Elasticsearch on it, and search the complete works of William Shakespeare!
Elasticsearch Overview
Let's look at the components of the Elastic Stack from a 30,000-foot level, and see how they all fit together.
Intro to HTTP and RESTful API's
Elasticsearch exposes a RESTful API, and we communicate with Elasticsearch using nothing but standard HTTPrequests and responses. Let's cover the basics of how that works.
Using Elasticsearch
We'll cover the logical concepts of Elasticsearch, how indices work, and different ways to interact with Elasticsearch.
Elasticsearch Architecture
Let's talk about how Elasticsearch scales horizontally on a cluster, using primary and replica shards.
Quiz: Elasticsearch Concepts and Architecture
Quiz time!Let's see what you learned about Elasticsearch at a conceptual level.
Mapping and Indexing Data
Create new search indices for structured and unstructured data, insert / update / delete documents, handle concurrency issues, and model relational data.
Connecting to your Cluster
We'll walk though setting up SSH on your server, and how to connect to it from your desktop.
Getting to Know the Movielens Data Set
The Movielens dataset will be used throughout the course; let's just familiarize ourselves with it.
Create a Mapping for MovieLens
We'll define a mapping, or a schema, in Elasticsearch for our movie data prior to importing it.
Requirements
  • You need access to a Windows, Mac, or Ubuntu PC with 20GB of free disk space
  • You should have some familiarity with web services and REST
  • Some familiarity with Linux will be helpful
  • Exposure to JSON-formatted data will help
Lecturers
Sundog Education by Frank Kane
Sundog Education by Frank Kane
Founder, Sundog Education. Machine Learning Pro
Frank Kane
Frank Kane
Founder, Sundog Education
Platform
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Udemy courses are suited to professional development. The platform is organized in such a way that it is experts themselves that decide the topic and when the course will start. All supporting documents are made available to you for lifetime access. On this platform, you can find a course on about any subject, and that is no exaggeration – from a tutorial on how to ride a motorcycle, to managing the financial markets. The language and the course format are established by the teacher. This is why it is important to read the information about the course carefully before parting with any money.
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