Elasticsearch 6 and Elastic Stack
In Depth and Hands-on
Frank Kane
  • Course duration: 7h 57m

I've been playing with and using the Elastic Stack for at least 4 years. This video course is by far the most informative, up-to-date and useful resource I've found.

S. Petersen
See it. Do it. Learn it! Packed with 60 engaging lectures in 8 hours of video, this essential liveVideo course will add highly marketable Elasticsearch skills to your toolbox! Elasticsearch 6 and Elastic Stack teaches you how to set up and manage a search and analytics platform using Elasticsearch and Elastic Stack.

Distributed by Manning Publications

This course was created independently by big data expert Frank Kane and is distributed by Manning through our exclusive liveVideo platform.

About the subject

Elasticsearch is an industry standard open source search engine. Built on Apache Lucene, Elasticsearch is lightning-fast, secure, and easy to use! Combine Elasticsearch with the Logstash data processing pipeline and the Kibana data analytics dashboard, and you have the powerful Elastic Stack platform, a complete data storage and analysis platform.

About the video

Elasticsearch 6 and Elastic Stack starts by showing you how to install Elasticsearch 6 on your PC and configure it on a cluster. From there, you’ll learn to bucket and analyze data using Elasticsearch and you’ll monitor your cluster’s health using X-Pack. You’ll set up search indices and query your data using common approaches like fuzzy searches, partial matches, search-as-you-type, and more. This amazing course teaches you to perform rolling restarts, scale up your cluster, and even spin up clusters in the cloud using Amazon Elasticsearch Service and the Elastic Cloud.

With Frank Kane’s practical instruction, you’ll tackle the often-overlooked problem of importing data into an Elasticsearch index. You’ll delve into raw RESTful queries and scripts using Elasticsearch APIs, and you’ll see how Elasticsearch seamlessly integrates with other big data systems like Spark and Kafka. After you’ve mastered Elasticsearch basics, you’ll explore the Elastic Stack. You’ll experience the data processing power of Logstash and pick up data analytics techniques with the interactive Kibana visual dashboard! Every lesson has hands-on examples, so you’ll practice your new search and analysis skills as you go!
Table of Contents detailed table of contents

Installing and Understanding Elasticsearch

Introduction, and installing Elasticsearch

Elasticsearch overview

Using Elasticsearch

Elasticsearch architecture

Quiz: Elasticsearch concepts and architecture

Mapping and indexing data

Connecting to your cluster

Getting to know the Movielens Data Set

Create a mapping for Movielens

Hacking CURL

Import a single movie via JSON/REST

Insert many movies at once

Updating data in Elasticsearch

Deleting data in Elasticsearch

Exercise: insert, update, and delete a fictitious movie

Dealing with concurrency

Using analyzers and tokenizers

Data modeling with Elasticsearch

Searching with Elasticsearch

Using query-string search

Using JSON search

Full-text versus phrase search

Exercise: search for new Star Wars films two different ways



Using filters

Exercise: search for science fiction movies before 1960, sorted by title

Fuzzy queries

Partial matching

N-grams and search as you type

Importing data into your index

Importing data from scripts

Exercise: import movie tags into a new index with a python script

Logstash overview

Installing Logstash

Importing Apache access logs with Logstash

Importing data from MySQL using Logstash

Importing data from AWS S3 using Logstash

Integrating Kafka with Elasticsearch

Integrating Spark and Hadoop with Elasticsearch

Exercise: Import movie ratings from Spark to Elasticsearch


Buckets and metrics


Aggregating time series data

Exercise: When did my site go down?

Nested aggregations

Using Kibana

Installing Kibana

Analyzing Shakespeare with Kibana

Exercise: Find the Shakespeare plays with the most lines

Analyzing log data with the Elastic Stack

The ELK Stack and Elastic Stack

Install, configure, and use Filebeat

Analyzing server logs with Kibana

Exercise: Narrow down the source of 404 errors

Elasticsearch operations

How many shards should I use?

Scaling with new indices

Choosing your hardware

Heap sizing

Monitoring with X-Pack

Practicing failover


Rolling Restarts

Elasticsearch in the cloud

Using Amazon Elasticsearch service

Using Elastic Cloud

You made it!

I made it! Now what?


For tech-minded individuals familiar with web services and REST. Some exposure to Linux and JSON-formatted data would also be beneficial.

What you will learn

  • Create search indices and mappings
  • Search full-text and structured data in several different ways
  • Integrate Elasticsearch with other systems including Spark and Kafka
  • Aggregate structured data using buckets and metrics
  • Import data into Elasticsearch using several different techniques
  • Use Logstash and Kibana to import streaming log data
  • Use Filebeats and the Elastic Stack to import streaming data at scale
  • Manage operations on production Elasticsearch clusters
  • Use cloud-based solutions including Amazon's Elasticsearch Service and Elastic Cloud

About the instructor

Frank Kane holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. He spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to millions of customers every day. Sundog Software, his own company specializing in virtual reality environment technology and teaching others about big data analysis, is his pride and joy.

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