Elasticsearch 8 and the Elastic Stack: In-Depth and Hands-On

Elasticsearch 8 and the Elastic Stack: In-Depth and Hands-On

by Frank Kane
Released September 2022
Publisher(s): Packt Publishing
ISBN: 9781788995122

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Video description

Elasticsearch 8 is a powerful tool for analyzing big datasets in a matter of milliseconds! It’s an increasingly popular technology for powering search and analytics on big websites, and a valuable skill to have in today’s job market.

The course starts with setting up search indices on an Elasticsearch 8 cluster and querying that data in many ways. Fuzzy searches, partial matches, search-as-you-type, pagination, sorting. Next, you will explore what’s new in Elasticsearch 8 and illustrate all the new syntax requirements of Elasticsearch commands. Elasticsearch isn’t just for search anymore—it has powerful aggregation capabilities for structured data, which allows you to glean new insights from your indexed data. You will learn to bucket and analyze data using Elasticsearch, and visualize it using the Elastic Stack’s web UI, Kibana, and Kibana Lens.

You will learn how to manage operations on your Elastic Stack, monitor your cluster’s health, and perform operational tasks such as scaling up your cluster and doing rolling restarts. We will also spin up Elasticsearch clusters in the cloud using Amazon Opensearch Service and the Elastic Cloud.

By the end of this course, you will develop the Elasticsearch skills needed for searching, analyzing, and visualizing big data.

What You Will Learn

  • Install and configure Elasticsearch 8 on a cluster
  • Find out how to create search indices and mappings
  • Use Logstash to import streaming log data into Elasticsearch
  • Aggregate structured data using buckets and metrics
  • Use Filebeat and Elastic Stack to import streaming data at scale
  • Manage operations on Elasticsearch clusters

Audience

This course is designed for anyone who is looking to learn Elasticsearch to search and analyze big datasets. A basic understanding of web services and REST API is needed to get started with this course.

About The Author

Frank Kane: Frank Kane has spent nine years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers all the time. He holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology and teaches others about big data analysis.

Table of contents

  1. Chapter 1 : Installing and Understanding Elasticsearch
    1. Section1 Introduction
    2. Installing Elasticsearch (Step-by-Step)
    3. Overview of Elasticsearch
    4. Introducing HTTP and RESTful APIs
    5. Elasticsearch Basics: Logical Concepts
    6. Term Frequency/Inverse Document Frequency (TF/IDF)
    7. Using Elasticsearch
    8. What's New in Elasticsearch 8?
    9. How Elasticsearch Scales
    10. Quiz: Elasticsearch Concepts and Architecture
    11. Section 1 Wrap-Up
  2. Chapter 2 : Mapping and Indexing Data
    1. Section 2 Introduction
    2. Connecting to Your Cluster
    3. Introducing the MovieLens Dataset
    4. Analyzers
    5. Import a Single Movie through JavaScript Object Notation/Representational State Transfer (JSON/REST) API
    6. Inserting Many Movies at Once with Bulk API
    7. Updating Data in Elasticsearch
    8. Deleting Data in Elasticsearch
    9. (Exercise) Inserting, Updating, and Deleting a Movie
    10. Dealing with Concurrency
    11. Using Analyzers and Tokenizers
    12. Data Modeling and Parent/Child Relationships - Part 1
    13. Data Modeling and Parent/Child Relationships - Part 2
    14. Flattened Datatype
    15. Dealing with Mapping Extensions
    16. Section 2 Wrap-Up
  3. Chapter 3 : Searching with Elasticsearch
    1. Section 3 Introduction
    2. Query Lite Interface
    3. JavaScript Object Notation (JSON) Search In-Depth
    4. Phrase Matching
    5. (Exercise) Querying in Different Ways
    6. Pagination
    7. Sorting
    8. More with Filters
    9. (Exercise) Using Filters
    10. Fuzzy Queries
    11. Partial Matching
    12. Query-Time Search-As-You-Type
    13. N-Grams - Part 1
    14. N-Grams - Part 2
    15. "Search-As-You-Type" Field Type
    16. Section 3 Wrap-Up
  4. Chapter 4 : Importing Data into Your Index - Big or Small
    1. Section 4 Introduction
    2. Importing Data with a Script
    3. Importing Data with Client Libraries
    4. (Exercise) Importing Data with a Script
    5. Introducing Logstash
    6. Installing Logstash
    7. Running Logstash
    8. Logstash and MySQL - Part 1
    9. Logstash and MySQL - Part 2
    10. Importing Comma Separated Values (CSV) Data with Logstash
    11. Importing JavaScript Object Notation (JSON) Data with Logstash
    12. Logstash and Simple Storage Service (S3)
    13. Parsing and Filtering Logstash with Grok
    14. Logstash Grok Examples for Common Log Formats
    15. Logstash Input Plug-Ins -Part 1: Heartbeat
    16. Logstash Input Plug-Ins -Part 2: Generator Input and Dead Letter Queue
    17. Logstash Input Plug-Ins -Part 3: HTTP Poller
    18. Logstash Input Plug-Ins -Part 4: Twitter
    19. Syslog with Logstash Deep Dive
    20. Elasticsearch and Kafka - Part 1
    21. Elasticsearch and Kafka - Part 2
    22. Elasticsearch and Apache Spark - Part 1
    23. Elasticsearch and Apache Spark - Part 2
    24. (Exercise) Importing Data with Spark
    25. Section 4 Wrap-Up
  5. Chapter 5 : Using Aggregation
    1. Section 5 Introduction
    2. Aggregations, Buckets, and Metrics
    3. Histograms
    4. Time Series
    5. (Exercise) Generating Histogram Data
    6. Nested Aggregations - Part 1
    7. Nested Aggregations - Part 2
    8. Section 5 Wrap-up
  6. Chapter 6 : Using Kibana
    1. Section 6 Introduction
    2. Installing Kibana
    3. Playing with Kibana
    4. (Exercise) Exploring Data with Kibana
    5. Kibana Lens
    6. Kibana Management
    7. Elasticsearch SQL
    8. Using the Kibana Canvas
    9. Elasticsearch and Apache Hadoop
    10. Section 6 Wrap-Up
  7. Chapter 7 : Analyzing Log Data with the Elastic Stack
    1. Section 7 Introduction
    2. Data Frame Transforms
    3. FileBeat and the Elastic Stack Architecture
    4. X-Pack Security
    5. Installing FileBeat
    6. Analyzing Logs with Kibana Dashboards
    7. (Exercise) Log Analysis with Kibana
    8. Section 7 Wrap-up
  8. Chapter 8 : Elasticsearch Operations
    1. Section 8 Introduction
    2. Choosing the Right Number of Shards
    3. Adding Indices as a Scaling Strategy
    4. Index Alias Rotation
    5. Index Lifecycle Management
    6. Choosing Your Cluster's Hardware
    7. Heap Sizing
    8. Monitoring
    9. Troubleshooting Common Issues
    10. Failover in Action - Part 1
    11. Index Design Changes
    12. Snapshots
    13. Snapshots Lifecycle Management
    14. Rolling Restarts
    15. Uptime Monitoring with Heartbeat
    16. Section 8 Wrap-up
  9. Chapter 9 : Elasticsearch in the Cloud
    1. Section 9 Introduction
    2. Amazon Elasticsearch Service - Part 1
    3. Amazon Elasticsearch Service, Part 2
    4. The Elastic Cloud
    5. Section 9 Wrap-Up
  10. Chapter 10 : You Made It!
    1. Wrapping Up

Product information

  • Title: Elasticsearch 8 and the Elastic Stack: In-Depth and Hands-On
  • Author(s): Frank Kane
  • Release date: September 2022
  • Publisher(s): Packt Publishing
  • ISBN: 9781788995122