Elasticsearch Queries In Practice
What you'll learn
- Elasticsearch Query DSL & Search API best practices
- Distributed search architecture & basic terms
- How to tune-up and analyze queries
- How to customize routing and scoring
- How to do highlighting, suggestions, spell corrections
- How to design effective notifications with Percolate Query
- How to analyze and aggregate data using aggregations
- How to use query templates
- No programming nor administrative experience needed
- Basic HTTP and RESTful API experience is fine enough
- Access to any running Elasticsearch/Kibana deployment is optional (course contains simple installation guide)
This course will guide you how to properly and effectively use Elasticsearch Query DSL (Domain Specific Language) based on JSON to define queries. Additionally I present most commonly used Search APIs that will help you fully understand how Elasticsearch works and how to use it to build modern search applications, like Google, Bing, Yahoo!, DuckDuckGo etc. Course contains a lot of practical knowledge, examples and hands-on lectures.
If you are a beginner, don't worry, course guides you from very generic concept of lucene inverted index and role of search engines like Elasticsearch) in the system architecture to more advanced features.
If you have no data to play with, don't worry we import sample datasets at the very beginning of this course.
If you already have experience with Elasticsearch, you will enjoy the advanced part of it. Maybe you wonder if the way that use use Elasticsearch is the proper way and maybe your queries can return results faster ? If so, then course will help you find answers to that questions, optionally grounding and strengthening your exiting experience. No matter what is your existing level of knowledge, after completing this course, you will be ready to become a true professional in the Elasticsearch community.
In this course, I will show you how to properly use Elasticsearch product. We will start by explaining basic terms and role of Elasticsearch in the system architecture. Then, after importing sample data, we will go through term based queries, range queries, specialized queries, geo queries, nested queries and so on. We will get to know how to build effective notifications by using percolate queries or aggregate and analyze results using aggregations.
I’ll show you how to do highlighting, suggestions, spell corrections, and template your queries. At the end we will cover tuning and optimization best practices, query profiling, performance testing and customize default routing and scoring.
Overall, you'll learn how to properly and effectively query Elasticsearch in the easy way, without spending hours reading manuals.
I hope to see you in the first lecture.
Who this course is for:
- Software Engineers
- DevOps & Administrators
- Developers & QA
I'm a Software Engineer with over 24 years of experience. Since 2013 I’ve been working with BigData systems which process hundreds of terabytes of various data on a daily basis. Among others, I spent those years mostly with RabbitMQ, Elasticsearch and AWS services.
Thanks to the many projects I have participated in and many projects I started to be responsible for, I've become a professional in the RabbitMQ and Elasticsearch domains. People started asking Me for a help with their clusters, architectures and to audit existing configurations and system architectures. In this way, I become a consultant and trainer.
I continue my professional career as a Software Engineer and Development Manager in many international companies, but I'm more than happy when I can meet with people to share experience and good practices on both technologies which brought me here: RabbitMQ and Elasticsearch.