Getting Started with Elasticsearch from scratch for absolute beginners.
Hello fellas, it’s been a long time I couldn’t write on my blog and today I am super excited to start an exciting course on Elasticsearch that will take some time to complete but if you will walk along with me on this journey I’ll make this exciting path of learning, a fun. 🙂
Chances are you already have some experience with Elasticsearch, or perhaps you never even heard about it. This course starts from the absolute beginning and guides you through the process of learning Elasticsearch, step by step.
Elasticsearch has great documentation but I feel for beginners who are struggling to master this technology find it more of an API reference than a guide, which makes it difficult to grasp its concepts.
Elasticsearch is a pretty complex technology, and figuring out where to start can be challenging. Even planning out this course was a challenge for me, and I have worked with Elasticsearch for years. You will see a lot of effort placed into introducing concepts gradually rather than giving you tons of information all at once.
This doesn’t mean that you won’t need the documentation, though. It’s impossible to cover all details of Elasticsearch, but I have taken the most important concepts and included them in the course.
The scope of this course is Elasticsearch, and not the Elastic Stack as a whole.
We will be using Kibana to easily send queries to Elasticsearch, but other than that, we will focus our attention on Elasticsearch specifically. The reason for that is that Elasticsearch by itself is a hugely complex technology, and if I were to cover the whole Elastic Stack, I would not be able to go into detail with anything.
The Elastic Stack includes quite a few products, and more products are added frequently. My approach is to cover Elasticsearch specifically and go into a lot of detail, and then cover other parts of the Elastic Stack later in separate courses.
Alright, so in this course you will be learning;
- How to write complex queries against the data stored in Elasticsearch. E.g for search, data analysis, APM, log management, server monitoring, security, etc.
- This course does not cover a specific use case, so you will be able to apply the concepts to whatever use case you are working with.
- You will learn the concepts required to build a modern search engine, including handling synonyms, stemming, search-as-you-type, auto-completion, and tuning of relevance scores.
- Apart from that, we will also cover aggregations, which is key for analyzing lots of data.
For your convenience, you can access all of the queries and commands that you see me type throughout the course, within a GitHub repository.
What I mentioned above is just a part of the content that you will find, below is the full content of this course.
Section 1: Introduction to Elasticsearch
In this section, I’ll introduce Elasticsearch, give an overview of the Elastic Stack, and will walkthrough the common architectures.
Section 2: Installation and understanding of Elasticsearch architecture
In this section, We will learn;
- The Installation process of Elasticsearch and Kibana.
- Understanding the basic architecture and inspecting the cluster
- Sending queries with cURL and Dev Tools of Kibana
- Sharing, scalability and replication concepts.
Section 3: Indexing and Managing Documents
In this section, We will learn;
- How to create & delete indices.
- Indexing of documents, Update, Retrieval, Replacing and Deleting documents.
- Understanding routing mechanism, how Elasticsaerch reads data and document versioning.
- Update and Delete by query, Batch processing and importing data with cURL.