Elasticsearch in Action

In this lecture, I will give you a brief introduction to Elasticsearch and will try to answer questions such as what is Elasticsearch, which companies use Elasticsearch and how we communicate with our Elasticsearch server.

In this lecture, I will talk about the terminology you will need about Elasticsearch.

After this lecture you will know what is

• Index
• Type
• Document
• Node
• Cluster
• Shard
• Replica

We will see how we can install and run Elasticsearch on Windows OS

We will learn how we can install and run Elasticsearch on Mac

In this lecture, I will explain how we can install Head and Marvel plug-ins which are quite useful.

Marvel contains Sense plug-in that we will use in every single lecture of our course.

If you use Elasticsearch >= 2.0 then skip Marvel and just install Head.

If you use Elasticsearch version greater than 2, then you will need to install Kibana which contains Sense plug-in that we will use in every single lecture of our course. Else you can skip this lecture.

In this lecture, we will look closely to building blocks of Elasticsearch: documents.

After this lecture, you'll have a knowledge about different parts of a document.

We will learn how to index a document.

After this lecture you will know how to index a document with custom or auto-generated id.

In this lecture you will learn how to fetch

• A document by id
• A part of a single document
• Multiple documents with mget, that is multiple get

In this lecture, you will learn how to check if the document exists in our Elasticsearch server just by checking its HTTP header. Later we will see how to check and index if not found with a single request.

In this lecture, you will learn several ways of deleting documents from Elasticsearch:

• delete by id
• delete by query

Delete by query is removed from Elasticsearch 2.0. If you use this version, you have to install it as a plugin.

In this lecture, you will understand how concurrency control is implemented in Elasticsearch and how we will use it using the version of documents.

In this lecture, we will talk about two methods of update in Elasticsearch:

• Partial update
• Full update

In this lecture, you will learn how to do bulk requests to Elasticsearch and do very fast CRUD operations in batch.

Making bulk requests is all time winner for faster create, update and delete operations.

During this lecture, you will understand mappings of Elasticsearch that are basically schemas for types.

You will learn

• Simple field types (string, integer, etc)
• Implicit _all field

In this lecture, you will learn what are analyzers, how they change the way full text is processed, what is an inverted index and how it is used in Elasticsearch.

Furthermore, you will understand how an inserted document will be analyzed and put into an inverted index in ES.

In this lecture, we will talk about out-of-the-box analyzer types and how to check their analysis results using analyze endpoint.

Default analyzers are

• Standard
• Simple
• Whitespace
• Stop
• Keyword
• Pattern
• Language
• Snowball Analyzers

If you use Elasticsearch 2.0 or greater then use the new sytax for analyze endpoint that you can find in the resources

In this chapter, we will summarize the things we learnt about analyzers.

In this lecture, you will learn how to create and update custom mappings for simple field types and see how custom mappings and different analyzers can change the resultset of your queries

In this lecture, we will explain how to create and update custom mappings but for complex field types and see how queries' resultset change thanks to custom mappings and analyzers.

In this lecture, we will explain the search in Elasticsearch. We will fist explain the different parts of a query result.

In this lecture, we will learn how to search documents with query string which is basically a query with just request parameters.

We will see how to query simple and complex type fields, several fields together, all fields at once and how to do AND and OR queries.

In this lecture, we will focus on empty body search of Query DSL. After that, we will talk about popular query types such as match_all, match and multi-match.

In this lecture, you will learn filters and difference between filters and queries. We will see the most popular filter statements such as term, range, exists and missing.

In this lecture, we will see filtered query which we will use for combining filters and queries.

In this lecture, we will learn how to validate our query syntax.

In this lecture, you will learn how to do pagination of your data, that is how to fetch your data part by part.

Pagination is useful for fetching data with chunks and not retrieving all of it in the same time.

During this lecture, we will learn how to sort the queried data based on one or multiple exact value fields.

In this lecture, you will learn how to sort your data based on a full text field. First we have to update our mapping and add a field, then sort based on this newly created field.

In this lecture, you will learn how to sort your data based on a full text field. First we have to update our mapping and add a field, then sort based on this newly created field.

This lecture contains all syntaxes of this course.