Lab
A Cloud Guru

Defining Custom Analyzers, Multi-Fields, and Mappings in Elasticsearch 7.13

Elasticsearch has a plethora of built-in analyzers, as well as the ability to automatically detect the data type for each of your fields. If you want to fine-tune how your fields are analyzed and mapped, then Elasticsearch has you covered. In this hands-on lab, you will create and use custom analyzers and multi-fields, and define both explicit and dynamic mappings in Elasticsearch.

Try for free Contact sales

Path Info

Level

Advanced

Duration

3h 0m

Published

Jan 28, 2022

Challenge

Create the strings_as_keywords Component Template
From the Kibana console, create the strings_as_keywords component template with the following requirements:
- Dynamically maps string fields as the keyword datatype.
- Only indexes the first 256 characters.
Challenge

Create the social_media_analyzer Component Template
From the Kibana console, create the social_media_analyzer component template with the following requirements:
- Creates a custom analyzer called social_media that uses the classic tokenizer.
- Uses the lowercase filter and a custom english_stop filter. The english_stop filter should remove English stop words.
- Uses a custom emoticons mapping character filter with the following mappings:
  - :) as happy
  - :D as laughing
  - :( as sad
  - :') as crying
  - :O as surprised
  - ;) as winking
Challenge

Create the twitter_template Index Template
From the Kibana console, create the twitter_template index template with the following requirements:
- Matches all indices that start with "twitter-".
- Composed of the strings_as_keywords and social_media_analyzer component templates.
- Maps the tweet field as an analyzed string field with the social_media analyzer.
- Maps a tweet.keyword multi-field as type keyword and only indexes the first 280 characters.
- Sets the number of shards to 1 and replicas to 0.

Author

A Cloud Guru

The Cloud Content team comprises subject matter experts hyper focused on services offered by the leading cloud vendors (AWS, GCP, and Azure), as well as cloud-related technologies such as Linux and DevOps. The team is thrilled to share their knowledge to help you build modern tech solutions from the ground up, secure and optimize your environments, and so much more!

What's a lab?

Hands-on Labs are real environments created by industry experts to help you learn. These environments help you gain knowledge and experience, practice without compromising your system, test without risk, destroy without fear, and let you learn from your mistakes. Hands-on Labs: practice your skills before delivering in the real world.