An example setup for the workshop could look like this:
1. What is Search?
With examples of real-life concepts used in search solutions are explained. Think about: Inverted index, features, signals, precision, recall, aggregations.
2. Creating your data model
Explain the different data types and structures that are possible in elasticsearch. When to use which to enable the user to find the most relevant documents.
3. Introduction of the Query DSL
Elasticsearch comes with a lot of different query options. You'll learn of about the different types of queries and how to combine queries to obtain relevant results.
4. Explain why certain documents are returned in the order they are
Elasticsearch provides a few api's like "explain" and "profile" to help you as a search engineer understand the query results. We'll show in depth how a score is calculated and why one query takes longer than another.
5. Examine and design your cluster
You'll learn about the options you have to create an elasticsearch cluster, the role of nodes, indexes, shards. You'll also learn about some of the options you have to create the cluster (bare metal, docker, Elastic cloud, AWS Elasticsearch.
6. Submitting content
Without content, there is nothing to search for. Adding content is not hard, but you have a lot of options to make it go faster and better. Is this module you'll learn about using curl or a client to submit documents.