[Lens] Introduce the concept of "related fields" to guide end-users #73152
Labels
discuss
Feature:Lens
loe:needs-research
This issue requires some research before it can be worked on or estimated
Team:Visualizations
Visualization editors, elastic-charts and infrastructure
This issue is not about implementing a specific proposal, but describing a concept that would improve the use of Lens for many types of data stored in Elasticsearch
Key concept: Fields can be related to each other for logical reasons, such as an ID field that is required for use by sub-metrics. This relationship is understood by the administrator who sets up the data, but not necessarily by a Lens user who wants to quickly create visualizations.
To give an example of the difference between what an administrator knows and what the end-user knows, imagine that an administrator has installed Metricbeat to measure metrics for Elasticsearch. Metricbeat has inherent structure to how it organizes its data into "modules" and metric sets, which is reflected in the naming of the fields. As an end-user you can guess that fields with similar names are related, but this is not as easy to use as Lens should be. Even worse, some datasets have "gotchas" that are not easily guessed at.
There are a few common types of relations that would benefit users:
Where to implement this?
The goal of "related fields" is to let administrators manage the relations so that the end-users get a good experience. An advanced enough end-user might also be able to configure related fields.
There are two main candidates for where to implement this:
No matter which of these is chosen, I would expect that Beats and the Ingest manager would take an active role in defining the relationships.
Alternatives to this proposal
Instead of defining the relationships manually, it might be possible to learn over time about how fields are used by tracking user behavior and building a recommendation system, but I think the accuracy would be higher on a manually-defined relationship than a learned one.
cc @mattkime @exekias
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