feat: minimal topology details for rest of the children #288
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@adityathebe can we add some tests for this ? |
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* fetch other columns that are essential to create the tree
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topology.go
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| // parents, incidents, analysis, checks columns need to fetched to create the topology tree even though they may not be essential to the UI. | ||
| return "name, namespace, id, is_leaf, status, status_reason, summary, topology_type, labels, team_names, agent_id, parent_id, type, parents, incidents, analysis, checks" | ||
| } |
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@moshloop had to add back these columns as they're essential during tree creation.
- parents
- incidents
- analysis
- checks
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I am not sure how much better this will perform - I also think we should use more sql functions / views and have this in a single db query rather than multiple trips to the db.
Generally I think there are phases:
- Find all top level components (no parents, or direct descendants) and apply label, type, team, agent filters at this level only.
- For each component summarize health, incidents, analysis of its descendants
// find all the descendants of a component, including those via relationships
find_descendants(id): returns id array
descendants = find_descendants(id)
select components.* from components where filters
with each top level component
select name, id, parent, type, icon, component_summary.* from components where id in @descandents
inner join component_summary
where component_summary is a view, that maybe becomes a materialized view in the future (which is refreshed on a debonce(check.transitioned, analysis.updated, incident.transitioned) etc..
- Union and then post process for top-level summary in go
- strip off parent(s), agent_id in final topology returned
wdyt @yashmehrotra ?
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Agree with point 1 of applying filters just at top level
for point 2, are we selecting all the descendants or just summarizing them ? cause summary right now happens in go not sql, so we might want to change that
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Resolves: #285