RHINENG-26117: Add recompute infrastructure for account_advisory

[rverdile]

Summary

This adds recompute and trigger infrastructure for account_advisory. It's mostly modeled after the existing recompute and trigger for account_advisory_data. I also added a little bit of Go infrastructure so that I could add unit tests.

This is dependent on this PR: #2184

Secure Coding Practices Checklist GitHub Link

• https://github.com/RedHatInsights/secure-coding-checklist

Secure Coding Checklist

• Input Validation
• Output Encoding
• Authentication and Password Management
• Session Management
• Access Control
• Cryptographic Practices
• Error Handling and Logging
• Data Protection
• Communication Security
• System Configuration
• Database Security
• File Management
• Memory Management
• General Coding Practices

Summary by Sourcery

Add database functions, indexes, models, and tests to support recomputing and backfilling account-level advisory aggregates.

New Features:

• Introduce PL/pgSQL functions to refresh and backfill account_advisory caches by advisory and account.
• Add indexes on account_advisory aggregate columns to support cache queries.
• Expose an AccountAdvisory GORM model and test helper functions for manipulating account_advisory data in tests.

Enhancements:

• Version the schema with a new migration adding account_advisory cache functions and indexes, with a corresponding down migration.

Tests:

• Add integration tests verifying that account_advisory cache refresh correctly recalculates counts and removes orphaned rows.

[sourcery-ai]

Reviewer's Guide

Implements recompute/backfill functions and indices for the workspace-scoped account_advisory aggregation, exposes a Go model plus DB test helpers, and adds integration tests to validate refresh and cleanup behavior.

File-Level Changes

Change	Details	Files
Add refresh/backfill infrastructure and indexes for account_advisory aggregates in the database schema and migrations.	Bump schema_migrations version to 157 to introduce new migration Define refresh_account_advisory_caches_multi to recompute per-account, per-workspace advisory counts from system_advisories/system_inventory/system_patch, with upsert and orphan cleanup semantics Add wrapper functions refresh_account_advisory_caches and backfill_account_advisory to drive recomputation for a single advisory or whole account Create indices on account_advisory for systems_applicable and systems_installable to optimize queries and updates Mirror the new PL/pgSQL functions and indexes into dedicated 157 up/down migration files, including cleanup and truncation in the down migration	database_admin/schema/create_schema.sql database_admin/migrations/157_account_advisory_queries.up.sql database_admin/migrations/157_account_advisory_queries.down.sql
Introduce a Go model for account_advisory and helper functions for manipulating it in tests.	Define AccountAdvisory struct with composite primary key (AdvisoryID, RhAccountID, WorkspaceID) and the systems/notified fields, plus TableName() binding to account_advisory Add AccountAdvisorySlice type alias for collections of account advisories Extend testing DB helpers to create, verify, and delete account_advisory rows, including account-scoped cleanup utility	base/models/models.go base/database/testing.go
Add integration tests to validate backfill and recompute behavior for account_advisory caches.	Create refresh_account_advisory_caches_test.go with DB-backed tests that backfill account_advisory for rh_account_id=1 and then verify refresh_account_advisory_caches restores correct counts after corruption Add test ensuring refresh_account_advisory_caches removes rows for workspaces whose systems have all become stale and validates cleanup after resetting staleness Use a fixed test workspace UUID and existing test setup utilities (SetupTestEnvironment, configure, SkipWithoutDB) to integrate with the current test harness	tasks/caches/refresh_account_advisory_caches_test.go

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[codecov-commenter]

Codecov Report

❌ Patch coverage is 0% with 30 lines in your changes missing coverage. Please review.
✅ Project coverage is 59.01%. Comparing base (8f1f21e) to head (f892d92).

Files with missing lines	Patch %	Lines
base/database/testing.go	0.00%	28 Missing ⚠️
base/models/models.go	0.00%	2 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master    #2195      +/-   ##
==========================================
- Coverage   59.21%   59.01%   -0.21%     
==========================================
  Files         137      137              
  Lines        8798     8828      +30     
==========================================
  Hits         5210     5210              
- Misses       3040     3070      +30     
  Partials      548      548              

Flag	Coverage Δ
unittests	59.01% <0.00%> (-0.21%)	⬇️

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[sourcery-ai]

Hey - I've left some high level feedback:

• The DDL for account_advisory indexes and the refresh/backfill functions is duplicated in both create_schema.sql and 157_account_advisory_queries.up.sql; consider centralizing this in migrations (and having create_schema generated from them) to avoid future drift between fresh installs and upgraded environments.
• The down migration 157_account_advisory_queries.down.sql truncates account_advisory, which is more destructive than a typical rollback; if this table contains any non-derivable or user-relevant data, consider dropping only the added indexes/functions and leaving the data intact.

Prompt for AI Agents

Please address the comments from this code review:

## Overall Comments
- The DDL for `account_advisory` indexes and the refresh/backfill functions is duplicated in both `create_schema.sql` and `157_account_advisory_queries.up.sql`; consider centralizing this in migrations (and having `create_schema` generated from them) to avoid future drift between fresh installs and upgraded environments.
- The down migration `157_account_advisory_queries.down.sql` truncates `account_advisory`, which is more destructive than a typical rollback; if this table contains any non-derivable or user-relevant data, consider dropping only the added indexes/functions and leaving the data intact.

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