Cascade on dropping membersGlobalActivityCount for dependent mvs
#2681
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WalkthroughThe changes involve modifications to the SQL script managing materialized views for member enrichment monitoring. Key updates include the addition of the Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant Database
User->>Database: Request to drop materialized view "membersGlobalActivityCount"
Database->>Database: Drop "membersGlobalActivityCount" with cascade
Database->>User: Confirmation of drop
User->>Database: Request to create new materialized views
Database->>Database: Create views: "memberEnrichmentMonitoringTotal", "memberEnrichmentMonitoringClearbit", "memberEnrichmentMonitoringCrustdata", "memberEnrichmentMonitoringProgaiGithub", "memberEnrichmentMonitoringProgaiLinkedin", "memberEnrichmentMonitoringSerp"
Database->>User: Confirmation of new views creation
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Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (2)
backend/src/database/migrations/R__memberEnrichmentMaterializedViews.sql (2)
418-419: Good addition of division by zero checks!The CASE statements prevent division by zero errors in progress and hit rate calculations. Consider reformatting for better readability:
- case when (select count from progai_enrichable_members)::numeric = 0 then 0 else - round((select count from attempted_to_enrich_among_progai_enrichable_members)::numeric / (select count from progai_enrichable_members)::numeric * 100, 2) end as progress, + case + when (select count from progai_enrichable_members)::numeric = 0 then 0 + else round( + (select count from attempted_to_enrich_among_progai_enrichable_members)::numeric / + (select count from progai_enrichable_members)::numeric * 100, + 2 + ) + end as progress,Also applies to: 421-422
Line range hint
1-700: Consider reducing code duplication through SQL functionsThere's significant code duplication in the Common Table Expressions (CTEs) across different materialized views, particularly in the LinkedIn profile selection logic. Consider extracting these common patterns into SQL functions to improve maintainability.
Example patterns that could be extracted:
- LinkedIn profile selection logic (used in Crustdata and ProgAI views)
- Enrichment metrics calculations (progress and hit rate calculations)
Would you like me to provide an example of how to refactor these common patterns into SQL functions?
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📒 Files selected for processing (1)
backend/src/database/migrations/R__memberEnrichmentMaterializedViews.sql(2 hunks)
🔇 Additional comments (1)
backend/src/database/migrations/R__memberEnrichmentMaterializedViews.sql (1)
2-2: Good addition of CASCADE option!
Adding the cascade option to the DROP statement ensures that all dependent objects are also dropped, preventing potential dependency issues when recreating the materialized views.
epipav
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bugfix/cascade-membersGlobalActivityCount-drop-on-repeatable-mig
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Feature,Improvement, orBug.Summary by CodeRabbit