No Query Performance Guidance or Index Recommendations

[richardwooding]

Summary

Library generates SQL but provides no guidance on indexing strategies for optimal performance.

Location

Architecture-level

Issue

Users don't know what indexes to create for:

• JSON path operations (GIN indexes)
• Array containment (GIN indexes)
• Regex matching (pg_trgm GIN indexes)
• Text search

Recommendation

Add query analysis feature:

type IndexRecommendation struct {
    Column     string
    IndexType  string
    Expression string
    Reason     string
}

func AnalyzeQuery(ast *cel.Ast) (sql string, recommendations []IndexRecommendation, err error)

Or at minimum, document recommended indexes in README.

[richardwooding]

Status: Confirmed - Valid Enhancement Request

The library generates SQL but provides no guidance on indexing strategies for optimal performance.

Missing Guidance For:

• JSON path operations → Need GIN indexes on JSONB columns
• Array containment → Need GIN indexes with appropriate operator classes
• Regex matching → May benefit from pg_trgm GIN indexes
• Text search operations → Need full-text search indexes
• Repeated field accesses → Need B-tree indexes on commonly filtered columns

Potential Solutions:

Option 1: Documentation (Low effort)
Add a "Performance and Indexing" section to README/docs with:

• Common patterns and recommended indexes
• Example CREATE INDEX statements
• Query performance best practices

Option 2: Query Analysis Feature (High effort)

type IndexRecommendation struct {
    Column     string
    IndexType  string   // "GIN", "BTREE", "GIST"
    Expression string   // Full CREATE INDEX statement
    Reason     string   // Why this index is recommended
}

func AnalyzeQuery(ast *cel.Ast) (sql string, recommendations []IndexRecommendation, err error)

Recommendation: Start with Option 1 (documentation) as it provides immediate value with minimal effort. Option 2 could be a future enhancement if there's demand.