Module db_optimize 

Database-specific optimizations.

This module provides performance optimizations tailored to each database:

• Prepared statement caching (PostgreSQL, MySQL, MSSQL)
• Batch size tuning for bulk operations
• MongoDB pipeline aggregation
• Query plan hints for complex queries

Performance Characteristics

Database	Optimization	Typical Gain
PostgreSQL	Prepared statement cache	30-50%
MySQL	Multi-row INSERT batching	40-60%
MongoDB	Bulk write batching	50-70%
MSSQL	Table-valued parameters	30-40%

Example

use prax_query::db_optimize::{PreparedStatementCache, BatchConfig, QueryHints};

// Prepared statement caching
let cache = PreparedStatementCache::new(100);
let stmt = cache.get_or_prepare("find_user", || {
    "SELECT * FROM users WHERE id = $1"
});

// Auto-tuned batching
let config = BatchConfig::auto_tune(payload_size, row_count);
for batch in data.chunks(config.batch_size) {
    execute_batch(batch);
}

// Query hints
let hints = QueryHints::new()
    .parallel(4)
    .index_hint("users_email_idx");

Structs

BatchConfig

Configuration for batch operations.

CachedStatement

A cached prepared statement entry.

IndexHint

An index hint.

JoinHint

A join method hint.

MongoPipelineBuilder

A builder for combining multiple MongoDB operations into a single pipeline.

PreparedStatementCache

A cache for prepared statements.

PreparedStatementStats

Statistics for prepared statement cache.

QueryHints

Query plan hints for optimizing complex queries.

Enums

IndexHintType

Type of index hint.

JoinMethod

Join methods.

PipelineStage

A MongoDB aggregation pipeline stage.

Functions

global_statement_cache

Global prepared statement cache.