🦀 Query Optimization in TuskLang for Rust

Rust Documentation

Query Optimization in TuskLang for Rust

TuskLang's Rust query optimization system provides type-safe, performance-focused query optimization with compile-time guarantees, async/await support, and comprehensive optimization strategies for high-performance database operations.

🚀 Why Rust Query Optimization?

Rust's type system and ownership model make it the perfect language for query optimization:

- Type Safety: Compile-time validation of optimization strategies - Performance: Zero-cost abstractions with native speed - Async/Await: Non-blocking optimization operations - Memory Safety: Automatic memory management for optimization data - Optimization Guarantees: Guaranteed performance improvements

Basic Query Optimization

use tusk_db::{QueryOptimizer, OptimizationStrategy, Result};
use serde::{Deserialize, Serialize};
use chrono::{DateTime, Utc};
#[derive(Debug, Serialize, Deserialize, Clone)]
struct User {
    pub id: Option<i32>,
    pub name: String,
    pub email: String,
    pub is_active: bool,
    pub created_at: Option<DateTime<Utc>>,
    pub updated_at: Option<DateTime<Utc>>,
}
#[derive(Debug, Serialize, Deserialize, Clone)]
struct Post {
    pub id: Option<i32>,
    pub title: String,
    pub content: String,
    pub user_id: i32,
    pub published: bool,
    pub view_count: i32,
    pub created_at: Option<DateTime<Utc>>,
    pub updated_at: Option<DateTime<Utc>>,
}
// Basic query optimization
async fn optimized_user_query() -> Result<Vec<User>> {
    let optimizer = @QueryOptimizer::new().await?;
    
    // Optimize query with automatic analysis
    let optimized_query = optimizer.optimize(|query| {
        query.table::<User>("users")
            .where_eq("is_active", true)
            .order_by("created_at", "DESC")
            .limit(100)
    }).await?;
    
    let users = optimized_query.get().await?;
    Ok(users)
}// Query with explicit optimization hints
async fn hinted_query_optimization() -> Result<Vec<User>> {
    let users = @db.table::<User>("users")
        .where_eq("is_active", true)
        .order_by("created_at", "DESC")
        .limit(100)
        .hint("USE INDEX (idx_users_active_created)")
        .hint("FORCE INDEX (idx_users_email)")
        .get()
        .await?;
    
    Ok(users)
}

Advanced Query Optimization Strategies

use tusk_db::{OptimizationStrategy, QueryAnalyzer, PerformanceMetrics};
// Query analyzer for performance insights
async fn analyze_query_performance() -> Result<()> {
    let analyzer = @QueryAnalyzer::new().await?;
    
    let query = @db.table::<User>("users")
        .where_eq("is_active", true)
        .where_like("email", "%@gmail.com")
        .order_by("created_at", "DESC");
    
    // Analyze query performance
    let analysis = analyzer.analyze(&query).await?;
    
    @log::info!("Query analysis", {
        estimated_rows: analysis.estimated_rows,
        index_usage: analysis.index_usage,
        execution_plan: analysis.execution_plan,
        optimization_suggestions: analysis.suggestions,
    });
    
    // Apply optimization suggestions
    let optimized_query = analyzer.apply_suggestions(&query, &analysis.suggestions).await?;
    
    let users = optimized_query.get().await?;
    Ok(())
}// Query optimization with multiple strategies
async fn multi_strategy_optimization() -> Result<Vec<User>> {
    let optimizer = @QueryOptimizer::new().await?;
    
    let strategies = vec![
        OptimizationStrategy::IndexUsage,
        OptimizationStrategy::QueryRewriting,
        OptimizationStrategy::JoinOptimization,
        OptimizationStrategy::SubqueryOptimization,
    ];
    
    let optimized_query = optimizer.optimize_with_strategies(|query| {
        query.table::<User>("users")
            .select(&["id", "name", "email"])
            .where_eq("is_active", true)
            .where_in("id", |subquery| {
                subquery.table("posts")
                    .select(&["user_id"])
                    .where_eq("published", true)
                    .group_by("user_id")
                    .having("COUNT(*)", ">", 5)
            })
            .order_by("name")
    }, &strategies).await?;
    
    let users = optimized_query.get().await?;
    Ok(users)
}

Index Optimization and Management

use tusk_db::{IndexOptimizer, IndexStrategy, IndexRecommendation};
// Index optimization
async fn optimize_indexes() -> Result<()> {
    let index_optimizer = @IndexOptimizer::new().await?;
    
    // Analyze current index usage
    let index_analysis = index_optimizer.analyze_indexes().await?;
    
    @log::info!("Index analysis", {
        unused_indexes: index_analysis.unused_indexes,
        missing_indexes: index_analysis.missing_indexes,
        duplicate_indexes: index_analysis.duplicate_indexes,
    });
    
    // Get index recommendations
    let recommendations = index_optimizer.get_recommendations().await?;
    
    for recommendation in &recommendations {
        @log::info!("Index recommendation", {
            table: &recommendation.table,
            columns: &recommendation.columns,
            type_: recommendation.index_type,
            reason: &recommendation.reason,
        });
    }
    
    // Apply recommended indexes
    for recommendation in recommendations {
        if recommendation.should_apply {
            index_optimizer.create_index(&recommendation).await?;
        }
    }
    
    Ok(())
}
// Automatic index creation for slow queries
async fn auto_index_optimization() -> Result<()> {
    let optimizer = @QueryOptimizer::new().await?;
    
    // Monitor slow queries and create indexes automatically
    optimizer.enable_auto_indexing(true).await?;
    optimizer.set_slow_query_threshold(100).await?; // 100ms
    
    // Run query that might be slow
    let users = @db.table::<User>("users")
        .where_eq("is_active", true)
        .where_like("email", "%@example.com")
        .order_by("created_at", "DESC")
        .get()
        .await?;
    
    // If query is slow, optimizer will suggest/create indexes
    Ok(users)
}// Composite index optimization
async fn composite_index_optimization() -> Result<()> {
    let index_optimizer = @IndexOptimizer::new().await?;
    
    // Create composite index for common query patterns
    let composite_index = IndexRecommendation {
        table: "users".to_string(),
        columns: vec!["is_active".to_string(), "created_at".to_string()],
        index_type: IndexType::BTree,
        reason: "Optimize active user queries with date filtering".to_string(),
        should_apply: true,
    };
    
    index_optimizer.create_index(&composite_index).await?;
    
    // Use the optimized query
    let users = @db.table::<User>("users")
        .where_eq("is_active", true)
        .where_gt("created_at", Utc::now() - chrono::Duration::days(30))
        .order_by("created_at", "DESC")
        .get()
        .await?;
    
    Ok(users)
}

Query Rewriting and Optimization

use tusk_db::{QueryRewriter, RewriteRule, QueryTransformer};
// Query rewriting for optimization
async fn query_rewriting_optimization() -> Result<Vec<User>> {
    let rewriter = @QueryRewriter::new().await?;
    
    // Define rewrite rules
    let rules = vec![
        RewriteRule::new("simplify_where", |query| {
            // Simplify complex WHERE clauses
            if query.has_complex_where() {
                query.simplify_where_clauses()
            }
        }),
        RewriteRule::new("optimize_joins", |query| {
            // Optimize JOIN order
            query.optimize_join_order()
        }),
        RewriteRule::new("eliminate_subqueries", |query| {
            // Convert subqueries to JOINs where possible
            query.convert_subqueries_to_joins()
        }),
    ];
    
    let original_query = @db.table::<User>("users")
        .where_in("id", |subquery| {
            subquery.table("posts")
                .select(&["user_id"])
                .where_eq("published", true)
        })
        .where_eq("is_active", true);
    
    // Apply rewrite rules
    let optimized_query = rewriter.rewrite_with_rules(&original_query, &rules).await?;
    
    let users = optimized_query.get().await?;
    Ok(users)
}// Query transformation for better performance
async fn query_transformation() -> Result<Vec<User>> {
    let transformer = @QueryTransformer::new().await?;
    
    // Transform complex query to more efficient version
    let complex_query = @db.table::<User>("users")
        .where_exists(|subquery| {
            subquery.table("posts")
                .where_raw("posts.user_id = users.id", &[])
                .where_eq("published", true)
        })
        .where_eq("is_active", true);
    
    let transformed_query = transformer.transform(&complex_query).await?;
    
    // The transformed query might use JOINs instead of EXISTS
    let users = transformed_query.get().await?;
    Ok(users)
}

Join Optimization

use tusk_db::{JoinOptimizer, JoinStrategy, JoinOrder};
// Join optimization
async fn join_optimization() -> Result<Vec<User>> {
    let join_optimizer = @JoinOptimizer::new().await?;
    
    let complex_query = @db.table::<User>("users")
        .join("posts", "users.id", "=", "posts.user_id")
        .join("comments", "posts.id", "=", "comments.post_id")
        .where_eq("users.is_active", true)
        .where_eq("posts.published", true)
        .select(&[
            "users.*",
            "COUNT(posts.id) as post_count",
            "COUNT(comments.id) as comment_count"
        ])
        .group_by("users.id");
    
    // Optimize join order and strategy
    let optimized_query = join_optimizer.optimize(&complex_query).await?;
    
    let results = optimized_query.get().await?;
    Ok(results)
}// Join strategy selection
async fn join_strategy_selection() -> Result<Vec<User>> {
    let join_optimizer = @JoinOptimizer::new().await?;
    
    // Analyze join strategies
    let strategies = join_optimizer.analyze_strategies(|query| {
        query.table::<User>("users")
            .join("posts", "users.id", "=", "posts.user_id")
            .where_eq("users.is_active", true)
    }).await?;
    
    // Select best strategy
    let best_strategy = join_optimizer.select_best_strategy(&strategies).await?;
    
    @log::info!("Selected join strategy", {
        strategy: best_strategy.name,
        estimated_cost: best_strategy.estimated_cost,
        reasoning: &best_strategy.reasoning,
    });
    
    // Apply the strategy
    let optimized_query = join_optimizer.apply_strategy(&best_strategy).await?;
    let users = optimized_query.get().await?;
    
    Ok(users)
}

Subquery Optimization

use tusk_db::{SubqueryOptimizer, SubqueryStrategy};
// Subquery optimization
async fn subquery_optimization() -> Result<Vec<User>> {
    let subquery_optimizer = @SubqueryOptimizer::new().await?;
    
    let query_with_subquery = @db.table::<User>("users")
        .where_in("id", |subquery| {
            subquery.table("posts")
                .select(&["user_id"])
                .where_eq("published", true)
                .group_by("user_id")
                .having("COUNT(*)", ">", 5)
        })
        .where_eq("is_active", true);
    
    // Optimize subquery
    let optimized_query = subquery_optimizer.optimize(&query_with_subquery).await?;
    
    let users = optimized_query.get().await?;
    Ok(users)
}// Convert subqueries to JOINs
async fn subquery_to_join_conversion() -> Result<Vec<User>> {
    let subquery_optimizer = @SubqueryOptimizer::new().await?;
    
    let query = @db.table::<User>("users")
        .where_exists(|subquery| {
            subquery.table("posts")
                .where_raw("posts.user_id = users.id", &[])
                .where_eq("published", true)
        });
    
    // Convert EXISTS subquery to JOIN
    let converted_query = subquery_optimizer.convert_to_join(&query).await?;
    
    let users = converted_query.get().await?;
    Ok(users)
}

Query Caching and Result Caching

use tusk_db::{QueryCache, CacheStrategy, CacheInvalidation};
// Query caching for performance
async fn query_caching_optimization() -> Result<Vec<User>> {
    let cache = @QueryCache::new().await?;
    
    // Configure cache strategy
    cache.set_strategy(CacheStrategy {
        ttl: 3600, // 1 hour
        max_size: 1000,
        eviction_policy: EvictionPolicy::LRU,
    }).await?;
    
    let query = @db.table::<User>("users")
        .where_eq("is_active", true)
        .order_by("created_at", "DESC")
        .limit(100);
    
    // Try to get from cache first
    let cache_key = query.generate_cache_key().await?;
    
    if let Some(cached_result) = cache.get(&cache_key).await? {
        @log::info!("Cache hit", { key: &cache_key });
        return Ok(cached_result);
    }
    
    // Cache miss, execute query
    @log::info!("Cache miss", { key: &cache_key });
    let users = query.get().await?;
    
    // Store in cache
    cache.set(&cache_key, &users).await?;
    
    Ok(users)
}// Result caching with invalidation
async fn result_caching_with_invalidation() -> Result<Vec<User>> {
    let cache = @QueryCache::new().await?;
    
    // Set up cache invalidation rules
    cache.set_invalidation_rules(&[
        CacheInvalidation::new("users", |event| {
            match event {
                "INSERT" | "UPDATE" | "DELETE" => true,
                _ => false,
            }
        }),
    ]).await?;
    
    let query = @db.table::<User>("users")
        .where_eq("is_active", true);
    
    let cache_key = query.generate_cache_key().await?;
    
    // Get from cache or execute
    let users = cache.get_or_execute(&cache_key, || async {
        query.get().await
    }).await?;
    
    Ok(users)
}

Query Performance Monitoring

use tusk_db::{QueryMonitor, PerformanceMetrics, SlowQueryDetector};
// Query performance monitoring
async fn query_performance_monitoring() -> Result<()> {
    let monitor = @QueryMonitor::new().await?;
    
    // Enable monitoring
    monitor.enable(true).await?;
    monitor.set_slow_query_threshold(100).await?; // 100ms
    
    // Execute query with monitoring
    let start = std::time::Instant::now();
    
    let users = @db.table::<User>("users")
        .where_eq("is_active", true)
        .order_by("created_at", "DESC")
        .limit(100)
        .get()
        .await?;
    
    let duration = start.elapsed();
    
    // Record metrics
    monitor.record_query_metrics(&QueryMetrics {
        sql: "SELECT * FROM users WHERE is_active = true ORDER BY created_at DESC LIMIT 100".to_string(),
        duration: duration.as_millis() as u64,
        rows_returned: users.len() as u64,
        timestamp: Utc::now(),
    }).await?;
    
    // Check for slow queries
    let slow_queries = monitor.get_slow_queries().await?;
    
    for slow_query in &slow_queries {
        @log::warn!("Slow query detected", {
            sql: &slow_query.sql,
            duration: slow_query.duration,
            suggestions: &slow_query.optimization_suggestions,
        });
    }
    
    Ok(())
}// Real-time query monitoring
async fn real_time_query_monitoring() -> Result<()> {
    let monitor = @QueryMonitor::new().await?;
    
    // Set up real-time monitoring
    monitor.enable_real_time_monitoring(true).await?;
    
    // Subscribe to query events
    let mut query_stream = monitor.subscribe_to_queries().await?;
    
    tokio::spawn(async move {
        while let Some(query_event) = query_stream.recv().await {
            match query_event {
                QueryEvent::SlowQuery(query) => {
                    @log::warn!("Real-time slow query alert", {
                        sql: &query.sql,
                        duration: query.duration,
                    });
                }
                QueryEvent::Error(query_error) => {
                    @log::error!("Query error", {
                        sql: &query_error.sql,
                        error: &query_error.error,
                    });
                }
                _ => {}
            }
        }
    });
    
    Ok(())
}

Query Optimization Best Practices

use tusk_db::{OptimizationBestPractices, QueryGuidelines};// Best practices for query optimization
async fn query_optimization_best_practices() -> Result<()> {
    let optimizer = @QueryOptimizer::new().await?;
    
    // 1. Use appropriate indexes
    let indexed_query = @db.table::<User>("users")
        .where_eq("is_active", true) // Uses index on is_active
        .where_eq("email", "test@example.com") // Uses unique index on email
        .get()
        .await?;
    
    // 2. Avoid SELECT *
    let selective_query = @db.table::<User>("users")
        .select(&["id", "name", "email"]) // Only select needed columns
        .where_eq("is_active", true)
        .get()
        .await?;
    
    // 3. Use LIMIT for large result sets
    let limited_query = @db.table::<User>("users")
        .where_eq("is_active", true)
        .order_by("created_at", "DESC")
        .limit(100) // Prevent large result sets
        .get()
        .await?;
    
    // 4. Optimize JOINs
    let optimized_join = @db.table::<User>("users")
        .join("posts", "users.id", "=", "posts.user_id")
        .where_eq("users.is_active", true)
        .where_eq("posts.published", true)
        .select(&["users.id", "users.name", "COUNT(posts.id) as post_count"])
        .group_by("users.id")
        .get()
        .await?;
    
    // 5. Use appropriate data types
    let typed_query = @db.table::<User>("users")
        .where_eq("is_active", true) // Boolean comparison
        .where_gt("created_at", Utc::now() - chrono::Duration::days(30)) // Date comparison
        .get()
        .await?;
    
    // 6. Avoid N+1 queries with eager loading
    let eager_loaded_query = @db.table::<User>("users")
        .with(&["posts", "posts.comments"]) // Eager load relationships
        .where_eq("is_active", true)
        .get()
        .await?;
    
    // 7. Use query caching for frequently accessed data
    let cached_query = @db.table::<User>("users")
        .where_eq("is_active", true)
        .cache(3600) // Cache for 1 hour
        .get()
        .await?;
    
    Ok(())
}

Testing Query Optimization

use tusk_db::test_utils::{TestQueryOptimizer, PerformanceTest};
// Test query optimization
#[tokio::test]
async fn test_query_optimization() -> Result<()> {
    let test_db = @TestDatabase::new().await?;
    let optimizer = @TestQueryOptimizer::new(&test_db).await?;
    
    // Create test data
    let users = @UserFactory::new()
        .count(1000)
        .create()
        .await?;
    
    // Test unoptimized query
    let start = std::time::Instant::now();
    let unoptimized_users = @db.table::<User>("users")
        .where_eq("is_active", true)
        .get()
        .await?;
    let unoptimized_duration = start.elapsed();
    
    // Test optimized query
    let start = std::time::Instant::now();
    let optimized_query = optimizer.optimize(|query| {
        query.table::<User>("users")
            .where_eq("is_active", true)
    }).await?;
    let optimized_users = optimized_query.get().await?;
    let optimized_duration = start.elapsed();
    
    // Verify optimization improved performance
    assert!(optimized_duration < unoptimized_duration);
    assert_eq!(unoptimized_users.len(), optimized_users.len());
    
    Ok(())
}// Performance regression testing
#[tokio::test]
async fn test_performance_regression() -> Result<()> {
    let test_db = @TestDatabase::new().await?;
    let performance_test = @PerformanceTest::new(&test_db).await?;
    
    // Define performance baseline
    let baseline = performance_test.establish_baseline(|query| {
        query.table::<User>("users")
            .where_eq("is_active", true)
            .order_by("created_at", "DESC")
            .limit(100)
    }).await?;
    
    // Run performance test
    let current_performance = performance_test.measure_performance(|query| {
        query.table::<User>("users")
            .where_eq("is_active", true)
            .order_by("created_at", "DESC")
            .limit(100)
    }).await?;
    
    // Check for performance regression
    assert!(current_performance.duration <= baseline.duration * 1.1); // Allow 10% regression
    
    Ok(())
}

Best Practices for Rust Query Optimization

1. Use Strong Types: Leverage Rust's type system for query safety 2. Index Strategy: Create appropriate indexes for query patterns 3. Query Analysis: Analyze query performance regularly 4. Caching: Use query caching for frequently accessed data 5. Monitoring: Monitor query performance in production 6. Testing: Test optimization strategies thoroughly 7. Documentation: Document complex optimization logic 8. Benchmarking: Benchmark before and after optimizations 9. Incremental: Apply optimizations incrementally 10. Monitoring: Continuously monitor for performance regressions