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SQL Optimization

Master plan for query performance tuning and database optimization. Covers indexing strategies, execution plan analysis, query rewriting techniques, and database-specific optimization patterns for high-performance data access.

Key Topics​

  • Index Design: B-tree, hash, bitmap, covering indexes, and index selection strategies
  • Execution Plan Analysis: Reading EXPLAIN plans, identifying bottlenecks, and cost estimation
  • Query Rewriting: Subquery optimization, join reordering, and predicate pushdown
  • Statistics Management: Table statistics, histogram updates, and query planner behavior
  • Partitioning Strategies: Range, list, hash partitioning for large table optimization
  • Join Optimization: Nested loop, hash join, merge join selection and tuning
  • Materialized Views: Pre-aggregation strategies, refresh patterns, and query rewriting
  • Window Functions: Optimizing ROW_NUMBER, LAG/LEAD, and complex analytics queries
  • Query Caching: Result caching, prepared statements, and connection pooling
  • Database-Specific Features: PostgreSQL (BRIN, GIN), MySQL (covering indexes), SQL Server (columnstore)

Primary Tools & Technologies​

Query Analysis:

  • Database EXPLAIN/ANALYZE (PostgreSQL, MySQL, SQL Server)
  • pgAdmin, MySQL Workbench, SQL Server Management Studio
  • pgBadger, pt-query-digest (PostgreSQL/MySQL log analysis)

Performance Monitoring:

  • pg_stat_statements (PostgreSQL query stats)
  • MySQL Performance Schema
  • SQL Server Query Store
  • SolarWinds Database Performance Analyzer

Query Optimization:

  • Database-native query optimizers
  • Query hints and plan guides
  • Index Advisor tools (Azure SQL, AWS RDS Performance Insights)

Profiling & Tracing:

  • Datadog APM, New Relic Database Monitoring
  • SolarWinds Database Performance Analyzer
  • pganalyze (PostgreSQL performance insights)

Load Testing:

  • Apache JMeter (database load testing)
  • pgbench (PostgreSQL benchmarking)
  • sysbench (MySQL benchmarking)

Integration Points​

Upstream Dependencies:

  • Data Architecture: Schema design directly impacting query performance
  • Data Transformation: Optimizing ETL/ELT query patterns
  • Streaming Data: Real-time query optimization for streaming analytics

Downstream Consumers:

  • API Performance: Backend query optimization for API response times
  • Data Visualization: Optimizing BI tool queries and dashboard load times
  • Analytics: Accelerating report generation and ad-hoc queries

Cross-Functional:

  • Performance Engineering: System-level optimization (CPU, memory, I/O)
  • Monitoring & Alerting: Slow query detection and alerting thresholds
  • Capacity Planning: Database sizing based on query patterns

Status​

Master Plan Available - Comprehensive guidance for SQL query optimization, covering indexing, execution plans, query rewriting, and database-specific tuning strategies.

Part of the Data Engineering skill collection focused on maximizing database query performance.