A regular view is a stored query that executes each time it's referenced, while a materialized view stores the result set physically. Materialized views offer better performance for complex queries but require storage and maintenance for data freshness.
WITH SCHEMABINDING prevents changes to referenced objects that would affect the view's definition. It's required for indexed views and helps maintain data integrity by preventing unauthorized schema changes.
Partitioned views combine data from multiple tables using UNION ALL. Consider partition elimination, constraint requirements, and performance impact. Ensure proper indexing and maintenance strategies.
Manage concurrency using appropriate isolation levels, proper transaction handling, and consideration of scope. Implement proper error handling and deadlock mitigation strategies.
Implement changes using proper version control, testing procedures, and impact analysis. Consider dependent objects, security implications, and backward compatibility.
Consider query patterns, update frequency, storage requirements, and maintenance overhead. Ensure proper statistics maintenance and monitor performance impact.
Implement appropriate error handling for view operations, consider impact of base table errors, and provide meaningful error messages. Handle NULL values and edge cases appropriately.
An indexed view physically stores its result set with a unique clustered index. It's useful for queries with expensive computations or aggregations that are frequently accessed but rarely updated. Consider maintenance overhead and storage requirements.
Temporary tables (#temp) are stored in tempdb with statistics and support indexes, while table variables (@table) are memory-optimized and have limited statistics. Temp tables persist until dropped or session ends, while table variables have procedure-level scope.
Optimize views by avoiding SELECT *, using appropriate indexes, limiting subquery usage, considering indexed views for frequent queries, and ensuring base table optimization. Consider the impact of view nesting and complexity on query performance.
Local temp tables (#table) are visible only to the creating session, while global temp tables (##table) are visible to all sessions. Use global temp tables for cross-session data sharing, but consider concurrency and cleanup implications.
Maintain consistency through refresh strategies (complete or incremental), appropriate refresh timing, and tracking of base table changes. Consider performance impact and business requirements for data freshness.
Implement explicit cleanup in stored procedures, use appropriate scope management, consider session handling, and implement error handling for cleanup. Monitor tempdb usage and implement regular maintenance procedures.
Implement comprehensive testing including performance, security, data accuracy, and edge cases. Consider impact of data volume and maintain test cases for regression testing.
Implement security using GRANT/DENY permissions, row-level security, column filtering, and schema binding when needed. Views can provide controlled access to sensitive data while hiding underlying table structures.
Minimize view nesting to avoid performance issues, consider materialization for complex views, analyze execution plans, and maintain clear documentation. Balance abstraction benefits against performance impact.
Implement RLS using filtered views, inline table-valued functions, or security policies. Consider performance impact, maintenance requirements, and security boundary effectiveness.
View resolution affects query optimization, with nested views potentially causing performance issues. Consider materialization, indexing strategies, and query plan analysis for optimal performance.
Implement dynamic filtering using parameterized views, inline table-valued functions, or CROSS APPLY. Consider performance impact and maintenance requirements of different approaches.
Use consistent naming conventions, document purpose and dependencies, maintain version history, and include performance considerations. Clear documentation helps maintain and troubleshoot views effectively.
Consider publication requirements, filter complexity, maintenance overhead, and performance impact. Ensure views work consistently across replicated environments.
CTEs provide better readability, are scope-limited to a single statement, and don't require cleanup. Temporary tables offer persistence, reuse, and index support. Choose based on use case requirements.
Use views to provide transparent access to archived data, implement partitioned views for historical data, and consider performance implications of cross-archive queries.
A view is a virtual table based on a SELECT query. Benefits include data abstraction, security through column/row filtering, query simplification, and data consistency. Views can hide complexity and provide a secure interface to underlying tables.
Views are updateable if they reference only one base table, don't include GROUP BY, DISTINCT, or aggregates, and don't use complex joins. Updates must map to single base table rows and respect all constraints.
Consider proper indexing, statistics maintenance, batch processing, and memory management. Monitor tempdb performance and implement appropriate cleanup strategies.
Configure proper tempdb files and sizes, monitor usage patterns, implement appropriate cleanup, and consider file placement and IO patterns.
Consider performance impact, maintenance windows, dependency management, and error handling. Implement appropriate logging and monitoring for ETL operations.
Manage schema changes through proper version control, impact analysis, and testing procedures. Consider dependent objects and implement appropriate update strategies.
