Modern applications often demand lightning-fast performance from their databases, whether they’re handling large transactional workloads or complex analytical queries. SQL Server’s in-memory OLTP feature addresses these needs by using memory-optimized tables and natively compiled stored procedures to boost throughput and reduce latency. This post provides an overview of natively compiled stored procedures, how to create them, and best practices for performance monitoring and maintenance.
Category: Query Optimization
SQL Server 2019 and the Memory Grant
When SQL Server runs a query, it needs memory for operations like sorting and joining data. It also relies on memory during query compilation to hold intermediate plans while the Query Optimizer finds the best execution strategy. In parallel processing scenarios, the memory requirement grows even further. SQL Server manages this by pre-allocating memory for each query through the SQL Server Operating System (SQLOS). This process ensures that no single query can monopolize the server’s memory
Exploring Spinlocks and Latch Contention in SQL Server
High concurrency can expose subtle performance bottlenecks in SQL Server, particularly those stemming from spinlocks and latch contention. Both mechanisms exist to synchronize access to shared data structures, yet they operate differently and require distinct troubleshooting approaches. By recognizing how they work and knowing what causes them to overload a system, DBAs can reduce CPU spikes, timeouts, and overall application slowdowns.
Reading SQL Server’s XML Deadlock Report Captured by the system_health Event
SQL Server includes an Extended Events session called system_health, which runs by default and, among other things, captures information about deadlocks as they occur. When two or more sessions block each other in such a way that no progress can be made (a deadlock), SQL Server chooses one session as the “victim,” rolls back its transaction, and frees resources so other sessions can continue. By reviewing the deadlock report in the system_health session’s XML output, you can see precisely why the deadlock happened and identify which queries or procedures were involved.
Optimizing Table Width and Data Types in SQL Server
Organizing data effectively in SQL Server can be a juggling act. You may be tempted to make tables as all-encompassing as possible by giving columns very large data types or piling on extra fields for convenience. While this seems harmless in the short term, it can lead to heavier storage requirements, slower queries, and frequent obstacles when updating the schema. Narrower tables, carefully chosen data types, and a normalized design often work together to keep a database agile and efficient.
Handling Compatibility Level Changes During SQL Server Upgrades
Compatibility levels determine how certain features of SQL Server behave, allowing databases to maintain functionality even as the server itself evolves. However, changing compatibility levels requires careful consideration to balance the benefits of new features against the potential risks of disrupting existing applications. This blog explores the importance of handling compatibility level changes thoughtfully during SQL Server upgrades, highlighting the risks of making changes too hastily and the advantages of adopting new compatibility levels within a reasonable timeframe.
Leveraging SQL Server 2019’s Last Known Actual Query Plan for Troubleshooting
Troubleshooting production performance issues is often challenging because detailed query execution data can vanish before you realize there’s a problem. Many times, you end up piecing together incomplete clues from runtime statistics or the plan cache. Fortunately, SQL Server 2019 introduced a powerful feature to address this pain point: the Last Known Actual Query Plan.
Using sp_getapplock to Prevent Concurrent Execution of Stored Procedures in SQL Server
In multi-user database environments, ensuring the integrity and consistency of data is essential. One common challenge is preventing multiple instances of the same stored procedure from executing at the same time, which can lead to data conflicts, race conditions, and unpredictable results. To address this, SQL Server provides a powerful tool called sp_getapplock. This post explains what sp_getapplock is, what you are actually locking when you use it, how to implement it to prevent concurrent executions of a stored procedure, and the difference between transaction-level and session-level locks.
SQL Server’s Query Store: Understanding Plan Forcing and Performance Optimization
The Query Store in SQL Server is a powerful feature that enables database administrators and developers to track and analyze query performance over time. By storing runtime statistics and execution plans, it provides invaluable insights into how queries behave and how they can be optimized. This blog looks into the mechanics of the Query Store, the necessity of plan forcing, and how to effectively use it to stabilize and enhance query performance.
Determining When to Optimize SQL Server Workloads Versus Upgrading Hardware
When your SQL Server isn’t performing as expected, it’s tempting to think that upgrading hardware is the quick fix. More CPUs, extra memory, faster disks—they all sound like solutions that should solve the problem. But before you start investing in new equipment, it’s worth taking a step back to see if optimization can address the issues.