In SQL Server Always On Availability Groups, maintaining data consistency during failovers is necessary for high availability and reliability. However, certain aspects of database behavior, such as the generation of values by IDENTITY columns and SEQUENCE objects, can lead to unexpected gaps or jumps after a failover or server restart. This can affect the continuity of sequential values, which is often important in business applications. In this post, we’ll look into how SQL Server handles IDENTITY columns and SEQUENCE objects in an Always On environment, explain the role of caching, and offer strategies to manage or prevent gaps in your sequences during failovers.
Category: Internals
The Hidden Costs of Data Type Decisions in SQL Server
When designing a SQL Server database, the choice of data types is one of the most fundamental decisions that will have a lasting impact on both performance and storage efficiency. Each data type in SQL Server has specific characteristics that determine how data is stored, how much space it consumes, and how it performs in various operations such as indexing, querying, and sorting. Understanding these characteristics and making informed decisions about data types can lead to significant improvements in both the speed and the efficiency of your database systems.
Enhancing Data Integrity: Automatic Page Repair with SQL Server Always On Availability Groups
SQL Server Always On Availability Groups are designed to provide a high-availability and disaster recovery solution that keeps your databases running smoothly even in the face of hardware failures and data corruption. One of the key features supporting this capability is Automatic Page Repair. This feature works behind the scenes to automatically fix corrupted pages in a database, thereby minimizing downtime and preserving data integrity. In this post, we will explore the mechanisms, benefits, and limitations of Automatic Page Repair, highlighting its role in enhancing SQL Server reliability.
A Look at Non-Buffer Latches in SQL Server
In SQL Server, latches are lightweight synchronization mechanisms that keep in-memory data structures consistent and safe. They are key to managing access when multiple threads are working with these structures at the same time. SQL Server uses two main types of latches: buffer latches and non-buffer latches. While buffer latches protect pages in the buffer pool, non-buffer latches are for other internal memory structures. This post focuses on non-buffer latches, explaining what they are, why they’re important, and what excessive non-buffer latch waits might mean.
Strategies for Optimizing Version Ghost Record Cleanup in SQL Server
This blog explores the challenges and strategies for managing version ghost records in SQL Server. It discusses issues like single-threaded cleanup tasks, long-running transactions, and locking levels that impact the cleanup process. The post provides actionable strategies such as updating SQL Server, utilizing trace flags, and regular index maintenance to improve ghost record cleanup efficiency.
SQL Server AG Readonly Secondaries and their Associated Overhead
In SQL Server Always On Availability Groups, configuring read-access for one or more secondary replicas introduces additional overhead to the primary databases. This overhead, specifically a 14-byte addition to modified, inserted, or deleted data rows, is essential for the row versioning feature that ensures data consistency across replicas. Row versioning allows secondary replicas to perform read operations without being affected by ongoing changes on the primary replica, ensuring a consistent view of the data. Understanding this overhead and its impact on storage and performance is crucial for optimizing SQL Server environments.
Five SQL Server Error Log Messages You Should Care About
SQL Server error logs are a treasure trove of information, containing important details about the health and performance of your database server. These logs are essential for troubleshooting issues, identifying potential problems before they escalate, and ensuring the overall stability of your SQL Server environment. By regularly monitoring and understanding the contents of these logs, database administrators (DBAs) can proactively manage their servers and avoid catastrophic failures. In this blog post, we will highlight five specific error log messages that should immediately catch your attention, explain what they mean, and outline the steps you should take when you encounter them.
Understanding SQL Server Checkpoints
In SQL Server, checkpoints are essential for maintaining data integrity and ensuring efficient recovery. During a checkpoint, changes made in memory (dirty pages) are written to disk, ensuring that the database state can be accurately recovered in the event of a failure. This process is governed by a mechanism called Write-Ahead Logging (WAL), which ensures that all log records related to changes are written to disk before the corresponding data pages.
Configuring Max Degree of Parallelism for Heavy SQL Server Workloads
In SQL Server, the Max Degree of Parallelism (MAXDOP) is a configuration setting that dictates the maximum number of processor cores that can be used for the execution of a single query. Properly configuring MAXDOP is crucial for optimizing performance, especially for databases with heavy workloads. This blog post provides detailed guidance on understanding and configuring MAXDOP and the cost threshold for parallelism to ensure optimal performance in high resource-consuming environments.
Understanding the Importance of Bucket Counts in Hash Indexes for Memory-Optimized Tables
In the realm of memory-optimized tables, every table must have at least one index to connect its rows. Notably, every index on such tables is also memory-optimized. Among the various types of indexes available, hash indexes stand out for their unique structure and functionality. Understanding the importance of bucket counts in hash indexes for memory-optimized tables is crucial for maintaining optimal performance in SQL Server. This post looks at the structure of hash indexes, how to specify and adjust bucket counts, and the consequences of incorrect bucket counts. Learn best practices for planning and optimizing your hash indexes to ensure efficient data management and avoid common performance pitfalls.