The new parallel buffer scan feature in SQL Server 2022 improves the performance of Buffer Pool scan operations on large-memory machines by utilizing multiple CPU cores. Customers running SQL Server on large-memory machines (e.g. TBs of memory) can see up to 4 ~ 20 times faster executions on some scenarios which has been slow due to Buffer Pool scan. Those scenarios include creating a new database, backup/restore operations, AlwaysOn failover, file drop, and DBCC check operations. Internal operations (e.g. checkpoint) that requires Buffer Pool scan will also get the benefits. The parallel scan feature also improves the Buffer Pool scan performance of small databases residing on large-memory machines.
Parallel Buffer Scan in SQL Server 2022
Background: Prior to SQL Server 2022, bulk insert and columnstore index build operations often relied on a single-threaded or limited parallelism approach for buffering and scanning data. This could lead to performance bottlenecks, especially when dealing with large volumes of data.
Parallelism Enhancement: With SQL Server 2022, Parallel Buffer Scan significantly enhances the parallelism and performance of these data ingestion operations.
Key Features and Benefits:
- Increased Parallelism: Parallel Buffer Scan allows multiple threads to simultaneously scan and buffer data from the source, leveraging the power of modern multi-core processors.
- Improved Data Throughput: The parallel processing of data buffering and scanning reduces the time required for data ingestion tasks, leading to improved data throughput and reduced overall processing time.
- Reduced Lock Contention: Parallel Buffer Scan can help reduce lock contention during data ingestion, leading to better concurrency and minimizing contention-related delays.
- Optimized Resource Utilization: SQL Server 2022 intelligently manages system resources to ensure optimal parallelism without overloading the system.
- Scalability: The feature scales with the hardware, making it suitable for both small and large-scale data ingestion scenarios.
Use Cases:
- Bulk Data Loading: Parallel Buffer Scan is particularly valuable for scenarios where large volumes of data need to be ingested into SQL Server, such as ETL (Extract, Transform, Load) processes.
- Columnstore Index Build: It significantly improves the performance of building and rebuilding columnstore indexes, which are often used for analytics workloads.
- Configuration: Parallel Buffer Scan is enabled by default in SQL Server 2022, and it dynamically adjusts the degree of parallelism based on the system’s capabilities and workload. However, you can also use query hints and trace flags to control its behavior in specific situations.
SQL Server 2022’s Parallel Buffer Scan is a significant enhancement that boosts the performance of data ingestion operations by introducing parallelism in the buffering and scanning phases. It’s particularly valuable for bulk data loading and columnstore index builds, and it dynamically adjusts to maximize resource utilization. This feature can significantly benefit organizations dealing with large-scale data processing and analytics workloads.
SQL Server 2022’s Parallel Buffer Scan works by enhancing the parallelism of data ingestion operations, such as bulk inserts and columnstore index builds, to improve the overall throughput and reduce processing time. Here’s how it works:
Source Data Reading: The process begins by reading data from the source, which could be flat files, data streams, or other sources.
Data Buffering: In traditional SQL Server versions, the source data was read and buffered in a single-threaded or limited parallelism manner. With Parallel Buffer Scan, multiple threads are employed to read and buffer data concurrently. Each thread is responsible for buffering a portion of the data.
Parallel Scanning: After buffering, the data is scanned for further processing. In this phase, each buffered data segment is processed in parallel by multiple threads. Each thread independently scans and processes its segment of data.
Concurrency and Locking: Parallel Buffer Scan is designed to minimize lock contention during the data processing phase. It helps reduce contention-related delays and improves concurrency, allowing multiple transactions to proceed simultaneously.
Resource Management: SQL Server 2022’s Parallel Buffer Scan dynamically manages system resources to optimize parallelism without overloading the system. This ensures that the system remains responsive and performs well even during data-intensive operations.
Degree of Parallelism (DOP): The degree of parallelism, or the number of threads used in parallel processing, is determined by SQL Server based on factors such as the available system resources, workload, and the configuration settings. The parallelism is adjusted dynamically to balance performance and resource utilization.
Monitoring and Control: Database administrators can monitor the behavior and performance of Parallel Buffer Scan using SQL Server performance counters, Extended Events, and Dynamic Management Views (DMVs). Additionally, query hints and trace flags can be used to control the degree of parallelism in specific scenarios.
Scalability: Parallel Buffer Scan is scalable and can take advantage of modern multi-core processors and memory configurations. This makes it suitable for both small-scale and large-scale data processing scenarios.
Use Cases: This feature is particularly beneficial for scenarios where large volumes of data need to be ingested into SQL Server or when building/rebuilding columnstore indexes, which are commonly used in data warehousing and analytics workloads.
Overall, Parallel Buffer Scan enhances data ingestion performance by parallelizing the buffering and scanning phases of data processing. By allowing multiple threads to work concurrently, it reduces processing time and improves throughput, making SQL Server 2022 more efficient in handling large-scale data operations.
Monitoring: You can monitor the performance and resource utilization related to Parallel Buffer Scan through SQL Server performance counters, Extended Events, and DMVs (Dynamic Management Views).
Monitoring SQL Server 2022’s Parallel Buffer Scan involves tracking its performance and resource utilization to ensure that it’s functioning optimally. You can use various SQL Server tools, performance counters, Extended Events, and Dynamic Management Views (DMVs) to monitor Parallel Buffer Scan. Here are steps and tools you can use:
Performance Counters:
Batch Requests/sec: Monitor the rate of batch requests per second, as high data ingestion rates can indicate the need for parallel processing.
SQL Server: SQL Statistics\Batch Requests/sec: Track the batch request rate.
SQL Server: Buffer Manager\Page reads/sec: Keep an eye on page read rates, as efficient parallel processing should reduce the need for reading data pages.
SQL Server: Buffer Manager\Page writes/sec: Similarly, monitor page write rates to ensure data is written efficiently.
Extended Events: Configure Extended Events to capture events related to parallelism and data loading. Events like sp_statement_completed and query_execution_stats can provide insights into the execution of parallel queries.
Dynamic Management Views (DMVs):
sys.dm_exec_requests: Monitor active requests to check if any of them are using parallelism.
sys.dm_exec_sessions: Analyze session-level information to identify parallel sessions.
sys.dm_os_waiting_tasks: Check for tasks waiting on parallelism-related resources.
Query and Execution Plans: Use query execution plans to analyze whether queries are taking advantage of parallelism. The presence of parallelism operators in execution plans (e.g., parallel scans or parallel sorts) indicates parallel processing.
SQL Server Management Studio (SSMS): Use SSMS to view live activity and execution plans. Activity Monitor provides a graphical representation of resource usage and running queries.
Custom Scripts: Develop custom scripts or automation to regularly collect and analyze performance-related data. For example, you can create PowerShell scripts that query relevant DMVs and performance counters.
SQL Server Agent Jobs: Schedule SQL Server Agent jobs to run periodic queries or scripts that monitor Parallel Buffer Scan-related metrics and report any anomalies.
Third-party Monitoring Tools: Consider using third-party monitoring and performance tuning tools that are designed to capture and analyze SQL Server performance metrics. These tools often provide advanced visualization and alerting capabilities.
Alerting: Set up alerts based on performance thresholds to proactively detect issues related to parallel processing or resource utilization.
Documentation: Maintain documentation of monitoring processes, including thresholds and performance baselines, to facilitate troubleshooting and performance tuning.
Conclusion
It’s essential to establish a baseline for your system’s normal behavior and performance, as this will help you detect anomalies and potential issues related to Parallel Buffer Scan. Regularly review and analyze the collected data to ensure that SQL Server is efficiently using parallelism during data ingestion operations.
By monitoring Parallel Buffer Scan and related metrics, you can identify performance bottlenecks, optimize parallelism settings, and ensure that your SQL Server environment is effectively utilizing this feature for improved data ingestion performance.