MSDN

Key Performance Areas

Advanced Query Tuning Strategies

Achieving optimal query performance is a continuous process. This section covers advanced techniques to fine-tune your T-SQL queries for maximum efficiency.

• Minimize data retrieval by selecting only necessary columns.
• Avoid using `SELECT *`.
• Use appropriate JOIN types and ensure join conditions are selective.
• Consider using CTEs and temporary tables judiciously.
• Understand the impact of scalar functions in WHERE clauses.

Understanding and Analyzing Execution Plans

Execution plans are the roadmap of how SQL Server executes your queries. Mastering their interpretation is crucial for identifying bottlenecks.

Key elements to look for:

• High-cost operators (e.g., Table Scan, Sort, Hash Match).
• Warnings (e.g., Implicit Conversion, Spills).
• Row counts vs. estimated row counts.
• Index Seek vs. Index Scan.

-- Example of generating an Actual Execution Plan
SET SHOWPLAN_ALL ON;
GO
SELECT TOP 10 * FROM YourTable WHERE YourColumn = 'SomeValue';
GO
SET SHOWPLAN_ALL OFF;
GO

Importance of Statistics for Query Performance

Statistics provide the query optimizer with information about the data distribution within tables and indexes, enabling it to generate efficient execution plans.

• Ensure statistics are up-to-date.
• Understand auto-update statistics and its limitations.
• Consider manual creation or update of statistics for critical workloads.
• Monitor statistics freshness and correlation.

Dealing with Parameter Sniffing Issues

Parameter sniffing occurs when a stored procedure's execution plan is cached based on the parameter values used during its first execution. Subsequent executions with different parameter values may experience suboptimal performance.

• Use `OPTION (RECOMPILE)` for stored procedures with highly variable parameters.
• Employ query hints like `OPTIMIZE FOR` or `OPTIMIZE FOR UNKNOWN`.
• Consider using local variables within the procedure.

Choosing the Right Index Types

The choice of index type significantly impacts data retrieval speed and data modification overhead.

• Clustered Index: Defines the physical storage order of data in the table. Only one per table.
• Non-Clustered Index: A separate structure containing key values and pointers to data rows. Multiple allowed per table.
• Columnstore Index: Optimized for data warehousing and analytics workloads, offering high compression and query performance for large datasets.

Effective Index Maintenance Techniques

Regular index maintenance is essential to prevent performance degradation due to fragmentation and outdated statistics.

• Reorganize for minor fragmentation.
• Rebuild for significant fragmentation or to update statistics.
• Schedule maintenance tasks during off-peak hours.

Identifying and Utilizing Missing Indexes

SQL Server can suggest missing indexes based on queries being executed. These suggestions, found in DMVs, can be invaluable for performance tuning.

-- Query to find missing index suggestions
SELECT
    mig.avg_total_user_statements,
    mig.avg_user_statements,
    mig.avg_driver_page_accesses,
    mid.statement AS unemp_statement,
    'CREATE INDEX index_name ON ' + mid.statement + ' (' +SUBSTRING(mid.equality_columns,1,LEN(mid.equality_columns)-1) +')' AS create_index_statement
FROM sys.dm_db_missing_index_groups AS mig
INNER JOIN sys.dm_db_missing_index_group_stats AS migs ON mig.index_group_handle = migs.group_handle
INNER JOIN sys.dm_db_missing_indices AS mid ON mig.index_handle = mid.index_handle
WHERE mid.object_id = OBJECT_ID('YourTableName')
ORDER BY mig.avg_total_user_statements DESC;

Managing Index Fragmentation

Fragmentation occurs when index pages are not stored contiguously. This can lead to slower data retrieval.

• Internal Fragmentation: Empty space within index pages.
• External Fragmentation: Pages out of order.
• Monitor fragmentation levels using DMVs.

Leveraging Performance Monitor Counters

Performance Monitor (PerfMon) provides real-time metrics for SQL Server and the operating system, helping to identify resource contention.

• Key SQL Server counters: `SQLServer:General Statistics` (e.g., `User Connections`), `SQLServer:Buffer Manager` (e.g., `Page life expectancy`), `SQLServer:Locks`.
• Key OS counters: `Processor` (`% Processor Time`), `Memory` (`Available MBytes`), `PhysicalDisk` (`Avg. Disk sec/Read`, `Avg. Disk sec/Write`).

Using Dynamic Management Views (DMVs)

DMVs offer detailed insights into SQL Server's internal state and performance metrics.

• sys.dm_exec_query_stats: Query performance statistics.
• sys.dm_os_wait_stats: Information about waits encountered by SQL Server.
• sys.dm_db_index_physical_stats: Index fragmentation and size.
• sys.dm_io_virtual_file_stats: I/O statistics for database files.

Analyzing Wait Statistics

Wait statistics reveal the primary reasons why SQL Server threads are blocking or delaying operations, pointing directly to performance bottlenecks.

• Common waits: `PAGEIOLATCH_SH`, `CXPACKET`, `LCK_M_X`, `ASYNC_NETWORK_IO`.
• Use DMVs to identify top waits and their associated resources.

Configuring Resource Governor

Resource Governor allows you to manage and prioritize SQL Server workloads by controlling CPU, memory, and I/O resources.

• Define Resource Pools for different workload types.
• Create Workload Groups to map requests to pools.
• Set CPU and Memory limits for Workload Groups.

Hardware Optimization for SQL Server

The underlying hardware plays a critical role in SQL Server performance.

• Adequate RAM for caching and buffer pool.
• Fast storage (SSD/NVMe) for I/O intensive operations.
• Sufficient CPU cores for processing power.
• Network bandwidth for client connections and replication.

Storage Subsystem Performance Tuning

Optimizing your storage is key to mitigating I/O bottlenecks.

• Separate data, log, and tempdb files onto different physical disks/arrays.
• Use RAID configurations that balance performance and redundancy.
• Ensure proper alignment of disk partitions.

Memory Management Best Practices

Effective memory management is crucial for SQL Server's performance.

• Allocate sufficient RAM to SQL Server, but leave enough for the OS.
• Monitor `Page Life Expectancy` as an indicator of buffer pool health.
• Avoid excessive I/O caused by insufficient memory.

Understanding and Tuning Parallelism

SQL Server can execute queries in parallel across multiple CPU cores, but improper configuration can lead to issues.

• Configure `max degree of parallelism` (MAXDOP) appropriately based on your server hardware and workload.
• Understand `Cost Threshold for Parallelism`.
• Monitor `CXPACKET` and `CXCONSUMER` waits.