Diagnosing SQL Server Storage Bottlenecks
By Tom Nonmacher
As a SQL Server Database Administrator, it is crucial to diagnose and resolve storage bottlenecks to ensure optimal performance of your databases. Storage bottlenecks can severely impact your database performance and can potentially cause disruptions in service. This post will walk you through the steps to identify and rectify storage bottlenecks in SQL Server 2016, SQL Server 2017, MySQL 5.7, DB2 11.1, and Azure SQL.
Let's begin with SQL Server 2016 and 2017. One of the first steps in diagnosing storage bottlenecks is to look at wait statistics. The SQL Server engine uses wait statistics to identify resources that queries are waiting for. You can query the sys.dm_os_wait_stats dynamic management view to look at wait statistics.
SELECT * FROM sys.dm_os_wait_stats
ORDER BY wait_time_ms DESC
In the output of this query, look for wait types like PAGEIOLATCH_SH, PAGEIOLATCH_EX, and WRITELOG. These wait types indicate storage related bottlenecks. High values for these wait types could indicate that your SQL Server is experiencing a storage bottleneck.
Moving on to MySQL 5.7, the SHOW GLOBAL STATUS command is a good starting point to identify storage bottlenecks. This command provides you with a wide range of server status information, including key disk usage metrics.
SHOW GLOBAL STATUS LIKE 'Innodb_buffer_pool%';
In the output, pay close attention to Innodb_buffer_pool_reads. This status variable indicates the number of reads that MySQL could not satisfy from the buffer pool, and had to read directly from disk. A high value might indicate a storage bottleneck.
For DB2 11.1, you can use the MON_GET_BUFFERPOOL table function to get information about buffer pool usage.
SELECT * FROM TABLE(MON_GET_BUFFERPOOL(NULL, -2)) AS t;
The column to watch is BP_PHYSICAL_READS. High values for this column may indicate that DB2 is having to read a lot from disk, which could be a symptom of a storage bottleneck.
Lastly, with Azure SQL, you have access to a variety of dynamic management views to help diagnose storage issues. For instance, the sys.dm_db_resource_stats view provides information about data IO, log write, and CPU consumption, which can be useful in identifying storage bottlenecks.
SELECT * FROM sys.dm_db_resource_stats;
In the output, look at the avg_data_io_percent and avg_log_write_percent columns. High values in these columns could indicate storage related bottlenecks. In addition, the sys.dm_io_virtual_file_stats function can provide useful insights into IO statistics at the database file level.
In conclusion, diagnosing SQL Server storage bottlenecks is a critical task for any DBA. Using the correct tools and techniques can help you identify and rectify storage bottlenecks, leading to smoother and more efficient database operations.