ApsaraDB RDS:What do I do if the CPU utilization of an ApsaraDB RDS for SQL Server instance is high?

Troubleshooting

When multiple threads are used to process tasks in parallel, the amount of data that is processed by each thread is different, and CXPACKET waits may occur. A large number of CXPACKET waits cause high CPU utilization. You can use Activity Monitor in SQL Server Management Studio (SSMS) or execute the following SQL statements several times to check whether a large number of CXPACKET waits exist.

WITH [Waits] AS (
SELECT [wait_type],
       [wait_time_ms] / 1000.0 AS [WaitS],
       ([wait_time_ms] - [signal_wait_time_ms]) / 1000.0 AS [ResourceS],
       [signal_wait_time_ms] / 1000.0 AS [SignalS],
       [waiting_tasks_count] AS [WaitCount],
       100.0 * [wait_time_ms] / SUM ([wait_time_ms]) OVER() AS [Percentage],
                                    ROW_NUMBER() OVER(
                                                      ORDER BY [wait_time_ms] DESC) AS [RowNum]
FROM sys.dm_os_wait_stats
WHERE [wait_type] NOT IN ( N'BROKER_EVENTHANDLER',
                            N'BROKER_RECEIVE_WAITFOR',
                             N'BROKER_TASK_STOP',
                              N'BROKER_TO_FLUSH',
                               N'BROKER_TRANSMITTER',
                                N'CHECKPOINT_QUEUE',
                                 N'CHKPT',
                                  N'CLR_AUTO_EVENT',
                                   N'CLR_MANUAL_EVENT',
                                    N'CLR_SEMAPHORE', -- Maybe uncomment these four if you have mirroring issues N'DBMIRROR_DBM_EVENT', N'DBMIRROR_EVENTS_QUEUE', N'DBMIRROR_WORKER_QUEUE', N'DBMIRRORING_CMD', N'DIRTY_PAGE_POLL', N'DISPATCHER_QUEUE_SEMAPHORE', N'EXECSYNC', N'FSAGENT', N'FT_IFTS_SCHEDULER_IDLE_WAIT', N'FT_IFTSHC_MUTEX', -- Maybe uncomment these six if you have AG issues N'HADR_CLUSAPI_CALL', N'HADR_FILESTREAM_IOMGR_IOCOMPLETION', N'HADR_LOGCAPTURE_WAIT', N'HADR_NOTIFICATION_DEQUEUE', N'HADR_TIMER_TASK', N'HADR_WORK_QUEUE', N'KSOURCE_WAKEUP', N'LAZYWRITER_SLEEP', N'LOGMGR_QUEUE', N'MEMORY_ALLOCATION_EXT', N'ONDEMAND_TASK_QUEUE', N'PREEMPTIVE_XE_GETTARGETSTATE', N'PWAIT_ALL_COMPONENTS_INITIALIZED', N'PWAIT_DIRECTLOGCONSUMER_GETNEXT', N'QDS_PERSIST_TASK_MAIN_LOOP_SLEEP', N'QDS_ASYNC_QUEUE', N'QDS_CLEANUP_STALE_QUERIES_TASK_MAIN_LOOP_SLEEP', N'QDS_SHUTDOWN_QUEUE', N'REDO_THREAD_PENDING_WORK', N'REQUEST_FOR_DEADLOCK_SEARCH', N'RESOURCE_QUEUE', N'SERVER_IDLE_CHECK', N'SLEEP_BPOOL_FLUSH', N'SLEEP_DBSTARTUP', N'SLEEP_DCOMSTARTUP', N'SLEEP_MASTERDBREADY', N'SLEEP_MASTERMDREADY', N'SLEEP_MASTERUPGRADED', N'SLEEP_MSDBSTARTUP', N'SLEEP_SYSTEMTASK', N'SLEEP_TASK', N'SLEEP_TEMPDBSTARTUP', N'SNI_HTTP_ACCEPT', N'SP_SERVER_DIAGNOSTICS_SLEEP', N'SQLTRACE_BUFFER_FLUSH', N'SQLTRACE_INCREMENTAL_FLUSH_SLEEP', N'SQLTRACE_WAIT_ENTRIES', N'WAIT_FOR_RESULTS', N'WAITFOR', N'WAITFOR_TASKSHUTDOWN', N'WAIT_XTP_RECOVERY', N'WAIT_XTP_HOST_WAIT', N'WAIT_XTP_OFFLINE_CKPT_NEW_LOG', N'WAIT_XTP_CKPT_CLOSE', N'XE_DISPATCHER_JOIN', N'XE_DISPATCHER_WAIT', N'XE_TIMER_EVENT') AND [waiting_tasks_count] > 0 )

  SELECT MAX ([W1].[wait_type]) AS [WaitType],
             CAST (MAX ([W1].[WaitS]) AS DECIMAL (16, 2)) AS [Wait_S],
                  CAST (MAX ([W1].[ResourceS]) AS DECIMAL (16, 2)) AS [Resource_S],
                       CAST (MAX ([W1].[SignalS]) AS DECIMAL (16, 2)) AS [Signal_S],
                            MAX ([W1].[WaitCount]) AS [WaitCount],
                                CAST (MAX ([W1].[Percentage]) AS DECIMAL (5, 2)) AS [Percentage],
                                     CAST ((MAX ([W1].[WaitS]) / MAX ([W1].[WaitCount])) AS DECIMAL (16, 4)) AS [AvgWait_S],
                                          CAST ((MAX ([W1].[ResourceS]) / MAX ([W1].[WaitCount])) AS DECIMAL (16, 4)) AS [AvgRes_S],
                                               CAST ((MAX ([W1].[SignalS]) / MAX ([W1].[WaitCount])) AS DECIMAL (16, 4)) AS [AvgSig_S]
  FROM [Waits] AS [W1]
  INNER JOIN [Waits] AS [W2] ON [W2].[RowNum] <= [W1].[RowNum]
GROUP BY [W1].[RowNum]
HAVING SUM ([W2].[Percentage]) - MAX([W1].[Percentage]) < 95;

Solutions

Symptom

The loads on an RDS instance are heavy. However, no slow queries occur or slow queries are not the root cause of heavy loads. The curves of queries per second (QPS) and CPU utilization match. This problem is common in optimized online transaction systems, such as order systems, and popular web applications that have high read rates.

Characteristics

The QPS is high. Query operations are simple. The query efficiency is high. Queries are difficult to be optimized.

Solutions

We recommend that you optimize the application architecture or upgrade the instance type.

• Upgrade the instance type of your RDS instance to increase CPU resources. For more information, see Change the specifications of an ApsaraDB RDS for SQL Server instance.

• Optimize queries to reduce execution costs and improve application scalability. You can optimize logic I/O operations and minimize the number of rows that a query needs to read in a table.

Symptom

Slow SQL queries occur. The QPS and CPU utilization curves do not match. Some SQL statements that consume multiple CPU resources involve large number of I/O operations.

Characteristics

The QPS is low. The query efficiency is low. A large amount of data needs to be scanned during queries. Queries can be optimized.

Solutions

• Check whether indexes are created for the large tables that are involved in a query. Check the execution plan of the query and optimize the full table scan. You can view suggestions on missing indexes in the execution plan.

  

• Use CloudDBA to check performance issues. For more information, see View the storage information of an ApsaraDB RDS for SQL Server instance.