Monitoring performance by using the Query Store
The SQL Server Query Store feature provides you with insight on query plan choice and performance. It simplifies performance troubleshooting by helping you quickly find performance differences caused by query plan changes. Query Store automatically captures a history of queries, plans, and runtime statistics, and retains these for your review. It separates data by time windows so you can see database usage patterns and understand when query plan changes happened on the server. You can configure query store using the ALTER DATABASE SET option.
For information about operating the Query Store in Azure SQL Database, see Operating the Query Store in Azure SQL Database.
If you are using Query Store for just in time workload insights in SQL Server 2016 (13.x), plan to install the performance scalability fixes in KB 4340759 as soon as possible.
Enabling the Query Store
Query Store is not active for new databases by default.
Use the Query Store Page in SQL Server Management Studio
In Object Explorer, right-click a database, and then click Properties.
Requires at least version 16 of Management Studio.
In the Database Properties dialog box, select the Query Store page.
In the Operation Mode (Requested) box, select Read Write.
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Use Transact-SQL Statements
Use the ALTER DATABASE statement to enable the query store. For example:
ALTER DATABASE AdventureWorks2012 SET QUERY_STORE (OPERATION_MODE = READ_WRITE);
For more syntax options related to the query store, see ALTER DATABASE SET Options (Transact-SQL).
You cannot enable the query store for the master or tempdb database.
For information on enabling Query Store and keeping it adjusted to your workload, refer to Best Practice with the Query Store.
Information in the Query Store
Execution plans for any specific query in SQL Server typically evolve over time due to a number of different reasons such as statistics changes, schema changes, creation/deletion of indexes, etc. The procedure cache (where cached query plans are stored) only stores the latest execution plan. Plans also get evicted from the plan cache due to memory pressure. As a result, query performance regressions caused by execution plan changes can be non-trivial and time consuming to resolve.
Since the query store retains multiple execution plans per query, it can enforce policies to direct the query processor to use a specific execution plan for a query. This is referred to as plan forcing. Plan forcing in Query Store is provided by using a mechanism similar to the USE PLAN query hint, but it does not require any change in user applications. Plan forcing can resolve a query performance regression caused by a plan change in a very short period of time.
Query Store collects plans for DML Statements such as SELECT, INSERT, UPDATE, DELETE, MERGE, and BULK INSERT.
Wait stats are another source of information that helps to troubleshoot performance in SQL Server. For a long time, wait statistics were available only on instance level, which made it hard to backtrack it to the actual query. In SQL Server 2017 and Azure SQL Database we added another dimension in Query Store that tracks wait stats.
Common scenarios for using the Query Store feature are:
- Quickly find and fix a plan performance regression by forcing the previous query plan. Fix queries that have recently regressed in performance due to execution plan changes.
- Determine the number of times a query was executed in a given time window, assisting a DBA in troubleshooting performance resource problems.
- Identify top n queries (by execution time, memory consumption, etc.) in the past x hours.
- Audit the history of query plans for a given query.
- Analyze the resource (CPU, I/O, and Memory) usage patterns for a particular database.
- Identify top n queries that are waiting on resources.
- Understand wait nature for a particular query or plan.
The query store contains three stores:
- a plan store for persisting the execution plan information.
- a runtime stats store for persisting the execution statistics information.
- a wait stats store for persisting wait statistics information.
The number of unique plans that can be stored for a query in the plan store is limited by the max_plans_per_query configuration option. To enhance performance, the information is written to the stores asynchronously. To minimize space usage, the runtime execution statistics in the runtime stats store are aggregated over a fixed time window. The information in these stores is visible by querying the query store catalog views.
The following query returns information about queries and plans in the query store.
SELECT Txt.query_text_id, Txt.query_sql_text, Pl.plan_id, Qry.* FROM sys.query_store_plan AS Pl INNER JOIN sys.query_store_query AS Qry ON Pl.query_id = Qry.query_id INNER JOIN sys.query_store_query_text AS Txt ON Qry.query_text_id = Txt.query_text_id ;
Use the Regressed Queries Feature
After enabling the query store, refresh the database portion of the Object Explorer pane to add the Query Store section.
Select Regressed Queries to open the Regressed Queries pane in SQL Server Management Studio. The Regressed Queries pane shows you the queries and plans in the query store. Use the drop down boxes at the top to filter queries based on various criteria: Duration (ms) (Default), CPU Time (ms), Logical Reads (KB), Logical Writes (KB), Physical Reads (KB), CLR Time (ms), DOP, Memory Consumption (KB), Row Count, Log Memory Used (KB), Temp DB Memory Used (KB), and Wait Time (ms).
Select a plan to see the graphical query plan. Buttons are available to view the source query, force and unforce a query plan, toggle between grid and chart formats, compare selected plans (if more than one is selected), and refresh the display.
To force a plan, select a query and plan, and then click Force Plan. You can only force plans that were saved by the query plan feature and are still retained in the query plan cache.
Finding wait queries
Starting with SQL Server 2017 (14.x) CTP 2.0 and Azure SQL Database, wait statistics per query over time are available in Query Store. In Query Store, wait types are combined into wait categories. The mapping of wait categories to wait types is available in sys.query_store_wait_stats (Transact-SQL).
Select Query Wait Statistics to open the Query Wait Statistics pane in SQL Server Management Studio v18 or higher. The Query Wait Statistics pane shows you a bar chart containing the top wait categories in the Query Store. Use the drop down at the top to select an aggregate criteria for the wait time: avg, max, min, std dev, and total (default).
Select a wait category by clicking on the bar and a detail view on the selected wait category displays. This new bar chart contains the queries that contributed to that wait category.
Use the drop down box at the top to filter queries based on various wait time criteria for the selected wait category: avg, max, min, std dev, and total (default). Select a plan to see the graphical query plan. Buttons are available to view the source query, force, and unforce a query plan, and refresh the display.
Wait categories are combining different wait types into buckets similar by nature. Different wait categories require a different follow up analysis to resolve the issue, but wait types from the same category lead to very similar troubleshooting experiences, and providing the affected query on top of waits would be the missing piece to complete the majority of such investigations successfully.
Here are some examples how you can get more insights into your workload before and after introducing wait categories in Query Store:
|Previous experience||New experience||Action|
|High RESOURCE_SEMAPHORE waits per database||High Memory waits in Query Store for specific queries||Find the top memory consuming queries in Query Store. These queries are probably delaying further progress of the affected queries. Consider using MAX_GRANT_PERCENT query hint for these queries, or for the affected queries.|
|High LCK_M_X waits per database||High Lock waits in Query Store for specific queries||Check the query texts for the affected queries and identify the target entities. Look in Query Store for other queries modifying the same entity, which are executed frequently and/or have high duration. After identifying these queries, consider changing the application logic to improve concurrency, or use a less restrictive isolation level.|
|High PAGEIOLATCH_SH waits per database||High Buffer IO waits in Query Store for specific queries||Find the queries with a high number of physical reads in Query Store. If they match the queries with high IO waits, consider introducing an index on the underlying entity, in order to do seeks instead of scans, and thus minimize the IO overhead of the queries.|
|High SOS_SCHEDULER_YIELD waits per database||High CPU waits in Query Store for specific queries||Find the top CPU consuming queries in Query Store. Among them, identify the queries for which high CPU trend correlates with high CPU waits for the affected queries. Focus on optimizing those queries - there could be a plan regression, or perhaps a missing index.|
The following options are available to configure query store parameters.
Can be READ_WRITE (default) or READ_ONLY.
STALE_QUERY_THRESHOLD_DAYS argument to specify the number of days to retain data in the query store. The default value is 30. For SQL Database Basic edition, default is 7 days.
Determines the frequency at which data written to the query store is persisted to disk. To optimize for performance, data collected by the query store is asynchronously written to the disk. The frequency at which this asynchronous transfer occurs is configured via
DATA_FLUSH_INTERVAL_SECONDS. The default value is 900 (15 min).
Configures the maximum size of the query store. If the data in the query store hits the
MAX_STORAGE_SIZE_MB limit, the query store automatically changes the state from read-write to read-only and stops collecting new data. The default value is 100 MB. For SQL Database Premium edition, default is 1 GB and for SQL Database Basic edition, default is 10 MB.
Determines the time interval at which runtime execution statistics data is aggregated into the query store. To optimize for space usage, the runtime execution statistics in the Runtime Stats Store are aggregated over a fixed time window. This fixed time window is configured via
INTERVAL_LENGTH_MINUTES. The default value is 60.
Controls whether the cleanup process will be automatically activated when total amount of data gets close to maximum size. Can be AUTO (default) or OFF.
Designates if the Query Store captures all queries, or relevant queries based on execution count and resource consumption, or stops adding new queries and just tracks current queries. Can be ALL (capture all queries), AUTO (ignore infrequent and queries with insignificant compile and execution duration) or NONE (stop capturing new queries). The default value on SQL Server (from SQL Server 2016 (13.x) to SQL Server 2017) is ALL, while on Azure SQL Database is AUTO.
An integer representing the maximum number of plans maintained for each query. The default value is 200.
Controls if Query Store captures wait statistics information. Can be OFF or ON (default).
Query the sys.database_query_store_options view to determine the current options of the query store. For more information about the values, see sys.database_query_store_options.
For more information about setting options by using Transact-SQL statements, see Option Management.
Related Views, Functions, and Procedures
View and manage Query Store through Management Studio or by using the following views and procedures.
Query Store Functions
Functions help operations with the Query Store.
Query Store Catalog Views
Catalog views present information about the Query Store.
Query Store Stored Procedures
Stored procedures configure the Query Store.
Key Usage Scenarios
This section provides some guidelines on managing Query Store feature itself.
Is Query Store currently active?
Query Store stores its data inside the user database and that is why it has size limit (configured with
MAX_STORAGE_SIZE_MB). If data in Query Store hits that limit Query Store will automatically change state from read-write to read-only and stop collecting new data.
Query sys.database_query_store_options to determine if Query Store is currently active, and whether it is currently collects runtime stats or not.
SELECT actual_state, actual_state_desc, readonly_reason, current_storage_size_mb, max_storage_size_mb FROM sys.database_query_store_options;
Query Store status is determined by actual_state column. If it's different than the desired status, the
readonly_reason column can give you more information.
When Query Store size exceeds the quota, the feature will switch to readon_only mode.
Get Query Store options
To find out detailed information about Query Store status, execute following in a user database.
SELECT * FROM sys.database_query_store_options;
Setting Query Store interval
You can override interval for aggregating query runtime statistics (default is 60 minutes).
ALTER DATABASE <database_name> SET QUERY_STORE (INTERVAL_LENGTH_MINUTES = 15);
Arbitrary values are not allowed for
INTERVAL_LENGTH_MINUTES. Use one of the following: 1, 5, 10, 15, 30, 60, or 1440 minutes.
New value for interval is exposed through sys.database_query_store_options view.
Query Store space usage
To check current the Query Store size and limit execute the following statement in the user database.
SELECT current_storage_size_mb, max_storage_size_mb FROM sys.database_query_store_options;
If the Query Store storage is full use the following statement to extend the storage.
ALTER DATABASE <database_name> SET QUERY_STORE (MAX_STORAGE_SIZE_MB = <new_size>);
Set all Query Store options
You can set multiple Query Store options at once with a single ALTER DATABASE statement.
ALTER DATABASE <database name> SET QUERY_STORE ( OPERATION_MODE = READ_WRITE, CLEANUP_POLICY = (STALE_QUERY_THRESHOLD_DAYS = 30), DATA_FLUSH_INTERVAL_SECONDS = 3000, MAX_STORAGE_SIZE_MB = 500, INTERVAL_LENGTH_MINUTES = 15, SIZE_BASED_CLEANUP_MODE = AUTO, QUERY_CAPTURE_MODE = AUTO, MAX_PLANS_PER_QUERY = 1000, WAIT_STATS_CAPTURE_MODE = ON );
Cleaning up the space
Query Store internal tables are created in the PRIMARY filegroup during database creation and that configuration cannot be changed later. If you are running out of space you might want to clear older Query Store data by using the following statement.
ALTER DATABASE <db_name> SET QUERY_STORE CLEAR;
Alternatively, you might want to clear up only ad-hoc query data, since it is less relevant for query optimizations and plan analysis but takes up just as much space.
Delete ad-hoc queries This deletes the queries that were only executed only once and that are more than 24 hours old.
DECLARE @id int DECLARE adhoc_queries_cursor CURSOR FOR SELECT q.query_id FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON q.query_text_id = qt.query_text_id JOIN sys.query_store_plan AS p ON p.query_id = q.query_id JOIN sys.query_store_runtime_stats AS rs ON rs.plan_id = p.plan_id GROUP BY q.query_id HAVING SUM(rs.count_executions) < 2 AND MAX(rs.last_execution_time) < DATEADD (hour, -24, GETUTCDATE()) ORDER BY q.query_id ; OPEN adhoc_queries_cursor ; FETCH NEXT FROM adhoc_queries_cursor INTO @id; WHILE @@fetch_status = 0 BEGIN PRINT @id EXEC sp_query_store_remove_query @id FETCH NEXT FROM adhoc_queries_cursor INTO @id END CLOSE adhoc_queries_cursor ; DEALLOCATE adhoc_queries_cursor;
You can define your own procedure with different logic for clearing up data you no longer want.
The example above uses the sp_query_store_remove_query extended stored procedure for removing unnecessary data. You can also use:
- sp_query_store_reset_exec_stats to clear runtime statistics for a given plan.
- sp_query_store_remove_plan to remove a single plan.
Performance Auditing and Troubleshooting
Query Store keeps a history of compilation and runtime metrics throughout query executions, allowing you to ask questions about your workload.
Last n queries executed on the database?
SELECT TOP 10 qt.query_sql_text, q.query_id, qt.query_text_id, p.plan_id, rs.last_execution_time FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p ON q.query_id = p.query_id JOIN sys.query_store_runtime_stats AS rs ON p.plan_id = rs.plan_id ORDER BY rs.last_execution_time DESC;
Number of executions for each query?
SELECT q.query_id, qt.query_text_id, qt.query_sql_text, SUM(rs.count_executions) AS total_execution_count FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p ON q.query_id = p.query_id JOIN sys.query_store_runtime_stats AS rs ON p.plan_id = rs.plan_id GROUP BY q.query_id, qt.query_text_id, qt.query_sql_text ORDER BY total_execution_count DESC;
The number of queries with the longest average execution time within last hour?
SELECT TOP 10 rs.avg_duration, qt.query_sql_text, q.query_id, qt.query_text_id, p.plan_id, GETUTCDATE() AS CurrentUTCTime, rs.last_execution_time FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p ON q.query_id = p.query_id JOIN sys.query_store_runtime_stats AS rs ON p.plan_id = rs.plan_id WHERE rs.last_execution_time > DATEADD(hour, -1, GETUTCDATE()) ORDER BY rs.avg_duration DESC;
The number of queries that had the biggest average physical IO reads in last 24 hours, with corresponding average row count and execution count?
SELECT TOP 10 rs.avg_physical_io_reads, qt.query_sql_text, q.query_id, qt.query_text_id, p.plan_id, rs.runtime_stats_id, rsi.start_time, rsi.end_time, rs.avg_rowcount, rs.count_executions FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p ON q.query_id = p.query_id JOIN sys.query_store_runtime_stats AS rs ON p.plan_id = rs.plan_id JOIN sys.query_store_runtime_stats_interval AS rsi ON rsi.runtime_stats_interval_id = rs.runtime_stats_interval_id WHERE rsi.start_time >= DATEADD(hour, -24, GETUTCDATE()) ORDER BY rs.avg_physical_io_reads DESC;
Queries with multiple plans? These queries are especially interesting because they are candidates for regressions due to plan choice change. The following query identifies these queries along with all plans:
WITH Query_MultPlans AS ( SELECT COUNT(*) AS cnt, q.query_id FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p ON p.query_id = q.query_id GROUP BY q.query_id HAVING COUNT(distinct plan_id) > 1 ) SELECT q.query_id, object_name(object_id) AS ContainingObject, query_sql_text, plan_id, p.query_plan AS plan_xml, p.last_compile_start_time, p.last_execution_time FROM Query_MultPlans AS qm JOIN sys.query_store_query AS q ON qm.query_id = q.query_id JOIN sys.query_store_plan AS p ON q.query_id = p.query_id JOIN sys.query_store_query_text qt ON qt.query_text_id = q.query_text_id ORDER BY query_id, plan_id;
Queries that recently regressed in performance (comparing different point in time)? The following query example returns all queries for which execution time doubled in last 48 hours due to a plan choice change. Query compares all runtime stat intervals side by side.
SELECT qt.query_sql_text, q.query_id, qt.query_text_id, rs1.runtime_stats_id AS runtime_stats_id_1, rsi1.start_time AS interval_1, p1.plan_id AS plan_1, rs1.avg_duration AS avg_duration_1, rs2.avg_duration AS avg_duration_2, p2.plan_id AS plan_2, rsi2.start_time AS interval_2, rs2.runtime_stats_id AS runtime_stats_id_2 FROM sys.query_store_query_text AS qt JOIN sys.query_store_query AS q ON qt.query_text_id = q.query_text_id JOIN sys.query_store_plan AS p1 ON q.query_id = p1.query_id JOIN sys.query_store_runtime_stats AS rs1 ON p1.plan_id = rs1.plan_id JOIN sys.query_store_runtime_stats_interval AS rsi1 ON rsi1.runtime_stats_interval_id = rs1.runtime_stats_interval_id JOIN sys.query_store_plan AS p2 ON q.query_id = p2.query_id JOIN sys.query_store_runtime_stats AS rs2 ON p2.plan_id = rs2.plan_id JOIN sys.query_store_runtime_stats_interval AS rsi2 ON rsi2.runtime_stats_interval_id = rs2.runtime_stats_interval_id WHERE rsi1.start_time > DATEADD(hour, -48, GETUTCDATE()) AND rsi2.start_time > rsi1.start_time AND p1.plan_id <> p2.plan_id AND rs2.avg_duration > 2*rs1.avg_duration ORDER BY q.query_id, rsi1.start_time, rsi2.start_time;
If you want to see performance all regressions (not only those related to plan choice change) than just remove condition
AND p1.plan_id <> p2.plan_id from the previous query.
Queries that are waiting the most? This query will return top 10 queries that wait the most.
SELECT TOP 10 qt.query_text_id, q.query_id, p.plan_id, sum(total_query_wait_time_ms) AS sum_total_wait_ms FROM sys.query_store_wait_stats ws JOIN sys.query_store_plan p ON ws.plan_id = p.plan_id JOIN sys.query_store_query q ON p.query_id = q.query_id JOIN sys.query_store_query_text qt ON q.query_text_id = qt.query_text_id GROUP BY qt.query_text_id, q.query_id, p.plan_id ORDER BY sum_total_wait_ms DESC
Queries that recently regressed in performance (comparing recent vs. history execution)? The next query compares query execution based periods of execution. In this particular example the query compares execution in recent period (1 hour) vs. history period (last day) and identifies those that introduced
additional_duration_workload. This metrics is calculated as a difference between recent average execution and history average execution multiplied by the number of recent executions. It actually represents how much of additional duration recent executions introduced compared to history:
--- "Recent" workload - last 1 hour DECLARE @recent_start_time datetimeoffset; DECLARE @recent_end_time datetimeoffset; SET @recent_start_time = DATEADD(hour, -1, SYSUTCDATETIME()); SET @recent_end_time = SYSUTCDATETIME(); --- "History" workload DECLARE @history_start_time datetimeoffset; DECLARE @history_end_time datetimeoffset; SET @history_start_time = DATEADD(hour, -24, SYSUTCDATETIME()); SET @history_end_time = SYSUTCDATETIME(); WITH hist AS ( SELECT p.query_id query_id, CONVERT(float, SUM(rs.avg_duration*rs.count_executions)) total_duration, SUM(rs.count_executions) count_executions, COUNT(distinct p.plan_id) num_plans FROM sys.query_store_runtime_stats AS rs JOIN sys.query_store_plan p ON p.plan_id = rs.plan_id WHERE (rs.first_execution_time >= @history_start_time AND rs.last_execution_time < @history_end_time) OR (rs.first_execution_time <= @history_start_time AND rs.last_execution_time > @history_start_time) OR (rs.first_execution_time <= @history_end_time AND rs.last_execution_time > @history_end_time) GROUP BY p.query_id ), recent AS ( SELECT p.query_id query_id, CONVERT(float, SUM(rs.avg_duration*rs.count_executions)) total_duration, SUM(rs.count_executions) count_executions, COUNT(distinct p.plan_id) num_plans FROM sys.query_store_runtime_stats AS rs JOIN sys.query_store_plan p ON p.plan_id = rs.plan_id WHERE (rs.first_execution_time >= @recent_start_time AND rs.last_execution_time < @recent_end_time) OR (rs.first_execution_time <= @recent_start_time AND rs.last_execution_time > @recent_start_time) OR (rs.first_execution_time <= @recent_end_time AND rs.last_execution_time > @recent_end_time) GROUP BY p.query_id ) SELECT results.query_id query_id, results.query_text query_text, results.additional_duration_workload additional_duration_workload, results.total_duration_recent total_duration_recent, results.total_duration_hist total_duration_hist, ISNULL(results.count_executions_recent, 0) count_executions_recent, ISNULL(results.count_executions_hist, 0) count_executions_hist FROM ( SELECT hist.query_id query_id, qt.query_sql_text query_text, ROUND(CONVERT(float, recent.total_duration/ recent.count_executions-hist.total_duration/hist.count_executions) *(recent.count_executions), 2) AS additional_duration_workload, ROUND(recent.total_duration, 2) total_duration_recent, ROUND(hist.total_duration, 2) total_duration_hist, recent.count_executions count_executions_recent, hist.count_executions count_executions_hist FROM hist JOIN recent ON hist.query_id = recent.query_id JOIN sys.query_store_query AS q ON q.query_id = hist.query_id JOIN sys.query_store_query_text AS qt ON q.query_text_id = qt.query_text_id ) AS results WHERE additional_duration_workload > 0 ORDER BY additional_duration_workload DESC OPTION (MERGE JOIN);
Maintaining Query Performance Stability
For queries executed multiple times you may notice that SQL Server uses different plans, resulting in different resource utilization and duration. With Query Store you can detect when query performance regressed and determine the optimal plan within a period of interest. You can then force that optimal plan for future query execution.
You can also identify inconsistent query performance for a query with parameters (either auto-parameterized or manually parameterized). Among different plans you can identify the plan which is fast and optimal enough for all or most of the parameter values and force that plan, keeping predictable performance for the wider set of user scenarios.
Force a plan for a query (apply forcing policy)
When a plan is forced for a certain query, SQL Server tries to force the plan in the optimizer. If plan forcing fails, an XEvent is fired and the optimizer is instructed to optimize in the normal way.
EXEC sp_query_store_force_plan @query_id = 48, @plan_id = 49;
When using sp_query_store_force_plan you can only force plans that were recorded by Query Store as a plan for that query. In other words, the only plans available for a query are those that were already used to execute that query while Query Store was active.
SQL Server 2019 CTP 2.3 Query Store supports the ability to force query execution plans for fast forward and static T-SQL and API cursors. Forcing is now supported via
sp_query_store_force_plan or through SQL Server Management Studio Query Store reports.
Remove plan forcing for a query
To rely again on the SQL Server query optimizer to calculate the optimal query plan, use sp_query_store_unforce_plan to unforce the plan that was selected for the query.
EXEC sp_query_store_unforce_plan @query_id = 48, @plan_id = 49;
Best Practice with the Query Store
Using the Query Store with In-Memory OLTP
Query Store Usage Scenarios
How Query Store Collects Data
Query Store Stored Procedures (Transact-SQL)
Query Store Catalog Views (Transact-SQL)
Monitor and Tune for Performance
Performance Monitoring and Tuning Tools
Open Activity Monitor (SQL Server Management Studio)
Live Query Statistics
Operating the Query Store in Azure SQL Database