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Query Store: How it works? How to use it?

Part 1

“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. “ msdn.

If you want to know, how to enable it, you can find information here: https://msdn.microsoft.com/en-US/library/dn817826.aspx

Once you enabled the Query Store for the database you can change some of the settings, for more information: Query Store - Settings and Limits

If you want to know more about the cleanup retention, you can find information here: Query Data Store Size Cleanup Retention

The focus of this post is to discuss how query store works internally and how to use it.

So, first things first, the query store execution flow, exemplified by figure 1:

1)      SQL Server existing components interact with query store by utilizing Query Store Manager.

2)      Query Store Manager determines which Store should be used and then passes execution to that store (Plan or Stats). Note: Query Store is enable per database, so that happens at database level.

3)      Plan and Runtime Stats store uses Query Data Store as an extension to SQL Server.fig_1_media

Figure 1: Query Store execution flow

You may be asking yourself right now what is plan store and runtime stats store. And if you are asking yourself this question, I have a good news. That is the next topic.

MSDN definition (https://msdn.microsoft.com/en-US/library/dn817826.aspx ) : The query store contains two stores; a plan store for persisting the execution plan information, and a runtime stats store for persisting the execution statistics information.

So….

Plan Store: it is accountable for capturing all information that is related to query compilation.

Runtime Stats Store: that one is probably the most frequently updated store. These statistics represent query execution data.

Each store has a set of DMVs that represents the idea of the store:

Plan store DMVs:

Run-time stats store DMVs:

Summarizing:  Query data store will store the data of the right store per threshold previously set, figure 2 tries to demonstrate this. More details here: https://blogs.technet.microsoft.com/dataplatform/2016/10/25/query-store-settings-and-limits/ :

  • The Plan Store is flushed every 15 minutes by default.
  • The default collection interval for the runtime statistics is 60 minutes.

fig_2_media

 

Figure 2: Query data store async

Note 1: Query Store is persisted to disk, so it survives a crash. But Query Store is also Async, it means if the data has not been persisted and a crash happens in the meantime, the data will be lost. Although, if SQL Server must be restart because of a maintenance routine you could force Query Store to be flush using the procedure: sp_query_store_flush_db

Note 2: If you want to copy the data from Query Store ( system query store tables)  from a database to another. You must do it manually copying the data to the user tables ( you could use BCP for instance). It is not possible at this moment ( SQL Server 2016 SP1) to copy the  Query Store system tables from one database to the Query Store system tables from another database.

Note 3:  Query Store could generate a performance overhead of up to 1.5-2% for the most intensive workloads. Additionally, CPU, memory and IO consumed by Query Data Store are all resource governed, especially on SQL Azure DB, where the lower tier instances have more strict resource limits. The purpose of all these limits is to limit the Query Store impact on the rest of the user database.

Ok. But, how to use query store?

Using Query Store Reports:

After enabling the query store, refresh the database portion of the Object Explorer pane to add the Query Store section. You will be able to see some reports:

fig_3_media

Figure 3: Query Store Reports

As it shows the figure 3 query store has four reports. More details here: https://msdn.microsoft.com/en-US/library/mt614796.aspx

Regressed Queries: is a report that can be used to identify all queries which execution metrics have been degraded in the period of time of interest (last hour, day, week, etc.).

Overall Resource Consumption: It shows the overall resource consumption during the last month in four charts: duration, execution count, CPU time, and logical reads

Tracked Queries: With this report is possible to monitor a specify query. Just filter using the query ID as demonstrate figure 4.

figure_4_media

Figure 4: Tracked Queries

Top Resource Consuming Queries as the name says are the queries that are consuming most of the resources, like most of CPU or the queries that are taking more time to finish the execution (elapsed time), or still the ones that are consuming more memory, or top logical reads, writes and even physical reads, as it shows figure 5. Although your workload may generate thousands of queries, typically only a handful of them use most of the system resources and therefore require your attention.

figure_5_media

Figure 5: Top Resource Consuming Queries

Regards to the reports provided by Query Store. There are a few features inside of them, that you could use for troubleshooting.

1)      It is possible to compare plans, especially useful in case of parameter sniffing.

Scenario: Suppose a situation when a procedure is compilated with a parameter that results in a few rows, after running this procedure a few times you realize that the data is skewed and the plan that was generated using that first parameter is not the best plan possible for other parameters. In this case, you choose to recompile your procedure once more with a different parameter, which results in a very different plan. At that point, you notice that you can have two different plans for the same procedure and you want to compare both.

Good news: Query store keeps the track for that kind of situation. As figure 6 and 07 shows.

figure_6_media 

Figure 6: Compare plans feature

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Figure 7: Compare plans

2)      It is also possible to force the plan.

Scenario: You have two different plans for the same procedure. That procedure was recompiled twice with two different parameters that returned a very different result set, the data is skewed. You understand that probably one of the plans is better than the other in a way that you want to prevent, even in a case of recompilation that the plan that is not good enough to be used. Query store provides the option: force plan, as you may see at figure 8 .

figure_8_media 

Figure 8: Force Plan.

 

That option is not only available at the Query Store report. It is also available using T-SQL:

o   Force Plan:

[sql] sp_query_store_force_plan @query_id, @plan_id [/sql]

In terms of T-SQL you have other couple of interesting options:

o   Stop plan forcing :

[sql] sp_query_store_unforce_plan [/sql]

Others T-SQL options:

o   Removes a single plan from Query Store:

[sql] sp_query_store_remove_plan [/sql]

 

o   Clear runtime stats for a specific query plan:

[sql] sp_query_store_reset_exec_stats [/sql]

 

o   Gets the stmt_sql_handle for a Transact-SQL statement under given parameterization type (simple or forced):

[sql] sys.fn_stmt_sql_handle_from_sql_stmt [/sql]

 

Everything that you have in the report and even more information you can have using the Query Store DMVs and you could also correlate Query Store Information with SQL Server dynamic view and functions:

[sql]

SELECT qt.query_text_id

, q.query_id, qt.query_sql_text

, qt.statement_sql_handle

, qs.max_elpased_time

FROM sys.query_store_query_text qt

JOIN sys.query_store_query q

ON qt.query_text_id = q.query_id

CROSS APPLY sys.fn_stmt_sql_handle_from_sql_stmt (qt.query_sql_text, null) fn_hanlde_from_stmt

JOIN sys.dm_exec_query_stats qs

ON fn_hanlde_from_stmt.statement_sql_handle = qs.statement_sql_handle

[/sql]

 

And again as always, thanks Dejan Krakovic for answer a lot of my doubts regards to query store!

Next post let’s try to explore more the power of Query Store DMVs.

 

Liliam Leme

UK SQL PFE

Comments

  • Anonymous
    September 01, 2017
    The comment has been removed
    • Anonymous
      September 02, 2017
      Thanks for the feedback. This has now been fixed.