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Category: Query Store

Query Store Plan Forcing and RECOMPILE

Vlad Drumea tests Betteridge’s Law of Headlines:

It’s 3AM and I’m curious if Query Store plan forcing works on queries that use the RECOMPILE hint (aka OPTION(RECOMPILE) ).
So might as well make a blog post out of it.

Hmm, on the one hand, Vlad blatantly violates Betteridge’s Law of Headlines, which loses points. On the other hand, Vlad dunks hard on LLMs, gaining points. I’m so conflicted right now…

But not about reading Vlad’s post. Go read it.

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Adaptive Joins and Equivalent Plans

Forrest McDaniel has a public service announcement:

In case you haven’t heard, moral decline is everywhere. The latest generation of query operators is a prime example of this rot. “But this is programming” you say, “what do morals have to do with anything?” No. This is SQL. And for us, we have the term morally equivalent plans which allows me to finally have an ethical excuse for sprinkling a post with degenerate puns.

I bit my tongue specifically to avoid doing exactly what Forrest does. So click through to read all of the terrible puns.

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Useful Query Store Metrics

Jared Poche gives us five:

Query Store is my favorite way to gather information about problem queries and plans, and I wanted to share some information on the useful metrics I use most.

The first two are obvious, but there’s a difference between them. The last two are not obvious but offer an unusual utility. I also wanted to explain why I use logical reads and mostly ignore physical reads.

Read on for Jared’s list.

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Fixing OPTIMIZATION_REPLAY_FAILED Errors in SQL Server

Kendra Little fixes a problem:

Forcing plans with Query Store can be a powerful tool—until it mysteriously fails. In real production systems, plan forcing sometimes just… doesn’t work. One common culprit is the cryptic OPTIMIZATION_REPLAY_FAILED error.

If you’re hitting OPTIMIZATION_REPLAY_FAILED, try re-forcing the plan using @disable_optimized_plan_forcing=1.

Click through for a summary of the problem and additional helpful information on the issue.

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SQL Server Execution Plan Analysis Features

Hugo Kornelis looks back at some nice additions to SQL Server:

It’s December. The last month of the year, and hence also the last T-SQL Tuesday of the year. Edition 181 is hosted by Kevin Chant. His chosen topic for this episode is to have us talk about which SQL Server announcement excited us the most.

This posed a bit of a problem for me. The only truthful answer here is that I have never been as excited about an announced new feature as when the Query Store was announced. But I also realized that I don’t have much to write about the Query Store, except how awesome it is. Okay, I could go on a full explanation, but many others do that much better, and have already done so. So that doesn’t leave much for me.

And that’s why I’ll also include my second favorite announcement.

Read on for a little bit around Query Store, followed up with coverage of several interesting additions to SQL Server over the years.

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The Joy of Query Store

Andy Brownsword gets into the spirit:

Reviewing performance for a SQL database over time can be a challenge without hand crafted tooling or using external monitoring apps. This isn’t about putting fires out, we’re looking at proactive monitoring and taking action for incremental improvements.

The Query Store comes to the rescue by providing built-in insights into key performance metrics over time. We can use different combinations of them to better understand how the database is working.

Query Store isn’t perfect, but it’s very good solution to an extremely common problem.

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Query Hash Value Changes

Kendra Little digs into a problem:

This is the worst bug I’ve found in SQL Server to date. Previously, my top find was SQL Server Online Index Rebuild sometimes happens offline without warning. This one has taken top slot because it makes my life more difficult on a daily basis.

Background: SQL Server generates a query_hash for each query. This is stored in sys.query_store_query and it’s one of the primary ways you can identify what a query is across different Query Stores, or even the same Query Store over time, as surrogate query_id values get reset if Query Store is cleared or data ages on. The query_hash is a “Zobrist hash over the shape of the individual query, based on the bound (input) logical query tree. Query hints aren’t included as part of the hash.” (Source)

Except that’s wrong.

Read the whole thing.

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Query Store Not Capturing Runtime Stats for Unfinished Queries

Matt Changchien does a bit of testing:

It’s beneficial to understand how Query Store captures query runtime stats when they are used for performance troubleshooting. According to public documentation: upon the query execution, runtime statistics are sent to Query Store.

I am curious whether Query Store will still capture execution statistics under certain scenarios. Hence, in this blog post, I will be testing the two following scenarios with my Azure SQL Database:

  1. Whether Query Store captures runtime stats for query that has completed within an uncommitted transaction, then the transaction rolls back due to a scaling process.
  2. Whether Query Store captures runtime stats for query that is blocked and does not finish before a disconnect caused by a disruptive event (e.g., a service tier scale-up).

Read on to learn more about these two scenarios. The specific context is Azure SQL Database, though the same rules would apply on-premises as well.

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Query Start Times in Query Store

Hugo Kornelis describes an issue:

I was hired by a customer who had a very annoying issue with the daily data load of their data warehouse. The volume of data to be loaded is high and they were already struggling to finish the load before business opens. But that was not their biggest issue. The biggest problem, the real pain point that they hired me for, is that at unpredictable moments, the load would run much longer than normal, pushing it well into business hours. They wanted me to find out what caused those irregular delays, and find a way to stop them from happening.

Read on to learn more about the issue itself, as well as a discrepancy in what Query Store showed. Hugo also points out that the quick-and-easy solution may not be the right solution.

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Automating Unforcing of Failed Query Store Forced Plans

Kendra Little has a script for us:

tldr; I’ve published a script to loop through all databases on an instance, identify if there are any query plans in a problematic “failed” forced state (which can hurt query performance), and un-force them if found. Get the dbo.dba_QueryStoreUnforceFailed stored procedure on GitHub.

This script is designed to work on SQL Server on-prem, in a VM, or in Azure SQL Managed Instance or SQL Server RDS. Since the script is instance-level and loops through all databases, this isn’t really designed for Azure SQL Database – and you don’t get a SQL Agent there anyway, so you probably want to change this around for that use case. The script is shared under the MIT license, feel free to contribute code and/or adapt away for your own uses.

Read on to learn more about what might cause these failure to occur and what you can do about them.

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