This situation remained exactly the same in SQL Server 2014, but has changed dramatically with SQL Server 2016. SSRS in SQL Server 2016 contains significant advancements, chief among them are a new HTML5 rendering engine, a new report portal, mobile reports, and (soon) Power BI Desktop rendering. This is fantastic news, but it also changes the game significantly with respect to the Integrated/Native mode decision. With SSRS 2016, most of the new investments are in Native mode only – the balance has shifted. The table below shows an (incomplete) list of new features, and their supported modes.
You still need Integrated mode to read Power View reports, and John mentions a few places where Native mode falls short, so take the time to plan out which is right for you.
Tim Radney shows us a new way of clearing the procedure cache in Azure SQL Databases (and in 2016 RC0 or later):
It turns out that
DBCC FREEPROCCACHEis not supported in Azure SQL Database. This was troubling to me, what if I’m in production and have some bad plans and want to clear the procedure cache like I can with the box version. A little Google/Bing research lead me to find the Microsoft article, “Understanding the Procedure Cache on SQL Azure,” which states:SQL Azure currently doesn’t support DBCC FREEPROCCACHE (Transact-SQL), so you cannot manually remove an execution plan from the cache. However, if you make changes to the table or view referenced by the query (ALTER TABLE and ALTER VIEW) the plan will be removed from the cache.
In discussing this with Kimberly Tripp after not seeing that described behavior, it does not flush the plan from cache, but it does invalidate the plan (and then the plan will be eventually aged out of the cache). While this is helpful in certain situations, this was not what I needed. For my demo I wanted to reset the counters in sys.dm_exec_cached_plans. Generating a new plan would not give me the desired results. I reached out to my team and Glenn Berry told me to try the following script:
Read on for the new command, and just like DBCC FREEPROCCACHE, be careful where you point that thing.
Typing a * sounds a lot easier than actually listing all of the columns you need. However is that really a good idea? You’ll hear lots of people saying it isn’t, but why?
Well there are several reasons.
Read on for his reasons.
So yeah, now it takes fewer keystrokes to get the job name. I used to:
WHERE job_id IN ( SELECT job_id
WHERE name LIKE ‘CollectorDBFilePropertiesGet-%’ );
But now I:
WHERE dbo.JobName(job_id) LIKE ‘CollectorDBFilePropertiesGet-%’ ;
Jen’s got the function available on her site.
This is where automation comes to the rescue again! Most of our SQLDWs can be paused after 6:00 PM on weekdays, as well as the entire weekend. Now, I could manually go and pause each individual SQLDW at the end of the day, but what happens if I have plans for dinner or something else during that time? I decided that I needed an automated process to check each SQLDW and pause it if it is running. Using Azure Automation andAzure Runbooks, I was able to create a scheduled task that looks for any running SQLDW and pauses it.
Here are the basic steps to implement the automated solution I came up with:
Create a credential in your automation account with access to all SQL Data Warehouses.
Create a PowerShell Workflow Runbook with the code below.
Create and link the schedule(s) needed for it to run.
Azure gripe #4 for me is that they’re so inconsistent about what I can do not to pay money. Apparently you can pause Azure SQL Data Warehouse, which is good. But DocumentDB or HDInsight? Nope, deletion is the only way to stop running up charges. Check out Brian’s script if you use Azure SQL Data Warehouse and save your company a bit of cash.
XPath is the bane of my life… it takes a while to find the correct value particularly as there are so many node names that are re-used yet embedded into them. So I added a simple example and a couple with more depth. Nevertheless, running the test should produce a green result. This could be used for more than just testing; DBA’s may find it useful in SQLCLR scenarios.
I’ve uploaded the code to GitHub. The repository is calledXQueryPlanPath.
9/10 would prefer F#.
Seriously, though, this is a nice start if you need to dig into execution plans programmatically.
In short, the plan is stored in the query store, even though the plan isn’t stored in cache. Now, this has implications. I’m not saying they’re good and I’m not saying they’re bad, but there are implications. If you’re in a situation where you need to use Optimize For Ad Hoc to help manage your cache, now, you’re going to possibly see negative impacts on your Query Store since it’s going to capture all the plans that you avoided. There are mechanisms for managing Query Store behavior.
I’d consider this correct behavior. I want to be able to see those one-off query plans. A quick note on Query Store, though: it chews up a lot of disk space in a busy environment, so if you’re planning on holding query store entries for a while, keep plenty of disk space available.
One of the steps I tried to remedy the problem was removing the SQLPS module directory from the PSModulePath environment variable, to see if the Import-Module would skip over it. Turns out I was only half right: I should have removed non 2016 versions of the module path, as Matteo goes on to explain:
I’m hoping there will be a real fix for RTM. This works, but it’s neither intuitive nor easily decipherable.
Here we are looking at the difference between the estimated and actual number of rows for an element of the plan. To look at this information you can either mouse over the element or right click and open the properties tab. In this case you will see that the estimated number of rows (what the optimizer thought would happen) is fairly low (117) particularly compared to what actually happened (1494900). When you see a big difference like that in a query plan there is something wrong.
This is a really nice and detailed walkthrough in which Rob plays Socrates and Kenneth your favorite of the group (Thrasymachus anyone?).
The where clause is exactly the same as before. The only difference is that we are now (deliberately) setting the partitioning column equal to itself. This will not change the value stored in that column, but it does affect the outcome. The update now succeeds (albeit with a more complex execution plan):
The optimizer has introduced new Split, Sort, and Collapse operators, and added the machinery necessary to maintain each potentially-affected nonclustered index separately (using a wide, or per-index strategy).
Read on for the reason why this happens, as well as a few solutions.