Plansplaining

Welcome back to my plansplaining blog series, where I dissect execution plans in order to increase our understanding of how SQL Server processes specific queries. We’re at part 33 already, and I’m still looking at cursors. After discussing the basics, static cursors, dynamic cursors, and keyset cursors, I will now look at the last of the cursor types: the fast forward cursor. Fast forward cursor One of the things that has always bothered me about the fast forward cursor type is the shocking lack of documentation of what it does exactly. Okay, the name suggests that it is fast. But…

Welcome to plansplaining, part 32, where we once more look at cursors. We already discussed the basics, and looked at static cursors and dynamic cursors. It is now time to cast our gaze upon the keyset cursor. The keyset cursor is sort of in between the static cursor (which presents a snapshot of the data is at was when the cursor was opened and disregards future changes) and the dynamic cursor (that always shows the current data). To be precise, a keyset cursor sees changes made to already existing rows, but does not see new rows that were added after…

We’re already at part 31 of the plansplaining series. And this is also the third part in my discussion of execution plans for cursors. After explaining the basics, and after diving into static cursors, it is now time to investigate dynamic cursors. As a quick reminder, recall that a static cursor presents data as it was when the cursor was opened (and does so by simply saving a snapshot of that data in tempdb), whereas a dynamic cursor is supposed to see all changes that are committed while the cursor is open. Let’s see how this change in semantics affects…

In part 30 of the plansplaining series, we’ll continue our discussion of cursor processing. I recommend first reading the previous post, where I explain all the necessary basics. Sample query Throughout the series, I will keep using the same sample query, that grabs some sales and product data for sales of more than 10 units, within a specified range of sales orders. SELECT soh.SalesOrderID, soh.OrderDate, sod.SalesOrderDetailID, sod.OrderQty, sod.ProductID, p.ProductID, p.Name FROM Sales.SalesOrderHeader AS soh INNER JOIN Sales.SalesOrderDetail AS sod ON sod.SalesOrderID = soh.SalesOrderID INNER JOIN Production.Product AS p ON p.ProductID = sod.ProductID WHERE soh.SalesOrderID BETWEEN 69401 AND 69410 AND sod.OrderQty…

This is already the 29th part of the plansplaining series, where I look in detail at interesting examples of execution plans in SQL Server. With this part, I’ll kick off another mini-series, this time on cursor processing Don’t use cursors! And yes, I know the mantra. Do not use cursors. They are slow. There is (almost) always a faster set-based alternative available. So why would I even waste blog space on cursors, when the only smart thing to do is to rip them out and replace them with a set-based alternative? Well, there are, in fact, many reasons. The “almost”…

In part twenty-eight of the plansplaining series, I’ll wrap up the six-part mini-series on window functions. After covering the basics, fast-track optimization, window frames ending at UNBOUNDED FOLLOWING, window frames specified with RANGE instead of ROWS, and LAG and LEAD, we will look at the LAST_VALUE and FIRST_VALUE analytical functions, and find that a function we would have expected to be available as an internal aggregate function does not exist at all! We’ll also find out how SQL Server works around that. LAST_VALUE We already encountered the LAST_VALUE internal aggregate function in the previous post, where it is used to…

This is part twenty-seven of the plansplaining series, and episode five in the mini-series on window functions. The previous parts covered the basics, fast-track optimization, window frames ending at UNBOUNDED FOLLOWING, and window frames specified with RANGE instead of ROWS. In this post, we will shift our attention to the LAG and LEAD functions. Two functions that do not even accept a window frame specification. So why are they in this series? Read on to find out! LAG LAG and LEAD were introduced in SQL Server 2012. They require an OVER clause, but it can only specify PARTITION BY and…

This is part twenty-six of the plansplaining series. And already the fourth episode about window functions. The first of those posts covered basic window functions; the second post focused on fast-track optimization for running aggregates, and the third post explained how the optimizer works around the lack of execution plan support for UNBOUNDED FOLLOWING. But all of those were about OVER specifications that use the ROWS keyword. Let’s now look at the alternative, the RANGE keyword. RANGE instead of ROWS When a RANGE specification is used, then number PRECEDING and number FOLLOWING are not allowed. So this leaves us with…

This is part twenty-five of the plansplaining series, and the third part that covers window functions. I have already explained how basic window functions work, with or without a window frame. When a window frame is present, a Window Spool operator will, for each row, return first that row, and then all rows that are visible in its frame. A Stream Aggregate then computes the requested aggregations on those rows. In the previous part, I then explained how “fast-track optimization” severely reduces the amount of work in cases where the window frame starts at UNBOUNDED PRECEDING. I also showed that…

This is part twenty-four of the plansplaining series. In the previous part, I explained the execution plans for basic window functions, with and without a window frame. Especially the latter group performed quite poorly in the examples. So let’s now look at an optimization that SQL Server can apply to most cases, that prevents this rather bad scaling. Running totals The examples in the previous post all used a window frame that started at (some number) PRECEDING. And as long as (some number) is quite low (and the end of the frame is not defined as (huge number) FOLLOWING), the…