As your products are being constantly updated, you would naturally want them to be properly (and timely) indexed – as that’s crucial to have the search results that would influence your customers into buying stuffs. For example, if you just drop the prices of your products , you would want those products to appear in new price segment as soon as possible.
This should be very easy with Find.Commerce – so if you are using Find (which you should) – stop reading, nothing for you here. Things, however, can be more complicated if you are using the more “traditional” SearchProvider.
This is something you don’t do daily, but you will probably need one day, so it might come in handy.
Recently we got a question on how to update the code of all entries in the catalog. This is interesting, because even thought you don’t update the codes that often (if at all, as the code is the identity to identify the entries with external system, such as ERPs or PIMs), it raises a question on how to do mass update on catalog entries.
Update the code directly via database query. It is supposedly the fastest to do such thing. If you have been following my posts closely, you must be familiar with my note regarding how Episerver does not disclose the database schema. I list it here because it’s an option, but not the good one. It easily goes wrong (and cause catastrophes), you have to deal with versions and cache, and those can be hairy to get right. Direct data manipulation should be only used as the last resort when no other option is available.
This time, we will talk about ecfVersion_ListFiltered, again.
This stored procedure was previously the subject of several blog posts regarding SQL Server performance optimizations. When I thought it is perfect (in term of performance), I learned something more.
Recently we received a performance report from a customer asking about an issue after upgrading from Commerce 10.4.2 to Commerce 10.8 (the last version before Commerce 11). The job “Publish Delayed Content Versions” starts to throw timeout exceptions.
This scheduled job calls to a ecfVersion_ListFiltered to load the content versions which are in status DelayedPublish, it looks like this when it reaches SQL Server:
This query is known to be slow. The reason is quite obvious – Status contains only 5 or 6 distinct values, so it’s not indexed. SQL Server will have to do a Clustered Index Scan, and if ecfVersion is big enough, it’s inevitably slow.
This is a continuation of my previous post about paging in SQL Server. When it comes to paging, you would naturally want to know the total number of rows satisfying, so you can display some nice, useful information to your end-users.
You would think, well, it’s just a count, and a simple query like this would be enough:
SELECT COUNT(Id)FROM MySecretTable
There should be nothing to worry about, right? Actually, there is.
Let’s get back to the example in previous post – we have to count the total number of orders in that big table.
No this is not really “art” – I’m just trying to have a more clickbait title. It’s more about understanding what you have at your disposal and use them for your benefits – in this case – how new SQL statement can drastically improve your performance.
In this blogpost we will look into paging feature of SQL Server. in Commerce we usually work with large set of data – millions of rows are fairly common, and it’s natural to load data by page. There is no point loading thousands, or even millions of rows in one go. First it’s not practical to display all of them. Second you’ll likely end up with an timeout exception and/or an out of memory exception. Even if you are lucky enough to get through, it’s still able to take your SQL Server instance to a knee, and transferring that much data over network will be another bottleneck for your system. So my friends, the best practice for loading data is to do it by batches, and to not load everything at once.
At Episerver development team, we understand the importance of good performance. Who would not like a lightning fast website? We work hard to ensure the framework is fast, and we seize (almost) every opportunity to make it faster.
You know in Commerce 10.2 we introduced a new cart mode – serializable cart, and it’s proven to bring great performance compared to the “old/traditional” approach. Our own tests showed an improvement of 3-5x times faster. But can it be even faster? Probably yes.
And actually we did some improvements in later versions. In the scope of this blog post, we will just focus into a specific aspect – and to learn a little more about SQL Server performance optimization.
Well, that was the title of my talk at the last week Meetup in Lund – hosted by Avensia. My first time in Lund – it is a very beautiful (small) city. It was a very nice event with about thirty developers from inside and outside Avensia, and I hope I did give some good information to make your Commerce solutions faster!
Then it comes to my attention that some of you might be interested in the talk. Unfortunately I don’t think the talk was recorded (I’d have been famous on Youtube!), but here’s the slides from the talk:
I have some more time to revisit the query now, and I realized I made a “small” mistake. The “optimized” query is using a Clustered Index Scan
So it’s not as fast as it should be, and it will perform quite poorly in no cache scenario (when the buffer is empty, for example) – it takes about 40s to complete. Yes it’s still better than the original one, both in non cached and cached cases. But it’s not good enough. An index scan, even cached, is not only slower, but also more prone to deadlocks. It’s also worse in best case scenario, when the original one can use the proper index seek.