Speed up your Catalog incremental indexing

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.

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Why you should upgrade to the latest version

I made no secret that I’m a die-hard advocate for upgrading to latest EPiServer CMS/Commerce version. There are several reasons for that, mostly from new shiny features that your businesses dearly need, new big performance improvements that your customers firmly demand.

But there is another, not so obvious reason: support.

Let me tell you a story.

This morning we received a support case from support team. A customer recently upgraded from Commerce 7.5 (Eww) to 11.7 (Yay!), things went well except they had a small problem with data displaying in Catalog UI. Some of the properties were not properly displayed, but they are still showing correct in Commerce Manager.

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World forums support vote up/down now, and what does that mean for you

I really wanted to post this in the official blog, however we don’t have a “World” blog, and this does not really fit into “Commerce blog” which we (Commerce development team) usually use for official announcements, so I have to use my personal blog instead.

If you haven’t noticed, then you can now vote up, or down a post in World forum. Thanks to the hard work of my colleagues in World development team, that feature went on live today! (Of which I’m very excited)

If you have been using StackOverflow (as as developer, you likely have), then you know the meaning of voting up and down. The idea is the same here, there are differences in the detail implementations, such as the amount of points given (or taken) from a vote up (down), but basically:

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ServiceAPI + Postman, a match in heaven

No, it’s just a note-to-self.

A lot of customers have been using ServiceAPI, and to great successes. We also have very good documentation here – of which largely thanks to my colleague Mark Hall. But what if you want to play around with ServiceAPI and don’t want to write app/build/run it yourself? The answer is simple: There are many REST Clients can do the job for you, and Postman is usually regarded as the best/most popular one.

But, the documentation are for C# client, it can be quite confusing to use Postman to work with ServiceAPI for the first time (or times). If you are experienced with Postman, great! But if you are not – like me – when you use Postman from time to time and everytime it’s new, then this post can be useful to you. Today I need to do some tests with ServiceAPI, and I had to spend some time figuring out how to use Postman – so I decided it’s better to have all of those noted for future reference.

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Mass update catalog entries

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.

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A curious case of SQL Server function

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:

declare @s [udttIdTable]
insert into @s values(6)
exec dbo.ecfVersion_ListFiltered @Statuses = @s, @StartIndex = 0, @MaxRows = 2147483646

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.

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Loading carts in a load balancing environment

UPDATE 1: Apparently HttpContext.Current.Request.AnonymousID already uses the cookie internally, so there might be something that makes it stop working. I’ll update when I found out.

Today we received a support ticket as customers seeing corrupted carts data being lost – line items with invalid data, duplicated line items etc. “Corrupted data” is one of the alarming words that we take very seriously, so I decided to jump on it right away.

The setup is a load balancing environment, and the problem only happens with anonymous users. However, it can be “fixed” by turning on the sticky sessions mode. So basically, instead of having sessions on the memory of a server (so sessions on server A can’t be seen by server B, and vice versa), they need a mechanism (can be a database) to share sessions between servers.

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Announcing a new book: Episerver Commerce: A problem – solution approach

More than one year ago, I announced that I was working on a book – a first Episerver Commerce book ever. It has been a work in progress until recently – and I am still adding updates here and there. The book has received quite positive feedback (I’m happy to say that everyone is nice enough to not tell me “Your book sucks”. Thanks, everyone). Am I happy with it? Yes, of course, proud even.

But to be completely honest,

I know something was missing.

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Optimizing T-SQL COUNT

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.

SELECT COUNT(ObjectId) FROM OrderGroup_PurchaseOrder

Because ObjectId is the clustered index of OrderGroup_PurchaseOrder, I did expect it to be use that index and be pretty fast. But does it? To my surprises, no.

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The art of paging

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.

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