A Fine Slice Of SQL Server
Ronen Ariely explains a warning message:
Warning: The ORDER BY clause is used only to determine the rows that are returned by the TOP clause in the view definition. The ORDER BY clause does not guarantee ordered results when the view is queried, unless ORDER BY is also specified in the query itself. Click CANCEL to discard your modifications. Click OK to save the view.
Read on for the full context of when you might see this warning message in SQL Server Management Studio.
Comments closedMagda Bronowska rounds to the nearest minute:
From MS Learn:
DATETRUNC() function returns an input date truncated to a specified datepart.
On the surface the work similarly to
DATEPART(), however that function returns integer values, opposed to the dates returned byDATETRUNC()(we will see that better in the example below).
Read on for plenty of examples of this, as well as two more syntax updates in SQL Server 2022.
Comments closedThis month, Deepthi Goguri (@dbanuggets) asks us about our favourite new feature in SQL Server 2022 or Azure. And while there are always a few, I’m going to write about why I have a particular fondness of “IS [NOT] DISTINCT FROM“, despite the fact that it’s overly wordy and the functionality isn’t actually new at all.
People understand my point that it’s a little wordy. Typing “IS NOT DISTINCT FROM” instead of “=” doesn’t sound fun to anyone, and I think “==” or “IS” ought to be fine. The fact that the functionality isn’t new… well that statement seems to raise a few eyebrows.
Read on for Rob’s take on what IS DISTINCT FROM (and its negative cousin) actually do and what performance-killing alternative people used prior to that.
Deborah Melkin handles missing servers with aplomb:
OPENROWSET is a functionality that allows you to access data sources outside your current server. This could be reading from an Excel file or calling another SQL Server instance. You’re able to treat that other data source as record set, or derived table, and work with the rows returned as you would a local table. One reason you may want to do this is that you need to use a stored procedures to query data from other servers and bring the data together, effectively creating an ELT (Extract – Load – Transform) process without having to use SSIS or Azure Data Factory (ADF).
Read on to see how OPENROWSET() works, what happens if you try to access a remote server which doesn’t exist (or times out), and how you can capture that error message in a CATCH block—something that is not possible to do by default.
Bob Ward enumerates some anti-patterns SQL Server can guilt you over:
If a query uses certain antipatterns, it will be detected during query optimization. For both SQL Server and Azure SQL (internally on by default), if these antipatterns are detected when optimizing the query, and the query_antipattern event has been added as part of a running extended event session, the output will be captured. The output will contain the relevant capture fields configured for the extended event session, allowing one to quickly identify which queries contain these antipatterns and are, therefore, prime candidates for tuning.
Read on for more information about this extended event, which is new to SQL Server 2022. I haven’t used this yet, so the two caveats I’m about to give are speculative in nature…though when has that ever stopped me? Caveat the first: just because something shows up as an anti-pattern doesn’t mean it needs to be fixed. There can be good reasons why you have chosen what is normally a less-efficient path. Caveat the second: just because something doesn’t show up as an anti-pattern doesn’t mean it’s fine. These are likely directional and my guess is that SQL Server will be fairly conservative in its estimation of what constitutes an anti-pattern so that you don’t get a lot of false positives.
Comments closedDeborah Melkin riddles us this on dynamic SQL:
I admit it – I do waaayyyy too much with dynamic SQL. But I just keep running into situations that require it. That being said, I ran into an interesting problem that had me puzzled. I found a bunch of different blog posts that pointed to me to the right direction but required a little extra work to find the solution.
There are several concepts that are at play here, so I’ll try to break this out so we can put the pieces together. The first once is centered around dynamic SQL. There are two parts of this I want to make sure we understand first – how it fits into sessions and how it gets executed.
Read the whole thing.
Comments closedKoen Verbeeck hits a concatenation issue:
I was writing some dynamic SQL that generates some SQL statements to load my facts and dimensions into a data warehouse. Some of those SQL statements can become very long, for example if a dimension has a lot of columns. When debugging, I noticed a couple of statements failing with various errors. Turns out, they were truncated after 4000 characters. What was going on?
Read on to see what happened.
Comments closedRyan Adams continues a series on querying the serverless SQL pool in Azure Synapse Analytics:
There are two ways to read data inside Data Lake using the Synapse Serverless engine. In this article, we’ll look at the second method which uses an external table to query a path within the lake.
Synapse is a collection of tools with four different analytical engines (Dedicated Pool, Spark Pool, Serverless Pool, Data Explorer Pool). This gives you a lot of options for ingesting, transforming, storing, and querying your data. Here you will use the Synapse Serverless Pool to query the data in your ADLS account.
Read on for a demonstration.
Comments closedRyan Adams begins a series on reading data from the data lake:
There are two ways to read data inside Data Lake using the Synapse Serverless engine. In this article, we’ll look at the first method which uses OPENROWSET to query a path within the lake.
Synapse is a collection of tools with four different analytical engines (Dedicated Pool, Spark Pool, Serverless Pool, Data Explorer Pool). This gives you a lot of options for ingesting, transforming, storing, and querying your data. The article will focus on how you can use the Synapse Serverless Pool to query the data in your ADLS account.
Click through for a primer on the topic, as well as a demo video.
Comments closedReitse Eskens does a performance comparison:
A few days ago, I heard someone stating that Group By was much quicker than Distinct. Less disk impact, less memory etc.
So, I thought I’d find out if it’s true or not because I found it interesting. I always thought there was no difference. I tested a single small table and found no difference in speed, reads or execution plan. But that’s no real world example. Usually the tables contain a lot of data and are joined to other tables.
Click through for the results of Reitse’s analysis.
Comments closed