SSAS 2017 introduces the 1400 compatibility level. Here are just some highlights of the new features:
New infrastructure for data connectivity and ingestion into tabular models with support for TOM APIs and TMSL scripting. This enables support for a range of additional data sources, and data transformation and mashup capabilities.
Support for BI tools such as Microsoft Excel enables drill-down to detailed data from an aggregated report. For example, when end-users view total sales for a region and month, they can view the associated order details.
Object-level security to secure table and column names in addition to the data within them.
Enhanced support for ragged hierarchies such as organizational charts and chart of accounts.
Various other improvements for performance, monitoring, and consistency with the Power BI modeling experience.
There’s plenty more where that came from (unless you’re a Multidimensional fan…), so click through for the details.
SQL Server doesn’t process parts of a query in the same order they’re written. Rather than start with SELECT the way we read and write it, here’s the order SQL Server progresses through:
- GROUP BY
- ORDER BY
The first four steps are all about getting the source data and reducing the result set down. Steps 5 & 6 determine which columns are presented and in which order. Step 7 (TOP) is only applied at the end because you can’t say which rows are in the top n rows until the set has been sorted. (You can read Itzik Ben-Gan’s explanation of this process in way more detail here.)
Definitely worth reading. Doug also shows how to get around this fact of life and get the equivalent of a window function inside a WHERE clause, at least in terms of function if not necessarily performance.
This is a good question. There’s a few ways to address it:
- We could configure two different connection strings and on failover, the alternative is used (by any arbitrary application mechanism)
- For mirroring, we can use the Failover Partner= element in the connection string – but this is transactional replication being used for DR, and failover should be manual
- We could set the instance names to be the same – however in this case it was too late since changing the instance name cleanly in SQL Server is practically impossible and breaks all sorts of things
None of these solutions was suitable. However, on each server, there was only one named instance and no default instance. What can we do?
Read on for a fourth solution.
As stated via official Microsoft documentation “Pausing the Database Engine service prevents new users from connecting to the Database Engine, but users who are already connected can continue to work until their connections are broken. Use pause when you want to wait for users to complete work before you stop the service. This enables them to complete transactions that are in progress”.
Very handy! Let’s see it in action and compare it to a STOP.
Read on for more.
Have you ever had the need to use Regular Expressions directly in SQL Server? I sometimes hear or see others refer to using RegEx in TSQL. But I always assume they’re talking about the TSQL LIKE operator, because RegEx isn’t natively supported. In TSQL’s defence, you can get a lot of mileage out of LIKE and some clever pattern matching strings, even though it’s not authentic RegEx. You can leverage RegEx libraries in the .NET Framework via a CLR stored procedure. You should also be able to do something similar with an old-school extended stored procedure.
I discussed all of this during a recent interview. It was a day or two afterwards (of course) when it dawned on me that there’s another way to leverage RegEx from TSQL: the R language. Prior to this mini-revelation, I had always thought of R (and Python) as strictly a means to an end for Data Science and related disciplines. Now I am thinking I’ve been looking at R and Python through too narrow of a lens and I should take a larger view.
I think I’d prefer CLR for this because there’s additional overhead to making R Services calls, but it’s a clever use of R Services.
Starting with SQL Server 2017, we are adopting a simplified, predictable mainstream servicing lifecycle:
- SPs will no longer be made available. Only CUs, and GDRs when needed.
- CUs will now accommodate localized content, allowing new feature completeness and supportability enhancements to be delivered faster.
- CUs will be delivered more often at first and then less frequently. Every month for the first 12 months, and every quarter for the remainder 4 years of the full 5-year mainstream lifecycle.
- CUs are delivered on the same week of the month: week of 3rd Tuesday.
Note: the Modern Servicing Model (MSM) only applies to SQL Server 2017 and future versions.
If you’re the type who waits for SP1 to drop, you’ll be waiting for Godot. Who should be here any minute now.
Today, October 2nd, we are excited to announce that SQL Server 2017 is generally available for purchase and download! The new release is available right now for evaluation or purchase through the Microsoft Store, and will be available to Volume Licensing customers later today. Customers now have the flexibility for the first time ever to run industry-leading SQL Server on their choice of Linux, Docker Enterprise Edition-certified containers and, of course, Windows Server. It’s a stride forward for our modern and hybrid data platform across on-premises and cloud.
In the 18 months since announcing our intent to bring SQL Server to Linux, we’ve been focused on making SQL Server perform and scale to the industry-leading levels customers expect from SQL Server, making SQL Server feel familiar yet native to Linux, and ensuring compatibility between SQL Server on Windows and Linux. With all the enterprise database features you rely on, from Active Directory authentication, to encryption, to Always On availability groups, to record-breaking performance, SQL Server is at parity on Windows and Linux. We have also brought SQL Server Integration Services to Linux so that you can perform data integration just like on Windows. SQL Server 2017 supports Red Hat Enterprise Linux, SUSE Linux Enterprise Server, and Ubuntu.
It’s only been a year, but there’s a lot in this new version. Click through for a high-level summary.