Put Your Thinking Caps On
Three contests from Red Gate Software are coming next week. Get a hint about what might be coming and set a reminder on your calendar.
Three contests from Red Gate Software are coming next week. Get a hint about what might be coming and set a reminder on your calendar.
One piece of advice that is often given to new SQL Server administrators is not to shrink their databases. But they seem to do it often enough anyway. For this Friday's poll, Steve Jones asks if we should do away with shrink.
Cross-posted from a Goal Keeping DBA blog:
Just recently, my oldest son entered the ranks of the teenagers. I shouldn’t actually...
I’ve been pretty quite since the PASS Summit and with good reason. Every year we have a chapter leader meeting....
Data warehousing and general reporting applications tend to be CPU intensive because they need to read and process a large number of rows. To facilitate quick data processing for queries that touch a large amount of data, Microsoft SQL Server exploits the power of multiple logical processors to provide parallel query processing operations such as parallel scans. Through extensive testing, we have learned that, for most large queries that are executed in a parallel fashion, SQL Server can deliver linear or nearly linear response time speedup as the number of logical processors increases. However, some queries in high parallelism scenarios perform suboptimally. There are also some parallelism issues that can occur in a multi-user parallel query workload. This white paper describes parallel performance problems you might encounter when you run such queries and workloads, and it explains why these issues occur. In addition, it presents how data warehouse developers can detect these issues, and how they can work around them or mitigate them.
Microsoft is working to certify vendors to build private clouds, which Steve Jones thinks is a great idea.
A look at what's happening with the SQLServerCentral servers based on the public information exposed by SQL Monitor.
Normalization is standard practice in database design, however, an over-normalized database can have issues. This article examines the case for denormalization.
The call for speakers is open through December 15, 2010, and I hope many of you will take the chance...
Can you accurately determine the cost or benefit of a new, cool project up front? Steve Jones thinks not, but coming up with new projects can be a way to set yourself apart from others.
If you've ever loaded a 2 GB CSV into pandas just to run a...
By James Serra
What problem is Fabric Ontology trying to solve? For years, most data conversations have...
By Steve Jones
Recently I ran across some code that used a lot of QUOTENAME() calls. A...
Comments posted to this topic are about the item The New Software Team
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Comments posted to this topic are about the item The string_agg function
We create the following table and then insert some records in it:
create table t1 ( id int primary key, category char(1) not null, product varchar(50) ); insert into t1 values (1, 'A', 'Product 1'), (2, 'A', 'Product 2'), (3, 'A', 'Product 3'), (4, 'B', 'Product 4'), (5, 'B', 'Product 5');What happens if we execute the following query in both Sql Server and PostgreSQL?
select id,
category,
string_agg(product, ';')
over (partition by category order by id
rows between unbounded preceding and unbounded following) as stragg
from t1; See possible answers