Parameter Sniffing In Action
This article will demonstrate what is parameter sniffing and how can it can kill performance
2017-10-24
2,150 reads
This article will demonstrate what is parameter sniffing and how can it can kill performance
2017-10-24
2,150 reads
One crucial aspect of all databases is the transaction log. The transaction log is used to write all transactions prior to committing the data to the data file. In some circumstances the transaction logs can get quite large and not knowing what is in the transaction log or how much space is being used can become a problem. So how to you determine how much of the transaction log is being used and what portions are being used?
2017-10-24
4,163 reads
Microsoft has added a ton of new features in SQL Server 2017, including expanded operating system support, Graph database capability, Python support, and more. Join Greg Larsen as he explores nine of these new features.
2017-10-23
5,498 reads
A tale in which is detailed how I used SWITCH PARTITION to efficiently load my data and save myself from the flaming jaws of death.
2017-10-20 (first published: 2015-11-02)
4,343 reads
Azure Data Lake stores petabytes of data and analyzes trillions of objects in one place with no constraints. Data Lake Store can store any type of data including massive data like high-resolution video, medical data, and data from a wide variety of industries. Data Lake Store scales throughput to support any size of analytic workload with low latency. Read on to learn more.
2017-10-20
3,483 reads
How does one get a truly random sample of data of a certain size from a SQL Server database table. Well, there are simple non-portable tricks one can use, such as the NewID() function, but then refining those can be tricky. Take the Rand() function for a start. Can it really provide you with a truly random number? Why doesn't the TABLESAMPLE clause give you a set number of rows? Joe Celko scratches his head a bit, explains some of the issues and invites some suggestions and tricks from readers.
2017-10-19
3,623 reads
There is already a template on the Azure marketplace for setting up an AlwaysOn Availability Group. In just a few easy steps you can get a working AlwaysOn Availability Group setup, configured and running - this post describes the steps to quickly set it up.
2017-10-18
3,292 reads
Erik figures out why SQL Server really doesn't like combining these two things in a query plan.
2017-10-17
3,790 reads
Python is new to SQL Server 2017. It is intended primarily to allow the use of Python-based machine-learning within SQL Server, but it can be used for far more than this, with any Python libraries or Frameworks. To provide an example of what is possible, Hitendra shows how to use the feature securely to provide intelligent application caching, where SQL Server can automatically indicate when data changes to trigger a cache refresh.
2017-10-16
5,024 reads
Can data alert us that something is going on, without baselines and thresholds?
2017-10-13 (first published: 2016-02-23)
4,144 reads
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
Comments posted to this topic are about the item Database Mail in SQL Server...
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