2023-07-18 (first published: 2009-11-11)
867 reads
2023-07-18 (first published: 2009-11-11)
867 reads
In the world of SQL Server, adaptation is key. While the built-in GENERATE_SERIES() function was a valuable addition in SQL Server 2022, its absence in older versions created a functionality gap. Enter the user-written GENERATE_SERIES function. Adapted from Jeff Moden's "dbo.fnTally", it offers an efficient means to generate a series of numbers within a defined range in older SQL Server versions. Its design mirrors the built-in function in SQL Server 2022, making the transition between versions as simple as removing the dbo. prefix. This forward-thinking design reflects the ingenuity of the SQL Server community, ensuring a seamless, efficient database migration experience.
2023-06-26 (first published: 2023-06-16)
2,818 reads
An audit finding relating to production data, containing customer identifiable data, in a UAT environment, prompted this simple script, which completely scrambles data in such a way that the original value can not be reconstituted.
2023-05-24 (first published: 2023-05-19)
915 reads
If you need to extract a substring or create a longer string by combining multiple strings, there are a few methods you can use. To extract a specific portion of a string, you can utilize a substring-extraction function.
2023-05-09 (first published: 2023-05-05)
384 reads
This Python 3 script is designed to take CSV file data pasted into the csv_data variable and generate SQL insert statements that can be used to insert the data into a MySQL database. The script is easy to use and can save you a lot of time when working with large amounts of data.
2023-05-08 (first published: 2023-05-05)
5,827 reads
The Problem As a data professional, I have often wished that there was a short, simple, and universal code to enable finding a place on earth. Addresses are nice but require a government authority to build a road, name it, and number its locations, and standardize its entry / use, and then they are far […]
2023-03-30 (first published: 2023-03-23)
210 reads
2023-02-22 (first published: 2023-02-14)
621 reads
A quick script that removes leading zeros in a numeric stored as a string.
2022-12-30 (first published: 2022-12-26)
2,669 reads
An alternative for Microsoft's STRING_SPLIT function that will work on SQL Server 2012 and higher.
2022-12-19 (first published: 2021-03-05)
430 reads
Simplified latitude / longitude in 10 fixed bytes.
2022-10-26 (first published: 2022-10-21)
605 reads
By Steve Jones
Redgate is a for-profit company. We look to make money by building and selling...
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...
Tlp/Wa_Cs:0817-866-887 Jl. Brigjen Sudiarto No.294, Palebon, Kec. Pedurungan, Kota Semarang, Jawa Tengah 50273
Tlp/Wa_Cs:0817-866-887 Jl. Majapahit No.112, Pandean Lamper, Kec. Gayamsari, Kota Semarang, Jawa Tengah 50161
Tlp/Wa_Cs:0817-866-887 Jl. Jenderal Ahmad Yani No.24-26, Panderejo, Kec. Banyuwangi, Kabupaten Banyuwangi, Jawa Timur 68416
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