External Article

Causation, Correlation and Crackpots

Joe Celko explores the dangers of muddling correlation and causation, emphasises the importance of determining how likely it is that a correlation has occurred by chance, and gets stuck into calculating correlation coefficients in SQL. Along the way, Joe illustrates the consequences of leaping to the wrong conclusion from correlations with tales of Pop Dread.

Blogs

Stop Using Pandas for Aggregations — Try DuckDB Instead

By

If you've ever loaded a 2 GB CSV into pandas just to run a...

Understanding Fabric Ontology

By

What problem is Fabric Ontology trying to solve? For years, most data conversations have...

QUOTENAME Basics: #SQLNewBlogger

By

Recently I ran across some code that used a lot of QUOTENAME() calls. A...

Read the latest Blogs

Forums

The New Software Team

By Steve Jones - SSC Editor

Comments posted to this topic are about the item The New Software Team

Database Mail in SQL Server 2022

By Abdellateef Ibrahim

Comments posted to this topic are about the item Database Mail in SQL Server...

The string_agg function

By Alessandro Mortola

Comments posted to this topic are about the item The string_agg function

Visit the forum

Question of the Day

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