Day 20 of 31 Days of Disaster Recovery: The Case of the Backups That Wouldn’t Restore
I have decided to spend day 20 of my 31 Days of Disaster Recovery series by relating a true tale...
2013-01-25
1,138 reads
I have decided to spend day 20 of my 31 Days of Disaster Recovery series by relating a true tale...
2013-01-25
1,138 reads
It’s day 19 of my 31 Days of Disaster Recovery series, and today I want to talk about how much...
2013-01-24
1,191 reads
Day 18 of my 31 Days of Disaster Recovery series is drawing to a close. It’s 11:22 PM here, and...
2013-01-23
1,190 reads
Today is day 17 of 31 Days of Disaster Recovery. The series has skipped a couple of days due to...
2013-01-24 (first published: 2013-01-21)
1,851 reads
It’s day 16 of my series 31 Days of Disaster Recovery. I’ve seen a lot of great DR related posts...
2013-01-18
911 reads
Welcome back to my 31 Days of Disaster Recovery series. Today is day 15, and I want to answer a...
2013-01-17
1,418 reads
Welcome to day 14 of my 31 Days of Disaster Recovery series. I’ve previously discussed handling corruption for nonclustered indexes...
2013-01-16
2,234 reads
31 Days of Disaster Recovery
Today’s post took longer to prepare than I had anticipated which is why day 13...
2013-01-15
1,447 reads
31 Days of Disaster Recovery
Fittingly, today’s focus on disaster recovery as part of my 31 Days of Disaster Recovery...
2013-01-12
1,334 reads
31 Days of Disaster Recovery
Welcome back to my series 31 Days of Disaster Recovery. Today is day 11, and...
2013-01-12
3,925 reads
By Steve Jones
Redgate is a for-profit company. We look to make money by building and selling...
I’ve uploaded the slides for my Techorama session Microsoft Fabric for Dummies and my...
If you've ever loaded a 2 GB CSV into pandas just to run a...
Comments posted to this topic are about the item Even When You Know What...
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...
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