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SQL Data Aggregation Aggravation

When we have to deal with and store a lot of data, it makes sense to aggregate it so that we store only the information we actually need. If we get this right, this works well, but the design of the system takes care and thought because the problems can be subtle and various. Joe Celko describes some of the ways that things can go wrong and end up providing incorrect, inaccurate or misleading results.

2017-09-12

3,866 reads

External Article

SQL Graph Objects in SQL Server 2017: the Good and the Bad

Graph databases are useful for certain types of database tasks that involve representing and traversing complex relationships between entities. These can be difficult to do in relational databases and even trickier to report on. Until now, we have had the choice of doing it awkwardly in SQL Server or having an ancillary database to tackle this type of task. SQL Server 2017 will be bringing graph capabilities to the product but will these features prove to be good enough to allow us to dispense with specialised Graph databases? Dennes Torres decided to find out.

2017-09-07

3,818 reads

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The string_agg function

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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;

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