Dinesh Asanka

  • Interests: Watching Cricket / Writing Articles

SQLServerCentral Article

Review Armtech for SQL Server

How many times have you wished you could throttle the CPU use of SQL Server? Or for a database? Prevent your developers from using too many resources while sharing the server with production or QA. ArmTech for Windows can do this and Dinsesh Asanka brings us a review of how this product worked in his environment.

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2005-07-26

5,481 reads

SQLServerCentral Article

The Multi Phase Data Pump

SQL Server 2000 has an amazing ETL tool in Data Transformation Services that is included at no charge, something none of the other database vendors include. DTS has great flexibility to make your job easier, but it has some quirks in this version. The Multi Phase Data Pump is hidden inside the tool, but can provide a great programming environment and Dinesh Asanka brings us a look at what you can do wit this tool.

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2005-03-29

12,009 reads

SQLServerCentral Article

Upsizing the Access Database into the SQL Server

SQL Server and Access are usually linked together as Access used for applications at the beginning of their lifecycle that are later moved to SQL Server when the load gets too high or the data sizes grow. There are often cases where you may also want to use SQL Server as a backend to an Access application. But how do you get your data from Access to SQL Server? Author Dinesh Asanka brings us an overview of the various ways that you can move your Access database to SQL Server.

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2005-02-21

16,935 reads

SQLServerCentral Article

Best Practices are always the Best

On this site, we have taken a contrarian approach to looking at the ways to configure SQL Server with our Worst Practices series. However Microsoft still looks at it from the other side and release a tool called the Best Practices Analyzer for SQL Server. Author Dinesh Asanka brings us a short look at this tool.

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2004-11-11

12,629 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;

See possible answers