Archiving with the OUTPUT clause

Most database developers have been faced with the task to archive old data. It could look something like this:

CREATE TABLE dbo.Cars(
  CarID int identity(1,1) PRIMARY KEY,
  BrandName varchar(100),
  ModelName varchar(100),
  releaseYear smallint
);

CREATE TABLE dbo.Cars_Archive(
  CarID int,
  BrandName varchar(100),
  ModelName varchar(100),
  releaseYear smallint,
  ArchivedDateTime datetime DEFAULT CURRENT_TIMESTAMP,
  CONSTRAINT PK_Cars_Archive PRIMARY KEY(CarID, ArchivedDateTime)
)

And updating a row would often require a stored procedure and some explicit transactions

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Statistics on ascending columns

I have had an annoying problem for a while. In a database used for a statistical survey system reporting is painfully slow in the beginning of each reporting period.

The system
The tables contain a few million rows. Ola Hallengren’s index maintenance (which includes UPDATE STATISTICS) is running weekly. Each month is a new reporting period. When a new reporting period opens, there are no rows for the current period. From the first day of the month, we receive input, each input being less than 2000 new rows in the table.

The problem
Reporting of any previous period is always consistent in execution time – around 3 seconds to produce a full report. That’s an OK performance. But when reporting is done for current period early in a reporting period, execution takes up to 10 minutes.

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Generate time slots

Here’s an Inline Table Valued Function (TVF) for generating time-slots from a start-date to an end-date, given a certain time for each slot, given in minutes.

This would be useful for many applications, like scheduling systems, sales statistics broken down into certain slices of time etc. The function does have some limitations, eg there can’t be more than 100.000 minutes between start and endtime. This is easily fixed by just adding Another CROSS JOIN to CTE2, or by changing the DATEADD-functions to use hour instead of minute if that fits your purpose.

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DELETE and Non Clustered Indexes

I’ll start off with a disclaimer: I’m going to tell you about something that happened in a specific system Environment. There’s no such thing as  a general advice you can build on this specific scenario. I’m just posting it because I was myself surprised by what order of magnitude I was able to speed up a specific query by slightly removing some of the work in the execution plan.

The other day I helped troubleshooting a database system. In a table with some 400 million records, a subset (50-60 million records) were to be deleted. The application kept timing out on this delete operation so I adviced the developer to split the delete operation into smaller chunks. I even helped writing a T-SQL script to perform the delete in one million row chunks. The script was pretty basic – a WHILE-loop which checked if any rows fulfilling the WHERE-condition of the delete was left in the table, and inside the loop a DELETE TOP(one million) followed by an explicit checkpoint.

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Impressions from Sql Saturday 433

I’m currently on a train from Gothenburg back home to Enköping. I have attended my first Sql Saturday (thank’s Mikael Wedham and crew for a great event!). I also did my first ever public SQL presentation at the event – a session about SQL Server partitioning.

The presentation and demo scripts can be downloaded from http://www.sqlsaturday.com/433/Sessions/Details.aspx?sid=38722

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SQL Saturday 433, Gothenburg

On September 5th, the first ever SQL Saturday in Sweden is held, in my favourite Swedish city Gothenburg. SQL Saturday Conferences are held all over the World and this first ever Swedish SQL Saturday event is the 433rd. And yeah, the Conference is for free. A full day of free training. If you are in the neighbourhood, you do want to be there. Check out the sessions and register here.

I’m very proud to have been selected on out of 24 speakers. My session – “Eight hours of work in 20 minutes” – is a case study of how a data load has evolved, from basically SSIS-loading data into a table, through some index maintenance as part of the data load, into table partitioning. The line-up makes me somewhat nervous, but it will be great fun to make a public appearance. Old friends showing up at the event makes it even better.

This is the first post on this blog. The future posts will be mostly about T-SQL.