Extreme wait-time when taking a SQL Server database offline

databaseperformancesql-server-2005

I'm trying to perform some offline maintenance (dev database restore from live backup) on my dev database, but the 'Take Offline' command via SQL Server Management Studio is performing extremely slowly – on the order of 30 minutes plus now. I am just about at my wits end and I can't seem to find any references online as to what might be causing the speed problem, or how to fix it.

Some sites have suggested that open connections to the database cause this slowdown, but the only application that uses this database is my dev machine's IIS instance, and the service is stopped – there are no more open connections.

What could be causing this slowdown, and what can I do to speed it up?

Best Answer

After some additional searching (new search terms inspired by gbn's answer and u07ch's comment on KMike's answer) I found this, which completed successfully in 2 seconds:

ALTER DATABASE <dbname> SET OFFLINE WITH ROLLBACK IMMEDIATE

(Update)

When this still fails with the following error, you can fix it as inspired by this blog post:

ALTER DATABASE failed because a lock could not be placed on database 'dbname' Try again later.

you can run the following command to find out who is keeping a lock on your database:

EXEC sp_who2

And use whatever SPID you find in the following command:

KILL <SPID>

Then run the ALTER DATABASE command again. It should now work.

Database Upgrade Scripts

A sequence database upgrade scripts that contain the DDL necessary to move the schema from version N to N+1. (These go in your version control system.) A _version_history_ table, something like

create table VersionHistory (
    Version int primary key,
    UpgradeStart datetime not null,
    UpgradeEnd datetime
    );

gets a new entry every time an upgrade script runs which corresponds to the new version.

This ensures that it's easy to see what version of the database schema exists and that database upgrade scripts are run only once. Again, these are not database dumps. Rather, each script represents the changes necessary to move from one version to the next. They're the script that you apply to your production database to "upgrade" it.

Developer Sandbox Synchronization

A script to backup, sanitize, and shrink a production database. Run this after each upgrade to the production DB.
A script to restore (and tweak, if necessary) the backup on a developer's workstation. Each developer runs this script after each upgrade to the production DB.

A caveat: My automated tests run against a schema-correct but empty database, so this advice will not perfectly suit your needs.

Sql – Add a column with a default value to an existing table in SQL Server

Syntax:

ALTER TABLE {TABLENAME} 
ADD {COLUMNNAME} {TYPE} {NULL|NOT NULL} 
CONSTRAINT {CONSTRAINT_NAME} DEFAULT {DEFAULT_VALUE}
WITH VALUES

Example:

ALTER TABLE SomeTable
        ADD SomeCol Bit NULL --Or NOT NULL.
 CONSTRAINT D_SomeTable_SomeCol --When Omitted a Default-Constraint Name is autogenerated.
    DEFAULT (0)--Optional Default-Constraint.
WITH VALUES --Add if Column is Nullable and you want the Default Value for Existing Records.

Notes:

Optional Constraint Name:
If you leave out CONSTRAINT D_SomeTable_SomeCol then SQL Server will autogenerate
a Default-Contraint with a funny Name like: DF__SomeTa__SomeC__4FB7FEF6

Optional With-Values Statement:
The WITH VALUES is only needed when your Column is Nullable
and you want the Default Value used for Existing Records.
If your Column is NOT NULL, then it will automatically use the Default Value
for all Existing Records, whether you specify WITH VALUES or not.

How Inserts work with a Default-Constraint:
If you insert a Record into SomeTable and do not Specify SomeCol's value, then it will Default to 0.
If you insert a Record and Specify SomeCol's value as NULL (and your column allows nulls),
then the Default-Constraint will not be used and NULL will be inserted as the Value.

Notes were based on everyone's great feedback below.
Special Thanks to:
@Yatrix, @WalterStabosz, @YahooSerious, and @StackMan for their Comments.