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What requires downtime?
When working with a database certain operations can be performed without taking GitLab offline, others do require a downtime period. This guide describes various operations, their impact, and how to perform them without requiring downtime.
Adding Columns
On PostgreSQL you can safely add a new column to an existing table as long as it does not have a default value. For example, this query would not require downtime:
ALTER TABLE projects ADD COLUMN random_value int;
Add a column with a default however does require downtime. For example, consider this query:
ALTER TABLE projects ADD COLUMN random_value int DEFAULT 42;
This requires updating every single row in the projects
table so that
random_value
is set to 42
by default. This requires updating all rows and
indexes in a table. This in turn acquires enough locks on the table for it to
effectively block any other queries.
As of MySQL 5.6 adding a column to a table is still quite an expensive
operation, even when using ALGORITHM=INPLACE
and LOCK=NONE
. This means
downtime may be required when modifying large tables as otherwise the
operation could potentially take hours to complete.
Adding a column with a default value can be done without requiring downtime
when using the migration helper method
Gitlab::Database::MigrationHelpers#add_column_with_default
. This method works
similar to add_column
except it updates existing rows in batches without
blocking access to the table being modified. See "Adding Columns With Default
Values" for more
information on how to use this method.
Dropping Columns
Removing columns is tricky because running GitLab processes may still be using the columns. To work around this you will need two separate merge requests and releases: one to ignore and then remove the column, and one to remove the ignore rule.
Step 1: Ignoring The Column
The first step is to ignore the column in the application code. This is
necessary because Rails caches the columns and re-uses this cache in various
places. This can be done by including the IgnorableColumn
module into the
model, followed by defining the columns to ignore. For example, to ignore
updated_at
in the User model you'd use the following:
class User < ActiveRecord::Base
include IgnorableColumn
ignore_column :updated_at
end
Once added you should create a post-deployment migration that removes the column. Both these changes should be submitted in the same merge request.
Step 2: Removing The Ignore Rule
Once the changes from step 1 have been released & deployed you can set up a
separate merge request that removes the ignore rule. This merge request can
simply remove the ignore_column
line, and the include IgnorableColumn
line
if no other ignore_column
calls remain.
Renaming Columns
Renaming columns the normal way requires downtime as an application may continue using the old column name during/after a database migration. To rename a column without requiring downtime we need two migrations: a regular migration, and a post-deployment migration. Both these migration can go in the same release.
Step 1: Add The Regular Migration
First we need to create the regular migration. This migration should use
Gitlab::Database::MigrationHelpers#rename_column_concurrently
to perform the
renaming. For example
# A regular migration in db/migrate
class RenameUsersUpdatedAtToUpdatedAtTimestamp < ActiveRecord::Migration
include Gitlab::Database::MigrationHelpers
disable_ddl_transaction!
def up
rename_column_concurrently :users, :updated_at, :updated_at_timestamp
end
def down
cleanup_concurrent_column_rename :users, :updated_at_timestamp, :updated_at
end
end
This will take care of renaming the column, ensuring data stays in sync, copying over indexes and foreign keys, etc.
NOTE: if a column contains 1 or more indexes that do not contain the name of the original column, the above procedure will fail. In this case you will first need to rename these indexes.
Step 2: Add A Post-Deployment Migration
The renaming procedure requires some cleaning up in a post-deployment migration.
We can perform this cleanup using
Gitlab::Database::MigrationHelpers#cleanup_concurrent_column_rename
:
# A post-deployment migration in db/post_migrate
class CleanupUsersUpdatedAtRename < ActiveRecord::Migration
include Gitlab::Database::MigrationHelpers
disable_ddl_transaction!
def up
cleanup_concurrent_column_rename :users, :updated_at, :updated_at_timestamp
end
def down
rename_column_concurrently :users, :updated_at_timestamp, :updated_at
end
end
Changing Column Constraints
Adding or removing a NOT NULL clause (or another constraint) can typically be
done without requiring downtime. However, this does require that any application
changes are deployed first. Thus, changing the constraints of a column should
happen in a post-deployment migration.
NOTE: Avoid using change_column
as it produces inefficient query because it re-defines
the whole column type. For example, to add a NOT NULL constraint, prefer change_column_null
Changing Column Types
Changing the type of a column can be done using
Gitlab::Database::MigrationHelpers#change_column_type_concurrently
. This
method works similarly to rename_column_concurrently
. For example, let's say
we want to change the type of users.username
from string
to text
.
Step 1: Create A Regular Migration
A regular migration is used to create a new column with a temporary name along with setting up some triggers to keep data in sync. Such a migration would look as follows:
# A regular migration in db/migrate
class ChangeUsersUsernameStringToText < ActiveRecord::Migration
include Gitlab::Database::MigrationHelpers
disable_ddl_transaction!
def up
change_column_type_concurrently :users, :username, :text
end
def down
cleanup_concurrent_column_type_change :users, :username
end
end
Step 2: Create A Post Deployment Migration
Next we need to clean up our changes using a post-deployment migration:
# A post-deployment migration in db/post_migrate
class ChangeUsersUsernameStringToTextCleanup < ActiveRecord::Migration
include Gitlab::Database::MigrationHelpers
disable_ddl_transaction!
def up
cleanup_concurrent_column_type_change :users
end
def down
change_column_type_concurrently :users, :username, :string
end
end
And that's it, we're done!
Changing Column Types For Large Tables
While change_column_type_concurrently
can be used for changing the type of a
column without downtime it doesn't work very well for large tables. Because all
of the work happens in sequence the migration can take a very long time to
complete, preventing a deployment from proceeding.
change_column_type_concurrently
can also produce a lot of pressure on the
database due to it rapidly updating many rows in sequence.
To reduce database pressure you should instead use
change_column_type_using_background_migration
when migrating a column in a
large table (e.g. issues
). This method works similar to
change_column_type_concurrently
but uses background migration to spread the
work / load over a longer time period, without slowing down deployments.
Usage of this method is fairly simple:
class ExampleMigration < ActiveRecord::Migration
include Gitlab::Database::MigrationHelpers
disable_ddl_transaction!
class Issue < ActiveRecord::Base
self.table_name = 'issues'
include EachBatch
def self.to_migrate
where('closed_at IS NOT NULL')
end
end
def up
change_column_type_using_background_migration(
Issue.to_migrate,
:closed_at,
:datetime_with_timezone
)
end
def down
change_column_type_using_background_migration(
Issue.to_migrate,
:closed_at,
:datetime
)
end
end
This would change the type of issues.closed_at
to timestamp with time zone
.
Keep in mind that the relation passed to
change_column_type_using_background_migration
must include EachBatch
,
otherwise it will raise a TypeError
.
Adding Indexes
Adding indexes is an expensive process that blocks INSERT and UPDATE queries for
the duration. When using PostgreSQL one can work arounds this by using the
CONCURRENTLY
option:
CREATE INDEX CONCURRENTLY index_name ON projects (column_name);
Migrations can take advantage of this by using the method
add_concurrent_index
. For example:
class MyMigration < ActiveRecord::Migration
def up
add_concurrent_index :projects, :column_name
end
def down
remove_index(:projects, :column_name) if index_exists?(:projects, :column_name)
end
end
Note that add_concurrent_index
can not be reversed automatically, thus you
need to manually define up
and down
.
When running this on PostgreSQL the CONCURRENTLY
option mentioned above is
used. On MySQL this method produces a regular CREATE INDEX
query.
MySQL doesn't really have a workaround for this. Supposedly it can create indexes without the need for downtime but only for variable width columns. The details on this are a bit sketchy. Since it's better to be safe than sorry one should assume that adding indexes requires downtime on MySQL.
Dropping Indexes
Dropping an index does not require downtime on both PostgreSQL and MySQL.
Adding Tables
This operation is safe as there's no code using the table just yet.
Dropping Tables
Dropping tables can be done safely using a post-deployment migration, but only if the application no longer uses the table.
Adding Foreign Keys
Adding foreign keys usually works in 3 steps:
- Start a transaction
- Run
ALTER TABLE
to add the constraint(s) - Check all existing data
Because ALTER TABLE
typically acquires an exclusive lock until the end of a
transaction this means this approach would require downtime.
GitLab allows you to work around this by using
Gitlab::Database::MigrationHelpers#add_concurrent_foreign_key
. This method
ensures that when PostgreSQL is used no downtime is needed.
Removing Foreign Keys
This operation does not require downtime.
Data Migrations
Data migrations can be tricky. The usual approach to migrate data is to take a 3 step approach:
- Migrate the initial batch of data
- Deploy the application code
- Migrate any remaining data
Usually this works, but not always. For example, if a field's format is to be changed from JSON to something else we have a bit of a problem. If we were to change existing data before deploying application code we'll most likely run into errors. On the other hand, if we were to migrate after deploying the application code we could run into the same problems.
If you merely need to correct some invalid data, then a post-deployment migration is usually enough. If you need to change the format of data (e.g. from JSON to something else) it's typically best to add a new column for the new data format, and have the application use that. In such a case the procedure would be:
- Add a new column in the new format
- Copy over existing data to this new column
- Deploy the application code
- In a post-deployment migration, copy over any remaining data
In general there is no one-size-fits-all solution, therefore it's best to discuss these kind of migrations in a merge request to make sure they are implemented in the best way possible.