debian-mirror-gitlab/doc/development/what_requires_downtime.md
2018-03-17 18:26:18 +05:30

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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:

  1. Start a transaction
  2. Run ALTER TABLE to add the constraint(s)
  3. 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:

  1. Migrate the initial batch of data
  2. Deploy the application code
  3. 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:

  1. Add a new column in the new format
  2. Copy over existing data to this new column
  3. Deploy the application code
  4. 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.