Dropping a database column in production without waiting time and/or schema-aware code, on a MySQL/Rails setup
We recently had to drop a column in production, from a relatively large (order of 10⁷ records) table.
On modern MySQL setups, dropping a column doesn’t lock the table (it does, actually, but for a relatively short time), however, we wanted to improve a very typical Rails migration scenario in a few ways:
- offloading the column dropping time from the deploy;
- ensuring that in the time between the column is dropped and the app servers restarted, the app doesn’t raise errors due to the expectation that the column is present;
- not overloading the database with I/O.
I’ll give the Gh-ost tool a brief introduction, and show how to fulfill the above requirements in a simple way, by using this tool and an ActiveRecord flag.
This workflow can be applied to almost any table alteration scenario.
- Setup and workflow
Gh-ost is a relatively recent tool by GitHub, which allows online table modifications without locking.
Tools like gh-ost existed before - the first being
pt-online-schema-change), developed by Percona.
The Percona tool relies on triggers in order to achieve the objective, which is a good enough, stable, solution. However, there are a variety of reasons that (can) make the tool inadequate for high-load conditions.
Gh-ost introduced the novel idea of reading from the binary log (which logs all the write operation) in order to reproduce the writes on the temporary table.
Gh-ost can be run in different setups; this article will show the simplest one.
Setup and workflow
Let’s assume the following table:
CREATE TABLE `customers` ( --- column definitions `source_id` int(11) NOT NULL, -- index definitions KEY `index_customers_on_source_id` (`source_id`) );
with the corresponding model:
class Customer < ApplicationRecord # model content end
class DropCustomersSourceId < ActiveRecord::Migration def change remove_column :customers, :source_id end end
Configure ActiveRecord for ignoring the column, and performing the deploy
First, we tackle point #2. Let’s have a look at the stages of a typical deploy with migrations:
- the deploy starts: various operations are performed, including copying the new codebase to a release directory, without the app servers actually (re)loading it;
- the migrations are executed - in this case, with an underlying
ALTER TABLEstatement, which will take a long time;
- the current release directory is linked to the new codebase, and the app servers (processes) are restarted;
- other operations are performed.
The problem is that between the stages 2. and 3. (and also, depending on the app server configuration, during the processes restart), the app servers will have in memory the old version of the codebase, which expects
customers.source_id to be present.
Although this time is relatively short, on a high-load environment, if a
Customer instance is saved, the operation will fail, because ActiveRecord will include the column in the underlying INSERT.
In systems engineering, schema-aware code strategy is sometimes applied: essentially, writing code in the form “if the schema is
bar, otherwise, do
In the case of a column drop, we have at our disposal a “cheap” schema-aware strategy:
ignored_columns (see the Rails PR).
This directive makes ActiveRecord entirely ignore a column, so that the column can disappear at any time, without ActiveRecord noticing.
Let’s update the model:
class Customer < ApplicationRecord self.ignored_columns = %w(source_id) # model content end
and the migration:
class DropcustomersSourceId < ActiveRecord::Migration[5.2] def change remove_column :customers, :source_id unless is_production_environment? end def is_production_environment? # choose strategy end end
We can now perform the deploy; this time, the table column will not be dropped. After the deploy, we will use gh-ost, as outlined in the next section.
Using gh-ost to drop the column
Gh-ost is pretty straightforward to use. In this context it’s used in the simplest way possible, that is, running directly on master.
Note that there are many options available, including:
- sharing the load with slaves,
- regulating the I/O load,
- not including the password in the command (for security reasons).
A summary document is available here; gh-ost has good documentation.
The sample command we use is:
$ GHOST_TABLE="customers" $ GHOST_ALTER="DROP source_id" $ gh-ost \ --user="$GHOST_USER" --password="$GHOST_PASSWORD" --host="$GHOST_HOST" \ --database="$GHOST_SCHEMA" --table="$GHOST_TABLE" --alter="$GHOST_ALTER" \ --allow-on-master --exact-rowcount --verbose --execute
The options are clear;
--exact-rowcount will trade a little execution time for more accurate progress estimation.
Gh-ost will create a temporary (in a logical, not SQL, sense) table, slowly fill it and update with original table updates, then swap (with negligible locking time) them.
A crucial detail is that gh-ost will leave the original table in the database, renamed (in this case,
Although there is an option to drop the table automatically, do not enable it or do not attempt to do it manually: dropping a large table creates a large amount of I/O, due to MySQL freeing the pool pages, which will likely halt the database system to a grind for some time. Instead, one should follow a progressive table drop workflow:
- drop the indexes (optionally, individually);
- delete the records in batches;
- drop the (now empty) table.
Between each drop/deletion,
SLEEP calls should be performed, in order to ensure that the writes are fully flushed.
Internally, we have a script for this, and it’s advised to find or develop something similar.
SLEEP can be replaced with sophisticated strategies (eg. relying on the server statistics to track the I/O), however, in our system,
SLEEP is a perfectly adequate while simple strategy.
ignored_columns and redeploy
At this point, in production, Rails will be completely unaware of the existence (or not) of the column (being) dropped.
After the column is dropped, we can remove the
Customer.ignored_columns directive, and deploy any time (or even wait for the next deploy).
We’ve been using gh-ost for a long time by now, and we’ve developed a surrounding tooling ecosystem.
Once one gets used to such workflows, it’s actually satisfying to perform “push-button” table alterations without any locking or performance drop in general, instead of being worried of the impact of (relatively) large-scale db operations.
Paraphrasing the typical joke:
- Did you notice the downtime today during the migration?
- WHAT!?! NO!