SQL Query Guidelines
This document describes various guidelines to follow when writing SQL queries, either using ActiveRecord/Arel or raw SQL queries.
LIKE
Statements
Using The most common way to search for data is using the LIKE
statement. For
example, to get all issues with a title starting with "Draft:" you'd write the
following query:
SELECT *
FROM issues
WHERE title LIKE 'Draft:%';
On PostgreSQL the LIKE
statement is case-sensitive. To perform a case-insensitive
LIKE
you have to use ILIKE
instead.
To handle this automatically you should use LIKE
queries using Arel instead
of raw SQL fragments, as Arel automatically uses ILIKE
on PostgreSQL.
Issue.where('title LIKE ?', 'Draft:%')
You'd write this instead:
Issue.where(Issue.arel_table[:title].matches('Draft:%'))
Here matches
generates the correct LIKE
/ ILIKE
statement depending on the
database being used.
If you need to chain multiple OR
conditions you can also do this using Arel:
table = Issue.arel_table
Issue.where(table[:title].matches('Draft:%').or(table[:foo].matches('Draft:%')))
On PostgreSQL, this produces:
SELECT *
FROM issues
WHERE (title ILIKE 'Draft:%' OR foo ILIKE 'Draft:%')
LIKE
& Indexes
PostgreSQL does not use any indexes when using LIKE
/ ILIKE
with a wildcard at
the start. For example, this does not use any indexes:
SELECT *
FROM issues
WHERE title ILIKE '%Draft:%';
Because the value for ILIKE
starts with a wildcard the database is not able to
use an index as it doesn't know where to start scanning the indexes.
Luckily, PostgreSQL does provide a solution: trigram Generalized Inverted Index (GIN) indexes. These indexes can be created as follows:
CREATE INDEX [CONCURRENTLY] index_name_here
ON table_name
USING GIN(column_name gin_trgm_ops);
The key here is the GIN(column_name gin_trgm_ops)
part. This creates a
GIN index
with the operator class set to gin_trgm_ops
. These indexes
can be used by ILIKE
/ LIKE
and can lead to greatly improved performance.
One downside of these indexes is that they can easily get quite large (depending
on the amount of data indexed).
To keep naming of these indexes consistent, use the following naming pattern:
index_TABLE_on_COLUMN_trigram
For example, a GIN/trigram index for issues.title
would be called
index_issues_on_title_trigram
.
Due to these indexes taking quite some time to be built they should be built
concurrently. This can be done by using CREATE INDEX CONCURRENTLY
instead of
just CREATE INDEX
. Concurrent indexes can not be created inside a
transaction. Transactions for migrations can be disabled using the following
pattern:
class MigrationName < Gitlab::Database::Migration[2.1]
disable_ddl_transaction!
end
For example:
class AddUsersLowerUsernameEmailIndexes < Gitlab::Database::Migration[2.1]
disable_ddl_transaction!
def up
execute 'CREATE INDEX CONCURRENTLY index_on_users_lower_username ON users (LOWER(username));'
execute 'CREATE INDEX CONCURRENTLY index_on_users_lower_email ON users (LOWER(email));'
end
def down
remove_index :users, :index_on_users_lower_username
remove_index :users, :index_on_users_lower_email
end
end
Reliably referencing database columns
ActiveRecord by default returns all columns from the queried database table. In some cases the returned rows might need to be customized, for example:
- Specify only a few columns to reduce the amount of data returned from the database.
- Include columns from
JOIN
relations. - Perform calculations (
SUM
,COUNT
).
In this example we specify the columns, but not their tables:
-
path
from theprojects
table -
user_id
from themerge_requests
table
The query:
# bad, avoid
Project.select("path, user_id").joins(:merge_requests) # SELECT path, user_id FROM "projects" ...
Later on, a new feature adds an extra column to the projects
table: user_id
. During deployment there might be a short time window where the database migration is already executed, but the new version of the application code is not deployed yet. When the query mentioned above executes during this period, the query fails with the following error message: PG::AmbiguousColumn: ERROR: column reference "user_id" is ambiguous
The problem is caused by the way the attributes are selected from the database. The user_id
column is present in both the users
and merge_requests
tables. The query planner cannot decide which table to use when looking up the user_id
column.
When writing a customized SELECT
statement, it's better to explicitly specify the columns with the table name.
Good (prefer)
Project.select(:path, 'merge_requests.user_id').joins(:merge_requests)
# SELECT "projects"."path", merge_requests.user_id as user_id FROM "projects" ...
Project.select(:path, :'merge_requests.user_id').joins(:merge_requests)
# SELECT "projects"."path", "merge_requests"."id" as user_id FROM "projects" ...
Example using Arel (arel_table
):
Project.select(:path, MergeRequest.arel_table[:user_id]).joins(:merge_requests)
# SELECT "projects"."path", "merge_requests"."user_id" FROM "projects" ...
When writing raw SQL query:
SELECT projects.path, merge_requests.user_id FROM "projects"...
When the raw SQL query is parameterized (needs escaping):
include ActiveRecord::ConnectionAdapters::Quoting
"""
SELECT
#{quote_table_name('projects')}.#{quote_column_name('path')},
#{quote_table_name('merge_requests')}.#{quote_column_name('user_id')}
FROM ...
"""
Bad (avoid)
Project.select('id, path, user_id').joins(:merge_requests).to_sql
# SELECT id, path, user_id FROM "projects" ...
Project.select("path", "user_id").joins(:merge_requests)
# SELECT "projects"."path", "user_id" FROM "projects" ...
# or
Project.select(:path, :user_id).joins(:merge_requests)
# SELECT "projects"."path", "user_id" FROM "projects" ...
When a column list is given, ActiveRecord tries to match the arguments against the columns defined in the projects
table and prepend the table name automatically. In this case, the id
column is not a problem, but the user_id
column could return unexpected data:
Project.select(:id, :user_id).joins(:merge_requests)
# Before deployment (user_id is taken from the merge_requests table):
# SELECT "projects"."id", "user_id" FROM "projects" ...
# After deployment (user_id is taken from the projects table):
# SELECT "projects"."id", "projects"."user_id" FROM "projects" ...
Plucking IDs
Be very careful using ActiveRecord's pluck
to load a set of values into memory only to
use them as an argument for another query. In general, moving query logic out of PostgreSQL
and into Ruby is detrimental because PostgreSQL has a query optimizer that performs better
when it has relatively more context about the desired operation.
If, for some reason, you need to pluck
and use the results in a single query then,
most likely, a materialized CTE will be a better choice:
WITH ids AS MATERIALIZED (
SELECT id FROM table...
)
SELECT * FROM projects
WHERE id IN (SELECT id FROM ids);
which will make PostgreSQL pluck the values into an internal array.
Some pluck-related mistakes that you should avoid:
- Passing too many integers into a query. While not explicitly limited, PostgreSQL has a practical arity limit of a couple thousand IDs. We don't want to run up against this limit.
- Generating gigantic query text that can cause problems for our logging infrastructure.
- Accidentally scanning an entire table. For example, this executes an extra unnecessary database query and load a lot of unnecessary data into memory:
projects = Project.all.pluck(:id)
MergeRequest.where(source_project_id: projects)
Instead you can just use sub-queries which perform far better:
MergeRequest.where(source_project_id: Project.all.select(:id))
A few specific reasons you might choose pluck
:
- You actually need to operate on the values in Ruby itself. For example, writing them to a file.
- The values get cached or memoized in order to be reused in multiple related queries.
In line with our CodeReuse/ActiveRecord
cop, you should only use forms like
pluck(:id)
or pluck(:user_id)
within model code. In the former case, you can
use the ApplicationRecord
-provided .pluck_primary_key
helper method instead.
In the latter, you should add a small helper method to the relevant model.
If you have strong reasons to use pluck
, it could make sense to limit the number
of records plucked. MAX_PLUCK
defaults to 1_000
in ApplicationRecord
. In all cases,
you should still consider using a subquery and make sure that using pluck
is a reliably
better option.
Inherit from ApplicationRecord
Most models in the GitLab codebase should inherit from ApplicationRecord
or Ci::ApplicationRecord
rather than from ActiveRecord::Base
. This allows
helper methods to be easily added.
An exception to this rule exists for models created in database migrations. As
these should be isolated from application code, they should continue to subclass
from MigrationRecord
which is available only in migration context.
Use UNIONs
UNION
s aren't very commonly used in most Rails applications but they're very
powerful and useful. Queries tend to use a lot of JOIN
s to
get related data or data based on certain criteria, but JOIN
performance can
quickly deteriorate as the data involved grows.
For example, if you want to get a list of projects where the name contains a value or the name of the namespace contains a value most people would write the following query:
SELECT *
FROM projects
JOIN namespaces ON namespaces.id = projects.namespace_id
WHERE projects.name ILIKE '%gitlab%'
OR namespaces.name ILIKE '%gitlab%';
Using a large database this query can easily take around 800 milliseconds to
run. Using a UNION
we'd write the following instead:
SELECT projects.*
FROM projects
WHERE projects.name ILIKE '%gitlab%'
UNION
SELECT projects.*
FROM projects
JOIN namespaces ON namespaces.id = projects.namespace_id
WHERE namespaces.name ILIKE '%gitlab%';
This query in turn only takes around 15 milliseconds to complete while returning the exact same records.
This doesn't mean you should start using UNIONs everywhere, but it's something to keep in mind when using lots of JOINs in a query and filtering out records based on the joined data.
GitLab comes with a Gitlab::SQL::Union
class that can be used to build a UNION
of multiple ActiveRecord::Relation
objects. You can use this class as
follows:
union = Gitlab::SQL::Union.new([projects, more_projects, ...])
Project.from("(#{union.to_sql}) projects")
The FromUnion
model concern provides a more convenient method to produce the same result as above:
class Project
include FromUnion
...
end
Project.from_union(projects, more_projects, ...)
UNION
is common through the codebase, but it's also possible to use the other SQL set operators of EXCEPT
and INTERSECT
:
class Project
include FromIntersect
include FromExcept
...
end
intersected = Project.from_intersect(all_projects, project_set_1, project_set_2)
excepted = Project.from_except(all_projects, project_set_1, project_set_2)
UNION
sub-queries
Uneven columns in the When the UNION
query has uneven columns in the SELECT
clauses, the database returns an error.
Consider the following UNION
query:
SELECT id FROM users WHERE id = 1
UNION
SELECT id, name FROM users WHERE id = 2
end
The query results in the following error message:
each UNION query must have the same number of columns
This problem is apparent and it can be easily fixed during development. One edge-case is when
UNION
queries are combined with explicit column listing where the list comes from the
ActiveRecord
schema cache.
Example (bad, avoid it):
scope1 = User.select(User.column_names).where(id: [1, 2, 3]) # selects the columns explicitly
scope2 = User.where(id: [10, 11, 12]) # uses SELECT users.*
User.connection.execute(Gitlab::SQL::Union.new([scope1, scope2]).to_sql)
When this code is deployed, it doesn't cause problems immediately. When another
developer adds a new database column to the users
table, this query breaks in
production and can cause downtime. The second query (SELECT users.*
) includes the
newly added column; however, the first query does not. The column_names
method returns stale
values (the new column is missing), because the values are cached within the ActiveRecord
schema
cache. These values are usually populated when the application boots up.
At this point, the only fix would be a full application restart so that the schema cache gets
updated. Since GitLab 16.1,
the schema cache will be automatically reset so that subsequent queries
will succeed. This reset can be disabled by disabling the ops
feature
flag reset_column_information_on_statement_invalid
.
The problem can be avoided if we always use SELECT users.*
or we always explicitly define the
columns.
Using SELECT users.*
:
# Bad, avoid it
scope1 = User.select(User.column_names).where(id: [1, 2, 3])
scope2 = User.where(id: [10, 11, 12])
# Good, both queries generate SELECT users.*
scope1 = User.where(id: [1, 2, 3])
scope2 = User.where(id: [10, 11, 12])
User.connection.execute(Gitlab::SQL::Union.new([scope1, scope2]).to_sql)
Explicit column list definition:
# Good, the SELECT columns are consistent
columns = User.cached_column_list # The helper returns fully qualified (table.column) column names (Arel)
scope1 = User.select(*columns).where(id: [1, 2, 3]) # selects the columns explicitly
scope2 = User.select(*columns).where(id: [10, 11, 12]) # uses SELECT users.*
User.connection.execute(Gitlab::SQL::Union.new([scope1, scope2]).to_sql)
Ordering by Creation Date
When ordering records based on the time they were created, you can order
by the id
column instead of ordering by created_at
. Because IDs are always
unique and incremented in the order that rows are created, doing so produces the
exact same results. This also means there's no need to add an index on
created_at
to ensure consistent performance as id
is already indexed by
default.
WHERE EXISTS
instead of WHERE IN
Use While WHERE IN
and WHERE EXISTS
can be used to produce the same data it is
recommended to use WHERE EXISTS
whenever possible. While in many cases
PostgreSQL can optimize WHERE IN
quite well there are also many cases where
WHERE EXISTS
performs (much) better.
In Rails you have to use this by creating SQL fragments:
Project.where('EXISTS (?)', User.select(1).where('projects.creator_id = users.id AND users.foo = X'))
This would then produce a query along the lines of the following:
SELECT *
FROM projects
WHERE EXISTS (
SELECT 1
FROM users
WHERE projects.creator_id = users.id
AND users.foo = X
)
.exists?
queries
Query plan flip problem with In Rails, calling .exists?
on an ActiveRecord scope could cause query plan flip issues, which
could lead to database statement timeouts. When preparing query plans for review, it's advisable to
check all variants of the underlying query form ActiveRecord scopes.
Example: check if there are any epics in the group and its subgroups.
# Similar queries, but they might behave differently (different query execution plan)
Epic.where(group_id: group.first.self_and_descendant_ids).order(:id).limit(20) # for pagination
Epic.where(group_id: group.first.self_and_descendant_ids).count # for providing total count
Epic.where(group_id: group.first.self_and_descendant_ids).exists? # for checking if there is at least one epic present
When the .exists?
method is called, Rails modifies the active record scope:
- Replaces the select columns with
SELECT 1
. - Adds
LIMIT 1
to the query.
When invoked, complex ActiveRecord scopes, such as those with IN
queries, could negatively alter database query planning behavior.
Execution plan:
Epic.where(group_id: group.first.self_and_descendant_ids).exists?
Limit (cost=126.86..591.11 rows=1 width=4)
-> Nested Loop Semi Join (cost=126.86..3255965.65 rows=7013 width=4)
Join Filter: (epics.group_id = namespaces.traversal_ids[array_length(namespaces.traversal_ids, 1)])
-> Index Only Scan using index_epics_on_group_id_and_iid on epics (cost=0.42..8846.02 rows=426445 width=4)
-> Materialize (cost=126.43..808.15 rows=435 width=28)
-> Bitmap Heap Scan on namespaces (cost=126.43..805.98 rows=435 width=28)
Recheck Cond: ((traversal_ids @> '{9970}'::integer[]) AND ((type)::text = 'Group'::text))
-> Bitmap Index Scan on index_namespaces_on_traversal_ids_for_groups (cost=0.00..126.32 rows=435 width=0)
Index Cond: (traversal_ids @> '{9970}'::integer[])
Notice the Index Only Scan
on the index_epics_on_group_id_and_iid
index where the planner estimates reading more than 400,000 rows.
If we execute the query without exists?
, we get a different execution plan:
Epic.where(group_id: Group.first.self_and_descendant_ids).to_a
Execution plan:
Nested Loop (cost=807.49..11198.57 rows=7013 width=1287)
-> HashAggregate (cost=807.06..811.41 rows=435 width=28)
Group Key: namespaces.traversal_ids[array_length(namespaces.traversal_ids, 1)]
-> Bitmap Heap Scan on namespaces (cost=126.43..805.98 rows=435 width=28)
Recheck Cond: ((traversal_ids @> '{9970}'::integer[]) AND ((type)::text = 'Group'::text))
-> Bitmap Index Scan on index_namespaces_on_traversal_ids_for_groups (cost=0.00..126.32 rows=435 width=0)
Index Cond: (traversal_ids @> '{9970}'::integer[])
-> Index Scan using index_epics_on_group_id_and_iid on epics (cost=0.42..23.72 rows=16 width=1287)
Index Cond: (group_id = (namespaces.traversal_ids)[array_length(namespaces.traversal_ids, 1)])
This query plan doesn't contain the MATERIALIZE
nodes and uses a more efficient access method by loading the group
hierarchy first.
Query plan flips can be accidentally introduced by even the smallest query change. Revisiting the .exists?
query where selecting
the group ID database column differently:
Epic.where(group_id: group.first.select(:id)).exists?
Limit (cost=126.86..672.26 rows=1 width=4)
-> Nested Loop (cost=126.86..1763.07 rows=3 width=4)
-> Bitmap Heap Scan on namespaces (cost=126.43..805.98 rows=435 width=4)
Recheck Cond: ((traversal_ids @> '{9970}'::integer[]) AND ((type)::text = 'Group'::text))
-> Bitmap Index Scan on index_namespaces_on_traversal_ids_for_groups (cost=0.00..126.32 rows=435 width=0)
Index Cond: (traversal_ids @> '{9970}'::integer[])
-> Index Only Scan using index_epics_on_group_id_and_iid on epics (cost=0.42..2.04 rows=16 width=4)
Index Cond: (group_id = namespaces.id)
Here we see again the better execution plan. In case we do a small change to the query, it flips again:
Epic.where(group_id: group.first.self_and_descendants.select('id + 0')).exists?
Limit (cost=126.86..591.11 rows=1 width=4)
-> Nested Loop Semi Join (cost=126.86..3255965.65 rows=7013 width=4)
Join Filter: (epics.group_id = (namespaces.id + 0))
-> Index Only Scan using index_epics_on_group_id_and_iid on epics (cost=0.42..8846.02 rows=426445 width=4)
-> Materialize (cost=126.43..808.15 rows=435 width=4)
-> Bitmap Heap Scan on namespaces (cost=126.43..805.98 rows=435 width=4)
Recheck Cond: ((traversal_ids @> '{9970}'::integer[]) AND ((type)::text = 'Group'::text))
-> Bitmap Index Scan on index_namespaces_on_traversal_ids_for_groups (cost=0.00..126.32 rows=435 width=0)
Index Cond: (traversal_ids @> '{9970}'::integer[])
Forcing an execution plan is possible if the IN
subquery is moved to a CTE:
cte = Gitlab::SQL::CTE.new(:group_ids, Group.first.self_and_descendant_ids)
Epic.where('epics.id IN (SELECT id FROM group_ids)').with(cte.to_arel).exists?
Limit (cost=817.27..818.12 rows=1 width=4)
CTE group_ids
-> Bitmap Heap Scan on namespaces (cost=126.43..807.06 rows=435 width=4)
Recheck Cond: ((traversal_ids @> '{9970}'::integer[]) AND ((type)::text = 'Group'::text))
-> Bitmap Index Scan on index_namespaces_on_traversal_ids_for_groups (cost=0.00..126.32 rows=435 width=0)
Index Cond: (traversal_ids @> '{9970}'::integer[])
-> Nested Loop (cost=10.21..380.29 rows=435 width=4)
-> HashAggregate (cost=9.79..11.79 rows=200 width=4)
Group Key: group_ids.id
-> CTE Scan on group_ids (cost=0.00..8.70 rows=435 width=4)
-> Index Only Scan using epics_pkey on epics (cost=0.42..1.84 rows=1 width=4)
Index Cond: (id = group_ids.id)
NOTE: Due to their complexity, using CTEs should be the last resort. Use CTEs only when simpler query changes don't produce a favorable execution plan.
.find_or_create_by
is not atomic
The inherent pattern with methods like .find_or_create_by
and
.first_or_create
and others is that they are not atomic. This means,
it first runs a SELECT
, and if there are no results an INSERT
is
performed. With concurrent processes in mind, there is a race condition
which may lead to trying to insert two similar records. This may not be
desired, or may cause one of the queries to fail due to a constraint
violation, for example.
Using transactions does not solve this problem.
To solve this we've added the ApplicationRecord.safe_find_or_create_by
.
This method can be used the same way as
find_or_create_by
, but it wraps the call in a new transaction (or a subtransaction) and
retries if it were to fail because of an
ActiveRecord::RecordNotUnique
error.
To be able to use this method, make sure the model you want to use
this on inherits from ApplicationRecord
.
In Rails 6 and later, there is a
.create_or_find_by
method. This method differs from our .safe_find_or_create_by
methods
because it performs the INSERT
, and then performs the SELECT
commands only if that call
fails.
If the INSERT
fails, it leaves a dead tuple around and
increment the primary key sequence (if any), among other downsides.
We prefer .safe_find_or_create_by
if the common path is that we
have a single record which is reused after it has first been created.
However, if the more common path is to create a new record, and we only
want to avoid duplicate records to be inserted on edge cases
(for example a job-retry), then .create_or_find_by
can save us a SELECT
.
Both methods use subtransactions internally if executed within the context of an existing transaction. This can significantly impact overall performance, especially if more than 64 live subtransactions are being used inside a single transaction.
.safe_find_or_create_by
?
Can I use If your code is generally isolated (for example it's executed in a worker only) and not wrapped with another transaction, then you can use .safe_find_or_create_by
. However, there is no tooling to catch cases when someone else calls your code within a transaction. Using .safe_find_or_create_by
will definitely carry some risks that cannot be eliminated completely at the moment.
Additionally, we have a RuboCop rule Performance/ActiveRecordSubtransactionMethods
that prevents the usage of .safe_find_or_create_by
. This rule can be disabled on a case by case basis via # rubocop:disable Performance/ActiveRecordSubtransactionMethods
.
Alternatives to .find_or_create_by
UPSERT
Alternative 1: The .upsert
method can be an alternative solution when the table is backed by a unique index.
Simple usage of the .upsert
method:
BuildTrace.upsert(
{
build_id: build_id,
title: title
},
unique_by: :build_id
)
A few things to be careful about:
- The sequence for the primary key will be incremented, even if the record was only updated.
- The created record is not returned. The
returning
option only returns data when anINSERT
happens (new record). -
ActiveRecord
validations are not executed.
An example of the .upsert
method with validations and record loading:
params = {
build_id: build_id,
title: title
}
build_trace = BuildTrace.new(params)
unless build_trace.valid?
raise 'notify the user here'
end
BuildTrace.upsert(params, unique_by: :build_id)
build_trace = BuildTrace.find_by!(build_id: build_id)
# do something with build_trace here
The code snippet above will not work well if there is a model-level uniqueness validation on the build_id
column because we invoke the validation before calling .upsert
.
To work around this, we have two options:
- Remove the uniqueness validation from the
ActiveRecord
model. - Use the
on
keyword and implement context-specific validation.
Alternative 2: Check existence and rescue
When the chance of concurrently creating the same record is very low, we can use a simpler approach:
def my_create_method
params = {
build_id: build_id,
title: title
}
build_trace = BuildTrace
.where(build_id: params[:build_id])
.first
build_trace = BuildTrace.new(params) if build_trace.blank?
build_trace.update!(params)
rescue ActiveRecord::RecordInvalid => invalid
retry if invalid.record&.errors&.of_kind?(:build_id, :taken)
end
The method does the following:
- Look up the model by the unique column.
- If no record found, build a new one.
- Persist the record.
There is a short race condition between the lookup query and the persist query where another process could insert the record and cause an ActiveRecord::RecordInvalid
exception.
The code rescues this particular exception and retries the operation. For the second run, the record would be successfully located. For example check this block of code in PreventApprovalByAuthorService
.
Monitor SQL queries in production
GitLab team members can monitor slow or canceled queries on GitLab.com using the PostgreSQL logs, which are indexed in Elasticsearch and searchable using Kibana.
See the runbook for more details.
When to use common table expressions
You can use common table expressions (CTEs) to create a temporary result set within a more complex query.
You can also use a recursive CTE to reference the CTE's result set within
the query itself. The following example queries a chain of
personal access tokens
referencing each other in the
previous_personal_access_token_id
column.
WITH RECURSIVE "personal_access_tokens_cte" AS (
(
SELECT
"personal_access_tokens".*
FROM
"personal_access_tokens"
WHERE
"personal_access_tokens"."previous_personal_access_token_id" = 15)
UNION (
SELECT
"personal_access_tokens".*
FROM
"personal_access_tokens",
"personal_access_tokens_cte"
WHERE
"personal_access_tokens"."previous_personal_access_token_id" = "personal_access_tokens_cte"."id"))
SELECT
"personal_access_tokens".*
FROM
"personal_access_tokens_cte" AS "personal_access_tokens"
id | previous_personal_access_token_id
----+-----------------------------------
16 | 15
17 | 16
18 | 17
19 | 18
20 | 19
21 | 20
(6 rows)
As CTEs are temporary result sets, you can use them within another SELECT
statement. Using CTEs with UPDATE
, or DELETE
could lead to unexpected
behavior:
Consider the following method:
def personal_access_token_chain(token)
cte = Gitlab::SQL::RecursiveCTE.new(:personal_access_tokens_cte)
personal_access_token_table = Arel::Table.new(:personal_access_tokens)
cte << PersonalAccessToken
.where(personal_access_token_table[:previous_personal_access_token_id].eq(token.id))
cte << PersonalAccessToken
.from([personal_access_token_table, cte.table])
.where(personal_access_token_table[:previous_personal_access_token_id].eq(cte.table[:id]))
PersonalAccessToken.with.recursive(cte.to_arel).from(cte.alias_to(personal_access_token_table))
end
It works as expected when it is used to query data:
> personal_access_token_chain(token)
WITH RECURSIVE "personal_access_tokens_cte" AS (
(
SELECT
"personal_access_tokens".*
FROM
"personal_access_tokens"
WHERE
"personal_access_tokens"."previous_personal_access_token_id" = 11)
UNION (
SELECT
"personal_access_tokens".*
FROM
"personal_access_tokens",
"personal_access_tokens_cte"
WHERE
"personal_access_tokens"."previous_personal_access_token_id" = "personal_access_tokens_cte"."id"))
SELECT
"personal_access_tokens".*
FROM
"personal_access_tokens_cte" AS "personal_access_tokens"
However, the CTE is dropped when used with #update_all
. As a result, the method
updates the entire table:
> personal_access_token_chain(token).update_all(revoked: true)
UPDATE
"personal_access_tokens"
SET
"revoked" = TRUE
To work around this behavior:
-
Query the
ids
of the records:> token_ids = personal_access_token_chain(token).pluck_primary_key => [16, 17, 18, 19, 20, 21]
-
Use this array to scope
PersonalAccessTokens
:PersonalAccessToken.where(id: token_ids).update_all(revoked: true)
Alternatively, combine these two steps:
PersonalAccessToken
.where(id: personal_access_token_chain(token).pluck_primary_key)
.update_all(revoked: true)
NOTE: Avoid updating large volumes of unbounded data. If there are no application limits on the data, or you are unsure about the data volume, you should update the data in batches.