Loose foreign keys
Problem statement
In relational databases (including PostgreSQL), foreign keys provide a way to link two database tables together, and ensure data-consistency between them. In GitLab, foreign keys are vital part of the database design process. Most of our database tables have foreign keys.
With the ongoing database decomposition work, linked records might be present on two different database servers. Ensuring data consistency between two databases is not possible with standard PostgreSQL foreign keys. PostgreSQL does not support foreign keys operating across multiple database servers.
Example:
- Database "Main":
projects
table - Database "CI":
ci_pipelines
table
A project can have many pipelines. When a project is deleted, the associated ci_pipeline
(via the
project_id
column) records must be also deleted.
With a multi-database setup, this cannot be achieved with foreign keys.
Asynchronous approach
Our preferred approach to this problem is eventual consistency. With the loose foreign keys feature, we can configure delayed association cleanup without negatively affecting the application performance.
How it works
In the previous example, a record in the projects
table can have multiple ci_pipeline
records. To keep the cleanup process separate from the actual parent record deletion,
we can:
- Create a
DELETE
trigger on theprojects
table. Record the deletions in a separate table (deleted_records
). - A job checks the
deleted_records
table every minute or two. - For each record in the table, delete the associated
ci_pipelines
records using theproject_id
column.
NOTE: For this procedure to work, we must register which tables to clean up asynchronously.
scripts/decomposition/generate-loose-foreign-key
The We built an automation tool to aid migration of foreign keys into loose foreign keys as part of decomposition effort. It presents existing keys and allows chosen foreign keys to be automatically converted into loose foreign keys. This ensures consistency between foreign key and loose foreign key definitions, and ensures that they are properly tested.
WARNING: We strongly advise you to use the automation script for swapping any foreign key to a loose foreign key.
The tool ensures that all aspects of swapping a foreign key are covered. This includes:
- Creating a migration to remove a foreign key.
- Updating
db/structure.sql
with the new migration. - Updating
config/gitlab_loose_foreign_keys.yml
to add the new loose foreign key. - Creating or updating a model's specs to ensure that the loose foreign key is properly supported.
The tool is located at scripts/decomposition/generate-loose-foreign-key
:
$ scripts/decomposition/generate-loose-foreign-key -h
Usage: scripts/decomposition/generate-loose-foreign-key [options] <filters...>
-c, --cross-schema Show only cross-schema foreign keys
-n, --dry-run Do not execute any commands (dry run)
-r, --[no-]rspec Create or not a rspecs automatically
-h, --help Prints this help
For the migration of cross-schema foreign keys, we use the -c
modifier to show the foreign keys
yet to migrate:
$ scripts/decomposition/generate-loose-foreign-key -c
Re-creating current test database
Dropped database 'gitlabhq_test_ee'
Dropped database 'gitlabhq_geo_test_ee'
Created database 'gitlabhq_test_ee'
Created database 'gitlabhq_geo_test_ee'
Showing cross-schema foreign keys (20):
ID | HAS_LFK | FROM | TO | COLUMN | ON_DELETE
0 | N | ci_builds | projects | project_id | cascade
1 | N | ci_job_artifacts | projects | project_id | cascade
2 | N | ci_pipelines | projects | project_id | cascade
3 | Y | ci_pipelines | merge_requests | merge_request_id | cascade
4 | N | external_pull_requests | projects | project_id | cascade
5 | N | ci_sources_pipelines | projects | project_id | cascade
6 | N | ci_stages | projects | project_id | cascade
7 | N | ci_pipeline_schedules | projects | project_id | cascade
8 | N | ci_runner_projects | projects | project_id | cascade
9 | Y | dast_site_profiles_pipelines | ci_pipelines | ci_pipeline_id | cascade
10 | Y | vulnerability_feedback | ci_pipelines | pipeline_id | nullify
11 | N | ci_variables | projects | project_id | cascade
12 | N | ci_refs | projects | project_id | cascade
13 | N | ci_builds_metadata | projects | project_id | cascade
14 | N | ci_subscriptions_projects | projects | downstream_project_id | cascade
15 | N | ci_subscriptions_projects | projects | upstream_project_id | cascade
16 | N | ci_sources_projects | projects | source_project_id | cascade
17 | N | ci_job_token_project_scope_links | projects | source_project_id | cascade
18 | N | ci_job_token_project_scope_links | projects | target_project_id | cascade
19 | N | ci_project_monthly_usages | projects | project_id | cascade
To match foreign key (FK), write one or many filters to match against FROM/TO/COLUMN:
- scripts/decomposition/generate-loose-foreign-key (filters...)
- scripts/decomposition/generate-loose-foreign-key ci_job_artifacts project_id
- scripts/decomposition/generate-loose-foreign-key dast_site_profiles_pipelines
The command accepts a list of regular expressions to match from, to, or column
for the purpose of the foreign key generation. For example, run this to swap
all foreign keys for ci_job_token_project_scope_links
for the decomposed database:
scripts/decomposition/generate-loose-foreign-key -c ci_job_token_project_scope_links
To swap only the source_project_id
of ci_job_token_project_scope_links
for the decomposed database, run:
scripts/decomposition/generate-loose-foreign-key -c ci_job_token_project_scope_links source_project_id
To match the exact name of a table or columns, you can make use of the regular expressions
position anchors ^
and $
. For example, this command matches only the
foreign keys on the events
table only, but not on the table
incident_management_timeline_events
.
scripts/decomposition/generate-loose-foreign-key -n ^events$
To swap all the foreign keys (all having _id
appended), but not create a new branch (only commit
the changes) and not create RSpec tests, run:
scripts/decomposition/generate-loose-foreign-key -c --no-branch --no-rspec _id
To swap all foreign keys referencing projects
, but not create a new branch (only commit the
changes), run:
scripts/decomposition/generate-loose-foreign-key -c --no-branch projects
Example migration and configuration
Configure the loose foreign key
Loose foreign keys are defined in a YAML file. The configuration requires the following information:
- Parent table name (
projects
) - Child table name (
ci_pipelines
) - The data cleanup method (
async_delete
orasync_nullify
)
The YAML file is located at config/gitlab_loose_foreign_keys.yml
. The file groups
foreign key definitions by the name of the child table. The child table can have multiple loose
foreign key definitions, therefore we store them as an array.
Example definition:
ci_pipelines:
- table: projects
column: project_id
on_delete: async_delete
If the ci_pipelines
key is already present in the YAML file, then a new entry can be added
to the array:
ci_pipelines:
- table: projects
column: project_id
on_delete: async_delete
- table: another_table
column: another_id
on_delete: :async_nullify
Track record changes
To know about deletions in the projects
table, configure a DELETE
trigger
using a post-deployment migration. The
trigger needs to be configured only once. If the model already has at least one
loose_foreign_key
definition, then this step can be skipped:
class TrackProjectRecordChanges < Gitlab::Database::Migration[2.1]
include Gitlab::Database::MigrationHelpers::LooseForeignKeyHelpers
def up
track_record_deletions(:projects)
end
def down
untrack_record_deletions(:projects)
end
end
Remove the foreign key
If there is an existing foreign key, then it can be removed from the database. This foreign key describes the link between the projects
and ci_pipelines
tables:
ALTER TABLE ONLY ci_pipelines
ADD CONSTRAINT fk_86635dbd80
FOREIGN KEY (project_id)
REFERENCES projects(id)
ON DELETE CASCADE;
The migration must run after the DELETE
trigger is installed and the loose
foreign key definition is deployed. As such, it must be a
post-deployment migration dated after the migration for the
trigger. If the foreign key is deleted earlier, there is a good chance of
introducing data inconsistency which needs manual cleanup:
class RemoveProjectsCiPipelineFk < Gitlab::Database::Migration[2.1]
disable_ddl_transaction!
def up
with_lock_retries do
remove_foreign_key_if_exists(:ci_pipelines, :projects, name: "fk_86635dbd80")
end
end
def down
add_concurrent_foreign_key(:ci_pipelines, :projects, name: "fk_86635dbd80", column: :project_id, target_column: :id, on_delete: "cascade")
end
end
At this point, the setup phase is concluded. The deleted projects
records should be automatically
picked up by the scheduled cleanup worker job.
Remove the loose foreign key
When the loose foreign key definition is no longer needed (parent table is removed, or FK is restored), we need to remove the definition from the YAML file and ensure that we don't leave pending deleted records in the database.
- Remove the loose foreign key definition from the configuration (
config/gitlab_loose_foreign_keys.yml
).
The deletion tracking trigger needs to be removed only when the parent table no longer uses loose foreign keys.
If the model still has at least one loose_foreign_key
definition remaining, then these steps can be skipped:
- Remove the trigger from the parent table (if the parent table is still there).
- Remove leftover deleted records from the
loose_foreign_keys_deleted_records
table.
Migration for removing the trigger:
class UnTrackProjectRecordChanges < Gitlab::Database::Migration[2.1]
include Gitlab::Database::MigrationHelpers::LooseForeignKeyHelpers
def up
untrack_record_deletions(:projects)
end
def down
track_record_deletions(:projects)
end
end
With the trigger removal, we prevent further records to be inserted in the loose_foreign_keys_deleted_records
table however, there is still a chance for having leftover pending records in the table. These records
must be removed with an inline data migration.
class RemoveLeftoverProjectDeletions < Gitlab::Database::Migration[2.1]
disable_ddl_transaction!
def up
loop do
result = execute <<~SQL
DELETE FROM "loose_foreign_keys_deleted_records"
WHERE
("loose_foreign_keys_deleted_records"."partition", "loose_foreign_keys_deleted_records"."id") IN (
SELECT "loose_foreign_keys_deleted_records"."partition", "loose_foreign_keys_deleted_records"."id"
FROM "loose_foreign_keys_deleted_records"
WHERE
"loose_foreign_keys_deleted_records"."fully_qualified_table_name" = 'public.projects' AND
"loose_foreign_keys_deleted_records"."status" = 1
LIMIT 100
)
SQL
break if result.cmd_tuples == 0
end
end
def down
# no-op
end
end
Testing
The "it has loose foreign keys
" shared example can be used to test the presence of the ON DELETE
trigger and the
loose foreign key definitions.
Add to the model test file:
it_behaves_like 'it has loose foreign keys' do
let(:factory_name) { :project }
end
After removing a foreign key,
use the "cleanup by a loose foreign key
" shared example to test a child record's deletion or nullification
via the added loose foreign key:
it_behaves_like 'cleanup by a loose foreign key' do
let!(:model) { create(:ci_pipeline, user: create(:user)) }
let!(:parent) { model.user }
end
Caveats of loose foreign keys
Record creation
The feature provides an efficient way of cleaning up associated records after the parent record is deleted. Without foreign keys, it's the application's responsibility to validate if the parent record exists when a new associated record is created.
A bad example: record creation with the given ID (project_id
comes from user input).
In this example, nothing prevents us from passing a random project ID:
Ci::Pipeline.create!(project_id: params[:project_id])
A good example: record creation with extra check:
project = Project.find(params[:project_id])
Ci::Pipeline.create!(project_id: project.id)
Association lookup
Consider the following HTTP request:
GET /projects/5/pipelines/100
The controller action ignores the project_id
parameter and finds the pipeline using the ID:
def show
# bad, avoid it
pipeline = Ci::Pipeline.find(params[:id]) # 100
end
This endpoint still works when the parent Project
model is deleted. This can be considered a
data leak which should not happen under typical circumstances:
def show
# good
project = Project.find(params[:project_id])
pipeline = project.pipelines.find(params[:pipeline_id]) # 100
end
NOTE: This example is unlikely in GitLab, because we usually look up the parent models to perform permission checks.
dependent: :destroy
and dependent: :nullify
A note on We considered using these Rails features as an alternative to foreign keys but there are several problems which include:
- These run on a different connection in the context of a transaction which we do not allow.
- These can lead to severe performance degradation as we load all records from PostgreSQL, loop over them in Ruby, and call individual
DELETE
queries. - These can miss data as they only cover the case when the
destroy
method is called directly on the model. There are other cases includingdelete_all
and cascading deletes from another parent table that could mean these are missed.
For non-trivial objects that need to clean up data outside the
database (for example, object storage) where you might wish to use dependent: :destroy
,
see alternatives in
Avoid dependent: :nullify
and dependent: :destroy
across databases.
Update target column to a value
A loose foreign key might be used to update a target column to a value when an entry in parent table is deleted.
It's important to add an index (if it doesn't exist yet) on
(column
, target_column
) to avoid any performance issues.
Any index starting with these two columns will work.
The configuration requires additional information:
- Column to be updated (
target_column
) - Value to be set in the target column (
target_value
)
Example definition:
packages:
- table: projects
column: project_id
on_delete: update_column_to
target_column: status
target_value: 4
Risks of loose foreign keys and possible mitigations
In general, the loose foreign keys architecture is eventually consistent and the cleanup latency might lead to problems visible to GitLab users or operators. We consider the tradeoff as acceptable, but there might be cases where the problems are too frequent or too severe, and we must implement a mitigation strategy. A general mitigation strategy might be to have an "urgent" queue for cleanup of records that have higher impact with a delayed cleanup.
Below are some more specific examples of problems that might occur and how we might mitigate them. In all the listed cases we might still consider the problem described to be low risk and low impact, and in that case we would choose to not implement any mitigation.
The record should be deleted but it shows up in a view
This hypothetical example might happen with a foreign key like:
ALTER TABLE ONLY vulnerability_occurrence_pipelines
ADD CONSTRAINT fk_rails_6421e35d7d FOREIGN KEY (pipeline_id) REFERENCES ci_pipelines(id) ON DELETE CASCADE;
In this example we expect to delete all associated vulnerability_occurrence_pipelines
records
whenever we delete the ci_pipelines
record associated with them. In this case
you might end up with some vulnerability page in GitLab which shows an occurrence
of a vulnerability. However, when you try to select a link to the pipeline, you get
a 404, because the pipeline is deleted. Then, when you navigate back you might find the
occurrence has disappeared too.
Mitigation
When rendering the vulnerability occurrences on the vulnerability page we could try to load the corresponding pipeline and choose to skip displaying that occurrence if pipeline is not found.
500
error
The deleted parent record is needed to render a view and causes a This hypothetical example might happen with a foreign key like:
ALTER TABLE ONLY vulnerability_occurrence_pipelines
ADD CONSTRAINT fk_rails_6421e35d7d FOREIGN KEY (pipeline_id) REFERENCES ci_pipelines(id) ON DELETE CASCADE;
In this example we expect to delete all associated vulnerability_occurrence_pipelines
records
whenever we delete the ci_pipelines
record associated with them. In this case
you might end up with a vulnerability page in GitLab which shows an "occurrence"
of a vulnerability. However, when rendering the occurrence we try to load, for example,
occurrence.pipeline.created_at
, which causes a 500 for the user.
Mitigation
When rendering the vulnerability occurrences on the vulnerability page we could try to load the corresponding pipeline and choose to skip displaying that occurrence if pipeline is not found.
The deleted parent record is accessed in a Sidekiq worker and causes a failed job
This hypothetical example might happen with a foreign key like:
ALTER TABLE ONLY vulnerability_occurrence_pipelines
ADD CONSTRAINT fk_rails_6421e35d7d FOREIGN KEY (pipeline_id) REFERENCES ci_pipelines(id) ON DELETE CASCADE;
In this example we expect to delete all associated vulnerability_occurrence_pipelines
records
whenever we delete the ci_pipelines
record associated with them. In this case
you might end up with a Sidekiq worker that is responsible for processing a
vulnerability and looping over all occurrences causing a Sidekiq job to fail if
it executes occurrence.pipeline.created_at
.
Mitigation
When looping through the vulnerability occurrences in the Sidekiq worker, we could try to load the corresponding pipeline and choose to skip processing that occurrence if pipeline is not found.
Architecture
The loose foreign keys feature is implemented within the LooseForeignKeys
Ruby namespace. The
code is isolated from the core application code and theoretically, it could be a standalone library.
The feature is invoked solely in the LooseForeignKeys::CleanupWorker
worker class. The worker is scheduled via a
cron job where the schedule depends on the configuration of the GitLab instance.
- Non-decomposed GitLab (1 database): invoked every minute.
- Decomposed GitLab (2 databases, CI and Main): invoked every minute, cleaning up one database at a time. For example, the cleanup worker for the main database runs every two minutes.
To avoid lock contention and the processing of the same database rows, the worker does not run parallel. This behavior is ensured with a Redis lock.
Record cleanup procedure:
- Acquire the Redis lock.
- Determine which database to clean up.
- Collect all database tables where the deletions are tracked (parent tables).
- This is achieved by reading the
config/gitlab_loose_foreign_keys.yml
file. - A table is considered "tracked" when a loose foreign key definition exists for the table and
the
DELETE
trigger is installed.
- This is achieved by reading the
- Cycle through the tables with an infinite loop.
- For each table, load a batch of deleted parent records to clean up.
- Depending on the YAML configuration, build
DELETE
orUPDATE
(nullify) queries for the referenced child tables. - Invoke the queries.
- Repeat until all child records are cleaned up or the maximum limit is reached.
- Remove the deleted parent records when all child records are cleaned up.
Database structure
The feature relies on triggers installed on the parent tables. When a parent record is deleted,
the trigger automatically inserts a new record into the loose_foreign_keys_deleted_records
database table.
The inserted record stores the following information about the deleted record:
-
fully_qualified_table_name
: name of the database table where the record was located. -
primary_key_value
: the ID of the record, the value is present in the child tables as the foreign key value. At the moment, composite primary keys are not supported, the parent table must have anid
column. -
status
: defaults to pending, represents the status of the cleanup process. -
consume_after
: defaults to the current time. -
cleanup_attempts
: defaults to 0. The number of times the worker tried to clean up this record. A non-zero number would mean that this record has many child records and cleaning it up requires several runs.
Database decomposition
The loose_foreign_keys_deleted_records
table exists on both database servers (ci
and main
)
after the database decomposition. The worker
ill determine which parent tables belong to which database by reading the
lib/gitlab/database/gitlab_schemas.yml
YAML file.
Example:
- Main database tables
projects
namespaces
merge_requests
- Ci database tables
ci_builds
ci_pipelines
When the worker is invoked for the ci
database, the worker loads deleted records only from the
ci_builds
and ci_pipelines
tables. During the cleanup process, DELETE
and UPDATE
queries
mostly run on tables located in the Main database. In this example, one UPDATE
query
nullifies the merge_requests.head_pipeline_id
column.
Database partitioning
Due to the large volume of inserts the database table receives daily, a special partitioning strategy was implemented to address data bloat concerns. Originally, the time-decay strategy was considered for the feature but due to the large data volume we decided to implement a new strategy.
A deleted record is considered fully processed when all its direct children records have been
cleaned up. When this happens, the loose foreign key worker updates the status
column of
the deleted record. After this step, the record is no longer needed.
The sliding partitioning strategy provides an efficient way of cleaning up old, unused data by
adding a new database partition and removing the old one when certain conditions are met.
The loose_foreign_keys_deleted_records
database table is list partitioned where most of the
time there is only one partition attached to the table.
Partitioned table "public.loose_foreign_keys_deleted_records"
Column | Type | Collation | Nullable | Default | Storage | Stats target | Description
----------------------------+--------------------------+-----------+----------+----------------------------------------------------------------+----------+--------------+-------------
id | bigint | | not null | nextval('loose_foreign_keys_deleted_records_id_seq'::regclass) | plain | |
partition | bigint | | not null | 84 | plain | |
primary_key_value | bigint | | not null | | plain | |
status | smallint | | not null | 1 | plain | |
created_at | timestamp with time zone | | not null | now() | plain | |
fully_qualified_table_name | text | | not null | | extended | |
consume_after | timestamp with time zone | | | now() | plain | |
cleanup_attempts | smallint | | | 0 | plain | |
Partition key: LIST (partition)
Indexes:
"loose_foreign_keys_deleted_records_pkey" PRIMARY KEY, btree (partition, id)
"index_loose_foreign_keys_deleted_records_for_partitioned_query" btree (partition, fully_qualified_table_name, consume_after, id) WHERE status = 1
Check constraints:
"check_1a541f3235" CHECK (char_length(fully_qualified_table_name) <= 150)
Partitions: gitlab_partitions_dynamic.loose_foreign_keys_deleted_records_84 FOR VALUES IN ('84')
The partition
column controls the insert direction, the partition
value determines which
partition gets the deleted rows inserted via the trigger. Notice that the default value of
the partition
table matches with the value of the list partition (84). In INSERT
query
within the trigger the value of the partition
is omitted, the trigger always relies on the
default value of the column.
Example INSERT
query for the trigger:
INSERT INTO loose_foreign_keys_deleted_records
(fully_qualified_table_name, primary_key_value)
SELECT TG_TABLE_SCHEMA || '.' || TG_TABLE_NAME, old_table.id FROM old_table;
The partition "sliding" process is controlled by two, regularly executed callbacks. These
callbacks are defined within the LooseForeignKeys::DeletedRecord
model.
The next_partition_if
callback controls when to create a new partition. A new partition is
created when the current partition has at least one record older than 24 hours. A new partition
is added by the PartitionManager
using the following steps:
- Create a new partition, where the
VALUE
for the partition isCURRENT_PARTITION + 1
. - Update the default value of the
partition
column toCURRENT_PARTITION + 1
.
With these steps, all new INSERT
queries via the triggers end up in the new partition. At this point,
the database table has two partitions.
The detach_partition_if
callback determines if the old partitions can be detached from the table.
A partition is detachable if there are no pending (unprocessed) records in the partition
(status = 1
). The detached partitions are available for some time, you can see the list
detached partitions in the detached_partitions
table:
select * from detached_partitions;
Cleanup queries
The LooseForeignKeys::CleanupWorker
has its database query builder which depends on Arel
.
The feature doesn't reference any application-specific ActiveRecord
models to avoid unexpected
side effects. The database queries are batched, which means that several parent records are being
cleaned up at the same time.
Example DELETE
query:
DELETE
FROM "merge_request_metrics"
WHERE ("merge_request_metrics"."id") IN
(SELECT "merge_request_metrics"."id"
FROM "merge_request_metrics"
WHERE "merge_request_metrics"."pipeline_id" IN (1, 2, 10, 20)
LIMIT 1000 FOR UPDATE SKIP LOCKED)
The primary key values of the parent records are 1, 2, 10, and 20.
Example UPDATE
(nullify) query:
UPDATE "merge_requests"
SET "head_pipeline_id" = NULL
WHERE ("merge_requests"."id") IN
(SELECT "merge_requests"."id"
FROM "merge_requests"
WHERE "merge_requests"."head_pipeline_id" IN (3, 4, 30, 40)
LIMIT 500 FOR UPDATE SKIP LOCKED)
These queries are batched, which means that in many cases, several invocations are needed to clean up all associated child records.
The batching is implemented with loops, the processing stops when all associated child records are cleaned up or the limit is reached.
loop do
modification_count = process_batch_with_skip_locked
break if modification_count == 0 || over_limit?
end
loop do
modification_count = process_batch
break if modification_count == 0 || over_limit?
end
The loop-based batch processing is preferred over EachBatch
for the following reasons:
- The records in the batch are modified, so the next batch contains different records.
- There is always an index on the foreign key column however, the column is usually not unique.
EachBatch
requires a unique column for the iteration. - The record order doesn't matter for the cleanup.
Notice that we have two loops. The initial loop processes records with the SKIP LOCKED
clause.
The query skips rows that are locked by other application processes. This ensures that the
cleanup worker is less likely to become blocked. The second loop executes the database
queries without SKIP LOCKED
to ensure that all records have been processed.
Processing limits
A constant, large volume of record updates or deletions can cause incidents and affect the availability of GitLab:
- Increased table bloat.
- Increased number of pending WAL files.
- Busy tables, difficulty when acquiring locks.
To mitigate these issues, several limits are applied when the worker runs.
- Each query has
LIMIT
, a query cannot process an unbounded number of rows. - The maximum number of record deletions and record updates is limited.
- The maximum runtime (30 seconds) for the database queries is limited.
The limit rules are implemented in the LooseForeignKeys::ModificationTracker
class. When one of
the limits (record modification count, time limit) is reached the processing is stopped
immediately. After some time, the next scheduled worker continues the cleanup process.
Performance characteristics
The database trigger on the parent tables decreases the record deletion speed. Each
statement that removes rows from the parent table invokes the trigger to insert records
into the loose_foreign_keys_deleted_records
table.
The queries within the cleanup worker are fairly efficient index scans, with limits in place they're unlikely to affect other parts of the application.
The database queries are not running in transaction, when an error happens for example a statement timeout or a worker crash, the next job continues the processing.
Troubleshooting
Accumulation of deleted records
There can be cases where the workers need to process an unusually large amount of data. This can happen under typical usage, for example when a large project or group is deleted. In this scenario, there can be several million rows to be deleted or nullified. Due to the limits enforced by the worker, processing this data takes some time.
When cleaning up "heavy-hitters", the feature ensures fair processing by rescheduling larger batches for later. This gives time for other deleted records to be processed.
For example, a project with millions of ci_builds
records is deleted. The ci_builds
records
is deleted by the loose foreign keys feature.
- The cleanup worker is scheduled and picks up a batch of deleted
projects
records. The large project is part of the batch. - Deletion of the orphaned
ci_builds
rows has started. - The time limit is reached, but the cleanup is not complete.
- The
cleanup_attempts
column is incremented for the deleted records. - Go to step 1. The next cleanup worker continues the cleanup.
- When the
cleanup_attempts
reaches 3, the batch is re-scheduled 10 minutes later by updating theconsume_after
column. - The next cleanup worker processes a different batch.
We have Prometheus metrics in place to monitor the deleted record cleanup:
-
loose_foreign_key_processed_deleted_records
: Number of processed deleted records. When large cleanup happens, this number would decrease. -
loose_foreign_key_incremented_deleted_records
: Number of deleted records which were not finished processing. Thecleanup_attempts
column was incremented. -
loose_foreign_key_rescheduled_deleted_records
: Number of deleted records that had to be rescheduled at a later time after 3 cleanup attempts.
Example PromQL query:
loose_foreign_key_rescheduled_deleted_records{env="gprd", table="ci_runners"}
Another way to look at the situation is by running a database query. This query gives the exact counts of the unprocessed records:
SELECT partition, fully_qualified_table_name, count(*)
FROM loose_foreign_keys_deleted_records
WHERE
status = 1
GROUP BY 1, 2;
Example output:
partition | fully_qualified_table_name | count
-----------+----------------------------+-------
87 | public.ci_builds | 874
87 | public.ci_job_artifacts | 6658
87 | public.ci_pipelines | 102
87 | public.ci_runners | 111
87 | public.merge_requests | 255
87 | public.namespaces | 25
87 | public.projects | 6
The query includes the partition number which can be useful to detect if the cleanup process is significantly lagging behind. When multiple different partition values are present in the list that means the cleanup of some deleted records didn't finish in several days (1 new partition is added every day).
Steps to diagnose the problem:
- Check which records are accumulating.
- Try to get an estimate of the number of remaining records.
- Looking into the worker performance stats (Kibana or Grafana).
Possible solutions:
- Short-term: increase the batch sizes.
- Long-term: invoke the worker more frequently. Parallelize the worker
For a one-time fix, we can run the cleanup worker several times from the rails console. The worker can run in parallel however, this can introduce lock contention and it could increase the worker runtime.
LooseForeignKeys::CleanupWorker.new.perform
When the cleanup is done, the older partitions are automatically detached by the
PartitionManager
.
PartitionManager bug
NOTE: This issue happened in the past on Staging and it has been mitigated.
When adding a new partition, the default value of the partition
column is also updated. This is
a schema change that is executed in the same transaction as the new partition creation. It's highly
unlikely that the partition
column goes outdated.
However, if this happens then this can cause application-wide incidents because the partition
value points to a partition that doesn't exist. Symptom: deletion of records from tables where the
DELETE
trigger is installed fails.
\d+ loose_foreign_keys_deleted_records;
Column | Type | Collation | Nullable | Default | Storage | Stats target | Description
----------------------------+--------------------------+-----------+----------+----------------------------------------------------------------+----------+--------------+-------------
id | bigint | | not null | nextval('loose_foreign_keys_deleted_records_id_seq'::regclass) | plain | |
partition | bigint | | not null | 4 | plain | |
primary_key_value | bigint | | not null | | plain | |
status | smallint | | not null | 1 | plain | |
created_at | timestamp with time zone | | not null | now() | plain | |
fully_qualified_table_name | text | | not null | | extended | |
consume_after | timestamp with time zone | | | now() | plain | |
cleanup_attempts | smallint | | | 0 | plain | |
Partition key: LIST (partition)
Indexes:
"loose_foreign_keys_deleted_records_pkey" PRIMARY KEY, btree (partition, id)
"index_loose_foreign_keys_deleted_records_for_partitioned_query" btree (partition, fully_qualified_table_name, consume_after, id) WHERE status = 1
Check constraints:
"check_1a541f3235" CHECK (char_length(fully_qualified_table_name) <= 150)
Partitions: gitlab_partitions_dynamic.loose_foreign_keys_deleted_records_3 FOR VALUES IN ('3')
Check the default value of the partition
column and compare it with the available partitions
(4 vs 3). The partition with the value of 4 does not exist. To mitigate the problem an emergency
schema change is required:
ALTER TABLE loose_foreign_keys_deleted_records ALTER COLUMN partition SET DEFAULT 3;