- Delete everything and start over
- Migration wrangling
- Manually access the database
- Access the database with a GUI
- Access the GDK database with Visual Studio Code
- FAQ
- Performance issues
Troubleshooting and debugging the database
This section is to help give some copy-pasta you can use as a reference when you run into some head-banging database problems.
A first step is to search for your error in Slack, or search for GitLab <my error>
with Google.
Available RAILS_ENV
:
-
production
(generally not for your main GDK database, but you might need this for other installations such as Omnibus). -
development
(this is your main GDK db). -
test
(used for tests like RSpec).
Delete everything and start over
If you just want to delete everything and start over with an empty DB (approximately 1 minute):
bundle exec rake db:reset RAILS_ENV=development
If you want to seed the empty DB with sample data (approximately 4 minutes):
bundle exec rake dev:setup
If you just want to delete everything and start over with sample data (approximately 4 minutes). This
also does db:reset
and runs DB-specific migrations:
bundle exec rake db:setup RAILS_ENV=development
If your test DB is giving you problems, it is safe to delete everything because it doesn’t contain important data:
bundle exec rake db:reset RAILS_ENV=test
Migration wrangling
-
bundle exec rake db:migrate RAILS_ENV=development
: Execute any pending migrations that you might have picked up from a MR -
bundle exec rake db:migrate:status RAILS_ENV=development
: Check if all migrations areup
ordown
-
bundle exec rake db:migrate:down:main VERSION=20170926203418 RAILS_ENV=development
: Tear down a migration -
bundle exec rake db:migrate:up:main VERSION=20170926203418 RAILS_ENV=development
: Set up a migration -
bundle exec rake db:migrate:redo:main VERSION=20170926203418 RAILS_ENV=development
: Re-run a specific migration
Replace main
in the above commands to execute against the ci
database instead of main
.
Manually access the database
Access the database with one of these commands. They all get you to the same place.
gdk psql -d gitlabhq_development
bundle exec rails dbconsole -e development
bundle exec rails db -e development
-
\q
: Quit/exit -
\dt
: List all tables -
\d+ issues
: List columns forissues
table -
CREATE TABLE board_labels();
: Create a table calledboard_labels
-
SELECT * FROM schema_migrations WHERE version = '20170926203418';
: Check if a migration was run -
DELETE FROM schema_migrations WHERE version = '20170926203418';
: Manually remove a migration
Access the database with a GUI
Most GUIs (DataGrip, RubyMine, DBeaver) require a TCP connection to the database, but by default the database runs on a UNIX socket. To be able to access the database from these tools, some steps are needed:
-
On the GDK root directory, run:
gdk config set postgresql.host localhost
-
Open your
gdk.yml
, and confirm that it has the following lines:postgresql: host: localhost
-
Reconfigure GDK:
gdk reconfigure
-
On your database GUI, select
localhost
as host,5432
as port andgitlabhq_development
as database. You can also use the connection stringpostgresql://localhost:5432/gitlabhq_development
.
The new connection should be working now.
Access the GDK database with Visual Studio Code
Create a database connection using the PostgreSQL extension in Visual Studio Code to access and explore the GDK database.
Prerequisites:
- Visual Studio (VS) Code.
- PostgreSQL VS Code extension.
To create a database connection:
- In the activity bar, select the PostgreSQL Explorer icon.
- From the opened pane, select + to add a new database connection:
- Enter the hostname of the database. Use the path to the PostgreSQL folder in your GDK directory.
- Example:
/dev/gitlab-development-kit/postgresql
- Example:
- Enter a PostgreSQL user to authenticate as.
Use your local username unless otherwise specified during PostgreSQL installation.
To verify your PostgreSQL username:
- Ensure you are in the
gitlab
directory. -
Access the PostgreSQL database. Run
rails db
. The output should look like:psql (14.9) Type "help" for help. gitlabhq_development=#
-
In the returned PostgreSQL prompt, run
\conninfo
to display the connected user and the port used to establish the connection. For example:You are connected to database "gitlabhq_development" as user "root" on host "localhost" (address "127.0.0.1") at port "5432".
- Ensure you are in the
- When prompted to enter the password of the PostgreSQL user, enter the password you set or leave the field blank.
- As you are logged in to the same machine that the Postgres server is running on, a password is not required.
- EnterPort number to connect to. The default port number is
5432
. - In the use an SSL connection? field, select the appropriate connection for your
installation. The options are:
- Use Secure Connection
- Standard Connection (default)
- In the optional database to connect to field, enter
gitlabhq_development
. - In the display name for the database connection field, enter
gitlabhq_development
.
Your gitlabhq_development
database connection is now displayed in the PostgreSQL Explorer pane.
Use the arrows to expand and explore the contents of the GDK database.
If you cannot connect, first ensure that GDK is running and try again. For further instructions on how to use the PostgreSQL Explorer extension for VS Code, see the usage section of the extension’s documentation.
FAQ
ActiveRecord::PendingMigrationError
with Spring
When running specs with the Spring pre-loader, the test database can get into a corrupted state. Trying to run the migration or dropping/resetting the test database has no effect.
$ bundle exec spring rspec some_spec.rb
...
Failure/Error: ActiveRecord::Migration.maintain_test_schema!
ActiveRecord::PendingMigrationError:
Migrations are pending. To resolve this issue, run:
bin/rake db:migrate RAILS_ENV=test
# ~/.rvm/gems/ruby-2.3.3/gems/activerecord-4.2.10/lib/active_record/migration.rb:392:in `check_pending!'
...
0 examples, 0 failures, 1 error occurred outside of examples
To resolve, you can kill the spring server and app that lives between spec runs.
$ ps aux | grep spring
eric 87304 1.3 2.9 3080836 482596 ?? Ss 10:12AM 4:08.36 spring app | gitlab | started 6 hours ago | test mode
eric 37709 0.0 0.0 2518640 7524 s006 S Wed11AM 0:00.79 spring server | gitlab | started 29 hours ago
$ kill 87304
$ kill 37709
db:migrate database version is too old to be migrated
error
Users receive this error when db:migrate
detects that the current schema version
is older than the MIN_SCHEMA_VERSION
defined in the Gitlab::Database
library
module.
Over time we cleanup/combine old migrations in the codebase, so it is not always possible to migrate GitLab from every previous version.
In some cases you might want to bypass this check. For example, if you were on a version
of GitLab schema later than the MIN_SCHEMA_VERSION
, and then rolled back the
to an older migration, from before. In this case, to migrate forward again,
you should set the SKIP_SCHEMA_VERSION_CHECK
environment variable.
bundle exec rake db:migrate SKIP_SCHEMA_VERSION_CHECK=true
Performance issues
Reduce connection overhead with connection pooling
Creating new database connections is not free, and in PostgreSQL specifically, it requires forking an entire process to handle each new one. In case a connection lives for a very long time, this is no problem. However, forking a process for several small queries can turn out to be costly. If left unattended, peaks of new database connections can cause performance degradation, or even lead to a complete outage.
A proven solution for instances that deal with surges of small, short-lived database connections is to implement PgBouncer as a connection pooler. This pool can be used to hold thousands of connections for almost no overhead. The drawback is the addition of a small amount of latency, in exchange for up to more than 90% performance improvement, depending on the usage patterns.
PgBouncer can be fine-tuned to fit different installations. See our documentation on fine-tuning PgBouncer for more information.
Run ANALYZE to regenerate database statistics
The ANALYZE
command is a good first approach for solving many performance issues.
By regenerating table statistics, the query planner creates more efficient query execution paths.
Up to date statistics never hurt!
-
For Linux packages, run:
gitlab-psql -c 'SET statement_timeout = 0; ANALYZE VERBOSE;'
-
On the SQL prompt, run:
-- needed because this is likely to run longer than the default statement_timeout SET statement_timeout = 0; ANALYZE VERBOSE;
Collect data on ACTIVE workload
Active queries are the only ones actually consuming significant resources from the database.
This query gathers meta information from all existing active queries, along with:
- their age
- originating service
-
wait_event
(if it’s in the waiting state) - other possibly relevant information:
-- long queries are usually easier to read with the fields arranged vertically
\x
SELECT
pid
,datname
,usename
,application_name
,client_hostname
,backend_start
,query_start
,query
,age(now(), query_start) AS "age"
,state
,wait_event
,wait_event_type
,backend_type
FROM pg_stat_activity
WHERE state = 'active';
This query captures a single snapshot, so consider running the query 3-5 times in a few minutes while the environment is unresponsive:
-- redirect output to a file
-- this location must be writable by `gitlab-psql`
\o /tmp/active1304.out
--
-- now execute the query above
--
-- all output goes to the file - if the prompt is = then it ran
-- cancel writing output
\o
This Python script can help you parse the
output of pg_stat_activity
into numbers that are easier to understand and correlate to performance issues.
Investigate queries that seem slow
When you identify a query is taking too long to finish, or hogging too much database resources,
check how the query planner is executing it with EXPLAIN
:
EXPLAIN (ANALYZE, BUFFERS) SELECT ... FROM ...
BUFFERS
also show approximately how much memory is involved. I/O might cause
the problem, so make sure to add BUFFERS
when running EXPLAIN
.
If the database is sometimes performant, and sometimes slow, capture this output for the same queries while the environment is in either state.
Investigate index bloat
Index bloat shouldn’t typically cause noticeable performance problems, but it can lead to high disk usage, particularly if there are autovacuum issues.
The query below calculates bloat percentage from PostgreSQL’s own postgres_index_bloat_estimates
table, and orders the results by percentage value. PostgresSQL needs some amount of
bloat to run correctly, so around 25% still represents standard behavior.
select a.identifier, a.bloat_size_bytes, b.tablename, b.ondisk_size_bytes,
(a.bloat_size_bytes/b.ondisk_size_bytes::float)*100 as percentage
from postgres_index_bloat_estimates a
join postgres_indexes b on a.identifier=b.identifier
where
-- to ensure the percentage calculation doesn't encounter zeroes
a.bloat_size_bytes>0 and
b.ondisk_size_bytes>1000000000
order by percentage desc;
Rebuild indexes
If you identify a bloated table, you can rebuild its indexes using the query below. You should also re-run ANALYZE afterward, as statistics can be reset after indexes are rebuilt.
SET statement_timeout = 0;
REINDEX TABLE CONCURRENTLY <table_name>;
Monitor the index rebuild process by running the query below with \watch 30
added after the semicolon:
SELECT
t.tablename, indexname, c.reltuples AS num_rows,
pg_size_pretty(pg_relation_size(quote_ident(t.tablename)::text)) AS table_size,
pg_size_pretty(pg_relation_size(quote_ident(indexrelname)::text)) AS index_size,
CASE WHEN indisvalid THEN 'Y'
ELSE 'N'
END AS VALID
FROM pg_tables t
LEFT OUTER JOIN pg_class c ON t.tablename=c.relname
LEFT OUTER JOIN
( SELECT c.relname AS ctablename, ipg.relname AS indexname, x.indnatts AS
number_of_columns, indexrelname, indisvalid FROM pg_index x
JOIN pg_class c ON c.oid = x.indrelid
JOIN pg_class ipg ON ipg.oid = x.indexrelid
JOIN pg_stat_all_indexes psai ON x.indexrelid = psai.indexrelid )
AS foo
ON t.tablename = foo.ctablename
WHERE
t.tablename in ('<comma_separated_table_names>')
ORDER BY 1,2; \watch 30