debian-mirror-gitlab/doc/development/database/database_lab.md

stage	group	info
Data Stores	Database	To determine the technical writer assigned to the Stage/Group associated with this page, see https://about.gitlab.com/handbook/product/ux/technical-writing/#assignments

Database Lab and Postgres.ai

Internal users at GitLab have access to the Database Lab Engine (DLE) and postgres.ai for testing performance of database queries on replicated production data. Unlike a typical read-only production replica, in the DLE you can also create, update, and delete rows. You can also test the performance of schema changes, like additional indexes or columns, in an isolated copy of production data.

Database Lab quick start

1. Visit the console.
2. Select Sign in with Google. (Not GitLab, as you need Google SSO to connect with our project.)
3. After you sign in, select the GitLab organization and then visit "Ask Joe" in the sidebar.
4. Select the database you're testing against:
   • Most queries for the GitLab project run against gitlab-production-tunnel-pg12.
   • If the query is for a CI table, select gitlab-production-ci.
   • If the query is for the container registry, select gitlab-production-registry.
5. Type explain <Query Text> in the chat box to get a plan.

Access Database Lab Engine

Access to the DLE is helpful for:

• Database reviewers and maintainers.
• Engineers who work on merge requests that have large effects on databases.

To access the DLE's services, you can:

• Perform query testing in the Postgres.ai web console. Employees access both services with their GitLab Google account. Query testing provides EXPLAIN (analyze, buffers) plans for queries executed there.
• Migration testing by triggering a job as a part of a merge request.
• Direct psql access to DLE instead of a production replica. Available to authorized users only. To request psql access, file an access request.

For more assistance, use the #database Slack channel.

NOTE: If you need only temporary access to a production replica, instead of a Database Lab clone, follow the runbook procedure for connecting to the database console with Teleport. This procedure is similar to Rails console access with Teleport.

Query testing

You can access Database Lab's query analysis features either:

• In the Postgres.ai web console. Shows only the commands you run.

Generate query plans

Query plans are an essential part of the database review process. These plans enable us to decide quickly if a given query can be performant on GitLab.com. Running the explain command generates an explain plan and a link to the Postgres.ai console with more query analysis. For example, running EXPLAIN SELECT * FROM application_settings does the following:

1. Runs explain (analyze, buffers) select * from application_settings; against a database clone.
2. Responds with timing and buffer details from the run.
3. Provides a detailed, shareable report on the results.

Making schema changes

Sometimes when testing queries, a contributor may realize that the query needs an index or other schema change to make added queries more performant. To test the query, run the exec command. For example, running this command:

exec CREATE INDEX on application_settings USING btree (instance_administration_project_id)

creates the specified index on the table. You can test queries leveraging the new index. exec does not return any results, only the time required to execute the query.

Reset the clone

After many changes, such as after a destructive query or an ineffective index, you must start over. To reset your designated clone, run reset.

Checking indexes

Use Database Lab to check the status of an index with the meta-command \d <index_name>.

Caveats:

• Indexes are created in both the main and ci databases, so be sure to use the instance that matches the table's gitlab_schema. For example, if the index is added to ci_builds, use gitlab-production-ci.
• Database Lab typically has a small delay of a few hours. If more up-to-date information is required, you can instead request access to a replica via Teleport

For example: \d index_design_management_designs_on_project_id produces:

Index "public.index_design_management_designs_on_project_id"
   Column   |  Type   | Key? | Definition
------------+---------+------+------------
 project_id | integer | yes  | project_id
btree, for table "public.design_management_designs"

In the case of an invalid index, the output ends with invalid, like:

Index "public.index_design_management_designs_on_project_id"
   Column   |  Type   | Key? | Definition
------------+---------+------+------------
 project_id | integer | yes  | project_id
btree, for table "public.design_management_designs", invalid

If the index doesn't exist, JoeBot throws an error like:

ERROR: psql error: psql:/tmp/psql-query-932227396:1: error: Did not find any relation named "no_index".

Migration testing

For information on testing migrations, review our database migration testing documentation.

Access the console with psql

NOTE: You must have AllFeaturesUser psql access to access the console with psql.

Simplified access through pgai Ruby gem

@mbobin created the pgai Ruby Gem that greatly simplifies access to a database clone, with support for:

• Access to all database clones listed in the Postgres.ai instances page;
• Multiple psql sessions on the same clone.

If you have AllFeaturesUser psql access, you can follow the steps below to configure the pgai Gem:

1. To get started, you need to gather some values from the Postgres.ai instances page:

   1. Navigate to the instance that you want to configure and the on right side of the screen.

   2. Under Connection, select Connect. The menu might be collapsed.

      A pop-up with everything that's needed for configuration appears, using this format:

      dblab init --url http://127.0.0.1:1234 --token TOKEN --environment-id <environment-id>
      

      ssh -NTML 1234:localhost:<environment-port> <postgresai-user>@<postgresai-proxy> -i ~/.ssh/id_rsa
      

2. Add the following snippet to your SSH configuration file at ~/.ssh/config, replacing the variable values:

   Host pgai-proxy
     HostName <postgresai-proxy>
     User <postgresai-user>
     IdentityFile ~/.ssh/id_ed25519
   

3. Run the following command so you can accept the server key fingerprint:

   ssh pgai-proxy
   

4. Run the following commands:

   gem install pgai
   
   # Grab an access token: https://console.postgres.ai/gitlab/tokens
   # GITLAB_USER is your GitLab handle
   pgai config --dbname=gitlabhq_dblab --prefix=$GITLAB_USER --proxy=pgai-proxy
   
   # Grab the respective port values from https://console.postgres.ai/gitlab/instances
   # for the instances you'll be using (in this case, for the `main` database instance)
   pgai env add --alias main --id <environment-id> --port <environment-port>
   

5. Once this one-time configuration is done, you can use pgai connect to connect to a particular database. For instance, to connect to the main database:

   pgai connect main
   

6. Once done with the clone, you can destroy it:

   pgai destroy main
   

Manual access through the Postgres.ai instances page

Team members with psql access, can gain direct access to a clone via psql. Access to psql enables you to see data, not just metadata.

To connect to a clone using psql:

1. Create a clone from the desired instance.
   1. Provide a Clone ID: Something that uniquely identifies your clone, such as yourname-testing-gitlabissue.
   2. Provide a Database username and Database password: Connects psql to your clone.
   3. Select Enable deletion protection if you want to preserve your clone. Avoid selecting this option. Clones are removed after 12 hours.
2. In the Clone details page of the Postgres.ai web interface, copy and run the command to start SSH port forwarding for the clone.
3. In the Clone details page of the Postgres.ai web interface, copy and run the psql connection string. Use the password provided at setup and set the dbname to gitlabhq_dblab (or check what databases are available by using psql -l with the same query string but dbname=postgres).

After you connect, use clone like you would any psql console in production, but with the added benefit and safety of an isolated writeable environment.