The previous implementation iterated across the entire patch set
to determine the number of lines added, deleted, and changed. Rugged
has a native method `Rugged::Diff#stat` that does this already,
which appears to be a little faster and require less RAM than doing
this ourselves.
Improves performance in #41524
Given the priorities shifted for the Gitaly team, this endpoint does not
get a dedicated endpoint yet. To make it work in a cloud native
environment the request needs to go to Gitaly, not rugged. This is
achieved by rerouting to the generic TreeEntry endpoint.
By importing this Ruby code into gitlab-rails (and gitaly-ruby), we avoid
200ms of startup time for each gitlab_projects subprocess we are eliminating.
By not having a gitlab_projects subprocess between gitlab-rails / sidekiq and
any git subprocesses (e.g. for fork_project, fetch_remote, etc, calls), we can
also manage these git processes more cleanly, and avoid sending SIGKILL to them
Moving the check out of the general requests, makes sure we don't have
any slowdown in the regular requests.
To keep the process performing this checks small, the check is still
performed inside a unicorn. But that is called from a process running
on the same server.
Because the checks are now done outside normal request, we can have a
simpler failure strategy:
The check is now performed in the background every
`circuitbreaker_check_interval`. Failures are logged in redis. The
failures are reset when the check succeeds. Per check we will try
`circuitbreaker_access_retries` times within
`circuitbreaker_storage_timeout` seconds.
When the number of failures exceeds
`circuitbreaker_failure_count_threshold`, we will block access to the
storage.
After `failure_reset_time` of no checks, we will clear the stored
failures. This could happen when the process that performs the checks
is not running.
Prior to this MR there were two GitHub related importers:
* Github::Import: the main importer used for GitHub projects
* Gitlab::GithubImport: importer that's somewhat confusingly used for
importing Gitea projects (apparently they have a compatible API)
This MR renames the Gitea importer to Gitlab::LegacyGithubImport and
introduces a new GitHub importer in the Gitlab::GithubImport namespace.
This new GitHub importer uses Sidekiq for importing multiple resources
in parallel, though it also has the ability to import data sequentially
should this be necessary.
The new code is spread across the following directories:
* lib/gitlab/github_import: this directory contains most of the importer
code such as the classes used for importing resources.
* app/workers/gitlab/github_import: this directory contains the Sidekiq
workers, most of which simply use the code from the directory above.
* app/workers/concerns/gitlab/github_import: this directory provides a
few modules that are included in every GitHub importer worker.
== Stages
The import work is divided into separate stages, with each stage
importing a specific set of data. Stages will schedule the work that
needs to be performed, followed by scheduling a job for the
"AdvanceStageWorker" worker. This worker will periodically check if all
work is completed and schedule the next stage if this is the case. If
work is not yet completed this worker will reschedule itself.
Using this approach we don't have to block threads by calling `sleep()`,
as doing so for large projects could block the thread from doing any
work for many hours.
== Retrying Work
Workers will reschedule themselves whenever necessary. For example,
hitting the GitHub API's rate limit will result in jobs rescheduling
themselves. These jobs are not processed until the rate limit has been
reset.
== User Lookups
Part of the importing process involves looking up user details in the
GitHub API so we can map them to GitLab users. The old importer used
an in-memory cache, but this obviously doesn't work when the work is
spread across different threads.
The new importer uses a Redis cache and makes sure we only perform
API/database calls if absolutely necessary. Frequently used keys are
refreshed, and lookup misses are also cached; removing the need for
performing API/database calls if we know we don't have the data we're
looking for.
== Performance & Models
The new importer in various places uses raw INSERT statements (as
generated by `Gitlab::Database.bulk_insert`) instead of using Rails
models. This allows us to bypass any validations and callbacks,
drastically reducing the number of SQL queries and Gitaly RPC calls
necessary to import projects.
To ensure the code produces valid data the corresponding tests check if
the produced rows are valid according to the model validation rules.
This allows input to start processing immediately without waiting for the process to complete.
This also allows long or infinite inputs to be partially processed,
which will termiate the process when reading stops with SIGPIPE.
Sean McGivern
Alejandro Rodríguez
Lin Jen-Shin (godfat)
Douwe Maan
Jacob Vosmaer
Dmitriy Zaporozhets
Rémy Coutable
Robert Speicher
Stan Hu
Ahmad Sherif
Zeger-Jan van de Weg
blackst0ne
Valery Sizov
Nick Thomas
Bob Van Landuyt
Zeger-Jan van de Weg
Kim "BKC" Carlbäcker
Douwe Maan
Jacopo
Yorick Peterse
James Edwards-Jones