Commit graph

7 commits

Author SHA1 Message Date
GitLab Bot
b7dfe2ae40 Add latest changes from gitlab-org/gitlab@master 2019-09-13 13:26:31 +00:00
Bob Van Landuyt
589b2db06c Setup Phabricator import
This sets up all the basics for importing Phabricator tasks into
GitLab issues.

To import all tasks from a Phabricator instance into GitLab, we'll
import all of them into a new project that will have its repository
disabled.

The import is hooked into a regular ProjectImport setup, but similar
to the GitHub parallel importer takes care of all the imports itself.

In this iteration, we're importing each page of tasks in a separate
sidekiq job.

The first thing we do when requesting a new page of tasks is schedule
the next page to be imported. But to avoid deadlocks, we only allow a
single job per worker type to run at the same time.

For now we're only importing basic Issue information, this should be
extended to richer information.
2019-05-31 09:40:54 +02:00
Tiago Botelho
4bd8a427d4
Removes all the irrelevant import related code and columns
Clears the import related columns and code from the Project
model over to the ProjectImportState model
2018-11-27 12:58:13 +00:00
Lin Jen-Shin
c61392b4e4 Bring changes from EE for parallel_importer.rb 2018-06-14 02:05:01 +08:00
Tiago Botelho
bddbcaefc2 Backports every CE related change from ee-44542 to CE 2018-05-04 17:33:26 +02:00
Douwe Maan
8da236611b Prefer polymorphism over specific type checks in Import service 2017-11-15 13:40:35 +01:00
Yorick Peterse
4dfe26cd8b
Rewrite the GitHub importer from scratch
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.
2017-11-07 23:24:59 +01:00