- 25 Mar, 2019 1 commit
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Douglas Barbosa Alexandre authored
GitHub importer: Use the project creator to create branches from forks Closes #59396 See merge request gitlab-org/gitlab-ce!26510
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- 20 Mar, 2019 1 commit
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Douglas Barbosa Alexandre authored
GitHub import: Create new branches as project owner See merge request gitlab-org/gitlab-ce!26335 (cherry picked from commit 6e74eb4e) 1e6ea914 GitHub import: Create new branches as project owner
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- 12 Feb, 2019 1 commit
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Stan Hu authored
When the GitHub importer creates a merge request, it retrieves the SHA but does not actually create the source branch. This makes it impossible to merge an open merge request, particularly if the source branch were from a forked project. In that case, the branch will never exist because the original `project-name:source-branch` name is never created, nor is it a valid branch name. To prevent possible branch name conflicts, forked source branches are now renamed `github/fork/project-name/source-branch` and created when necessary. Note that we only create the source branch if the merge request is open. For projects that have many merge requests, the project would end up with a lot of possibly dead branches. Closes https://gitlab.com/gitlab-org/gitlab-ce/issues/57370
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- 24 Aug, 2018 1 commit
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Stan Hu authored
This in preparation for addressing idle-in-transaction timeouts for other importers. Part of #50021
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- 20 Aug, 2018 1 commit
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Yorick Peterse authored
This refactors the AutocompleteController according to the guidelines and boundaries discussed in https://gitlab.com/gitlab-org/gitlab-ce/issues/49653. Specifically, ActiveRecord logic is moved to different finders, which are then used in the controller. View logic in turn is moved to presenters, instead of directly using ActiveRecord's "to_json" method. The finder MoveToProjectFinder is also adjusted according to the abstraction guidelines and boundaries, resulting in a much more simple finder. By using finders (and other abstractions) more actively, we can push a lot of logic out of the controller. We also remove the need for various "before_action" hooks, though this could be achieved without using finders as well. The various finders related to AutcompleteController have also been moved into a namespace. This removes the need for calling everything "AutocompleteSmurfFinder", instead you can use "Autocomplete::SmurfFinder".
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- 16 Aug, 2018 1 commit
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Andreas Brandl authored
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- 12 Jun, 2018 1 commit
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Yorick Peterse authored
In rare cases it could happen that an MR was created, but creating the MR diffs somehow failed (e.g. due to an error). This commit adds an additional check to make sure MR diffs are always present when importing GitHub pull requests.
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- 04 Jun, 2018 1 commit
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Yorick Peterse authored
When importing a GitHub pull request we would perform all work in a single database transaction. This is less than ideal, because we perform various slow Git operations when creating a merge request. This in turn can lead to many DB connections being used, while just waiting for an IO operation to complete. To work around this, we now move most of the heavy lifting out of the database transaction. Some extra error handling is added to ensure we can resume importing a partially imported pull request, instead of just throwing an error. This commit also changes the specs for IssueImporter so they don't rely on deprecated RSpec methods.
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- 07 Nov, 2017 1 commit
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Yorick Peterse authored
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.
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