gitlab-org--gitlab-foss/lib/gitlab/job_waiter.rb

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# frozen_string_literal: true
Fix race conditions for AuthorizedProjectsWorker There were two cases that could be problematic: 1. Because sometimes AuthorizedProjectsWorker would be scheduled in a transaction it was possible for a job to run/complete before a COMMIT; resulting in it either producing an error, or producing no new data. 2. When scheduling jobs the code would not wait until completion. This could lead to a user creating a project and then immediately trying to push to it. Usually this will work fine, but given enough load it might take a few seconds before a user has access. The first one is problematic, the second one is mostly just annoying (but annoying enough to warrant a solution). This commit changes two things to deal with this: 1. Sidekiq scheduling now takes places after a COMMIT, this is ensured by scheduling using Rails' after_commit hook instead of doing so in an arbitrary method. 2. When scheduling jobs the calling thread now waits for all jobs to complete. Solution 2 requires tracking of job completions. Sidekiq provides a way to find a job by its ID, but this involves scanning over the entire queue; something that is very in-efficient for large queues. As such a more efficient solution is necessary. There are two main Gems that can do this in a more efficient manner: * sidekiq-status * sidekiq_status No, this is not a joke. Both Gems do a similar thing (but slightly different), and the only difference in their name is a dash vs an underscore. Both Gems however provide far more than just checking if a job has been completed, and both have their problems. sidekiq-status does not appear to be actively maintained, with the last release being in 2015. It also has some issues during testing as API calls are not stubbed in any way. sidekiq_status on the other hand does not appear to be very popular, and introduces a similar amount of code. Because of this I opted to write a simple home grown solution. After all, all we need is storing a job ID somewhere so we can efficiently look it up; we don't need extra web UIs (as provided by sidekiq-status) or complex APIs to update progress, etc. This is where Gitlab::SidekiqStatus comes in handy. This namespace contains some code used for tracking, removing, and looking up job IDs; all without having to scan over an entire queue. Data is removed explicitly, but also expires automatically just in case. Using this API we can now schedule jobs in a fork-join like manner: we schedule the jobs in Sidekiq, process them in parallel, then wait for completion. By using Sidekiq we can leverage all the benefits such as being able to scale across multiple cores and hosts, retrying failed jobs, etc. The one downside is that we need to make sure we can deal with unexpected increases in job processing timings. To deal with this the class Gitlab::JobWaiter (used for waiting for jobs to complete) will only wait a number of seconds (30 by default). Once this timeout is reached it will simply return. For GitLab.com almost all AuthorizedProjectWorker jobs complete in seconds, only very rarely do we spike to job timings of around a minute. These in turn seem to be the result of external factors (e.g. deploys), in which case a user is most likely not able to use the system anyway. In short, this new solution should ensure that jobs are processed properly and that in almost all cases a user has access to their resources whenever they need to have access.
2017-01-22 12:22:02 -05:00
module Gitlab
# JobWaiter can be used to wait for a number of Sidekiq jobs to complete.
#
# Its use requires the cooperation of the sidekiq jobs themselves. Set up the
# waiter, then start the jobs, passing them its `key`. Their `perform` methods
# should look like:
#
# def perform(args, notify_key)
# # do work
# ensure
# ::Gitlab::JobWaiter.notify(notify_key, jid)
# end
#
# The JobWaiter blocks popping items from a Redis array. All the sidekiq jobs
# push to that array when done. Once the waiter has popped `count` items, it
# knows all the jobs are done.
Fix race conditions for AuthorizedProjectsWorker There were two cases that could be problematic: 1. Because sometimes AuthorizedProjectsWorker would be scheduled in a transaction it was possible for a job to run/complete before a COMMIT; resulting in it either producing an error, or producing no new data. 2. When scheduling jobs the code would not wait until completion. This could lead to a user creating a project and then immediately trying to push to it. Usually this will work fine, but given enough load it might take a few seconds before a user has access. The first one is problematic, the second one is mostly just annoying (but annoying enough to warrant a solution). This commit changes two things to deal with this: 1. Sidekiq scheduling now takes places after a COMMIT, this is ensured by scheduling using Rails' after_commit hook instead of doing so in an arbitrary method. 2. When scheduling jobs the calling thread now waits for all jobs to complete. Solution 2 requires tracking of job completions. Sidekiq provides a way to find a job by its ID, but this involves scanning over the entire queue; something that is very in-efficient for large queues. As such a more efficient solution is necessary. There are two main Gems that can do this in a more efficient manner: * sidekiq-status * sidekiq_status No, this is not a joke. Both Gems do a similar thing (but slightly different), and the only difference in their name is a dash vs an underscore. Both Gems however provide far more than just checking if a job has been completed, and both have their problems. sidekiq-status does not appear to be actively maintained, with the last release being in 2015. It also has some issues during testing as API calls are not stubbed in any way. sidekiq_status on the other hand does not appear to be very popular, and introduces a similar amount of code. Because of this I opted to write a simple home grown solution. After all, all we need is storing a job ID somewhere so we can efficiently look it up; we don't need extra web UIs (as provided by sidekiq-status) or complex APIs to update progress, etc. This is where Gitlab::SidekiqStatus comes in handy. This namespace contains some code used for tracking, removing, and looking up job IDs; all without having to scan over an entire queue. Data is removed explicitly, but also expires automatically just in case. Using this API we can now schedule jobs in a fork-join like manner: we schedule the jobs in Sidekiq, process them in parallel, then wait for completion. By using Sidekiq we can leverage all the benefits such as being able to scale across multiple cores and hosts, retrying failed jobs, etc. The one downside is that we need to make sure we can deal with unexpected increases in job processing timings. To deal with this the class Gitlab::JobWaiter (used for waiting for jobs to complete) will only wait a number of seconds (30 by default). Once this timeout is reached it will simply return. For GitLab.com almost all AuthorizedProjectWorker jobs complete in seconds, only very rarely do we spike to job timings of around a minute. These in turn seem to be the result of external factors (e.g. deploys), in which case a user is most likely not able to use the system anyway. In short, this new solution should ensure that jobs are processed properly and that in almost all cases a user has access to their resources whenever they need to have access.
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class JobWaiter
KEY_PREFIX = "gitlab:job_waiter"
def self.notify(key, jid)
Gitlab::Redis::SharedState.with { |redis| redis.lpush(key, jid) }
end
def self.key?(key)
key.is_a?(String) && key =~ /\A#{KEY_PREFIX}:\h{8}-\h{4}-\h{4}-\h{4}-\h{12}\z/
end
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.
2017-10-13 12:50:36 -04:00
attr_reader :key, :finished
attr_accessor :jobs_remaining
Fix race conditions for AuthorizedProjectsWorker There were two cases that could be problematic: 1. Because sometimes AuthorizedProjectsWorker would be scheduled in a transaction it was possible for a job to run/complete before a COMMIT; resulting in it either producing an error, or producing no new data. 2. When scheduling jobs the code would not wait until completion. This could lead to a user creating a project and then immediately trying to push to it. Usually this will work fine, but given enough load it might take a few seconds before a user has access. The first one is problematic, the second one is mostly just annoying (but annoying enough to warrant a solution). This commit changes two things to deal with this: 1. Sidekiq scheduling now takes places after a COMMIT, this is ensured by scheduling using Rails' after_commit hook instead of doing so in an arbitrary method. 2. When scheduling jobs the calling thread now waits for all jobs to complete. Solution 2 requires tracking of job completions. Sidekiq provides a way to find a job by its ID, but this involves scanning over the entire queue; something that is very in-efficient for large queues. As such a more efficient solution is necessary. There are two main Gems that can do this in a more efficient manner: * sidekiq-status * sidekiq_status No, this is not a joke. Both Gems do a similar thing (but slightly different), and the only difference in their name is a dash vs an underscore. Both Gems however provide far more than just checking if a job has been completed, and both have their problems. sidekiq-status does not appear to be actively maintained, with the last release being in 2015. It also has some issues during testing as API calls are not stubbed in any way. sidekiq_status on the other hand does not appear to be very popular, and introduces a similar amount of code. Because of this I opted to write a simple home grown solution. After all, all we need is storing a job ID somewhere so we can efficiently look it up; we don't need extra web UIs (as provided by sidekiq-status) or complex APIs to update progress, etc. This is where Gitlab::SidekiqStatus comes in handy. This namespace contains some code used for tracking, removing, and looking up job IDs; all without having to scan over an entire queue. Data is removed explicitly, but also expires automatically just in case. Using this API we can now schedule jobs in a fork-join like manner: we schedule the jobs in Sidekiq, process them in parallel, then wait for completion. By using Sidekiq we can leverage all the benefits such as being able to scale across multiple cores and hosts, retrying failed jobs, etc. The one downside is that we need to make sure we can deal with unexpected increases in job processing timings. To deal with this the class Gitlab::JobWaiter (used for waiting for jobs to complete) will only wait a number of seconds (30 by default). Once this timeout is reached it will simply return. For GitLab.com almost all AuthorizedProjectWorker jobs complete in seconds, only very rarely do we spike to job timings of around a minute. These in turn seem to be the result of external factors (e.g. deploys), in which case a user is most likely not able to use the system anyway. In short, this new solution should ensure that jobs are processed properly and that in almost all cases a user has access to their resources whenever they need to have access.
2017-01-22 12:22:02 -05:00
# jobs_remaining - the number of jobs left to wait for
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.
2017-10-13 12:50:36 -04:00
# key - The key of this waiter.
def initialize(jobs_remaining = 0, key = "#{KEY_PREFIX}:#{SecureRandom.uuid}")
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.
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@key = key
@jobs_remaining = jobs_remaining
@finished = []
Fix race conditions for AuthorizedProjectsWorker There were two cases that could be problematic: 1. Because sometimes AuthorizedProjectsWorker would be scheduled in a transaction it was possible for a job to run/complete before a COMMIT; resulting in it either producing an error, or producing no new data. 2. When scheduling jobs the code would not wait until completion. This could lead to a user creating a project and then immediately trying to push to it. Usually this will work fine, but given enough load it might take a few seconds before a user has access. The first one is problematic, the second one is mostly just annoying (but annoying enough to warrant a solution). This commit changes two things to deal with this: 1. Sidekiq scheduling now takes places after a COMMIT, this is ensured by scheduling using Rails' after_commit hook instead of doing so in an arbitrary method. 2. When scheduling jobs the calling thread now waits for all jobs to complete. Solution 2 requires tracking of job completions. Sidekiq provides a way to find a job by its ID, but this involves scanning over the entire queue; something that is very in-efficient for large queues. As such a more efficient solution is necessary. There are two main Gems that can do this in a more efficient manner: * sidekiq-status * sidekiq_status No, this is not a joke. Both Gems do a similar thing (but slightly different), and the only difference in their name is a dash vs an underscore. Both Gems however provide far more than just checking if a job has been completed, and both have their problems. sidekiq-status does not appear to be actively maintained, with the last release being in 2015. It also has some issues during testing as API calls are not stubbed in any way. sidekiq_status on the other hand does not appear to be very popular, and introduces a similar amount of code. Because of this I opted to write a simple home grown solution. After all, all we need is storing a job ID somewhere so we can efficiently look it up; we don't need extra web UIs (as provided by sidekiq-status) or complex APIs to update progress, etc. This is where Gitlab::SidekiqStatus comes in handy. This namespace contains some code used for tracking, removing, and looking up job IDs; all without having to scan over an entire queue. Data is removed explicitly, but also expires automatically just in case. Using this API we can now schedule jobs in a fork-join like manner: we schedule the jobs in Sidekiq, process them in parallel, then wait for completion. By using Sidekiq we can leverage all the benefits such as being able to scale across multiple cores and hosts, retrying failed jobs, etc. The one downside is that we need to make sure we can deal with unexpected increases in job processing timings. To deal with this the class Gitlab::JobWaiter (used for waiting for jobs to complete) will only wait a number of seconds (30 by default). Once this timeout is reached it will simply return. For GitLab.com almost all AuthorizedProjectWorker jobs complete in seconds, only very rarely do we spike to job timings of around a minute. These in turn seem to be the result of external factors (e.g. deploys), in which case a user is most likely not able to use the system anyway. In short, this new solution should ensure that jobs are processed properly and that in almost all cases a user has access to their resources whenever they need to have access.
2017-01-22 12:22:02 -05:00
end
# Waits for all the jobs to be completed.
#
# timeout - The maximum amount of seconds to block the caller for. This
# ensures we don't indefinitely block a caller in case a job takes
# long to process, or is never processed.
def wait(timeout = 10)
deadline = Time.now.utc + timeout
Gitlab::Redis::SharedState.with do |redis|
# Fallback key expiry: allow a long grace period to reduce the chance of
# a job pushing to an expired key and recreating it
redis.expire(key, [timeout * 2, 10.minutes.to_i].max)
while jobs_remaining > 0
# Redis will not take fractional seconds. Prefer waiting too long over
# not waiting long enough
seconds_left = (deadline - Time.now.utc).ceil
Fix race conditions for AuthorizedProjectsWorker There were two cases that could be problematic: 1. Because sometimes AuthorizedProjectsWorker would be scheduled in a transaction it was possible for a job to run/complete before a COMMIT; resulting in it either producing an error, or producing no new data. 2. When scheduling jobs the code would not wait until completion. This could lead to a user creating a project and then immediately trying to push to it. Usually this will work fine, but given enough load it might take a few seconds before a user has access. The first one is problematic, the second one is mostly just annoying (but annoying enough to warrant a solution). This commit changes two things to deal with this: 1. Sidekiq scheduling now takes places after a COMMIT, this is ensured by scheduling using Rails' after_commit hook instead of doing so in an arbitrary method. 2. When scheduling jobs the calling thread now waits for all jobs to complete. Solution 2 requires tracking of job completions. Sidekiq provides a way to find a job by its ID, but this involves scanning over the entire queue; something that is very in-efficient for large queues. As such a more efficient solution is necessary. There are two main Gems that can do this in a more efficient manner: * sidekiq-status * sidekiq_status No, this is not a joke. Both Gems do a similar thing (but slightly different), and the only difference in their name is a dash vs an underscore. Both Gems however provide far more than just checking if a job has been completed, and both have their problems. sidekiq-status does not appear to be actively maintained, with the last release being in 2015. It also has some issues during testing as API calls are not stubbed in any way. sidekiq_status on the other hand does not appear to be very popular, and introduces a similar amount of code. Because of this I opted to write a simple home grown solution. After all, all we need is storing a job ID somewhere so we can efficiently look it up; we don't need extra web UIs (as provided by sidekiq-status) or complex APIs to update progress, etc. This is where Gitlab::SidekiqStatus comes in handy. This namespace contains some code used for tracking, removing, and looking up job IDs; all without having to scan over an entire queue. Data is removed explicitly, but also expires automatically just in case. Using this API we can now schedule jobs in a fork-join like manner: we schedule the jobs in Sidekiq, process them in parallel, then wait for completion. By using Sidekiq we can leverage all the benefits such as being able to scale across multiple cores and hosts, retrying failed jobs, etc. The one downside is that we need to make sure we can deal with unexpected increases in job processing timings. To deal with this the class Gitlab::JobWaiter (used for waiting for jobs to complete) will only wait a number of seconds (30 by default). Once this timeout is reached it will simply return. For GitLab.com almost all AuthorizedProjectWorker jobs complete in seconds, only very rarely do we spike to job timings of around a minute. These in turn seem to be the result of external factors (e.g. deploys), in which case a user is most likely not able to use the system anyway. In short, this new solution should ensure that jobs are processed properly and that in almost all cases a user has access to their resources whenever they need to have access.
2017-01-22 12:22:02 -05:00
# Redis interprets 0 as "wait forever", so skip the final `blpop` call
break if seconds_left <= 0
Fix race conditions for AuthorizedProjectsWorker There were two cases that could be problematic: 1. Because sometimes AuthorizedProjectsWorker would be scheduled in a transaction it was possible for a job to run/complete before a COMMIT; resulting in it either producing an error, or producing no new data. 2. When scheduling jobs the code would not wait until completion. This could lead to a user creating a project and then immediately trying to push to it. Usually this will work fine, but given enough load it might take a few seconds before a user has access. The first one is problematic, the second one is mostly just annoying (but annoying enough to warrant a solution). This commit changes two things to deal with this: 1. Sidekiq scheduling now takes places after a COMMIT, this is ensured by scheduling using Rails' after_commit hook instead of doing so in an arbitrary method. 2. When scheduling jobs the calling thread now waits for all jobs to complete. Solution 2 requires tracking of job completions. Sidekiq provides a way to find a job by its ID, but this involves scanning over the entire queue; something that is very in-efficient for large queues. As such a more efficient solution is necessary. There are two main Gems that can do this in a more efficient manner: * sidekiq-status * sidekiq_status No, this is not a joke. Both Gems do a similar thing (but slightly different), and the only difference in their name is a dash vs an underscore. Both Gems however provide far more than just checking if a job has been completed, and both have their problems. sidekiq-status does not appear to be actively maintained, with the last release being in 2015. It also has some issues during testing as API calls are not stubbed in any way. sidekiq_status on the other hand does not appear to be very popular, and introduces a similar amount of code. Because of this I opted to write a simple home grown solution. After all, all we need is storing a job ID somewhere so we can efficiently look it up; we don't need extra web UIs (as provided by sidekiq-status) or complex APIs to update progress, etc. This is where Gitlab::SidekiqStatus comes in handy. This namespace contains some code used for tracking, removing, and looking up job IDs; all without having to scan over an entire queue. Data is removed explicitly, but also expires automatically just in case. Using this API we can now schedule jobs in a fork-join like manner: we schedule the jobs in Sidekiq, process them in parallel, then wait for completion. By using Sidekiq we can leverage all the benefits such as being able to scale across multiple cores and hosts, retrying failed jobs, etc. The one downside is that we need to make sure we can deal with unexpected increases in job processing timings. To deal with this the class Gitlab::JobWaiter (used for waiting for jobs to complete) will only wait a number of seconds (30 by default). Once this timeout is reached it will simply return. For GitLab.com almost all AuthorizedProjectWorker jobs complete in seconds, only very rarely do we spike to job timings of around a minute. These in turn seem to be the result of external factors (e.g. deploys), in which case a user is most likely not able to use the system anyway. In short, this new solution should ensure that jobs are processed properly and that in almost all cases a user has access to their resources whenever they need to have access.
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list, jid = redis.blpop(key, timeout: seconds_left)
break unless list && jid # timed out
@finished << jid
@jobs_remaining -= 1
end
# All jobs have finished, so expire the key immediately
redis.expire(key, 0) if jobs_remaining == 0
Fix race conditions for AuthorizedProjectsWorker There were two cases that could be problematic: 1. Because sometimes AuthorizedProjectsWorker would be scheduled in a transaction it was possible for a job to run/complete before a COMMIT; resulting in it either producing an error, or producing no new data. 2. When scheduling jobs the code would not wait until completion. This could lead to a user creating a project and then immediately trying to push to it. Usually this will work fine, but given enough load it might take a few seconds before a user has access. The first one is problematic, the second one is mostly just annoying (but annoying enough to warrant a solution). This commit changes two things to deal with this: 1. Sidekiq scheduling now takes places after a COMMIT, this is ensured by scheduling using Rails' after_commit hook instead of doing so in an arbitrary method. 2. When scheduling jobs the calling thread now waits for all jobs to complete. Solution 2 requires tracking of job completions. Sidekiq provides a way to find a job by its ID, but this involves scanning over the entire queue; something that is very in-efficient for large queues. As such a more efficient solution is necessary. There are two main Gems that can do this in a more efficient manner: * sidekiq-status * sidekiq_status No, this is not a joke. Both Gems do a similar thing (but slightly different), and the only difference in their name is a dash vs an underscore. Both Gems however provide far more than just checking if a job has been completed, and both have their problems. sidekiq-status does not appear to be actively maintained, with the last release being in 2015. It also has some issues during testing as API calls are not stubbed in any way. sidekiq_status on the other hand does not appear to be very popular, and introduces a similar amount of code. Because of this I opted to write a simple home grown solution. After all, all we need is storing a job ID somewhere so we can efficiently look it up; we don't need extra web UIs (as provided by sidekiq-status) or complex APIs to update progress, etc. This is where Gitlab::SidekiqStatus comes in handy. This namespace contains some code used for tracking, removing, and looking up job IDs; all without having to scan over an entire queue. Data is removed explicitly, but also expires automatically just in case. Using this API we can now schedule jobs in a fork-join like manner: we schedule the jobs in Sidekiq, process them in parallel, then wait for completion. By using Sidekiq we can leverage all the benefits such as being able to scale across multiple cores and hosts, retrying failed jobs, etc. The one downside is that we need to make sure we can deal with unexpected increases in job processing timings. To deal with this the class Gitlab::JobWaiter (used for waiting for jobs to complete) will only wait a number of seconds (30 by default). Once this timeout is reached it will simply return. For GitLab.com almost all AuthorizedProjectWorker jobs complete in seconds, only very rarely do we spike to job timings of around a minute. These in turn seem to be the result of external factors (e.g. deploys), in which case a user is most likely not able to use the system anyway. In short, this new solution should ensure that jobs are processed properly and that in almost all cases a user has access to their resources whenever they need to have access.
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end
finished
Fix race conditions for AuthorizedProjectsWorker There were two cases that could be problematic: 1. Because sometimes AuthorizedProjectsWorker would be scheduled in a transaction it was possible for a job to run/complete before a COMMIT; resulting in it either producing an error, or producing no new data. 2. When scheduling jobs the code would not wait until completion. This could lead to a user creating a project and then immediately trying to push to it. Usually this will work fine, but given enough load it might take a few seconds before a user has access. The first one is problematic, the second one is mostly just annoying (but annoying enough to warrant a solution). This commit changes two things to deal with this: 1. Sidekiq scheduling now takes places after a COMMIT, this is ensured by scheduling using Rails' after_commit hook instead of doing so in an arbitrary method. 2. When scheduling jobs the calling thread now waits for all jobs to complete. Solution 2 requires tracking of job completions. Sidekiq provides a way to find a job by its ID, but this involves scanning over the entire queue; something that is very in-efficient for large queues. As such a more efficient solution is necessary. There are two main Gems that can do this in a more efficient manner: * sidekiq-status * sidekiq_status No, this is not a joke. Both Gems do a similar thing (but slightly different), and the only difference in their name is a dash vs an underscore. Both Gems however provide far more than just checking if a job has been completed, and both have their problems. sidekiq-status does not appear to be actively maintained, with the last release being in 2015. It also has some issues during testing as API calls are not stubbed in any way. sidekiq_status on the other hand does not appear to be very popular, and introduces a similar amount of code. Because of this I opted to write a simple home grown solution. After all, all we need is storing a job ID somewhere so we can efficiently look it up; we don't need extra web UIs (as provided by sidekiq-status) or complex APIs to update progress, etc. This is where Gitlab::SidekiqStatus comes in handy. This namespace contains some code used for tracking, removing, and looking up job IDs; all without having to scan over an entire queue. Data is removed explicitly, but also expires automatically just in case. Using this API we can now schedule jobs in a fork-join like manner: we schedule the jobs in Sidekiq, process them in parallel, then wait for completion. By using Sidekiq we can leverage all the benefits such as being able to scale across multiple cores and hosts, retrying failed jobs, etc. The one downside is that we need to make sure we can deal with unexpected increases in job processing timings. To deal with this the class Gitlab::JobWaiter (used for waiting for jobs to complete) will only wait a number of seconds (30 by default). Once this timeout is reached it will simply return. For GitLab.com almost all AuthorizedProjectWorker jobs complete in seconds, only very rarely do we spike to job timings of around a minute. These in turn seem to be the result of external factors (e.g. deploys), in which case a user is most likely not able to use the system anyway. In short, this new solution should ensure that jobs are processed properly and that in almost all cases a user has access to their resources whenever they need to have access.
2017-01-22 12:22:02 -05:00
end
end
end