Time Master: Attempted Upgrade

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These are documented here. Sometimes we miss requests and there are plenty of them. Maybe we were thinking on something. It will encourage consideration. In the meantime if you could rebase the pull request so that it can be cherry-picked more easily we will love you for a long time. As a bonus brew update will merge your changes with upstream so you can still keep the formula up-to-date with your personal modifications! Just brew create URL. Yes, brew is designed to not get in your way so you can use it how you like.

Install your own stuff, but be aware that if you install common libraries like libexpat yourself, it may cause trouble when trying to build certain Homebrew formula. As a result brew doctor will warn you about this. Like so:. Likely because it had unresolved issues or our analytics identified it was not widely used.

By the time he realised it was, it was too late. This means most tools will not find it. You can still link in the formula if you need to with brew link. Currently there is no other way to do this. All your terminology needs can be found here. Homebrew Documentation. If you would like to specify the default connection and queue that should be used for the chained jobs, you may use the allOnConnection and allOnQueue methods. By pushing jobs to different queues, you may "categorize" your queued jobs and even prioritize how many workers you assign to various queues.

Keep in mind, this does not push jobs to different queue "connections" as defined by your queue configuration file, but only to specific queues within a single connection. To specify the queue, use the onQueue method when dispatching the job:. If you are working with multiple queue connections, you may specify which connection to push a job to. To specify the connection, use the onConnection method when dispatching the job:. You may chain the onConnection and onQueue methods to specify the connection and the queue for a job:.

One approach to specifying the maximum number of times a job may be attempted is via the --tries switch on the Artisan command line:. However, you may take a more granular approach by defining the maximum number of attempts on the job class itself. If the maximum number of attempts is specified on the job, it will take precedence over the value provided on the command line:. As an alternative to defining how many times a job may be attempted before it fails, you may define a time at which the job should timeout.

This allows a job to be attempted any number of times within a given time frame. To define the time at which a job should timeout, add a retryUntil method to your job class:. Likewise, the maximum number of seconds that jobs can run may be specified using the --timeout switch on the Artisan command line:. However, you may also define the maximum number of seconds a job should be allowed to run on the job class itself. If the timeout is specified on the job, it will take precedence over any timeout specified on the command line:. If your application interacts with Redis, you may throttle your queued jobs by time or concurrency.

This feature can be of assistance when your queued jobs are interacting with APIs that are also rate limited. For example, using the throttle method, you may throttle a given type of job to only run 10 times every 60 seconds. If a lock can not be obtained, you should typically release the job back onto the queue so it can be retried later:. For example, you may wish to construct the key based on the class name of the job and the IDs of the Eloquent models it operates on.

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Alternatively, you may specify the maximum number of workers that may simultaneously process a given job. This can be helpful when a queued job is modifying a resource that should only be modified by one job at a time. For example, using the funnel method, you may limit jobs of a given type to only be processed by one worker at a time:. Therefore, it is useful to combine rate limiting with time based attempts. If an exception is thrown while the job is being processed, the job will automatically be released back onto the queue so it may be attempted again.

The job will continue to be released until it has been attempted the maximum number of times allowed by your application.


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The maximum number of attempts is defined by the --tries switch used on the queue:work Artisan command. Alternatively, the maximum number of attempts may be defined on the job class itself. More information on running the queue worker can be found below. Instead of dispatching a job class to the queue, you may also dispatch a Closure. This is great for quick, simple tasks that need to be executed outside of the current request cycle:. When dispatching Closures to the queue, the Closure's code contents is cryptographically signed so it can not be modified in transit.

Laravel includes a queue worker that will process new jobs as they are pushed onto the queue. You may run the worker using the queue:work Artisan command. Note that once the queue:work command has started, it will continue to run until it is manually stopped or you close your terminal:.

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Remember, queue workers are long-lived processes and store the booted application state in memory. As a result, they will not notice changes in your code base after they have been started. So, during your deployment process, be sure to restart your queue workers. You may also specify which queue connection the worker should utilize. You may customize your queue worker even further by only processing particular queues for a given connection. For example, if all of your emails are processed in an emails queue on your redis queue connection, you may issue the following command to start a worker that only processes only that queue:.

The --once option may be used to instruct the worker to only process a single job from the queue:. The --stop-when-empty option may be used to instruct the worker to process all jobs and then exit gracefully.

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This option can be useful when working Laravel queues within a Docker container if you wish to shutdown the container after the queue is empty:. Daemon queue workers do not "reboot" the framework before processing each job. Therefore, you should free any heavy resources after each job completes.

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For example, if you are doing image manipulation with the GD library, you should free the memory with imagedestroy when you are done. Sometimes you may wish to prioritize how your queues are processed. However, occasionally you may wish to push a job to a high priority queue like so:. To start a worker that verifies that all of the high queue jobs are processed before continuing to any jobs on the low queue, pass a comma-delimited list of queue names to the work command:.

Since queue workers are long-lived processes, they will not pick up changes to your code without being restarted. So, the simplest way to deploy an application using queue workers is to restart the workers during your deployment process. You may gracefully restart all of the workers by issuing the queue:restart command:. This command will instruct all queue workers to gracefully "die" after they finish processing their current job so that no existing jobs are lost.

Since the queue workers will die when the queue:restart command is executed, you should be running a process manager such as Supervisor to automatically restart the queue workers. This option specifies how many seconds the queue connection should wait before retrying a job that is being processed.

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The queue:work Artisan command exposes a --timeout option. The --timeout option specifies how long the Laravel queue master process will wait before killing off a child queue worker that is processing a job. Sometimes a child queue process can become "frozen" for various reasons, such as an external HTTP call that is not responding.

The --timeout option removes frozen processes that have exceeded that specified time limit:.

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This will ensure that a worker processing a given job is always killed before the job is retried. When jobs are available on the queue, the worker will keep processing jobs with no delay in between them. However, the sleep option determines how long in seconds the worker will "sleep" if there are no new jobs available.

While sleeping, the worker will not process any new jobs - the jobs will be processed after the worker wakes up again. Supervisor is a process monitor for the Linux operating system, and will automatically restart your queue:work process if it fails.

To install Supervisor on Ubuntu, you may use the following command:. Within this directory, you may create any number of configuration files that instruct supervisor how your processes should be monitored. For example, let's create a laravel-worker. In this example, the numprocs directive will instruct Supervisor to run 8 queue:work processes and monitor all of them, automatically restarting them if they fail.

You should change the queue:work sqs portion of the command directive to reflect your desired queue connection. Once the configuration file has been created, you may update the Supervisor configuration and start the processes using the following commands:. For more information on Supervisor, consult the Supervisor documentation.

Sometimes your queued jobs will fail. Don't worry, things don't always go as planned! Laravel includes a convenient way to specify the maximum number of times a job should be attempted.