Auto-removal of jobs

By default, when your queue jobs are completed (or failed), they are stored in two special sets, the "completed" and the "failed" set. This is useful so that you can examine the results of your jobs, particularly in the early stages of development. However, as the solution reaches a production-grade level, we usually need to restrict the number of finished jobs to be kept, so that we do not fill Redis with data that is not particularly useful.

BullMQ supports different strategies for auto-removing finalized jobs. These strategies are configured on the Worker's options removeOnCompletearrow-up-right and removeOnFailarrow-up-right.

Remove all finalized jobs

The simplest option is to set removeOnComplete/removeOnFail to {count: 0}, in this case, all jobs will be removed automatically as soon as they are finalized:

const myWorker = new Worker(
  'myQueueName',
  async job => {
    // do some work
  },
  {
    connection,
    removeOnFail: { count: 0 },
  },
);
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Keep a certain number of jobs

It is also possible to specify a maximum number of jobs to keep. A good practice is to keep a handful of completed jobs and a much larger value of failed jobs:

const myWorker = new Worker(
  'myQueueName',
  async job => {
    // do some work
  },
  {
    connection,
    removeOnComplete: { count: 1000 },
    removeOnFail: { count: 5000 },
  },
);

Keep jobs based on their age

Another possibility is to keep jobs up to a certain age. The removeOn option accepts a KeepJobsarrow-up-right object, that includes age, count, and limit fields. The age is used to specify how old jobs to keep (in seconds), the count can be used to limit the total amount to keep, and the limit controls how many jobs are removed per cleanup iteration. The count option is useful in cases we get an unexpected amount of jobs in a very short time, in this case we may just want to limit to a certain amount to avoid running out of memory. The limit option helps control the performance impact of cleanup operations by limiting how many jobs are processed at once.

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The auto removal of jobs works lazily. This means that jobs are not removed unless a new job completes or fails, since that is when the auto-removal takes place.

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