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375 lines
19 KiB
Markdown
375 lines
19 KiB
Markdown
<!-- BEGIN MUNGE: UNVERSIONED_WARNING -->
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<!-- BEGIN STRIP_FOR_RELEASE -->
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<img src="http://kubernetes.io/img/warning.png" alt="WARNING"
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width="25" height="25">
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<img src="http://kubernetes.io/img/warning.png" alt="WARNING"
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<img src="http://kubernetes.io/img/warning.png" alt="WARNING"
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width="25" height="25">
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<img src="http://kubernetes.io/img/warning.png" alt="WARNING"
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<img src="http://kubernetes.io/img/warning.png" alt="WARNING"
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width="25" height="25">
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<h2>PLEASE NOTE: This document applies to the HEAD of the source tree</h2>
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If you are using a released version of Kubernetes, you should
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refer to the docs that go with that version.
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<!-- TAG RELEASE_LINK, added by the munger automatically -->
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<strong>
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The latest release of this document can be found
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[here](http://releases.k8s.io/release-1.1/docs/user-guide/jobs.md).
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Documentation for other releases can be found at
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[releases.k8s.io](http://releases.k8s.io).
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</strong>
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--
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<!-- END STRIP_FOR_RELEASE -->
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<!-- END MUNGE: UNVERSIONED_WARNING -->
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# Jobs
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**Table of Contents**
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<!-- BEGIN MUNGE: GENERATED_TOC -->
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- [Jobs](#jobs)
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- [What is a _job_?](#what-is-a-job)
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- [Running an example Job](#running-an-example-job)
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- [Writing a Job Spec](#writing-a-job-spec)
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- [Pod Template](#pod-template)
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- [Pod Selector](#pod-selector)
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- [Parallel Jobs](#parallel-jobs)
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- [Controlling Parallelism](#controlling-parallelism)
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- [Handling Pod and Container Failures](#handling-pod-and-container-failures)
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- [Job Patterns](#job-patterns)
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- [Alternatives](#alternatives)
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- [Bare Pods](#bare-pods)
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- [Replication Controller](#replication-controller)
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- [Single Job starts Controller Pod](#single-job-starts-controller-pod)
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- [Caveats](#caveats)
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- [Future work](#future-work)
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<!-- END MUNGE: GENERATED_TOC -->
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## What is a _job_?
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A _job_ creates one or more pods and ensures that a specified number of them successfully terminate.
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As pods successfully complete, the _job_ tracks the successful completions. When a specified number
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of successful completions is reached, the job itself is complete. Deleting a Job will cleanup the
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pods it created.
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A simple case is to create 1 Job object in order to reliably run one Pod to completion.
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The Job object will start a new Pod if the first pod fails or is deleted (for example
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due to a node hardware failure or a node reboot).
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A Job can also be used to run multiple pods in parallel.
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## Running an example Job
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Here is an example Job config. It computes π to 2000 places and prints it out.
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It takes around 10s to complete.
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<!-- BEGIN MUNGE: EXAMPLE job.yaml -->
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```yaml
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apiVersion: extensions/v1beta1
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kind: Job
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metadata:
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name: pi
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spec:
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selector:
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matchLabels:
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app: pi
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template:
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metadata:
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name: pi
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labels:
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app: pi
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spec:
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containers:
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- name: pi
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image: perl
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command: ["perl", "-Mbignum=bpi", "-wle", "print bpi(2000)"]
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restartPolicy: Never
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```
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[Download example](job.yaml?raw=true)
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<!-- END MUNGE: EXAMPLE job.yaml -->
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Run the example job by downloading the example file and then running this command:
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```console
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$ kubectl create -f ./job.yaml
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job "pi" created
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```
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Check on the status of the job using this command:
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```console
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$ kubectl describe jobs/pi
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Name: pi
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Namespace: default
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Image(s): perl
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Selector: app in (pi)
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Parallelism: 1
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Completions: 1
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Start Time: Mon, 11 Jan 2016 15:35:52 -0800
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Labels: app=pi
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Pods Statuses: 0 Running / 1 Succeeded / 0 Failed
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No volumes.
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Events:
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FirstSeen LastSeen Count From SubobjectPath Type Reason Message
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--------- -------- ----- ---- ------------- -------- ------ -------
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1m 1m 1 {job-controller } Normal SuccessfulCreate Created pod: pi-dtn4q
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```
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To view completed pods of a job, use `kubectl get pods --show-all`. The `--show-all` will show completed pods too.
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To list all the pods that belong to job in a machine readable form, you can use a command like this:
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```console
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$ pods=$(kubectl get pods --selector=app=pi --output=jsonpath={.items..metadata.name})
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echo $pods
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pi-aiw0a
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```
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Here, the selector is the same as the selector for the job. The `--output=jsonpath` option specifies an expression
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that just gets the name from each pod in the returned list.
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View the standard output of one of the pods:
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```console
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$ kubectl logs $pods
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3.1415926535897932384626433832795028841971693993751058209749445923078164062862089986280348253421170679821480865132823066470938446095505822317253594081284811174502841027019385211055596446229489549303819644288109756659334461284756482337867831652712019091456485669234603486104543266482133936072602491412737245870066063155881748815209209628292540917153643678925903600113305305488204665213841469519415116094330572703657595919530921861173819326117931051185480744623799627495673518857527248912279381830119491298336733624406566430860213949463952247371907021798609437027705392171762931767523846748184676694051320005681271452635608277857713427577896091736371787214684409012249534301465495853710507922796892589235420199561121290219608640344181598136297747713099605187072113499999983729780499510597317328160963185950244594553469083026425223082533446850352619311881710100031378387528865875332083814206171776691473035982534904287554687311595628638823537875937519577818577805321712268066130019278766111959092164201989380952572010654858632788659361533818279682303019520353018529689957736225994138912497217752834791315155748572424541506959508295331168617278558890750983817546374649393192550604009277016711390098488240128583616035637076601047101819429555961989467678374494482553797747268471040475346462080466842590694912933136770289891521047521620569660240580381501935112533824300355876402474964732639141992726042699227967823547816360093417216412199245863150302861829745557067498385054945885869269956909272107975093029553211653449872027559602364806654991198818347977535663698074265425278625518184175746728909777727938000816470600161452491921732172147723501414419735685481613611573525521334757418494684385233239073941433345477624168625189835694855620992192221842725502542568876717904946016534668049886272327917860857843838279679766814541009538837863609506800642251252051173929848960841284886269456042419652850222106611863067442786220391949450471237137869609563643719172874677646575739624138908658326459958133904780275901
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```
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## Writing a Job Spec
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As with all other Kubernetes config, a Job needs `apiVersion`, `kind`, and `metadata` fields. For
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general information about working with config files, see [deploying applications](deploying-applications.md),
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[configuring containers](configuring-containers.md), and [working with resources](working-with-resources.md) documents.
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A Job also needs a [`.spec` section](../devel/api-conventions.md#spec-and-status).
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### Pod Template
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The `.spec.template` is the only required field of the `.spec`.
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The `.spec.template` is a [pod template](replication-controller.md#pod-template). It has exactly
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the same schema as a [pod](pods.md), except it is nested and does not have an `apiVersion` or
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`kind`.
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In addition to required fields for a Pod, a pod template in a job must specify appropriate
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labels (see [pod selector](#pod-selector) and an appropriate restart policy.
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Only a [`RestartPolicy`](pod-states.md) equal to `Never` or `OnFailure` are allowed.
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### Pod Selector
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The `.spec.selector` field is a label query over a set of pods.
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The `spec.selector` is an object consisting of two fields:
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* `matchLabels` - works the same as the `.spec.selector` of a [ReplicationController](replication-controller.md)
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* `matchExpressions` - allows to build more sophisticated selectors by specifying key,
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list of values and an operator that relates the key and values.
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When the two are specified the result is ANDed.
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If `.spec.selector` is unspecified, `.spec.selector.matchLabels` will be defaulted to
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`.spec.template.metadata.labels`.
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Also you should not normally create any pods whose labels match this selector, either directly,
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via another Job, or via another controller such as ReplicationController. Otherwise, the Job will
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think that those pods were created by it. Kubernetes will not stop you from doing this.
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### Parallel Jobs
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There are three main types of jobs:
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1. Non-parallel Jobs
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- normally only one pod is started, unless the pod fails.
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- job is complete as soon as Pod terminates successfully.
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1. Parallel Jobs with a *fixed completion count*:
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- specify a non-zero positive value for `.spec.completions`
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- the job is complete when there is one successful pod for each value in the range 1 to `.spec.completions`.
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- **not implemented yet:** each pod passed a different index in the range 1 to `.spec.completions`.
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1. Parallel Jobs with a *work queue*:
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- do not specify `.spec.completions`
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- the pods must coordinate with themselves or an external service to determine what each should work on
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- each pod is independently capable of determining whether or not all its peers are done, thus the entire Job is done.
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- when _any_ pod terminates with success, no new pods are created.
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- once at least one pod has terminated with success and all pods are terminated, then the job is completed with success.
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- once any pod has exited with success, no other pod should still be doing any work or writing any output. They should all be
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in the process of exiting.
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For a Non-parallel job, you can leave both `.spec.completions` and `.spec.parallelism` unset. When both are
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unset, both are defaulted to 1.
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For a Fixed Completion Count job, you should set `.spec.completions` to the number of completions needed.
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You can set `.spec.parallelism`, or leave it unset and it will default to 1.
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For a Work Queue Job, you must leave `.spec.completions` unset, and set `.spec.parallelism` to
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a non-negative integer.
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For more information about how to make use of the different types of job, see the [job patterns](#job-patterns) section.
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#### Controlling Parallelism
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The requested parallelism (`.spec.parallelism`) can be set to any non-negative value.
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If it is unspecified, it defaults to 1.
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If it is specified as 0, then the Job is effectively paused until it is increased.
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A job can be scaled up using the `kubectl scale` command. For example, the following
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command sets `.spec.parallelism` of a job called `myjob` to 10:
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```console
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$ kubectl scale --replicas=$N jobs/myjob
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job "myjob" scaled
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```
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You can also use the `scale` subresource of the Job resource.
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Actual parallelism (number of pods running at any instant) may be more or less than requested
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parallelism, for a variety or reasons:
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- For Fixed Completion Count jobs, the actual number of pods running in parallel will not exceed the number of
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remaining completions. Higher values of `.spec.parallelism` are effectively ignored.
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- For work queue jobs, no new pods are started after any pod has succeeded -- remaining pods are allowed to complete, however.
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- If the controller has not had time to react.
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- If the controller failed to create pods for any reason (lack of ResourceQuota, lack of permission, etc),
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then there may be fewer pods than requested.
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- The controller may throttle new pod creation due to excessive previous pod failures in the same Job.
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- When a pod is gracefully shutdown, it make take time to stop.
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## Handling Pod and Container Failures
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A Container in a Pod may fail for a number of reasons, such as because the process in it exited with
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a non-zero exit code, or the Container was killed for exceeding a memory limit, etc. If this
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happens, and the `.spec.template.containers[].restartPolicy = "OnFailure"`, then the Pod stays
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on the node, but the Container is re-run. Therefore, your program needs to handle the the case when it is
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restarted locally, or else specify `.spec.template.containers[].restartPolicy = "Never"`.
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See [pods-states](pod-states.md) for more information on `restartPolicy`.
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An entire Pod can also fail, for a number of reasons, such as when the pod is kicked off the node
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(node is upgraded, rebooted, deleted, etc.), or if a container of the Pod fails and the
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`.spec.template.containers[].restartPolicy = "Never"`. When a Pod fails, then the Job controller
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starts a new Pod. Therefore, your program needs to handle the case when it is restarted in a new
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pod. In particular, it needs to handle temporary files, locks, incomplete output and the like
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caused by previous runs.
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Note that even if you specify `.spec.parallelism = 1` and `.spec.completions = 1` and
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`.spec.template.containers[].restartPolicy = "Never"`, the same program may
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sometimes be started twice.
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If you do specify `.spec.parallelism` and `.spec.completions` both greater than 1, then there may be
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multiple pods running at once. Therefore, your pods must also be tolerant of concurrency.
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## Job Patterns
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The Job object can be used to support reliable parallel execution of Pods. The Job object is not
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designed to support closely-communicating parallel processes, as commonly found in scientific
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computing. It does support parallel processing of a set of independent but related *work items*.
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These might be emails to be sent, frames to be rendered, files to be transcoded, ranges of keys in a
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NoSQL database to scan, and so on.
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In a complex system, there may be multiple different sets of work items. Here we are just
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considering one set of work items that the user wants to manage together — a *batch job*.
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There are several different patterns for parallel computation, each with strengths and weaknesses.
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The tradeoffs are:
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- One Job object for each work item, vs a single Job object for all work items. The latter is
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better for large numbers of work items. The former creates some overhead for the user and for the
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system to manage large numbers of Job objects. Also, with the latter, the resource usage of the job
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(number of concurrently running pods) can be easily adjusted using the `kubectl scale` command.
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- Number of pods created equals number of work items, vs each pod can process multiple work items.
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The former typically requires less modification to existing code and containers. The latter
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is better for large numbers of work items, for similar reasons to the previous bullet.
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- Several approaches use a work queue. This requires running a queue service,
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and modifications to the existing program or container to make it use the work queue.
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Other approaches are easier to adapt to an existing containerised application.
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The tradeoffs are summarized here, with columns 2 to 4 corresponding to the above tradeoffs.
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The pattern names are also links to examples and more detailed description.
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| Pattern | Single Job object | Fewer pods than work items? | Use app unmodified? | Works in Kube 1.1? |
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| -------------------------------------------------------------------------- |:-----------------:|:---------------------------:|:-------------------:|:-------------------:|
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| [Job Template Expansion](../../examples/job/expansions/README.md) | | | ✓ | ✓ |
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| [Queue with Pod Per Work Item](../../examples/job/work-queue-1/README.md) | ✓ | | sometimes | ✓ |
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| [Queue with Variable Pod Count](../../examples/job/work-queue-2/README.md) | | ✓ | ✓ | | ✓ |
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| Single Job with Static Work Assignment | ✓ | | ✓ | |
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When you specify completions with `.spec.completions`, each Pod created by the Job controller
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has an identical [`spec`](../devel/api-conventions.md#spec-and-status). This means that
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all pods will have the same command line and the same
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image, the same volumes, and (almost) the same environment variables. These patterns
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are different ways to arrange for pods to work on different things.
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This table shows the required settings for `.spec.parallelism` and `.spec.completions` for each of the patterns.
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Here, `W` is the number of work items.
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| Pattern | `.spec.completions` | `.spec.parallelism` |
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| -------------------------------------------------------------------------- |:-------------------:|:--------------------:|
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| [Job Template Expansion](../../examples/job/expansions/README.md) | 1 | should be 1 |
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| [Queue with Pod Per Work Item](../../examples/job/work-queue-1/README.md) | W | any |
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| [Queue with Variable Pod Count](../../examples/job/work-queue-2/README.md) | 1 | any |
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| Single Job with Static Work Assignment | W | any |
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## Alternatives
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### Bare Pods
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When the node that a pod is running on reboots or fails, the pod is terminated
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and will not be restarted. However, a Job will create new pods to replace terminated ones.
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For this reason, we recommend that you use a job rather than a bare pod, even if your application
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requires only a single pod.
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### Replication Controller
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Jobs are complementary to [Replication Controllers](replication-controller.md).
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A Replication Controller manages pods which are not expected to terminate (e.g. web servers), and a Job
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manages pods that are expected to terminate (e.g. batch jobs).
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As discussed in [life of a pod](pod-states.md), `Job` is *only* appropriate for pods with
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`RestartPolicy` equal to `OnFailure` or `Never`. (Note: If `RestartPolicy` is not set, the default
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value is `Always`.)
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### Single Job starts Controller Pod
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Another pattern is for a single Job to create a pod which then creates other pods, acting as a sort
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of custom controller for those pods. This allows the most flexibility, but may be somewhat
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complicated to get started with and offers less integration with Kubernetes.
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One example of this pattern would be a Job which starts a Pod which runs a script that in turn
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starts a Spark master controller (see [spark example](../../examples/spark/README.md)), runs a spark
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driver, and then cleans up.
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An advantage of this approach is that the overall process gets the completion guarantee of a Job
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object, but complete control over what pods are created and how work is assigned to them.
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## Caveats
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Job objects are in the [`extensions` API Group](../api.md#api-groups).
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Job objects have [API version `v1beta1`](../api.md#api-versioning). Beta objects may
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undergo changes to their schema and/or semantics in future software releases, but
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similar functionality will be supported.
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## Future work
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Support for creating Jobs at specified times/dates (i.e. cron) is expected in the next minor
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release.
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<!-- BEGIN MUNGE: GENERATED_ANALYTICS -->
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[]()
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<!-- END MUNGE: GENERATED_ANALYTICS -->
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