* Adding parameter for Aurora so that we're able to run SLA aware updates with less than 20 instances. Lowered time it takes to run test by reducing watch time per instance as well. * Reducing the number of instances and time for SLA aware instances in docker-compose set up. * Adding another Mesos agent to the docker-compose setup. * Huge thanks to @zircote for this contribution.
343 lines
9.8 KiB
Go
343 lines
9.8 KiB
Go
/**
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package realis
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import (
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"strconv"
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"github.com/paypal/gorealis/gen-go/apache/aurora"
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)
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type Job interface {
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// Set Job Key environment.
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Environment(env string) Job
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Role(role string) Job
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Name(name string) Job
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CPU(cpus float64) Job
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CronSchedule(cron string) Job
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CronCollisionPolicy(policy aurora.CronCollisionPolicy) Job
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Disk(disk int64) Job
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RAM(ram int64) Job
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ExecutorName(name string) Job
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ExecutorData(data string) Job
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AddPorts(num int) Job
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AddLabel(key string, value string) Job
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AddNamedPorts(names ...string) Job
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AddLimitConstraint(name string, limit int32) Job
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AddValueConstraint(name string, negated bool, values ...string) Job
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// From Aurora Docs:
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// dedicated attribute. Aurora treats this specially, and only allows matching jobs
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// to run on these machines, and will only schedule matching jobs on these machines.
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// When a job is created, the scheduler requires that the $role component matches
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// the role field in the job configuration, and will reject the job creation otherwise.
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// A wildcard (*) may be used for the role portion of the dedicated attribute, which
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// will allow any owner to elect for a job to run on the host(s)
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AddDedicatedConstraint(role, name string) Job
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AddURIs(extract bool, cache bool, values ...string) Job
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JobKey() *aurora.JobKey
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JobConfig() *aurora.JobConfiguration
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TaskConfig() *aurora.TaskConfig
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IsService(isService bool) Job
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InstanceCount(instCount int32) Job
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GetInstanceCount() int32
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MaxFailure(maxFail int32) Job
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Container(container Container) Job
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PartitionPolicy(policy *aurora.PartitionPolicy) Job
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Tier(tier string) Job
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SlaPolicy(policy *aurora.SlaPolicy) Job
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}
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type ResourceType int
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const (
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CPU ResourceType = iota
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RAM
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DISK
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GPU
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)
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// Structure to collect all information pertaining to an Aurora job.
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type AuroraJob struct {
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jobConfig *aurora.JobConfiguration
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resources map[ResourceType]*aurora.Resource
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portCount int
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}
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// Create a Job object with everything initialized.
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func NewJob() Job {
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jobConfig := aurora.NewJobConfiguration()
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taskConfig := aurora.NewTaskConfig()
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jobKey := aurora.NewJobKey()
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// Job Config
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jobConfig.Key = jobKey
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jobConfig.TaskConfig = taskConfig
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// Task Config
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taskConfig.Job = jobKey
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taskConfig.Container = aurora.NewContainer()
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taskConfig.Container.Mesos = aurora.NewMesosContainer()
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// Resources
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numCpus := aurora.NewResource()
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ramMb := aurora.NewResource()
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diskMb := aurora.NewResource()
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resources := map[ResourceType]*aurora.Resource{CPU: numCpus, RAM: ramMb, DISK: diskMb}
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taskConfig.Resources = []*aurora.Resource{numCpus, ramMb, diskMb}
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numCpus.NumCpus = new(float64)
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ramMb.RamMb = new(int64)
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diskMb.DiskMb = new(int64)
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return &AuroraJob{
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jobConfig: jobConfig,
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resources: resources,
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portCount: 0,
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}
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}
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// Set Job Key environment.
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func (j *AuroraJob) Environment(env string) Job {
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j.jobConfig.Key.Environment = env
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return j
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}
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// Set Job Key Role.
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func (j *AuroraJob) Role(role string) Job {
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j.jobConfig.Key.Role = role
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//Will be deprecated
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identity := &aurora.Identity{User: role}
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j.jobConfig.Owner = identity
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j.jobConfig.TaskConfig.Owner = identity
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return j
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}
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// Set Job Key Name.
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func (j *AuroraJob) Name(name string) Job {
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j.jobConfig.Key.Name = name
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return j
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}
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// Set name of the executor that will the task will be configured to.
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func (j *AuroraJob) ExecutorName(name string) Job {
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if j.jobConfig.TaskConfig.ExecutorConfig == nil {
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j.jobConfig.TaskConfig.ExecutorConfig = aurora.NewExecutorConfig()
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}
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j.jobConfig.TaskConfig.ExecutorConfig.Name = name
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return j
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}
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// Will be included as part of entire task inside the scheduler that will be serialized.
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func (j *AuroraJob) ExecutorData(data string) Job {
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if j.jobConfig.TaskConfig.ExecutorConfig == nil {
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j.jobConfig.TaskConfig.ExecutorConfig = aurora.NewExecutorConfig()
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}
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j.jobConfig.TaskConfig.ExecutorConfig.Data = data
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return j
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}
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func (j *AuroraJob) CPU(cpus float64) Job {
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*j.resources[CPU].NumCpus = cpus
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return j
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}
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func (j *AuroraJob) RAM(ram int64) Job {
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*j.resources[RAM].RamMb = ram
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return j
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}
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func (j *AuroraJob) Disk(disk int64) Job {
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*j.resources[DISK].DiskMb = disk
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return j
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}
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func (j *AuroraJob) GPU(gpu int64) Job {
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// GPU resource must be set explicitly since the scheduler by default
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// rejects jobs with GPU resources attached to it.
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if _, ok := j.resources[GPU]; !ok {
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j.resources[GPU] = &aurora.Resource{}
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j.JobConfig().GetTaskConfig().Resources = append(j.JobConfig().GetTaskConfig().Resources, j.resources[GPU])
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}
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j.resources[GPU].NumGpus = &gpu
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return j
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}
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// How many failures to tolerate before giving up.
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func (j *AuroraJob) MaxFailure(maxFail int32) Job {
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j.jobConfig.TaskConfig.MaxTaskFailures = maxFail
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return j
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}
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// How many instances of the job to run
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func (j *AuroraJob) InstanceCount(instCount int32) Job {
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j.jobConfig.InstanceCount = instCount
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return j
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}
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func (j *AuroraJob) CronSchedule(cron string) Job {
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j.jobConfig.CronSchedule = &cron
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return j
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}
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func (j *AuroraJob) CronCollisionPolicy(policy aurora.CronCollisionPolicy) Job {
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j.jobConfig.CronCollisionPolicy = policy
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return j
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}
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// How many instances of the job to run
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func (j *AuroraJob) GetInstanceCount() int32 {
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return j.jobConfig.InstanceCount
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}
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// Restart the job's tasks if they fail
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func (j *AuroraJob) IsService(isService bool) Job {
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j.jobConfig.TaskConfig.IsService = isService
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return j
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}
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// Get the current job configurations key to use for some realis calls.
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func (j *AuroraJob) JobKey() *aurora.JobKey {
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return j.jobConfig.Key
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}
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// Get the current job configurations key to use for some realis calls.
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func (j *AuroraJob) JobConfig() *aurora.JobConfiguration {
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return j.jobConfig
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}
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func (j *AuroraJob) TaskConfig() *aurora.TaskConfig {
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return j.jobConfig.TaskConfig
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}
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// Add a list of URIs with the same extract and cache configuration. Scheduler must have
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// --enable_mesos_fetcher flag enabled. Currently there is no duplicate detection.
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func (j *AuroraJob) AddURIs(extract bool, cache bool, values ...string) Job {
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for _, value := range values {
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j.jobConfig.TaskConfig.MesosFetcherUris = append(j.jobConfig.TaskConfig.MesosFetcherUris,
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&aurora.MesosFetcherURI{Value: value, Extract: &extract, Cache: &cache})
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}
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return j
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}
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// Adds a Mesos label to the job. Note that Aurora will add the
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// prefix "org.apache.aurora.metadata." to the beginning of each key.
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func (j *AuroraJob) AddLabel(key string, value string) Job {
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j.jobConfig.TaskConfig.Metadata = append(j.jobConfig.TaskConfig.Metadata, &aurora.Metadata{Key: key, Value: value})
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return j
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}
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// Add a named port to the job configuration These are random ports as it's
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// not currently possible to request specific ports using Aurora.
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func (j *AuroraJob) AddNamedPorts(names ...string) Job {
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j.portCount += len(names)
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for _, name := range names {
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j.jobConfig.TaskConfig.Resources = append(j.jobConfig.TaskConfig.Resources, &aurora.Resource{NamedPort: &name})
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}
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return j
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}
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// Adds a request for a number of ports to the job configuration. The names chosen for these ports
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// will be org.apache.aurora.port.X, where X is the current port count for the job configuration
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// starting at 0. These are random ports as it's not currently possible to request
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// specific ports using Aurora.
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func (j *AuroraJob) AddPorts(num int) Job {
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start := j.portCount
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j.portCount += num
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for i := start; i < j.portCount; i++ {
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portName := "org.apache.aurora.port." + strconv.Itoa(i)
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j.jobConfig.TaskConfig.Resources = append(j.jobConfig.TaskConfig.Resources, &aurora.Resource{NamedPort: &portName})
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}
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return j
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}
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// From Aurora Docs:
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// Add a Value constraint
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// name - Mesos slave attribute that the constraint is matched against.
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// If negated = true , treat this as a 'not' - to avoid specific values.
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// Values - list of values we look for in attribute name
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func (j *AuroraJob) AddValueConstraint(name string, negated bool, values ...string) Job {
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j.jobConfig.TaskConfig.Constraints = append(j.jobConfig.TaskConfig.Constraints,
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&aurora.Constraint{
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Name: name,
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Constraint: &aurora.TaskConstraint{
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Value: &aurora.ValueConstraint{
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Negated: negated,
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Values: values,
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},
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Limit: nil,
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},
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})
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return j
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}
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// From Aurora Docs:
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// A constraint that specifies the maximum number of active tasks on a host with
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// a matching attribute that may be scheduled simultaneously.
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func (j *AuroraJob) AddLimitConstraint(name string, limit int32) Job {
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j.jobConfig.TaskConfig.Constraints = append(j.jobConfig.TaskConfig.Constraints,
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&aurora.Constraint{
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Name: name,
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Constraint: &aurora.TaskConstraint{
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Value: nil,
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Limit: &aurora.LimitConstraint{Limit: limit},
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},
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})
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return j
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}
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func (j *AuroraJob) AddDedicatedConstraint(role, name string) Job {
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j.AddValueConstraint("dedicated", false, role+"/"+name)
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return j
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}
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// Set a container to run for the job configuration to run.
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func (j *AuroraJob) Container(container Container) Job {
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j.jobConfig.TaskConfig.Container = container.Build()
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return j
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}
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// Set a partition policy for the job configuration to implement.
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func (j *AuroraJob) PartitionPolicy(policy *aurora.PartitionPolicy) Job {
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j.jobConfig.TaskConfig.PartitionPolicy = policy
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return j
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}
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// Set the Tier for the Job.
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func (j *AuroraJob) Tier(tier string) Job {
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j.jobConfig.TaskConfig.Tier = &tier
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return j
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}
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// Set an SlaPolicy for the Job.
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func (j *AuroraJob) SlaPolicy(policy *aurora.SlaPolicy) Job {
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j.jobConfig.TaskConfig.SlaPolicy = policy
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return j
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}
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