Splitting off Aurora task from Aurora Job since Update mechanism only needs task.
This commit is contained in:
parent
b0c25e9013
commit
5836ede37b
4 changed files with 312 additions and 178 deletions
222
job.go
222
job.go
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@ -15,16 +15,13 @@
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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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// 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[string]*aurora.Resource
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portCount int
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task *Task
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}
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// Create a AuroraJob object with everything initialized.
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@ -33,45 +30,23 @@ func NewJob() *AuroraJob {
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jobKey := &aurora.JobKey{}
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// Task clientConfig
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taskConfig := &aurora.TaskConfig{
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Job: jobKey,
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MesosFetcherUris: make([]*aurora.MesosFetcherURI, 0),
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Metadata: make([]*aurora.Metadata, 0),
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Constraints: make([]*aurora.Constraint, 0),
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// Container is a Union so one container field must be set. Set Mesos by default.
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Container: NewMesosContainer().Build(),
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}
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task := NewTask()
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task.task.Job = jobKey
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// AuroraJob clientConfig
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jobConfig := &aurora.JobConfiguration{
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Key: jobKey,
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TaskConfig: taskConfig,
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TaskConfig: task.TaskConfig(),
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}
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// Resources
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numCpus := &aurora.Resource{}
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ramMb := &aurora.Resource{}
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diskMb := &aurora.Resource{}
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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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resources := make(map[string]*aurora.Resource)
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resources["cpu"] = numCpus
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resources["ram"] = ramMb
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resources["disk"] = diskMb
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taskConfig.Resources = []*aurora.Resource{numCpus, ramMb, diskMb}
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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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task: task,
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}
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}
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// Set AuroraJob Key environment.
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// Set AuroraJob Key environment. Explicit changes to Task's job key are not needed
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// because they share a pointer to the same JobKey.
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func (j *AuroraJob) Environment(env string) *AuroraJob {
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j.jobConfig.Key.Environment = env
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return j
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@ -94,58 +69,6 @@ func (j *AuroraJob) Name(name string) *AuroraJob {
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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) *AuroraJob {
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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) *AuroraJob {
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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) *AuroraJob {
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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) *AuroraJob {
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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) *AuroraJob {
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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) Tier(tier string) *AuroraJob {
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*j.jobConfig.TaskConfig.Tier = tier
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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) *AuroraJob {
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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) *AuroraJob {
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j.jobConfig.InstanceCount = instCount
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@ -167,12 +90,6 @@ 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) *AuroraJob {
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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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@ -183,107 +100,90 @@ func (j *AuroraJob) JobConfig() *aurora.JobConfiguration {
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return j.jobConfig
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}
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/*
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Task specific API, see task.go for further documentation.
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These functions are provided for the convenience of chaining API calls.
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*/
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func (j *AuroraJob) ExecutorName(name string) *AuroraJob {
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j.task.ExecutorName(name)
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return j
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}
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func (j *AuroraJob) ExecutorData(data string) *AuroraJob {
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j.task.ExecutorData(data)
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return j
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}
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func (j *AuroraJob) CPU(cpus float64) *AuroraJob {
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j.task.CPU(cpus)
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return j
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}
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func (j *AuroraJob) RAM(ram int64) *AuroraJob {
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j.task.RAM(ram)
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return j
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}
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func (j *AuroraJob) Disk(disk int64) *AuroraJob {
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j.task.Disk(disk)
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return j
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}
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func (j *AuroraJob) Tier(tier string) *AuroraJob {
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j.task.Tier(tier)
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return j
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}
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func (j *AuroraJob) MaxFailure(maxFail int32) *AuroraJob {
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j.task.MaxFailure(maxFail)
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return j
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}
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func (j *AuroraJob) IsService(isService bool) *AuroraJob {
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j.task.IsService(isService)
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return j
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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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return j.task.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) *AuroraJob {
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for _, value := range values {
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j.jobConfig.TaskConfig.MesosFetcherUris = append(
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j.jobConfig.TaskConfig.MesosFetcherUris,
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&aurora.MesosFetcherURI{Value: value, Extract: &extract, Cache: &cache})
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}
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j.task.AddURIs(extract, cache, values...)
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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) *AuroraJob {
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j.jobConfig.TaskConfig.Metadata = append(j.jobConfig.TaskConfig.Metadata, &aurora.Metadata{Key: key, Value: value})
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j.task.AddLabel(key, 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) *AuroraJob {
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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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j.task.AddNamedPorts(names...)
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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) *AuroraJob {
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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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j.task.AddPorts(num)
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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) *AuroraJob {
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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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j.task.AddValueConstraint(name, negated, values...)
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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) *AuroraJob {
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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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j.task.AddLimitConstraint(name, limit)
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return j
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}
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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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func (j *AuroraJob) AddDedicatedConstraint(role, name string) *AuroraJob {
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j.AddValueConstraint("dedicated", false, role+"/"+name)
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j.task.AddDedicatedConstraint(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) *AuroraJob {
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j.jobConfig.TaskConfig.Container = container.Build()
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j.task.Container(container)
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return j
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}
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