putjob

type NewPutJob func(jobid string) *PutJob

type PutJob struct {
	// contains filtered or unexported fields
}

type Request struct {

	// AllowLazyOpen Advanced configuration option. Specifies whether this job can open when there
	// is insufficient machine learning node capacity for it to be immediately
	// assigned to a node. By default, if a machine learning node with capacity to
	// run the job cannot immediately be found, the open anomaly detection jobs API
	// returns an error. However, this is also subject to the cluster-wide
	// `xpack.ml.max_lazy_ml_nodes` setting. If this option is set to true, the open
	// anomaly detection jobs API does not return an error and the job waits in the
	// opening state until sufficient machine learning node capacity is available.
	AllowLazyOpen *bool `json:"allow_lazy_open,omitempty"`
	// AnalysisConfig Specifies how to analyze the data. After you create a job, you cannot change
	// the analysis configuration; all the properties are informational.
	AnalysisConfig types.AnalysisConfig `json:"analysis_config"`
	// AnalysisLimits Limits can be applied for the resources required to hold the mathematical
	// models in memory. These limits are approximate and can be set per job. They
	// do not control the memory used by other processes, for example the
	// Elasticsearch Java processes.
	AnalysisLimits *types.AnalysisLimits `json:"analysis_limits,omitempty"`
	// BackgroundPersistInterval Advanced configuration option. The time between each periodic persistence of
	// the model. The default value is a randomized value between 3 to 4 hours,
	// which avoids all jobs persisting at exactly the same time. The smallest
	// allowed value is 1 hour. For very large models (several GB), persistence
	// could take 10-20 minutes, so do not set the `background_persist_interval`
	// value too low.
	BackgroundPersistInterval types.Duration `json:"background_persist_interval,omitempty"`
	// CustomSettings Advanced configuration option. Contains custom meta data about the job.
	CustomSettings json.RawMessage `json:"custom_settings,omitempty"`
	// DailyModelSnapshotRetentionAfterDays Advanced configuration option, which affects the automatic removal of old
	// model snapshots for this job. It specifies a period of time (in days) after
	// which only the first snapshot per day is retained. This period is relative to
	// the timestamp of the most recent snapshot for this job. Valid values range
	// from 0 to `model_snapshot_retention_days`.
	DailyModelSnapshotRetentionAfterDays *int64 `json:"daily_model_snapshot_retention_after_days,omitempty"`
	// DataDescription Defines the format of the input data when you send data to the job by using
	// the post data API. Note that when configure a datafeed, these properties are
	// automatically set. When data is received via the post data API, it is not
	// stored in Elasticsearch. Only the results for anomaly detection are retained.
	DataDescription types.DataDescription `json:"data_description"`
	// DatafeedConfig Defines a datafeed for the anomaly detection job. If Elasticsearch security
	// features are enabled, your datafeed remembers which roles the user who
	// created it had at the time of creation and runs the query using those same
	// roles. If you provide secondary authorization headers, those credentials are
	// used instead.
	DatafeedConfig *types.DatafeedConfig `json:"datafeed_config,omitempty"`
	// Description A description of the job.
	Description *string `json:"description,omitempty"`
	// Groups A list of job groups. A job can belong to no groups or many.
	Groups []string `json:"groups,omitempty"`
	// ModelPlotConfig This advanced configuration option stores model information along with the
	// results. It provides a more detailed view into anomaly detection. If you
	// enable model plot it can add considerable overhead to the performance of the
	// system; it is not feasible for jobs with many entities. Model plot provides a
	// simplified and indicative view of the model and its bounds. It does not
	// display complex features such as multivariate correlations or multimodal
	// data. As such, anomalies may occasionally be reported which cannot be seen in
	// the model plot. Model plot config can be configured when the job is created
	// or updated later. It must be disabled if performance issues are experienced.
	ModelPlotConfig *types.ModelPlotConfig `json:"model_plot_config,omitempty"`
	// ModelSnapshotRetentionDays Advanced configuration option, which affects the automatic removal of old
	// model snapshots for this job. It specifies the maximum period of time (in
	// days) that snapshots are retained. This period is relative to the timestamp
	// of the most recent snapshot for this job. By default, snapshots ten days
	// older than the newest snapshot are deleted.
	ModelSnapshotRetentionDays *int64 `json:"model_snapshot_retention_days,omitempty"`
	// RenormalizationWindowDays Advanced configuration option. The period over which adjustments to the score
	// are applied, as new data is seen. The default value is the longer of 30 days
	// or 100 bucket spans.
	RenormalizationWindowDays *int64 `json:"renormalization_window_days,omitempty"`
	// ResultsIndexName A text string that affects the name of the machine learning results index. By
	// default, the job generates an index named `.ml-anomalies-shared`.
	ResultsIndexName *string `json:"results_index_name,omitempty"`
	// ResultsRetentionDays Advanced configuration option. The period of time (in days) that results are
	// retained. Age is calculated relative to the timestamp of the latest bucket
	// result. If this property has a non-null value, once per day at 00:30 (server
	// time), results that are the specified number of days older than the latest
	// bucket result are deleted from Elasticsearch. The default value is null,
	// which means all results are retained. Annotations generated by the system
	// also count as results for retention purposes; they are deleted after the same
	// number of days as results. Annotations added by users are retained forever.
	ResultsRetentionDays *int64 `json:"results_retention_days,omitempty"`
}

type Response struct {
	AllowLazyOpen                        bool                     `json:"allow_lazy_open"`
	AnalysisConfig                       types.AnalysisConfigRead `json:"analysis_config"`
	AnalysisLimits                       types.AnalysisLimits     `json:"analysis_limits"`
	BackgroundPersistInterval            types.Duration           `json:"background_persist_interval,omitempty"`
	CreateTime                           types.DateTime           `json:"create_time"`
	CustomSettings                       json.RawMessage          `json:"custom_settings,omitempty"`
	DailyModelSnapshotRetentionAfterDays int64                    `json:"daily_model_snapshot_retention_after_days"`
	DataDescription                      types.DataDescription    `json:"data_description"`
	DatafeedConfig                       *types.MLDatafeed        `json:"datafeed_config,omitempty"`
	Description                          *string                  `json:"description,omitempty"`
	Groups                               []string                 `json:"groups,omitempty"`
	JobId                                string                   `json:"job_id"`
	JobType                              string                   `json:"job_type"`
	JobVersion                           string                   `json:"job_version"`
	ModelPlotConfig                      *types.ModelPlotConfig   `json:"model_plot_config,omitempty"`
	ModelSnapshotId                      *string                  `json:"model_snapshot_id,omitempty"`
	ModelSnapshotRetentionDays           int64                    `json:"model_snapshot_retention_days"`
	RenormalizationWindowDays            *int64                   `json:"renormalization_window_days,omitempty"`
	ResultsIndexName                     string                   `json:"results_index_name"`
	ResultsRetentionDays                 *int64                   `json:"results_retention_days,omitempty"`
}