putjob

package
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 Go to latest Published: May 10, 2024 License: Apache-2.0 Imports: 12 Imported by: 0

Documentation

Overview

Instantiates an anomaly detection job.

Index

Constants

This section is empty.

Variables

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var ErrBuildPath = errors.New("cannot build path, check for missing path parameters")

ErrBuildPath is returned in case of missing parameters within the build of the request.

Functions

This section is empty.

Types

type NewPutJob 

type NewPutJob func(jobid string) *PutJob

NewPutJob type alias for index.

func NewPutJobFunc 

func NewPutJobFunc(tp elastictransport.Interface) NewPutJob

NewPutJobFunc returns a new instance of PutJob with the provided transport. Used in the index of the library this allows to retrieve every apis in once place.

type PutJob 

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

func New 

func New(tp elastictransport.Interface) *PutJob

Instantiates an anomaly detection job.

https://www.elastic.co/guide/en/elasticsearch/reference/current/ml-put-job.html

func (*PutJob) AllowLazyOpen 

func (r *PutJob) AllowLazyOpen(allowlazyopen bool) *PutJob

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. API name: allow_lazy_open

func (*PutJob) AnalysisConfig 

func (r *PutJob) AnalysisConfig(analysisconfig *types.AnalysisConfig) *PutJob

AnalysisConfig Specifies how to analyze the data. After you create a job, you cannot change the analysis configuration; all the properties are informational. API name: analysis_config

func (*PutJob) AnalysisLimits 

func (r *PutJob) AnalysisLimits(analysislimits *types.AnalysisLimits) *PutJob

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. API name: analysis_limits

func (*PutJob) BackgroundPersistInterval 

func (r *PutJob) BackgroundPersistInterval(duration types.Duration) *PutJob

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. API name: background_persist_interval

func (*PutJob) CustomSettings 

func (r *PutJob) CustomSettings(customsettings json.RawMessage) *PutJob

CustomSettings Advanced configuration option. Contains custom meta data about the job. API name: custom_settings

func (*PutJob) DailyModelSnapshotRetentionAfterDays 

func (r *PutJob) DailyModelSnapshotRetentionAfterDays(dailymodelsnapshotretentionafterdays int64) *PutJob

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`. API name: daily_model_snapshot_retention_after_days

func (*PutJob) DataDescription 

func (r *PutJob) DataDescription(datadescription *types.DataDescription) *PutJob

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. API name: data_description

func (*PutJob) DatafeedConfig 

func (r *PutJob) DatafeedConfig(datafeedconfig *types.DatafeedConfig) *PutJob

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. API name: datafeed_config

func (*PutJob) Description 

func (r *PutJob) Description(description string) *PutJob

Description A description of the job. API name: description

func (PutJob) Do 

func (r PutJob) Do(providedCtx context.Context) (*Response, error)

Do runs the request through the transport, handle the response and returns a putjob.Response

func (*PutJob) Groups 

func (r *PutJob) Groups(groups ...string) *PutJob

Groups A list of job groups. A job can belong to no groups or many. API name: groups

func (*PutJob) Header 

func (r *PutJob) Header(key, value string) *PutJob

Header set a key, value pair in the PutJob headers map.

func (*PutJob) HttpRequest 

func (r *PutJob) HttpRequest(ctx context.Context) (*http.Request, error)

HttpRequest returns the http.Request object built from the given parameters.

func (*PutJob) ModelPlotConfig 

func (r *PutJob) ModelPlotConfig(modelplotconfig *types.ModelPlotConfig) *PutJob

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. API name: model_plot_config

func (*PutJob) ModelSnapshotRetentionDays 

func (r *PutJob) ModelSnapshotRetentionDays(modelsnapshotretentiondays int64) *PutJob

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. API name: model_snapshot_retention_days

func (PutJob) Perform 

func (r PutJob) Perform(providedCtx context.Context) (*http.Response, error)

Perform runs the http.Request through the provided transport and returns an http.Response.

func (*PutJob) Raw 

func (r *PutJob) Raw(raw io.Reader) *PutJob

Raw takes a json payload as input which is then passed to the http.Request If specified Raw takes precedence on Request method.

func (*PutJob) RenormalizationWindowDays 

func (r *PutJob) RenormalizationWindowDays(renormalizationwindowdays int64) *PutJob

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. API name: renormalization_window_days

func (*PutJob) Request 

func (r *PutJob) Request(req *Request) *PutJob

Request allows to set the request property with the appropriate payload.

func (*PutJob) ResultsIndexName 

func (r *PutJob) ResultsIndexName(indexname string) *PutJob

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`. API name: results_index_name

func (*PutJob) ResultsRetentionDays 

func (r *PutJob) ResultsRetentionDays(resultsretentiondays int64) *PutJob

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. API name: results_retention_days

type Request 

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"`
}

Request holds the request body struct for the package putjob

https://github.com/elastic/elasticsearch-specification/blob/5fb8f1ce9c4605abcaa44aa0f17dbfc60497a757/specification/ml/put_job/MlPutJobRequest.ts#L30-L111

func NewRequest 

func NewRequest() *Request

NewRequest returns a Request

func (*Request) FromJSON 

func (r *Request) FromJSON(data string) (*Request, error)

FromJSON allows to load an arbitrary json into the request structure

func (*Request) UnmarshalJSON 

func (s *Request) UnmarshalJSON(data []byte) error

type Response 

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"`
}

Response holds the response body struct for the package putjob

https://github.com/elastic/elasticsearch-specification/blob/5fb8f1ce9c4605abcaa44aa0f17dbfc60497a757/specification/ml/put_job/MlPutJobResponse.ts#L29-L52

func NewResponse 

func NewResponse() *Response

NewResponse returns a Response

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