Class PutJobRequest.Builder
- All Implemented Interfaces:
ObjectBuilder<PutJobRequest>
- Enclosing class:
- PutJobRequest
public static class PutJobRequest.Builder extends ObjectBuilderBase implements ObjectBuilder<PutJobRequest>
PutJobRequest
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Constructor Summary
Constructors Constructor Description Builder()
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Method Summary
Modifier and Type Method Description PutJobRequest.Builder
allowLazyOpen(java.lang.Boolean value)
Advanced configuration option.PutJobRequest.Builder
analysisConfig(AnalysisConfig value)
Required - Specifies how to analyze the data.PutJobRequest.Builder
analysisConfig(java.util.function.Function<AnalysisConfig.Builder,ObjectBuilder<AnalysisConfig>> fn)
Required - Specifies how to analyze the data.PutJobRequest.Builder
analysisLimits(AnalysisLimits value)
Limits can be applied for the resources required to hold the mathematical models in memory.PutJobRequest.Builder
analysisLimits(java.util.function.Function<AnalysisLimits.Builder,ObjectBuilder<AnalysisLimits>> fn)
Limits can be applied for the resources required to hold the mathematical models in memory.PutJobRequest.Builder
backgroundPersistInterval(Time value)
Required - Advanced configuration option.PutJobRequest.Builder
backgroundPersistInterval(java.util.function.Function<Time.Builder,ObjectBuilder<Time>> fn)
Required - Advanced configuration option.PutJobRequest
build()
Builds aPutJobRequest
.PutJobRequest.Builder
customSettings(JsonData value)
Advanced configuration option.PutJobRequest.Builder
dailyModelSnapshotRetentionAfterDays(java.lang.Long value)
Advanced configuration option, which affects the automatic removal of old model snapshots for this job.PutJobRequest.Builder
dataDescription(DataDescription value)
Required - Defines the format of the input data when you send data to the job by using the post data API.PutJobRequest.Builder
dataDescription(java.util.function.Function<DataDescription.Builder,ObjectBuilder<DataDescription>> fn)
Required - Defines the format of the input data when you send data to the job by using the post data API.PutJobRequest.Builder
datafeedConfig(DatafeedConfig value)
Defines a datafeed for the anomaly detection job.PutJobRequest.Builder
datafeedConfig(java.util.function.Function<DatafeedConfig.Builder,ObjectBuilder<DatafeedConfig>> fn)
Defines a datafeed for the anomaly detection job.PutJobRequest.Builder
description(java.lang.String value)
A description of the job.PutJobRequest.Builder
groups(java.lang.String value, java.lang.String... values)
A list of job groups.PutJobRequest.Builder
groups(java.util.List<java.lang.String> list)
A list of job groups.PutJobRequest.Builder
jobId(java.lang.String value)
Required - The identifier for the anomaly detection job.PutJobRequest.Builder
modelPlotConfig(ModelPlotConfig value)
This advanced configuration option stores model information along with the results.PutJobRequest.Builder
modelPlotConfig(java.util.function.Function<ModelPlotConfig.Builder,ObjectBuilder<ModelPlotConfig>> fn)
This advanced configuration option stores model information along with the results.PutJobRequest.Builder
modelSnapshotRetentionDays(java.lang.Long value)
Advanced configuration option, which affects the automatic removal of old model snapshots for this job.PutJobRequest.Builder
renormalizationWindowDays(java.lang.Long value)
Advanced configuration option.PutJobRequest.Builder
resultsIndexName(java.lang.String value)
A text string that affects the name of the machine learning results index.PutJobRequest.Builder
resultsRetentionDays(java.lang.Long value)
Advanced configuration option.Methods inherited from class co.elastic.clients.util.ObjectBuilderBase
_checkSingleUse, _listAdd, _listAddAll, _mapPut, _mapPutAll
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
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Constructor Details
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Builder
public Builder()
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Method Details
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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-widexpack.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
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analysisConfig
Required - 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
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analysisConfig
public final PutJobRequest.Builder analysisConfig(java.util.function.Function<AnalysisConfig.Builder,ObjectBuilder<AnalysisConfig>> fn)Required - 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
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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
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analysisLimits
public final PutJobRequest.Builder analysisLimits(java.util.function.Function<AnalysisLimits.Builder,ObjectBuilder<AnalysisLimits>> fn)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
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backgroundPersistInterval
Required - 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 thebackground_persist_interval
value too low.API name:
background_persist_interval
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backgroundPersistInterval
public final PutJobRequest.Builder backgroundPersistInterval(java.util.function.Function<Time.Builder,ObjectBuilder<Time>> fn)Required - 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 thebackground_persist_interval
value too low.API name:
background_persist_interval
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customSettings
Advanced configuration option. Contains custom meta data about the job.API name:
custom_settings
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dailyModelSnapshotRetentionAfterDays
public final PutJobRequest.Builder dailyModelSnapshotRetentionAfterDays(@Nullable java.lang.Long value)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 tomodel_snapshot_retention_days
.API name:
daily_model_snapshot_retention_after_days
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dataDescription
Required - 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
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dataDescription
public final PutJobRequest.Builder dataDescription(java.util.function.Function<DataDescription.Builder,ObjectBuilder<DataDescription>> fn)Required - 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
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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
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datafeedConfig
public final PutJobRequest.Builder datafeedConfig(java.util.function.Function<DatafeedConfig.Builder,ObjectBuilder<DatafeedConfig>> fn)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
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description
A description of the job.API name:
description
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groups
A list of job groups. A job can belong to no groups or many.API name:
groups
Adds all elements of
list
togroups
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groups
A list of job groups. A job can belong to no groups or many.API name:
groups
Adds one or more values to
groups
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jobId
Required - The identifier for the anomaly detection job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters.API name:
job_id
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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
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modelPlotConfig
public final PutJobRequest.Builder modelPlotConfig(java.util.function.Function<ModelPlotConfig.Builder,ObjectBuilder<ModelPlotConfig>> fn)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
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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
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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
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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
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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
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build
Builds aPutJobRequest
.- Specified by:
build
in interfaceObjectBuilder<PutJobRequest>
- Throws:
java.lang.NullPointerException
- if some of the required fields are null.
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