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/*
* Licensed to Elasticsearch B.V. under one or more contributor
* license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright
* ownership. Elasticsearch B.V. licenses this file to you under
* the Apache License, Version 2.0 (the "License"); you may
* not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package co.elastic.clients.elasticsearch.ml;
import co.elastic.clients.ApiClient;
import co.elastic.clients.elasticsearch._types.ElasticsearchException;
import co.elastic.clients.elasticsearch._types.ErrorResponse;
import co.elastic.clients.transport.ElasticsearchTransport;
import co.elastic.clients.transport.Endpoint;
import co.elastic.clients.transport.JsonEndpoint;
import co.elastic.clients.transport.Transport;
import co.elastic.clients.transport.TransportOptions;
import co.elastic.clients.transport.endpoints.EndpointWithResponseMapperAttr;
import co.elastic.clients.util.ObjectBuilder;
import java.io.IOException;
import java.lang.reflect.Type;
import java.util.function.Function;
import javax.annotation.Nullable;
//----------------------------------------------------------------
// THIS CODE IS GENERATED. MANUAL EDITS WILL BE LOST.
//----------------------------------------------------------------
//
// This code is generated from the Elasticsearch API specification
// at https://github.com/elastic/elasticsearch-specification
//
// Manual updates to this file will be lost when the code is
// re-generated.
//
// If you find a property that is missing or wrongly typed, please
// open an issue or a PR on the API specification repository.
//
//----------------------------------------------------------------
/**
* Client for the ml namespace.
*/
public class ElasticsearchMlClient extends ApiClient {
public ElasticsearchMlClient(ElasticsearchTransport transport) {
super(transport, null);
}
public ElasticsearchMlClient(ElasticsearchTransport transport, @Nullable TransportOptions transportOptions) {
super(transport, transportOptions);
}
@Override
public ElasticsearchMlClient withTransportOptions(@Nullable TransportOptions transportOptions) {
return new ElasticsearchMlClient(this.transport, transportOptions);
}
// ----- Endpoint: ml.clear_trained_model_deployment_cache
/**
* Clear trained model deployment cache.
*
* Cache will be cleared on all nodes where the trained model is assigned. A
* trained model deployment may have an inference cache enabled. As requests are
* handled by each allocated node, their responses may be cached on that
* individual node. Calling this API clears the caches without restarting the
* deployment.
*
* @see Documentation
* on elastic.co
*/
public ClearTrainedModelDeploymentCacheResponse clearTrainedModelDeploymentCache(
ClearTrainedModelDeploymentCacheRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) ClearTrainedModelDeploymentCacheRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Clear trained model deployment cache.
*
* Cache will be cleared on all nodes where the trained model is assigned. A
* trained model deployment may have an inference cache enabled. As requests are
* handled by each allocated node, their responses may be cached on that
* individual node. Calling this API clears the caches without restarting the
* deployment.
*
* @param fn
* a function that initializes a builder to create the
* {@link ClearTrainedModelDeploymentCacheRequest}
* @see Documentation
* on elastic.co
*/
public final ClearTrainedModelDeploymentCacheResponse clearTrainedModelDeploymentCache(
Function> fn)
throws IOException, ElasticsearchException {
return clearTrainedModelDeploymentCache(
fn.apply(new ClearTrainedModelDeploymentCacheRequest.Builder()).build());
}
// ----- Endpoint: ml.close_job
/**
* Close anomaly detection jobs.
*
* A job can be opened and closed multiple times throughout its lifecycle. A
* closed job cannot receive data or perform analysis operations, but you can
* still explore and navigate results. When you close a job, it runs
* housekeeping tasks such as pruning the model history, flushing buffers,
* calculating final results and persisting the model snapshots. Depending upon
* the size of the job, it could take several minutes to close and the
* equivalent time to re-open. After it is closed, the job has a minimal
* overhead on the cluster except for maintaining its meta data. Therefore it is
* a best practice to close jobs that are no longer required to process data. If
* you close an anomaly detection job whose datafeed is running, the request
* first tries to stop the datafeed. This behavior is equivalent to calling stop
* datafeed API with the same timeout and force parameters as the close job
* request. When a datafeed that has a specified end date stops, it
* automatically closes its associated job.
*
* @see Documentation
* on elastic.co
*/
public CloseJobResponse closeJob(CloseJobRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) CloseJobRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Close anomaly detection jobs.
*
* A job can be opened and closed multiple times throughout its lifecycle. A
* closed job cannot receive data or perform analysis operations, but you can
* still explore and navigate results. When you close a job, it runs
* housekeeping tasks such as pruning the model history, flushing buffers,
* calculating final results and persisting the model snapshots. Depending upon
* the size of the job, it could take several minutes to close and the
* equivalent time to re-open. After it is closed, the job has a minimal
* overhead on the cluster except for maintaining its meta data. Therefore it is
* a best practice to close jobs that are no longer required to process data. If
* you close an anomaly detection job whose datafeed is running, the request
* first tries to stop the datafeed. This behavior is equivalent to calling stop
* datafeed API with the same timeout and force parameters as the close job
* request. When a datafeed that has a specified end date stops, it
* automatically closes its associated job.
*
* @param fn
* a function that initializes a builder to create the
* {@link CloseJobRequest}
* @see Documentation
* on elastic.co
*/
public final CloseJobResponse closeJob(Function> fn)
throws IOException, ElasticsearchException {
return closeJob(fn.apply(new CloseJobRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_calendar
/**
* Delete a calendar.
*
* Remove all scheduled events from a calendar, then delete it.
*
* @see Documentation
* on elastic.co
*/
public DeleteCalendarResponse deleteCalendar(DeleteCalendarRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteCalendarRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete a calendar.
*
* Remove all scheduled events from a calendar, then delete it.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteCalendarRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteCalendarResponse deleteCalendar(
Function> fn)
throws IOException, ElasticsearchException {
return deleteCalendar(fn.apply(new DeleteCalendarRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_calendar_event
/**
* Delete events from a calendar.
*
* @see Documentation
* on elastic.co
*/
public DeleteCalendarEventResponse deleteCalendarEvent(DeleteCalendarEventRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteCalendarEventRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete events from a calendar.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteCalendarEventRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteCalendarEventResponse deleteCalendarEvent(
Function> fn)
throws IOException, ElasticsearchException {
return deleteCalendarEvent(fn.apply(new DeleteCalendarEventRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_calendar_job
/**
* Delete anomaly jobs from a calendar.
*
* @see Documentation
* on elastic.co
*/
public DeleteCalendarJobResponse deleteCalendarJob(DeleteCalendarJobRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteCalendarJobRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete anomaly jobs from a calendar.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteCalendarJobRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteCalendarJobResponse deleteCalendarJob(
Function> fn)
throws IOException, ElasticsearchException {
return deleteCalendarJob(fn.apply(new DeleteCalendarJobRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_data_frame_analytics
/**
* Delete a data frame analytics job.
*
* @see Documentation
* on elastic.co
*/
public DeleteDataFrameAnalyticsResponse deleteDataFrameAnalytics(DeleteDataFrameAnalyticsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteDataFrameAnalyticsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete a data frame analytics job.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteDataFrameAnalyticsRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteDataFrameAnalyticsResponse deleteDataFrameAnalytics(
Function> fn)
throws IOException, ElasticsearchException {
return deleteDataFrameAnalytics(fn.apply(new DeleteDataFrameAnalyticsRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_datafeed
/**
* Delete a datafeed.
*
* @see Documentation
* on elastic.co
*/
public DeleteDatafeedResponse deleteDatafeed(DeleteDatafeedRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteDatafeedRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete a datafeed.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteDatafeedRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteDatafeedResponse deleteDatafeed(
Function> fn)
throws IOException, ElasticsearchException {
return deleteDatafeed(fn.apply(new DeleteDatafeedRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_expired_data
/**
* Delete expired ML data.
*
* Delete all job results, model snapshots and forecast data that have exceeded
* their retention days period. Machine learning state documents that are not
* associated with any job are also deleted. You can limit the request to a
* single or set of anomaly detection jobs by using a job identifier, a group
* name, a comma-separated list of jobs, or a wildcard expression. You can
* delete expired data for all anomaly detection jobs by using
* _all, by specifying * as the
* <job_id>, or by omitting the <job_id>.
*
* @see Documentation
* on elastic.co
*/
public DeleteExpiredDataResponse deleteExpiredData(DeleteExpiredDataRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteExpiredDataRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete expired ML data.
*
* Delete all job results, model snapshots and forecast data that have exceeded
* their retention days period. Machine learning state documents that are not
* associated with any job are also deleted. You can limit the request to a
* single or set of anomaly detection jobs by using a job identifier, a group
* name, a comma-separated list of jobs, or a wildcard expression. You can
* delete expired data for all anomaly detection jobs by using
* _all, by specifying * as the
* <job_id>, or by omitting the <job_id>.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteExpiredDataRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteExpiredDataResponse deleteExpiredData(
Function> fn)
throws IOException, ElasticsearchException {
return deleteExpiredData(fn.apply(new DeleteExpiredDataRequest.Builder()).build());
}
/**
* Delete expired ML data.
*
* Delete all job results, model snapshots and forecast data that have exceeded
* their retention days period. Machine learning state documents that are not
* associated with any job are also deleted. You can limit the request to a
* single or set of anomaly detection jobs by using a job identifier, a group
* name, a comma-separated list of jobs, or a wildcard expression. You can
* delete expired data for all anomaly detection jobs by using
* _all, by specifying * as the
* <job_id>, or by omitting the <job_id>.
*
* @see Documentation
* on elastic.co
*/
public DeleteExpiredDataResponse deleteExpiredData() throws IOException, ElasticsearchException {
return this.transport.performRequest(new DeleteExpiredDataRequest.Builder().build(),
DeleteExpiredDataRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.delete_filter
/**
* Delete a filter.
*
* If an anomaly detection job references the filter, you cannot delete the
* filter. You must update or delete the job before you can delete the filter.
*
* @see Documentation
* on elastic.co
*/
public DeleteFilterResponse deleteFilter(DeleteFilterRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteFilterRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete a filter.
*
* If an anomaly detection job references the filter, you cannot delete the
* filter. You must update or delete the job before you can delete the filter.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteFilterRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteFilterResponse deleteFilter(
Function> fn)
throws IOException, ElasticsearchException {
return deleteFilter(fn.apply(new DeleteFilterRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_forecast
/**
* Delete forecasts from a job.
*
* By default, forecasts are retained for 14 days. You can specify a different
* retention period with the expires_in parameter in the forecast
* jobs API. The delete forecast API enables you to delete one or more forecasts
* before they expire.
*
* @see Documentation
* on elastic.co
*/
public DeleteForecastResponse deleteForecast(DeleteForecastRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteForecastRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete forecasts from a job.
*
* By default, forecasts are retained for 14 days. You can specify a different
* retention period with the expires_in parameter in the forecast
* jobs API. The delete forecast API enables you to delete one or more forecasts
* before they expire.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteForecastRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteForecastResponse deleteForecast(
Function> fn)
throws IOException, ElasticsearchException {
return deleteForecast(fn.apply(new DeleteForecastRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_job
/**
* Delete an anomaly detection job.
*
* All job configuration, model state and results are deleted. It is not
* currently possible to delete multiple jobs using wildcards or a comma
* separated list. If you delete a job that has a datafeed, the request first
* tries to delete the datafeed. This behavior is equivalent to calling the
* delete datafeed API with the same timeout and force parameters as the delete
* job request.
*
* @see Documentation
* on elastic.co
*/
public DeleteJobResponse deleteJob(DeleteJobRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteJobRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete an anomaly detection job.
*
* All job configuration, model state and results are deleted. It is not
* currently possible to delete multiple jobs using wildcards or a comma
* separated list. If you delete a job that has a datafeed, the request first
* tries to delete the datafeed. This behavior is equivalent to calling the
* delete datafeed API with the same timeout and force parameters as the delete
* job request.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteJobRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteJobResponse deleteJob(Function> fn)
throws IOException, ElasticsearchException {
return deleteJob(fn.apply(new DeleteJobRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_model_snapshot
/**
* Delete a model snapshot.
*
* You cannot delete the active model snapshot. To delete that snapshot, first
* revert to a different one. To identify the active model snapshot, refer to
* the model_snapshot_id in the results from the get jobs API.
*
* @see Documentation
* on elastic.co
*/
public DeleteModelSnapshotResponse deleteModelSnapshot(DeleteModelSnapshotRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteModelSnapshotRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete a model snapshot.
*
* You cannot delete the active model snapshot. To delete that snapshot, first
* revert to a different one. To identify the active model snapshot, refer to
* the model_snapshot_id in the results from the get jobs API.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteModelSnapshotRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteModelSnapshotResponse deleteModelSnapshot(
Function> fn)
throws IOException, ElasticsearchException {
return deleteModelSnapshot(fn.apply(new DeleteModelSnapshotRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_trained_model
/**
* Delete an unreferenced trained model.
*
* The request deletes a trained inference model that is not referenced by an
* ingest pipeline.
*
* @see Documentation
* on elastic.co
*/
public DeleteTrainedModelResponse deleteTrainedModel(DeleteTrainedModelRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteTrainedModelRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete an unreferenced trained model.
*
* The request deletes a trained inference model that is not referenced by an
* ingest pipeline.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteTrainedModelRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteTrainedModelResponse deleteTrainedModel(
Function> fn)
throws IOException, ElasticsearchException {
return deleteTrainedModel(fn.apply(new DeleteTrainedModelRequest.Builder()).build());
}
// ----- Endpoint: ml.delete_trained_model_alias
/**
* Delete a trained model alias.
*
* This API deletes an existing model alias that refers to a trained model. If
* the model alias is missing or refers to a model other than the one identified
* by the model_id, this API returns an error.
*
* @see Documentation
* on elastic.co
*/
public DeleteTrainedModelAliasResponse deleteTrainedModelAlias(DeleteTrainedModelAliasRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) DeleteTrainedModelAliasRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Delete a trained model alias.
*
* This API deletes an existing model alias that refers to a trained model. If
* the model alias is missing or refers to a model other than the one identified
* by the model_id, this API returns an error.
*
* @param fn
* a function that initializes a builder to create the
* {@link DeleteTrainedModelAliasRequest}
* @see Documentation
* on elastic.co
*/
public final DeleteTrainedModelAliasResponse deleteTrainedModelAlias(
Function> fn)
throws IOException, ElasticsearchException {
return deleteTrainedModelAlias(fn.apply(new DeleteTrainedModelAliasRequest.Builder()).build());
}
// ----- Endpoint: ml.estimate_model_memory
/**
* Estimate job model memory usage.
*
* Make an estimation of the memory usage for an anomaly detection job model.
* The estimate is based on analysis configuration details for the job and
* cardinality estimates for the fields it references.
*
* @see Documentation
* on elastic.co
*/
public EstimateModelMemoryResponse estimateModelMemory(EstimateModelMemoryRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) EstimateModelMemoryRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Estimate job model memory usage.
*
* Make an estimation of the memory usage for an anomaly detection job model.
* The estimate is based on analysis configuration details for the job and
* cardinality estimates for the fields it references.
*
* @param fn
* a function that initializes a builder to create the
* {@link EstimateModelMemoryRequest}
* @see Documentation
* on elastic.co
*/
public final EstimateModelMemoryResponse estimateModelMemory(
Function> fn)
throws IOException, ElasticsearchException {
return estimateModelMemory(fn.apply(new EstimateModelMemoryRequest.Builder()).build());
}
/**
* Estimate job model memory usage.
*
* Make an estimation of the memory usage for an anomaly detection job model.
* The estimate is based on analysis configuration details for the job and
* cardinality estimates for the fields it references.
*
* @see Documentation
* on elastic.co
*/
public EstimateModelMemoryResponse estimateModelMemory() throws IOException, ElasticsearchException {
return this.transport.performRequest(new EstimateModelMemoryRequest.Builder().build(),
EstimateModelMemoryRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.evaluate_data_frame
/**
* Evaluate data frame analytics.
*
* The API packages together commonly used evaluation metrics for various types
* of machine learning features. This has been designed for use on indexes
* created by data frame analytics. Evaluation requires both a ground truth
* field and an analytics result field to be present.
*
* @see Documentation
* on elastic.co
*/
public EvaluateDataFrameResponse evaluateDataFrame(EvaluateDataFrameRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) EvaluateDataFrameRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Evaluate data frame analytics.
*
* The API packages together commonly used evaluation metrics for various types
* of machine learning features. This has been designed for use on indexes
* created by data frame analytics. Evaluation requires both a ground truth
* field and an analytics result field to be present.
*
* @param fn
* a function that initializes a builder to create the
* {@link EvaluateDataFrameRequest}
* @see Documentation
* on elastic.co
*/
public final EvaluateDataFrameResponse evaluateDataFrame(
Function> fn)
throws IOException, ElasticsearchException {
return evaluateDataFrame(fn.apply(new EvaluateDataFrameRequest.Builder()).build());
}
// ----- Endpoint: ml.explain_data_frame_analytics
/**
* Explain data frame analytics config.
*
* This API provides explanations for a data frame analytics config that either
* exists already or one that has not been created yet. The following
* explanations are provided:
*
* - which fields are included or not in the analysis and why,
* - how much memory is estimated to be required. The estimate can be used
* when deciding the appropriate value for model_memory_limit setting later on.
* If you have object fields or fields that are excluded via source filtering,
* they are not included in the explanation.
*
*
* @see Documentation
* on elastic.co
*/
public ExplainDataFrameAnalyticsResponse explainDataFrameAnalytics(ExplainDataFrameAnalyticsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) ExplainDataFrameAnalyticsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Explain data frame analytics config.
*
* This API provides explanations for a data frame analytics config that either
* exists already or one that has not been created yet. The following
* explanations are provided:
*
* - which fields are included or not in the analysis and why,
* - how much memory is estimated to be required. The estimate can be used
* when deciding the appropriate value for model_memory_limit setting later on.
* If you have object fields or fields that are excluded via source filtering,
* they are not included in the explanation.
*
*
* @param fn
* a function that initializes a builder to create the
* {@link ExplainDataFrameAnalyticsRequest}
* @see Documentation
* on elastic.co
*/
public final ExplainDataFrameAnalyticsResponse explainDataFrameAnalytics(
Function> fn)
throws IOException, ElasticsearchException {
return explainDataFrameAnalytics(fn.apply(new ExplainDataFrameAnalyticsRequest.Builder()).build());
}
/**
* Explain data frame analytics config.
*
* This API provides explanations for a data frame analytics config that either
* exists already or one that has not been created yet. The following
* explanations are provided:
*
* - which fields are included or not in the analysis and why,
* - how much memory is estimated to be required. The estimate can be used
* when deciding the appropriate value for model_memory_limit setting later on.
* If you have object fields or fields that are excluded via source filtering,
* they are not included in the explanation.
*
*
* @see Documentation
* on elastic.co
*/
public ExplainDataFrameAnalyticsResponse explainDataFrameAnalytics() throws IOException, ElasticsearchException {
return this.transport.performRequest(new ExplainDataFrameAnalyticsRequest.Builder().build(),
ExplainDataFrameAnalyticsRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.flush_job
/**
* Force buffered data to be processed. The flush jobs API is only applicable
* when sending data for analysis using the post data API. Depending on the
* content of the buffer, then it might additionally calculate new results. Both
* flush and close operations are similar, however the flush is more efficient
* if you are expecting to send more data for analysis. When flushing, the job
* remains open and is available to continue analyzing data. A close operation
* additionally prunes and persists the model state to disk and the job must be
* opened again before analyzing further data.
*
* @see Documentation
* on elastic.co
*/
public FlushJobResponse flushJob(FlushJobRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) FlushJobRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Force buffered data to be processed. The flush jobs API is only applicable
* when sending data for analysis using the post data API. Depending on the
* content of the buffer, then it might additionally calculate new results. Both
* flush and close operations are similar, however the flush is more efficient
* if you are expecting to send more data for analysis. When flushing, the job
* remains open and is available to continue analyzing data. A close operation
* additionally prunes and persists the model state to disk and the job must be
* opened again before analyzing further data.
*
* @param fn
* a function that initializes a builder to create the
* {@link FlushJobRequest}
* @see Documentation
* on elastic.co
*/
public final FlushJobResponse flushJob(Function> fn)
throws IOException, ElasticsearchException {
return flushJob(fn.apply(new FlushJobRequest.Builder()).build());
}
// ----- Endpoint: ml.forecast
/**
* Predict future behavior of a time series.
*
* Forecasts are not supported for jobs that perform population analysis; an
* error occurs if you try to create a forecast for a job that has an
* over_field_name in its configuration. Forcasts predict future
* behavior based on historical data.
*
* @see Documentation
* on elastic.co
*/
public ForecastResponse forecast(ForecastRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) ForecastRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Predict future behavior of a time series.
*
* Forecasts are not supported for jobs that perform population analysis; an
* error occurs if you try to create a forecast for a job that has an
* over_field_name in its configuration. Forcasts predict future
* behavior based on historical data.
*
* @param fn
* a function that initializes a builder to create the
* {@link ForecastRequest}
* @see Documentation
* on elastic.co
*/
public final ForecastResponse forecast(Function> fn)
throws IOException, ElasticsearchException {
return forecast(fn.apply(new ForecastRequest.Builder()).build());
}
// ----- Endpoint: ml.get_buckets
/**
* Get anomaly detection job results for buckets. The API presents a
* chronological view of the records, grouped by bucket.
*
* @see Documentation
* on elastic.co
*/
public GetBucketsResponse getBuckets(GetBucketsRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetBucketsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get anomaly detection job results for buckets. The API presents a
* chronological view of the records, grouped by bucket.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetBucketsRequest}
* @see Documentation
* on elastic.co
*/
public final GetBucketsResponse getBuckets(Function> fn)
throws IOException, ElasticsearchException {
return getBuckets(fn.apply(new GetBucketsRequest.Builder()).build());
}
// ----- Endpoint: ml.get_calendar_events
/**
* Get info about events in calendars.
*
* @see Documentation
* on elastic.co
*/
public GetCalendarEventsResponse getCalendarEvents(GetCalendarEventsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetCalendarEventsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get info about events in calendars.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetCalendarEventsRequest}
* @see Documentation
* on elastic.co
*/
public final GetCalendarEventsResponse getCalendarEvents(
Function> fn)
throws IOException, ElasticsearchException {
return getCalendarEvents(fn.apply(new GetCalendarEventsRequest.Builder()).build());
}
// ----- Endpoint: ml.get_calendars
/**
* Get calendar configuration info.
*
* @see Documentation
* on elastic.co
*/
public GetCalendarsResponse getCalendars(GetCalendarsRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetCalendarsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get calendar configuration info.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetCalendarsRequest}
* @see Documentation
* on elastic.co
*/
public final GetCalendarsResponse getCalendars(
Function> fn)
throws IOException, ElasticsearchException {
return getCalendars(fn.apply(new GetCalendarsRequest.Builder()).build());
}
/**
* Get calendar configuration info.
*
* @see Documentation
* on elastic.co
*/
public GetCalendarsResponse getCalendars() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetCalendarsRequest.Builder().build(), GetCalendarsRequest._ENDPOINT,
this.transportOptions);
}
// ----- Endpoint: ml.get_categories
/**
* Get anomaly detection job results for categories.
*
* @see Documentation
* on elastic.co
*/
public GetCategoriesResponse getCategories(GetCategoriesRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetCategoriesRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get anomaly detection job results for categories.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetCategoriesRequest}
* @see Documentation
* on elastic.co
*/
public final GetCategoriesResponse getCategories(
Function> fn)
throws IOException, ElasticsearchException {
return getCategories(fn.apply(new GetCategoriesRequest.Builder()).build());
}
// ----- Endpoint: ml.get_data_frame_analytics
/**
* Get data frame analytics job configuration info. You can get information for
* multiple data frame analytics jobs in a single API request by using a
* comma-separated list of data frame analytics jobs or a wildcard expression.
*
* @see Documentation
* on elastic.co
*/
public GetDataFrameAnalyticsResponse getDataFrameAnalytics(GetDataFrameAnalyticsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetDataFrameAnalyticsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get data frame analytics job configuration info. You can get information for
* multiple data frame analytics jobs in a single API request by using a
* comma-separated list of data frame analytics jobs or a wildcard expression.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetDataFrameAnalyticsRequest}
* @see Documentation
* on elastic.co
*/
public final GetDataFrameAnalyticsResponse getDataFrameAnalytics(
Function> fn)
throws IOException, ElasticsearchException {
return getDataFrameAnalytics(fn.apply(new GetDataFrameAnalyticsRequest.Builder()).build());
}
/**
* Get data frame analytics job configuration info. You can get information for
* multiple data frame analytics jobs in a single API request by using a
* comma-separated list of data frame analytics jobs or a wildcard expression.
*
* @see Documentation
* on elastic.co
*/
public GetDataFrameAnalyticsResponse getDataFrameAnalytics() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetDataFrameAnalyticsRequest.Builder().build(),
GetDataFrameAnalyticsRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.get_data_frame_analytics_stats
/**
* Get data frame analytics job stats.
*
* @see Documentation
* on elastic.co
*/
public GetDataFrameAnalyticsStatsResponse getDataFrameAnalyticsStats(GetDataFrameAnalyticsStatsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetDataFrameAnalyticsStatsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get data frame analytics job stats.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetDataFrameAnalyticsStatsRequest}
* @see Documentation
* on elastic.co
*/
public final GetDataFrameAnalyticsStatsResponse getDataFrameAnalyticsStats(
Function> fn)
throws IOException, ElasticsearchException {
return getDataFrameAnalyticsStats(fn.apply(new GetDataFrameAnalyticsStatsRequest.Builder()).build());
}
/**
* Get data frame analytics job stats.
*
* @see Documentation
* on elastic.co
*/
public GetDataFrameAnalyticsStatsResponse getDataFrameAnalyticsStats() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetDataFrameAnalyticsStatsRequest.Builder().build(),
GetDataFrameAnalyticsStatsRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.get_datafeed_stats
/**
* Get datafeed stats. You can get statistics for multiple datafeeds in a single
* API request by using a comma-separated list of datafeeds or a wildcard
* expression. You can get statistics for all datafeeds by using
* _all, by specifying * as the
* <feed_id>, or by omitting the
* <feed_id>. If the datafeed is stopped, the only
* information you receive is the datafeed_id and the
* state. This API returns a maximum of 10,000 datafeeds.
*
* @see Documentation
* on elastic.co
*/
public GetDatafeedStatsResponse getDatafeedStats(GetDatafeedStatsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetDatafeedStatsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get datafeed stats. You can get statistics for multiple datafeeds in a single
* API request by using a comma-separated list of datafeeds or a wildcard
* expression. You can get statistics for all datafeeds by using
* _all, by specifying * as the
* <feed_id>, or by omitting the
* <feed_id>. If the datafeed is stopped, the only
* information you receive is the datafeed_id and the
* state. This API returns a maximum of 10,000 datafeeds.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetDatafeedStatsRequest}
* @see Documentation
* on elastic.co
*/
public final GetDatafeedStatsResponse getDatafeedStats(
Function> fn)
throws IOException, ElasticsearchException {
return getDatafeedStats(fn.apply(new GetDatafeedStatsRequest.Builder()).build());
}
/**
* Get datafeed stats. You can get statistics for multiple datafeeds in a single
* API request by using a comma-separated list of datafeeds or a wildcard
* expression. You can get statistics for all datafeeds by using
* _all, by specifying * as the
* <feed_id>, or by omitting the
* <feed_id>. If the datafeed is stopped, the only
* information you receive is the datafeed_id and the
* state. This API returns a maximum of 10,000 datafeeds.
*
* @see Documentation
* on elastic.co
*/
public GetDatafeedStatsResponse getDatafeedStats() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetDatafeedStatsRequest.Builder().build(),
GetDatafeedStatsRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.get_datafeeds
/**
* Get datafeeds configuration info. You can get information for multiple
* datafeeds in a single API request by using a comma-separated list of
* datafeeds or a wildcard expression. You can get information for all datafeeds
* by using _all, by specifying * as the
* <feed_id>, or by omitting the
* <feed_id>. This API returns a maximum of 10,000 datafeeds.
*
* @see Documentation
* on elastic.co
*/
public GetDatafeedsResponse getDatafeeds(GetDatafeedsRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetDatafeedsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get datafeeds configuration info. You can get information for multiple
* datafeeds in a single API request by using a comma-separated list of
* datafeeds or a wildcard expression. You can get information for all datafeeds
* by using _all, by specifying * as the
* <feed_id>, or by omitting the
* <feed_id>. This API returns a maximum of 10,000 datafeeds.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetDatafeedsRequest}
* @see Documentation
* on elastic.co
*/
public final GetDatafeedsResponse getDatafeeds(
Function> fn)
throws IOException, ElasticsearchException {
return getDatafeeds(fn.apply(new GetDatafeedsRequest.Builder()).build());
}
/**
* Get datafeeds configuration info. You can get information for multiple
* datafeeds in a single API request by using a comma-separated list of
* datafeeds or a wildcard expression. You can get information for all datafeeds
* by using _all, by specifying * as the
* <feed_id>, or by omitting the
* <feed_id>. This API returns a maximum of 10,000 datafeeds.
*
* @see Documentation
* on elastic.co
*/
public GetDatafeedsResponse getDatafeeds() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetDatafeedsRequest.Builder().build(), GetDatafeedsRequest._ENDPOINT,
this.transportOptions);
}
// ----- Endpoint: ml.get_filters
/**
* Get filters. You can get a single filter or all filters.
*
* @see Documentation
* on elastic.co
*/
public GetFiltersResponse getFilters(GetFiltersRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetFiltersRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get filters. You can get a single filter or all filters.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetFiltersRequest}
* @see Documentation
* on elastic.co
*/
public final GetFiltersResponse getFilters(Function> fn)
throws IOException, ElasticsearchException {
return getFilters(fn.apply(new GetFiltersRequest.Builder()).build());
}
/**
* Get filters. You can get a single filter or all filters.
*
* @see Documentation
* on elastic.co
*/
public GetFiltersResponse getFilters() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetFiltersRequest.Builder().build(), GetFiltersRequest._ENDPOINT,
this.transportOptions);
}
// ----- Endpoint: ml.get_influencers
/**
* Get anomaly detection job results for influencers. Influencers are the
* entities that have contributed to, or are to blame for, the anomalies.
* Influencer results are available only if an
* influencer_field_name is specified in the job configuration.
*
* @see Documentation
* on elastic.co
*/
public GetInfluencersResponse getInfluencers(GetInfluencersRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetInfluencersRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get anomaly detection job results for influencers. Influencers are the
* entities that have contributed to, or are to blame for, the anomalies.
* Influencer results are available only if an
* influencer_field_name is specified in the job configuration.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetInfluencersRequest}
* @see Documentation
* on elastic.co
*/
public final GetInfluencersResponse getInfluencers(
Function> fn)
throws IOException, ElasticsearchException {
return getInfluencers(fn.apply(new GetInfluencersRequest.Builder()).build());
}
// ----- Endpoint: ml.get_job_stats
/**
* Get anomaly detection job stats.
*
* @see Documentation
* on elastic.co
*/
public GetJobStatsResponse getJobStats(GetJobStatsRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetJobStatsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get anomaly detection job stats.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetJobStatsRequest}
* @see Documentation
* on elastic.co
*/
public final GetJobStatsResponse getJobStats(
Function> fn)
throws IOException, ElasticsearchException {
return getJobStats(fn.apply(new GetJobStatsRequest.Builder()).build());
}
/**
* Get anomaly detection job stats.
*
* @see Documentation
* on elastic.co
*/
public GetJobStatsResponse getJobStats() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetJobStatsRequest.Builder().build(), GetJobStatsRequest._ENDPOINT,
this.transportOptions);
}
// ----- Endpoint: ml.get_jobs
/**
* Get anomaly detection jobs configuration info. You can get information for
* multiple anomaly detection jobs in a single API request by using a group
* name, a comma-separated list of jobs, or a wildcard expression. You can get
* information for all anomaly detection jobs by using _all, by
* specifying * as the <job_id>, or by omitting
* the <job_id>.
*
* @see Documentation
* on elastic.co
*/
public GetJobsResponse getJobs(GetJobsRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetJobsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get anomaly detection jobs configuration info. You can get information for
* multiple anomaly detection jobs in a single API request by using a group
* name, a comma-separated list of jobs, or a wildcard expression. You can get
* information for all anomaly detection jobs by using _all, by
* specifying * as the <job_id>, or by omitting
* the <job_id>.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetJobsRequest}
* @see Documentation
* on elastic.co
*/
public final GetJobsResponse getJobs(Function> fn)
throws IOException, ElasticsearchException {
return getJobs(fn.apply(new GetJobsRequest.Builder()).build());
}
/**
* Get anomaly detection jobs configuration info. You can get information for
* multiple anomaly detection jobs in a single API request by using a group
* name, a comma-separated list of jobs, or a wildcard expression. You can get
* information for all anomaly detection jobs by using _all, by
* specifying * as the <job_id>, or by omitting
* the <job_id>.
*
* @see Documentation
* on elastic.co
*/
public GetJobsResponse getJobs() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetJobsRequest.Builder().build(), GetJobsRequest._ENDPOINT,
this.transportOptions);
}
// ----- Endpoint: ml.get_memory_stats
/**
* Get machine learning memory usage info. Get information about how machine
* learning jobs and trained models are using memory, on each node, both within
* the JVM heap, and natively, outside of the JVM.
*
* @see Documentation
* on elastic.co
*/
public GetMemoryStatsResponse getMemoryStats(GetMemoryStatsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetMemoryStatsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get machine learning memory usage info. Get information about how machine
* learning jobs and trained models are using memory, on each node, both within
* the JVM heap, and natively, outside of the JVM.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetMemoryStatsRequest}
* @see Documentation
* on elastic.co
*/
public final GetMemoryStatsResponse getMemoryStats(
Function> fn)
throws IOException, ElasticsearchException {
return getMemoryStats(fn.apply(new GetMemoryStatsRequest.Builder()).build());
}
/**
* Get machine learning memory usage info. Get information about how machine
* learning jobs and trained models are using memory, on each node, both within
* the JVM heap, and natively, outside of the JVM.
*
* @see Documentation
* on elastic.co
*/
public GetMemoryStatsResponse getMemoryStats() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetMemoryStatsRequest.Builder().build(),
GetMemoryStatsRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.get_model_snapshot_upgrade_stats
/**
* Get anomaly detection job model snapshot upgrade usage info.
*
* @see Documentation
* on elastic.co
*/
public GetModelSnapshotUpgradeStatsResponse getModelSnapshotUpgradeStats(
GetModelSnapshotUpgradeStatsRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetModelSnapshotUpgradeStatsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get anomaly detection job model snapshot upgrade usage info.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetModelSnapshotUpgradeStatsRequest}
* @see Documentation
* on elastic.co
*/
public final GetModelSnapshotUpgradeStatsResponse getModelSnapshotUpgradeStats(
Function> fn)
throws IOException, ElasticsearchException {
return getModelSnapshotUpgradeStats(fn.apply(new GetModelSnapshotUpgradeStatsRequest.Builder()).build());
}
// ----- Endpoint: ml.get_model_snapshots
/**
* Get model snapshots info.
*
* @see Documentation
* on elastic.co
*/
public GetModelSnapshotsResponse getModelSnapshots(GetModelSnapshotsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetModelSnapshotsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get model snapshots info.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetModelSnapshotsRequest}
* @see Documentation
* on elastic.co
*/
public final GetModelSnapshotsResponse getModelSnapshots(
Function> fn)
throws IOException, ElasticsearchException {
return getModelSnapshots(fn.apply(new GetModelSnapshotsRequest.Builder()).build());
}
// ----- Endpoint: ml.get_overall_buckets
/**
* Get overall bucket results.
*
* Retrievs overall bucket results that summarize the bucket results of multiple
* anomaly detection jobs.
*
* The overall_score is calculated by combining the scores of all
* the buckets within the overall bucket span. First, the maximum
* anomaly_score per anomaly detection job in the overall bucket is
* calculated. Then the top_n of those scores are averaged to
* result in the overall_score. This means that you can fine-tune
* the overall_score so that it is more or less sensitive to the
* number of jobs that detect an anomaly at the same time. For example, if you
* set top_n to 1, the overall_score is
* the maximum bucket score in the overall bucket. Alternatively, if you set
* top_n to the number of jobs, the overall_score is
* high only when all jobs detect anomalies in that overall bucket. If you set
* the bucket_span parameter (to a value greater than its default),
* the overall_score is the maximum overall_score of
* the overall buckets that have a span equal to the jobs' largest bucket span.
*
* @see Documentation
* on elastic.co
*/
public GetOverallBucketsResponse getOverallBuckets(GetOverallBucketsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetOverallBucketsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get overall bucket results.
*
* Retrievs overall bucket results that summarize the bucket results of multiple
* anomaly detection jobs.
*
* The overall_score is calculated by combining the scores of all
* the buckets within the overall bucket span. First, the maximum
* anomaly_score per anomaly detection job in the overall bucket is
* calculated. Then the top_n of those scores are averaged to
* result in the overall_score. This means that you can fine-tune
* the overall_score so that it is more or less sensitive to the
* number of jobs that detect an anomaly at the same time. For example, if you
* set top_n to 1, the overall_score is
* the maximum bucket score in the overall bucket. Alternatively, if you set
* top_n to the number of jobs, the overall_score is
* high only when all jobs detect anomalies in that overall bucket. If you set
* the bucket_span parameter (to a value greater than its default),
* the overall_score is the maximum overall_score of
* the overall buckets that have a span equal to the jobs' largest bucket span.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetOverallBucketsRequest}
* @see Documentation
* on elastic.co
*/
public final GetOverallBucketsResponse getOverallBuckets(
Function> fn)
throws IOException, ElasticsearchException {
return getOverallBuckets(fn.apply(new GetOverallBucketsRequest.Builder()).build());
}
// ----- Endpoint: ml.get_records
/**
* Get anomaly records for an anomaly detection job. Records contain the
* detailed analytical results. They describe the anomalous activity that has
* been identified in the input data based on the detector configuration. There
* can be many anomaly records depending on the characteristics and size of the
* input data. In practice, there are often too many to be able to manually
* process them. The machine learning features therefore perform a sophisticated
* aggregation of the anomaly records into buckets. The number of record results
* depends on the number of anomalies found in each bucket, which relates to the
* number of time series being modeled and the number of detectors.
*
* @see Documentation
* on elastic.co
*/
public GetRecordsResponse getRecords(GetRecordsRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetRecordsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get anomaly records for an anomaly detection job. Records contain the
* detailed analytical results. They describe the anomalous activity that has
* been identified in the input data based on the detector configuration. There
* can be many anomaly records depending on the characteristics and size of the
* input data. In practice, there are often too many to be able to manually
* process them. The machine learning features therefore perform a sophisticated
* aggregation of the anomaly records into buckets. The number of record results
* depends on the number of anomalies found in each bucket, which relates to the
* number of time series being modeled and the number of detectors.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetRecordsRequest}
* @see Documentation
* on elastic.co
*/
public final GetRecordsResponse getRecords(Function> fn)
throws IOException, ElasticsearchException {
return getRecords(fn.apply(new GetRecordsRequest.Builder()).build());
}
// ----- Endpoint: ml.get_trained_models
/**
* Get trained model configuration info.
*
* @see Documentation
* on elastic.co
*/
public GetTrainedModelsResponse getTrainedModels(GetTrainedModelsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetTrainedModelsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get trained model configuration info.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetTrainedModelsRequest}
* @see Documentation
* on elastic.co
*/
public final GetTrainedModelsResponse getTrainedModels(
Function> fn)
throws IOException, ElasticsearchException {
return getTrainedModels(fn.apply(new GetTrainedModelsRequest.Builder()).build());
}
/**
* Get trained model configuration info.
*
* @see Documentation
* on elastic.co
*/
public GetTrainedModelsResponse getTrainedModels() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetTrainedModelsRequest.Builder().build(),
GetTrainedModelsRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.get_trained_models_stats
/**
* Get trained models usage info. You can get usage information for multiple
* trained models in a single API request by using a comma-separated list of
* model IDs or a wildcard expression.
*
* @see Documentation
* on elastic.co
*/
public GetTrainedModelsStatsResponse getTrainedModelsStats(GetTrainedModelsStatsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) GetTrainedModelsStatsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Get trained models usage info. You can get usage information for multiple
* trained models in a single API request by using a comma-separated list of
* model IDs or a wildcard expression.
*
* @param fn
* a function that initializes a builder to create the
* {@link GetTrainedModelsStatsRequest}
* @see Documentation
* on elastic.co
*/
public final GetTrainedModelsStatsResponse getTrainedModelsStats(
Function> fn)
throws IOException, ElasticsearchException {
return getTrainedModelsStats(fn.apply(new GetTrainedModelsStatsRequest.Builder()).build());
}
/**
* Get trained models usage info. You can get usage information for multiple
* trained models in a single API request by using a comma-separated list of
* model IDs or a wildcard expression.
*
* @see Documentation
* on elastic.co
*/
public GetTrainedModelsStatsResponse getTrainedModelsStats() throws IOException, ElasticsearchException {
return this.transport.performRequest(new GetTrainedModelsStatsRequest.Builder().build(),
GetTrainedModelsStatsRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.infer_trained_model
/**
* Evaluate a trained model.
*
* @see Documentation
* on elastic.co
*/
public InferTrainedModelResponse inferTrainedModel(InferTrainedModelRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) InferTrainedModelRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Evaluate a trained model.
*
* @param fn
* a function that initializes a builder to create the
* {@link InferTrainedModelRequest}
* @see Documentation
* on elastic.co
*/
public final InferTrainedModelResponse inferTrainedModel(
Function> fn)
throws IOException, ElasticsearchException {
return inferTrainedModel(fn.apply(new InferTrainedModelRequest.Builder()).build());
}
// ----- Endpoint: ml.info
/**
* Get machine learning information. Get defaults and limits used by machine
* learning. This endpoint is designed to be used by a user interface that needs
* to fully understand machine learning configurations where some options are
* not specified, meaning that the defaults should be used. This endpoint may be
* used to find out what those defaults are. It also provides information about
* the maximum size of machine learning jobs that could run in the current
* cluster configuration.
*
* @see Documentation
* on elastic.co
*/
public MlInfoResponse info() throws IOException, ElasticsearchException {
return this.transport.performRequest(MlInfoRequest._INSTANCE, MlInfoRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.open_job
/**
* Open anomaly detection jobs.
*
* An anomaly detection job must be opened to be ready to receive and analyze
* data. It can be opened and closed multiple times throughout its lifecycle.
* When you open a new job, it starts with an empty model. When you open an
* existing job, the most recent model state is automatically loaded. The job is
* ready to resume its analysis from where it left off, once new data is
* received.
*
* @see Documentation
* on elastic.co
*/
public OpenJobResponse openJob(OpenJobRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) OpenJobRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Open anomaly detection jobs.
*
* An anomaly detection job must be opened to be ready to receive and analyze
* data. It can be opened and closed multiple times throughout its lifecycle.
* When you open a new job, it starts with an empty model. When you open an
* existing job, the most recent model state is automatically loaded. The job is
* ready to resume its analysis from where it left off, once new data is
* received.
*
* @param fn
* a function that initializes a builder to create the
* {@link OpenJobRequest}
* @see Documentation
* on elastic.co
*/
public final OpenJobResponse openJob(Function> fn)
throws IOException, ElasticsearchException {
return openJob(fn.apply(new OpenJobRequest.Builder()).build());
}
// ----- Endpoint: ml.post_calendar_events
/**
* Add scheduled events to the calendar.
*
* @see Documentation
* on elastic.co
*/
public PostCalendarEventsResponse postCalendarEvents(PostCalendarEventsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PostCalendarEventsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Add scheduled events to the calendar.
*
* @param fn
* a function that initializes a builder to create the
* {@link PostCalendarEventsRequest}
* @see Documentation
* on elastic.co
*/
public final PostCalendarEventsResponse postCalendarEvents(
Function> fn)
throws IOException, ElasticsearchException {
return postCalendarEvents(fn.apply(new PostCalendarEventsRequest.Builder()).build());
}
// ----- Endpoint: ml.post_data
/**
* Send data to an anomaly detection job for analysis.
*
* IMPORTANT: For each job, data can be accepted from only a single connection
* at a time. It is not currently possible to post data to multiple jobs using
* wildcards or a comma-separated list.
*
* @see Documentation
* on elastic.co
*/
public PostDataResponse postData(PostDataRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint, PostDataResponse, ErrorResponse> endpoint = (JsonEndpoint, PostDataResponse, ErrorResponse>) PostDataRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Send data to an anomaly detection job for analysis.
*
* IMPORTANT: For each job, data can be accepted from only a single connection
* at a time. It is not currently possible to post data to multiple jobs using
* wildcards or a comma-separated list.
*
* @param fn
* a function that initializes a builder to create the
* {@link PostDataRequest}
* @see Documentation
* on elastic.co
*/
public final PostDataResponse postData(
Function, ObjectBuilder>> fn)
throws IOException, ElasticsearchException {
return postData(fn.apply(new PostDataRequest.Builder()).build());
}
// ----- Endpoint: ml.preview_data_frame_analytics
/**
* Preview features used by data frame analytics. Preview the extracted features
* used by a data frame analytics config.
*
* @see Documentation
* on elastic.co
*/
public PreviewDataFrameAnalyticsResponse previewDataFrameAnalytics(PreviewDataFrameAnalyticsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PreviewDataFrameAnalyticsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Preview features used by data frame analytics. Preview the extracted features
* used by a data frame analytics config.
*
* @param fn
* a function that initializes a builder to create the
* {@link PreviewDataFrameAnalyticsRequest}
* @see Documentation
* on elastic.co
*/
public final PreviewDataFrameAnalyticsResponse previewDataFrameAnalytics(
Function> fn)
throws IOException, ElasticsearchException {
return previewDataFrameAnalytics(fn.apply(new PreviewDataFrameAnalyticsRequest.Builder()).build());
}
/**
* Preview features used by data frame analytics. Preview the extracted features
* used by a data frame analytics config.
*
* @see Documentation
* on elastic.co
*/
public PreviewDataFrameAnalyticsResponse previewDataFrameAnalytics() throws IOException, ElasticsearchException {
return this.transport.performRequest(new PreviewDataFrameAnalyticsRequest.Builder().build(),
PreviewDataFrameAnalyticsRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.preview_datafeed
/**
* Preview a datafeed. This API returns the first "page" of search
* results from a datafeed. You can preview an existing datafeed or provide
* configuration details for a datafeed and anomaly detection job in the API.
* The preview shows the structure of the data that will be passed to the
* anomaly detection engine. IMPORTANT: When Elasticsearch security features are
* enabled, the preview uses the credentials of the user that called the API.
* However, when the datafeed starts it uses the roles of the last user that
* created or updated the datafeed. To get a preview that accurately reflects
* the behavior of the datafeed, use the appropriate credentials. You can also
* use secondary authorization headers to supply the credentials.
*
* @see Documentation
* on elastic.co
*/
public PreviewDatafeedResponse previewDatafeed(PreviewDatafeedRequest request,
Class tDocumentClass) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint, ErrorResponse> endpoint = (JsonEndpoint, ErrorResponse>) PreviewDatafeedRequest._ENDPOINT;
endpoint = new EndpointWithResponseMapperAttr<>(endpoint,
"co.elastic.clients:Deserializer:ml.preview_datafeed.Response.TDocument",
getDeserializer(tDocumentClass));
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Preview a datafeed. This API returns the first "page" of search
* results from a datafeed. You can preview an existing datafeed or provide
* configuration details for a datafeed and anomaly detection job in the API.
* The preview shows the structure of the data that will be passed to the
* anomaly detection engine. IMPORTANT: When Elasticsearch security features are
* enabled, the preview uses the credentials of the user that called the API.
* However, when the datafeed starts it uses the roles of the last user that
* created or updated the datafeed. To get a preview that accurately reflects
* the behavior of the datafeed, use the appropriate credentials. You can also
* use secondary authorization headers to supply the credentials.
*
* @param fn
* a function that initializes a builder to create the
* {@link PreviewDatafeedRequest}
* @see Documentation
* on elastic.co
*/
public final PreviewDatafeedResponse previewDatafeed(
Function> fn,
Class tDocumentClass) throws IOException, ElasticsearchException {
return previewDatafeed(fn.apply(new PreviewDatafeedRequest.Builder()).build(), tDocumentClass);
}
/**
* Overload of {@link #previewDatafeed(PreviewDatafeedRequest, Class)}, where
* Class is defined as Void, meaning the documents will not be deserialized.
*/
public PreviewDatafeedResponse previewDatafeed(PreviewDatafeedRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint, ErrorResponse> endpoint = (JsonEndpoint, ErrorResponse>) PreviewDatafeedRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Overload of {@link #previewDatafeed(Function, Class)}, where Class is defined
* as Void, meaning the documents will not be deserialized.
*/
public final PreviewDatafeedResponse previewDatafeed(
Function> fn)
throws IOException, ElasticsearchException {
return previewDatafeed(fn.apply(new PreviewDatafeedRequest.Builder()).build(), Void.class);
}
/**
* Preview a datafeed. This API returns the first "page" of search
* results from a datafeed. You can preview an existing datafeed or provide
* configuration details for a datafeed and anomaly detection job in the API.
* The preview shows the structure of the data that will be passed to the
* anomaly detection engine. IMPORTANT: When Elasticsearch security features are
* enabled, the preview uses the credentials of the user that called the API.
* However, when the datafeed starts it uses the roles of the last user that
* created or updated the datafeed. To get a preview that accurately reflects
* the behavior of the datafeed, use the appropriate credentials. You can also
* use secondary authorization headers to supply the credentials.
*
* @see Documentation
* on elastic.co
*/
public PreviewDatafeedResponse previewDatafeed(PreviewDatafeedRequest request,
Type tDocumentType) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint, ErrorResponse> endpoint = (JsonEndpoint, ErrorResponse>) PreviewDatafeedRequest._ENDPOINT;
endpoint = new EndpointWithResponseMapperAttr<>(endpoint,
"co.elastic.clients:Deserializer:ml.preview_datafeed.Response.TDocument",
getDeserializer(tDocumentType));
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Preview a datafeed. This API returns the first "page" of search
* results from a datafeed. You can preview an existing datafeed or provide
* configuration details for a datafeed and anomaly detection job in the API.
* The preview shows the structure of the data that will be passed to the
* anomaly detection engine. IMPORTANT: When Elasticsearch security features are
* enabled, the preview uses the credentials of the user that called the API.
* However, when the datafeed starts it uses the roles of the last user that
* created or updated the datafeed. To get a preview that accurately reflects
* the behavior of the datafeed, use the appropriate credentials. You can also
* use secondary authorization headers to supply the credentials.
*
* @param fn
* a function that initializes a builder to create the
* {@link PreviewDatafeedRequest}
* @see Documentation
* on elastic.co
*/
public final PreviewDatafeedResponse previewDatafeed(
Function> fn, Type tDocumentType)
throws IOException, ElasticsearchException {
return previewDatafeed(fn.apply(new PreviewDatafeedRequest.Builder()).build(), tDocumentType);
}
// ----- Endpoint: ml.put_calendar
/**
* Create a calendar.
*
* @see Documentation
* on elastic.co
*/
public PutCalendarResponse putCalendar(PutCalendarRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PutCalendarRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Create a calendar.
*
* @param fn
* a function that initializes a builder to create the
* {@link PutCalendarRequest}
* @see Documentation
* on elastic.co
*/
public final PutCalendarResponse putCalendar(
Function> fn)
throws IOException, ElasticsearchException {
return putCalendar(fn.apply(new PutCalendarRequest.Builder()).build());
}
// ----- Endpoint: ml.put_calendar_job
/**
* Add anomaly detection job to calendar.
*
* @see Documentation
* on elastic.co
*/
public PutCalendarJobResponse putCalendarJob(PutCalendarJobRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PutCalendarJobRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Add anomaly detection job to calendar.
*
* @param fn
* a function that initializes a builder to create the
* {@link PutCalendarJobRequest}
* @see Documentation
* on elastic.co
*/
public final PutCalendarJobResponse putCalendarJob(
Function> fn)
throws IOException, ElasticsearchException {
return putCalendarJob(fn.apply(new PutCalendarJobRequest.Builder()).build());
}
// ----- Endpoint: ml.put_data_frame_analytics
/**
* Create a data frame analytics job. This API creates a data frame analytics
* job that performs an analysis on the source indices and stores the outcome in
* a destination index. By default, the query used in the source configuration
* is {"match_all": {}}.
*
* If the destination index does not exist, it is created automatically when you
* start the job.
*
* If you supply only a subset of the regression or classification parameters,
* hyperparameter optimization occurs. It determines a value for each of the
* undefined parameters.
*
* @see Documentation
* on elastic.co
*/
public PutDataFrameAnalyticsResponse putDataFrameAnalytics(PutDataFrameAnalyticsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PutDataFrameAnalyticsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Create a data frame analytics job. This API creates a data frame analytics
* job that performs an analysis on the source indices and stores the outcome in
* a destination index. By default, the query used in the source configuration
* is {"match_all": {}}.
*
* If the destination index does not exist, it is created automatically when you
* start the job.
*
* If you supply only a subset of the regression or classification parameters,
* hyperparameter optimization occurs. It determines a value for each of the
* undefined parameters.
*
* @param fn
* a function that initializes a builder to create the
* {@link PutDataFrameAnalyticsRequest}
* @see Documentation
* on elastic.co
*/
public final PutDataFrameAnalyticsResponse putDataFrameAnalytics(
Function> fn)
throws IOException, ElasticsearchException {
return putDataFrameAnalytics(fn.apply(new PutDataFrameAnalyticsRequest.Builder()).build());
}
// ----- Endpoint: ml.put_datafeed
/**
* Create a datafeed. Datafeeds retrieve data from Elasticsearch for analysis by
* an anomaly detection job. You can associate only one datafeed with each
* anomaly detection job. The datafeed contains a query that runs at a defined
* interval (frequency). If you are concerned about delayed data,
* you can add a delay (query_delay) at each interval. By default,
* the datafeed uses the following query:
* {"match_all": {"boost": 1}}.
*
* When 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. You must use Kibana, this API, or the
* create anomaly detection jobs API to create a datafeed. Do not add a datafeed
* directly to the .ml-config index. Do not give users
* write privileges on the .ml-config index.
*
* @see Documentation
* on elastic.co
*/
public PutDatafeedResponse putDatafeed(PutDatafeedRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PutDatafeedRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Create a datafeed. Datafeeds retrieve data from Elasticsearch for analysis by
* an anomaly detection job. You can associate only one datafeed with each
* anomaly detection job. The datafeed contains a query that runs at a defined
* interval (frequency). If you are concerned about delayed data,
* you can add a delay (query_delay) at each interval. By default,
* the datafeed uses the following query:
* {"match_all": {"boost": 1}}.
*
* When 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. You must use Kibana, this API, or the
* create anomaly detection jobs API to create a datafeed. Do not add a datafeed
* directly to the .ml-config index. Do not give users
* write privileges on the .ml-config index.
*
* @param fn
* a function that initializes a builder to create the
* {@link PutDatafeedRequest}
* @see Documentation
* on elastic.co
*/
public final PutDatafeedResponse putDatafeed(
Function> fn)
throws IOException, ElasticsearchException {
return putDatafeed(fn.apply(new PutDatafeedRequest.Builder()).build());
}
// ----- Endpoint: ml.put_filter
/**
* Create a filter. A filter contains a list of strings. It can be used by one
* or more anomaly detection jobs. Specifically, filters are referenced in the
* custom_rules property of detector configuration objects.
*
* @see Documentation
* on elastic.co
*/
public PutFilterResponse putFilter(PutFilterRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PutFilterRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Create a filter. A filter contains a list of strings. It can be used by one
* or more anomaly detection jobs. Specifically, filters are referenced in the
* custom_rules property of detector configuration objects.
*
* @param fn
* a function that initializes a builder to create the
* {@link PutFilterRequest}
* @see Documentation
* on elastic.co
*/
public final PutFilterResponse putFilter(Function> fn)
throws IOException, ElasticsearchException {
return putFilter(fn.apply(new PutFilterRequest.Builder()).build());
}
// ----- Endpoint: ml.put_job
/**
* Create an anomaly detection job.
*
* If you include a datafeed_config, you must have read index
* privileges on the source index. If you include a datafeed_config
* but do not provide a query, the datafeed uses
* {"match_all": {"boost": 1}}.
*
* @see Documentation
* on elastic.co
*/
public PutJobResponse putJob(PutJobRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PutJobRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Create an anomaly detection job.
*
* If you include a datafeed_config, you must have read index
* privileges on the source index. If you include a datafeed_config
* but do not provide a query, the datafeed uses
* {"match_all": {"boost": 1}}.
*
* @param fn
* a function that initializes a builder to create the
* {@link PutJobRequest}
* @see Documentation
* on elastic.co
*/
public final PutJobResponse putJob(Function> fn)
throws IOException, ElasticsearchException {
return putJob(fn.apply(new PutJobRequest.Builder()).build());
}
// ----- Endpoint: ml.put_trained_model
/**
* Create a trained model. Enable you to supply a trained model that is not
* created by data frame analytics.
*
* @see Documentation
* on elastic.co
*/
public PutTrainedModelResponse putTrainedModel(PutTrainedModelRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PutTrainedModelRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Create a trained model. Enable you to supply a trained model that is not
* created by data frame analytics.
*
* @param fn
* a function that initializes a builder to create the
* {@link PutTrainedModelRequest}
* @see Documentation
* on elastic.co
*/
public final PutTrainedModelResponse putTrainedModel(
Function> fn)
throws IOException, ElasticsearchException {
return putTrainedModel(fn.apply(new PutTrainedModelRequest.Builder()).build());
}
// ----- Endpoint: ml.put_trained_model_alias
/**
* Create or update a trained model alias. A trained model alias is a logical
* name used to reference a single trained model. You can use aliases instead of
* trained model identifiers to make it easier to reference your models. For
* example, you can use aliases in inference aggregations and processors. An
* alias must be unique and refer to only a single trained model. However, you
* can have multiple aliases for each trained model. If you use this API to
* update an alias such that it references a different trained model ID and the
* model uses a different type of data frame analytics, an error occurs. For
* example, this situation occurs if you have a trained model for regression
* analysis and a trained model for classification analysis; you cannot reassign
* an alias from one type of trained model to another. If you use this API to
* update an alias and there are very few input fields in common between the old
* and new trained models for the model alias, the API returns a warning.
*
* @see Documentation
* on elastic.co
*/
public PutTrainedModelAliasResponse putTrainedModelAlias(PutTrainedModelAliasRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PutTrainedModelAliasRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Create or update a trained model alias. A trained model alias is a logical
* name used to reference a single trained model. You can use aliases instead of
* trained model identifiers to make it easier to reference your models. For
* example, you can use aliases in inference aggregations and processors. An
* alias must be unique and refer to only a single trained model. However, you
* can have multiple aliases for each trained model. If you use this API to
* update an alias such that it references a different trained model ID and the
* model uses a different type of data frame analytics, an error occurs. For
* example, this situation occurs if you have a trained model for regression
* analysis and a trained model for classification analysis; you cannot reassign
* an alias from one type of trained model to another. If you use this API to
* update an alias and there are very few input fields in common between the old
* and new trained models for the model alias, the API returns a warning.
*
* @param fn
* a function that initializes a builder to create the
* {@link PutTrainedModelAliasRequest}
* @see Documentation
* on elastic.co
*/
public final PutTrainedModelAliasResponse putTrainedModelAlias(
Function> fn)
throws IOException, ElasticsearchException {
return putTrainedModelAlias(fn.apply(new PutTrainedModelAliasRequest.Builder()).build());
}
// ----- Endpoint: ml.put_trained_model_definition_part
/**
* Create part of a trained model definition.
*
* @see Documentation
* on elastic.co
*/
public PutTrainedModelDefinitionPartResponse putTrainedModelDefinitionPart(
PutTrainedModelDefinitionPartRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PutTrainedModelDefinitionPartRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Create part of a trained model definition.
*
* @param fn
* a function that initializes a builder to create the
* {@link PutTrainedModelDefinitionPartRequest}
* @see Documentation
* on elastic.co
*/
public final PutTrainedModelDefinitionPartResponse putTrainedModelDefinitionPart(
Function> fn)
throws IOException, ElasticsearchException {
return putTrainedModelDefinitionPart(fn.apply(new PutTrainedModelDefinitionPartRequest.Builder()).build());
}
// ----- Endpoint: ml.put_trained_model_vocabulary
/**
* Create a trained model vocabulary. This API is supported only for natural
* language processing (NLP) models. The vocabulary is stored in the index as
* described in inference_config.*.vocabulary of the trained model
* definition.
*
* @see Documentation
* on elastic.co
*/
public PutTrainedModelVocabularyResponse putTrainedModelVocabulary(PutTrainedModelVocabularyRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) PutTrainedModelVocabularyRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Create a trained model vocabulary. This API is supported only for natural
* language processing (NLP) models. The vocabulary is stored in the index as
* described in inference_config.*.vocabulary of the trained model
* definition.
*
* @param fn
* a function that initializes a builder to create the
* {@link PutTrainedModelVocabularyRequest}
* @see Documentation
* on elastic.co
*/
public final PutTrainedModelVocabularyResponse putTrainedModelVocabulary(
Function> fn)
throws IOException, ElasticsearchException {
return putTrainedModelVocabulary(fn.apply(new PutTrainedModelVocabularyRequest.Builder()).build());
}
// ----- Endpoint: ml.reset_job
/**
* Reset an anomaly detection job. All model state and results are deleted. The
* job is ready to start over as if it had just been created. It is not
* currently possible to reset multiple jobs using wildcards or a comma
* separated list.
*
* @see Documentation
* on elastic.co
*/
public ResetJobResponse resetJob(ResetJobRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) ResetJobRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Reset an anomaly detection job. All model state and results are deleted. The
* job is ready to start over as if it had just been created. It is not
* currently possible to reset multiple jobs using wildcards or a comma
* separated list.
*
* @param fn
* a function that initializes a builder to create the
* {@link ResetJobRequest}
* @see Documentation
* on elastic.co
*/
public final ResetJobResponse resetJob(Function> fn)
throws IOException, ElasticsearchException {
return resetJob(fn.apply(new ResetJobRequest.Builder()).build());
}
// ----- Endpoint: ml.revert_model_snapshot
/**
* Revert to a snapshot. The machine learning features react quickly to
* anomalous input, learning new behaviors in data. Highly anomalous input
* increases the variance in the models whilst the system learns whether this is
* a new step-change in behavior or a one-off event. In the case where this
* anomalous input is known to be a one-off, then it might be appropriate to
* reset the model state to a time before this event. For example, you might
* consider reverting to a saved snapshot after Black Friday or a critical
* system failure.
*
* @see Documentation
* on elastic.co
*/
public RevertModelSnapshotResponse revertModelSnapshot(RevertModelSnapshotRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) RevertModelSnapshotRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Revert to a snapshot. The machine learning features react quickly to
* anomalous input, learning new behaviors in data. Highly anomalous input
* increases the variance in the models whilst the system learns whether this is
* a new step-change in behavior or a one-off event. In the case where this
* anomalous input is known to be a one-off, then it might be appropriate to
* reset the model state to a time before this event. For example, you might
* consider reverting to a saved snapshot after Black Friday or a critical
* system failure.
*
* @param fn
* a function that initializes a builder to create the
* {@link RevertModelSnapshotRequest}
* @see Documentation
* on elastic.co
*/
public final RevertModelSnapshotResponse revertModelSnapshot(
Function> fn)
throws IOException, ElasticsearchException {
return revertModelSnapshot(fn.apply(new RevertModelSnapshotRequest.Builder()).build());
}
// ----- Endpoint: ml.set_upgrade_mode
/**
* Set upgrade_mode for ML indices. Sets a cluster wide upgrade_mode setting
* that prepares machine learning indices for an upgrade. When upgrading your
* cluster, in some circumstances you must restart your nodes and reindex your
* machine learning indices. In those circumstances, there must be no machine
* learning jobs running. You can close the machine learning jobs, do the
* upgrade, then open all the jobs again. Alternatively, you can use this API to
* temporarily halt tasks associated with the jobs and datafeeds and prevent new
* jobs from opening. You can also use this API during upgrades that do not
* require you to reindex your machine learning indices, though stopping jobs is
* not a requirement in that case. You can see the current value for the
* upgrade_mode setting by using the get machine learning info API.
*
* @see Documentation
* on elastic.co
*/
public SetUpgradeModeResponse setUpgradeMode(SetUpgradeModeRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) SetUpgradeModeRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Set upgrade_mode for ML indices. Sets a cluster wide upgrade_mode setting
* that prepares machine learning indices for an upgrade. When upgrading your
* cluster, in some circumstances you must restart your nodes and reindex your
* machine learning indices. In those circumstances, there must be no machine
* learning jobs running. You can close the machine learning jobs, do the
* upgrade, then open all the jobs again. Alternatively, you can use this API to
* temporarily halt tasks associated with the jobs and datafeeds and prevent new
* jobs from opening. You can also use this API during upgrades that do not
* require you to reindex your machine learning indices, though stopping jobs is
* not a requirement in that case. You can see the current value for the
* upgrade_mode setting by using the get machine learning info API.
*
* @param fn
* a function that initializes a builder to create the
* {@link SetUpgradeModeRequest}
* @see Documentation
* on elastic.co
*/
public final SetUpgradeModeResponse setUpgradeMode(
Function> fn)
throws IOException, ElasticsearchException {
return setUpgradeMode(fn.apply(new SetUpgradeModeRequest.Builder()).build());
}
/**
* Set upgrade_mode for ML indices. Sets a cluster wide upgrade_mode setting
* that prepares machine learning indices for an upgrade. When upgrading your
* cluster, in some circumstances you must restart your nodes and reindex your
* machine learning indices. In those circumstances, there must be no machine
* learning jobs running. You can close the machine learning jobs, do the
* upgrade, then open all the jobs again. Alternatively, you can use this API to
* temporarily halt tasks associated with the jobs and datafeeds and prevent new
* jobs from opening. You can also use this API during upgrades that do not
* require you to reindex your machine learning indices, though stopping jobs is
* not a requirement in that case. You can see the current value for the
* upgrade_mode setting by using the get machine learning info API.
*
* @see Documentation
* on elastic.co
*/
public SetUpgradeModeResponse setUpgradeMode() throws IOException, ElasticsearchException {
return this.transport.performRequest(new SetUpgradeModeRequest.Builder().build(),
SetUpgradeModeRequest._ENDPOINT, this.transportOptions);
}
// ----- Endpoint: ml.start_data_frame_analytics
/**
* Start a data frame analytics job. A data frame analytics job can be started
* and stopped multiple times throughout its lifecycle. If the destination index
* does not exist, it is created automatically the first time you start the data
* frame analytics job. The index.number_of_shards and
* index.number_of_replicas settings for the destination index are
* copied from the source index. If there are multiple source indices, the
* destination index copies the highest setting values. The mappings for the
* destination index are also copied from the source indices. If there are any
* mapping conflicts, the job fails to start. If the destination index exists,
* it is used as is. You can therefore set up the destination index in advance
* with custom settings and mappings.
*
* @see Documentation
* on elastic.co
*/
public StartDataFrameAnalyticsResponse startDataFrameAnalytics(StartDataFrameAnalyticsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) StartDataFrameAnalyticsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Start a data frame analytics job. A data frame analytics job can be started
* and stopped multiple times throughout its lifecycle. If the destination index
* does not exist, it is created automatically the first time you start the data
* frame analytics job. The index.number_of_shards and
* index.number_of_replicas settings for the destination index are
* copied from the source index. If there are multiple source indices, the
* destination index copies the highest setting values. The mappings for the
* destination index are also copied from the source indices. If there are any
* mapping conflicts, the job fails to start. If the destination index exists,
* it is used as is. You can therefore set up the destination index in advance
* with custom settings and mappings.
*
* @param fn
* a function that initializes a builder to create the
* {@link StartDataFrameAnalyticsRequest}
* @see Documentation
* on elastic.co
*/
public final StartDataFrameAnalyticsResponse startDataFrameAnalytics(
Function> fn)
throws IOException, ElasticsearchException {
return startDataFrameAnalytics(fn.apply(new StartDataFrameAnalyticsRequest.Builder()).build());
}
// ----- Endpoint: ml.start_datafeed
/**
* Start datafeeds.
*
* A datafeed must be started in order to retrieve data from Elasticsearch. A
* datafeed can be started and stopped multiple times throughout its lifecycle.
*
* Before you can start a datafeed, the anomaly detection job must be open.
* Otherwise, an error occurs.
*
* If you restart a stopped datafeed, it continues processing input data from
* the next millisecond after it was stopped. If new data was indexed for that
* exact millisecond between stopping and starting, it will be ignored.
*
* When Elasticsearch security features are enabled, your datafeed remembers
* which roles the last user to create or update it had at the time of creation
* or update and runs the query using those same roles. If you provided
* secondary authorization headers when you created or updated the datafeed,
* those credentials are used instead.
*
* @see Documentation
* on elastic.co
*/
public StartDatafeedResponse startDatafeed(StartDatafeedRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) StartDatafeedRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Start datafeeds.
*
* A datafeed must be started in order to retrieve data from Elasticsearch. A
* datafeed can be started and stopped multiple times throughout its lifecycle.
*
* Before you can start a datafeed, the anomaly detection job must be open.
* Otherwise, an error occurs.
*
* If you restart a stopped datafeed, it continues processing input data from
* the next millisecond after it was stopped. If new data was indexed for that
* exact millisecond between stopping and starting, it will be ignored.
*
* When Elasticsearch security features are enabled, your datafeed remembers
* which roles the last user to create or update it had at the time of creation
* or update and runs the query using those same roles. If you provided
* secondary authorization headers when you created or updated the datafeed,
* those credentials are used instead.
*
* @param fn
* a function that initializes a builder to create the
* {@link StartDatafeedRequest}
* @see Documentation
* on elastic.co
*/
public final StartDatafeedResponse startDatafeed(
Function> fn)
throws IOException, ElasticsearchException {
return startDatafeed(fn.apply(new StartDatafeedRequest.Builder()).build());
}
// ----- Endpoint: ml.start_trained_model_deployment
/**
* Start a trained model deployment. It allocates the model to every machine
* learning node.
*
* @see Documentation
* on elastic.co
*/
public StartTrainedModelDeploymentResponse startTrainedModelDeployment(StartTrainedModelDeploymentRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) StartTrainedModelDeploymentRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Start a trained model deployment. It allocates the model to every machine
* learning node.
*
* @param fn
* a function that initializes a builder to create the
* {@link StartTrainedModelDeploymentRequest}
* @see Documentation
* on elastic.co
*/
public final StartTrainedModelDeploymentResponse startTrainedModelDeployment(
Function> fn)
throws IOException, ElasticsearchException {
return startTrainedModelDeployment(fn.apply(new StartTrainedModelDeploymentRequest.Builder()).build());
}
// ----- Endpoint: ml.stop_data_frame_analytics
/**
* Stop data frame analytics jobs. A data frame analytics job can be started and
* stopped multiple times throughout its lifecycle.
*
* @see Documentation
* on elastic.co
*/
public StopDataFrameAnalyticsResponse stopDataFrameAnalytics(StopDataFrameAnalyticsRequest request)
throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) StopDataFrameAnalyticsRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Stop data frame analytics jobs. A data frame analytics job can be started and
* stopped multiple times throughout its lifecycle.
*
* @param fn
* a function that initializes a builder to create the
* {@link StopDataFrameAnalyticsRequest}
* @see Documentation
* on elastic.co
*/
public final StopDataFrameAnalyticsResponse stopDataFrameAnalytics(
Function> fn)
throws IOException, ElasticsearchException {
return stopDataFrameAnalytics(fn.apply(new StopDataFrameAnalyticsRequest.Builder()).build());
}
// ----- Endpoint: ml.stop_datafeed
/**
* Stop datafeeds. A datafeed that is stopped ceases to retrieve data from
* Elasticsearch. A datafeed can be started and stopped multiple times
* throughout its lifecycle.
*
* @see Documentation
* on elastic.co
*/
public StopDatafeedResponse stopDatafeed(StopDatafeedRequest request) throws IOException, ElasticsearchException {
@SuppressWarnings("unchecked")
JsonEndpoint endpoint = (JsonEndpoint) StopDatafeedRequest._ENDPOINT;
return this.transport.performRequest(request, endpoint, this.transportOptions);
}
/**
* Stop datafeeds. A datafeed that is stopped ceases to retrieve data from
* Elasticsearch. A datafeed can be started and stopped multiple times
* throughout its lifecycle.
*
* @param fn
* a function that initializes a builder to create the
* {@link StopDatafeedRequest}
* @see