Class PutDataFrameAnalyticsRequest
java.lang.Object
co.elastic.clients.elasticsearch._types.RequestBase
co.elastic.clients.elasticsearch.ml.PutDataFrameAnalyticsRequest
- All Implemented Interfaces:
JsonpSerializable
@JsonpDeserializable
public class PutDataFrameAnalyticsRequest
extends RequestBase
implements JsonpSerializable
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 Also:
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Nested Class Summary
Nested ClassesNested classes/interfaces inherited from class co.elastic.clients.elasticsearch._types.RequestBase
RequestBase.AbstractBuilder<BuilderT extends RequestBase.AbstractBuilder<BuilderT>> -
Field Summary
FieldsModifier and TypeFieldDescriptionstatic final JsonpDeserializer<PutDataFrameAnalyticsRequest>Json deserializer forPutDataFrameAnalyticsRequestEndpoint "ml.put_data_frame_analytics". -
Method Summary
Modifier and TypeMethodDescriptionfinal BooleanSpecifies whether this job can start when there is insufficient machine learning node capacity for it to be immediately assigned to a node.final DataframeAnalysisanalysis()Required - The analysis configuration, which contains the information necessary to perform one of the following types of analysis: classification, outlier detection, or regression.Specifiesincludesand/orexcludespatterns to select which fields will be included in the analysis.final StringA description of the job.dest()Required - The destination configuration.headers()API name:headersfinal Stringid()Required - Identifier for the data frame analytics job.final IntegerThe maximum number of threads to be used by the analysis.meta()API name:_metafinal StringThe approximate maximum amount of memory resources that are permitted for analytical processing.static PutDataFrameAnalyticsRequestvoidserialize(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper) Serialize this object to JSON.protected voidserializeInternal(jakarta.json.stream.JsonGenerator generator, JsonpMapper mapper) protected static voidsetupPutDataFrameAnalyticsRequestDeserializer(ObjectDeserializer<PutDataFrameAnalyticsRequest.Builder> op) final DataframeAnalyticsSourcesource()Required - The configuration of how to source the analysis data.final Stringversion()API name:versionMethods inherited from class co.elastic.clients.elasticsearch._types.RequestBase
toString
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Field Details
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_DESERIALIZER
Json deserializer forPutDataFrameAnalyticsRequest -
_ENDPOINT
public static final Endpoint<PutDataFrameAnalyticsRequest,PutDataFrameAnalyticsResponse, _ENDPOINTErrorResponse> Endpoint "ml.put_data_frame_analytics".
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Method Details
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of
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meta
API name:_meta -
allowLazyStart
Specifies whether this job can start when there is insufficient machine learning node capacity for it to be immediately assigned to a node. If set tofalseand a machine learning node with capacity to run the job cannot be immediately found, the API returns an error. If set totrue, the API does not return an error; the job waits in thestartingstate until sufficient machine learning node capacity is available. This behavior is also affected by the cluster-widexpack.ml.max_lazy_ml_nodessetting.API name:
allow_lazy_start -
analysis
Required - The analysis configuration, which contains the information necessary to perform one of the following types of analysis: classification, outlier detection, or regression.API name:
analysis -
analyzedFields
Specifiesincludesand/orexcludespatterns to select which fields will be included in the analysis. The patterns specified inexcludesare applied last, thereforeexcludestakes precedence. In other words, if the same field is specified in bothincludesandexcludes, then the field will not be included in the analysis. Ifanalyzed_fieldsis not set, only the relevant fields will be included. For example, all the numeric fields for outlier detection. The supported fields vary for each type of analysis. Outlier detection requires numeric orbooleandata to analyze. The algorithms don’t support missing values therefore fields that have data types other than numeric or boolean are ignored. Documents where included fields contain missing values, null values, or an array are also ignored. Therefore thedestindex may contain documents that don’t have an outlier score. Regression supports fields that are numeric,boolean,text,keyword, andipdata types. It is also tolerant of missing values. Fields that are supported are included in the analysis, other fields are ignored. Documents where included fields contain an array with two or more values are also ignored. Documents in thedestindex that don’t contain a results field are not included in the regression analysis. Classification supports fields that are numeric,boolean,text,keyword, andipdata types. It is also tolerant of missing values. Fields that are supported are included in the analysis, other fields are ignored. Documents where included fields contain an array with two or more values are also ignored. Documents in thedestindex that don’t contain a results field are not included in the classification analysis. Classification analysis can be improved by mapping ordinal variable values to a single number. For example, in case of age ranges, you can model the values as0-14 = 0,15-24 = 1,25-34 = 2, and so on.API name:
analyzed_fields -
description
A description of the job.API name:
description -
dest
Required - The destination configuration.API name:
dest -
headers
API name:headers -
id
Required - Identifier for the data frame analytics job. This identifier can contain lowercase alphanumeric characters (a-z and 0-9), hyphens, and underscores. It must start and end with alphanumeric characters.API name:
id -
maxNumThreads
The maximum number of threads to be used by the analysis. Using more threads may decrease the time necessary to complete the analysis at the cost of using more CPU. Note that the process may use additional threads for operational functionality other than the analysis itself.API name:
max_num_threads -
modelMemoryLimit
The approximate maximum amount of memory resources that are permitted for analytical processing. If yourelasticsearch.ymlfile contains anxpack.ml.max_model_memory_limitsetting, an error occurs when you try to create data frame analytics jobs that havemodel_memory_limitvalues greater than that setting.API name:
model_memory_limit -
source
Required - The configuration of how to source the analysis data.API name:
source -
version
API name:version -
serialize
Serialize this object to JSON.- Specified by:
serializein interfaceJsonpSerializable
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serializeInternal
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setupPutDataFrameAnalyticsRequestDeserializer
protected static void setupPutDataFrameAnalyticsRequestDeserializer(ObjectDeserializer<PutDataFrameAnalyticsRequest.Builder> op)
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