Class MemMlStats.Builder
java.lang.Object
co.elastic.clients.util.ObjectBuilderBase
co.elastic.clients.util.WithJsonObjectBuilderBase<MemMlStats.Builder>
co.elastic.clients.elasticsearch.ml.get_memory_stats.MemMlStats.Builder
- All Implemented Interfaces:
WithJson<MemMlStats.Builder>,ObjectBuilder<MemMlStats>
- Enclosing class:
- MemMlStats
public static class MemMlStats.Builder
extends WithJsonObjectBuilderBase<MemMlStats.Builder>
implements ObjectBuilder<MemMlStats>
Builder for
MemMlStats.-
Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionfinal MemMlStats.BuilderanomalyDetectors(String value) Amount of native memory set aside for anomaly detection jobs.final MemMlStats.BuilderanomalyDetectorsInBytes(int value) Required - Amount of native memory, in bytes, set aside for anomaly detection jobs.build()Builds aMemMlStats.final MemMlStats.BuilderdataFrameAnalytics(String value) Amount of native memory set aside for data frame analytics jobs.final MemMlStats.BuilderdataFrameAnalyticsInBytes(int value) Required - Amount of native memory, in bytes, set aside for data frame analytics jobs.final MemMlStats.BuilderMaximum amount of native memory (separate to the JVM heap) that may be used by machine learning native processes.final MemMlStats.BuildermaxInBytes(int value) Required - Maximum amount of native memory (separate to the JVM heap), in bytes, that may be used by machine learning native processes.final MemMlStats.BuildernativeCodeOverhead(String value) Amount of native memory set aside for loading machine learning native code shared libraries.final MemMlStats.BuildernativeCodeOverheadInBytes(int value) Required - Amount of native memory, in bytes, set aside for loading machine learning native code shared libraries.final MemMlStats.BuildernativeInference(String value) Amount of native memory set aside for trained models that have a PyTorch model_type.final MemMlStats.BuildernativeInferenceInBytes(int value) Required - Amount of native memory, in bytes, set aside for trained models that have a PyTorch model_type.protected MemMlStats.Builderself()Methods inherited from class co.elastic.clients.util.WithJsonObjectBuilderBase
withJsonMethods inherited from class co.elastic.clients.util.ObjectBuilderBase
_checkSingleUse, _listAdd, _listAddAll, _mapPut, _mapPutAll
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Constructor Details
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Builder
public Builder()
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Method Details
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anomalyDetectors
Amount of native memory set aside for anomaly detection jobs.API name:
anomaly_detectors -
anomalyDetectorsInBytes
Required - Amount of native memory, in bytes, set aside for anomaly detection jobs.API name:
anomaly_detectors_in_bytes -
dataFrameAnalytics
Amount of native memory set aside for data frame analytics jobs.API name:
data_frame_analytics -
dataFrameAnalyticsInBytes
Required - Amount of native memory, in bytes, set aside for data frame analytics jobs.API name:
data_frame_analytics_in_bytes -
max
Maximum amount of native memory (separate to the JVM heap) that may be used by machine learning native processes.API name:
max -
maxInBytes
Required - Maximum amount of native memory (separate to the JVM heap), in bytes, that may be used by machine learning native processes.API name:
max_in_bytes -
nativeCodeOverhead
Amount of native memory set aside for loading machine learning native code shared libraries.API name:
native_code_overhead -
nativeCodeOverheadInBytes
Required - Amount of native memory, in bytes, set aside for loading machine learning native code shared libraries.API name:
native_code_overhead_in_bytes -
nativeInference
Amount of native memory set aside for trained models that have a PyTorch model_type.API name:
native_inference -
nativeInferenceInBytes
Required - Amount of native memory, in bytes, set aside for trained models that have a PyTorch model_type.API name:
native_inference_in_bytes -
self
- Specified by:
selfin classWithJsonObjectBuilderBase<MemMlStats.Builder>
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build
Builds aMemMlStats.- Specified by:
buildin interfaceObjectBuilder<MemMlStats>- Throws:
NullPointerException- if some of the required fields are null.
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