Uses of Class
com.logicalclocks.hsfs.TrainingDataset

Packages that use TrainingDataset

Package	Description
com.logicalclocks.hsfs
com.logicalclocks.hsfs.engine
com.logicalclocks.hsfs.metadata

Uses of TrainingDataset in com.logicalclocks.hsfs

Methods in com.logicalclocks.hsfs that return TrainingDataset

Modifier and Type	Method and Description
TrainingDataset	TrainingDataset.TrainingDatasetBuilder.build()
TrainingDataset	FeatureStore.getTrainingDataset(String name) Get a training dataset object with the default version `1` from the selected feature store.
TrainingDataset	FeatureStore.getTrainingDataset(@NonNull String name, @NonNull Integer version) Get a training dataset object from the selected feature store.

Methods in com.logicalclocks.hsfs that return types with arguments of type TrainingDataset

Modifier and Type	Method and Description
scala.collection.Seq<TrainingDataset>	FeatureStore.getTrainingDatasets(@NonNull String name) Get all versions of a training dataset object from the selected feature store.

Uses of TrainingDataset in com.logicalclocks.hsfs.engine

Methods in com.logicalclocks.hsfs.engine that return TrainingDataset

Modifier and Type	Method and Description
TrainingDataset	TrainingDatasetEngine.save(TrainingDataset trainingDataset, Query query, Map<String,String> userWriteOptions) Make a REST call to Hopsworks to create the metadata and write the data on the File System.

Methods in com.logicalclocks.hsfs.engine with parameters of type TrainingDataset

Modifier and Type	Method and Description
void	TrainingDatasetEngine.addTag(TrainingDataset trainingDataset, String name, Object value)
Statistics	StatisticsEngine.computeStatistics(FeatureView featureView, TrainingDataset trainingDataset, org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> dataFrame)
Statistics	FeatureViewEngine.computeStatistics(FeatureView featureView, TrainingDataset trainingDataset, org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>[] datasets)
Statistics	StatisticsEngine.computeStatistics(TrainingDataset trainingDataset, org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> dataFrame)
TrainingDatasetBundle	FeatureViewEngine.createTrainingDataset(FeatureView featureView, TrainingDataset trainingDataset, Map<String,String> userWriteOptions)
void	TrainingDatasetEngine.delete(TrainingDataset trainingDataset)
void	TrainingDatasetEngine.deleteTag(TrainingDataset trainingDataset, String name)
Statistics	StatisticsEngine.get(TrainingDataset trainingDataset, String commitTime)
List<Object>	VectorServer.getFeatureVector(TrainingDataset trainingDataset, Map<String,Object> entry)
List<Object>	VectorServer.getFeatureVector(TrainingDataset trainingDataset, Map<String,Object> entry, boolean external)
List<List<Object>>	VectorServer.getFeatureVectors(TrainingDataset trainingDataset, Map<String,List<Object>> entry)
List<List<Object>>	VectorServer.getFeatureVectors(TrainingDataset trainingDataset, Map<String,List<Object>> entry, boolean external)
Statistics	StatisticsEngine.getLast(TrainingDataset trainingDataset)
String	TrainingDatasetEngine.getQuery(TrainingDataset trainingDataset, Storage storage, boolean withLabel, boolean isHiveQuery)
Statistics	StatisticsEngine.getSplitStatistics(TrainingDataset trainingDataset)
Statistics	StatisticsEngine.getSplitStatistics(TrainingDataset trainingDataset, Map<String,org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>> splitDatasets)
Object	TrainingDatasetEngine.getTag(TrainingDataset trainingDataset, String name)
Map<String,Object>	TrainingDatasetEngine.getTags(TrainingDataset trainingDataset)
TrainingDatasetBundle	FeatureViewEngine.getTrainingDataset(FeatureView featureView, TrainingDataset trainingDataset, List<String> requestedSplits, Map<String,String> userReadOptions)
TrainingDatasetBundle	FeatureViewEngine.getTrainingDataset(FeatureView featureView, TrainingDataset trainingDataset, Map<String,String> userReadOptions)
void	VectorServer.initPreparedStatement(TrainingDataset trainingDataset, boolean batch)
void	VectorServer.initPreparedStatement(TrainingDataset trainingDataset, boolean batch, boolean external)
void	VectorServer.initServing(TrainingDataset trainingDataset, boolean batch)
void	VectorServer.initServing(TrainingDataset trainingDataset, boolean batch, boolean external)
org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>	TrainingDatasetEngine.read(TrainingDataset trainingDataset, String split, Map<String,String> providedOptions)
Statistics	StatisticsEngine.registerSplitStatistics(FeatureView featureView, TrainingDataset trainingDataset, Map<String,org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>> splitDatasets)
Statistics	StatisticsEngine.registerSplitStatistics(TrainingDataset trainingDataset)
TrainingDataset	TrainingDatasetEngine.save(TrainingDataset trainingDataset, Query query, Map<String,String> userWriteOptions) Make a REST call to Hopsworks to create the metadata and write the data on the File System.
void	CodeEngine.saveCode(TrainingDataset trainingDataset)
org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>[]	SparkEngine.splitDataset(TrainingDataset trainingDataset, Query query, Map<String,String> readOptions)
void	TrainingDatasetEngine.updateStatisticsConfig(TrainingDataset trainingDataset)
org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>[]	SparkEngine.write(TrainingDataset trainingDataset, Query query, Map<String,String> queryReadOptions, Map<String,String> writeOptions, org.apache.spark.sql.SaveMode saveMode) Setup Spark to write the data on the File System.
void	FeatureViewEngine.writeTrainingDataset(FeatureView featureView, TrainingDataset trainingDataset, Map<String,String> userWriteOptions)

Uses of TrainingDataset in com.logicalclocks.hsfs.metadata

Methods in com.logicalclocks.hsfs.metadata that return TrainingDataset

Modifier and Type	Method and Description
TrainingDataset	FeatureViewApi.createTrainingData(String featureViewName, Integer featureViewVersion, TrainingDataset trainingData)
TrainingDataset	TrainingDatasetApi.createTrainingDataset(TrainingDataset trainingDataset)
TrainingDataset	FeatureViewApi.getTrainingData(FeatureStore featureStore, String featureViewName, Integer featureViewVersion, Integer trainingDataVersion)
TrainingDataset	TrainingDatasetApi.getTrainingDataset(FeatureStore featureStore, String tdName, Integer tdVersion)
TrainingDataset	TrainingDatasetApi.updateMetadata(TrainingDataset trainingDataset, String queryParameter)

Methods in com.logicalclocks.hsfs.metadata that return types with arguments of type TrainingDataset

Modifier and Type	Method and Description
List<TrainingDataset>	TrainingDatasetApi.get(FeatureStore featureStore, String tdName, Integer tdVersion)

Methods in com.logicalclocks.hsfs.metadata with parameters of type TrainingDataset

Modifier and Type	Method and Description
void	TagsApi.add(TrainingDataset trainingDataset, String name, Object value)
TrainingDataset	FeatureViewApi.createTrainingData(String featureViewName, Integer featureViewVersion, TrainingDataset trainingData)
TrainingDataset	TrainingDatasetApi.createTrainingDataset(TrainingDataset trainingDataset)
void	TrainingDatasetApi.delete(TrainingDataset trainingDataset)
void	TagsApi.deleteTag(TrainingDataset trainingDataset, String name)
Map<String,Object>	TagsApi.get(TrainingDataset trainingDataset)
Statistics	StatisticsApi.get(TrainingDataset trainingDataset, String commitTime)
Object	TagsApi.get(TrainingDataset trainingDataset, String name)
Statistics	StatisticsApi.getLast(TrainingDataset trainingDataset)
FsQuery	TrainingDatasetApi.getQuery(TrainingDataset trainingDataset, boolean withLabel, boolean isHiveQuery)
List<ServingPreparedStatement>	TrainingDatasetApi.getServingPreparedStatement(TrainingDataset trainingDataset, boolean batch)
List<TransformationFunctionAttached>	TrainingDatasetApi.getTransformationFunctions(TrainingDataset trainingDataset)
void	CodeApi.post(TrainingDataset trainingDataset, Code code, String entityId, Code.RunType type, String browserHostName)
Statistics	StatisticsApi.post(TrainingDataset trainingDataset, Statistics statistics)
TrainingDataset	TrainingDatasetApi.updateMetadata(TrainingDataset trainingDataset, String queryParameter)