Uses of Class
com.logicalclocks.hsfs.spark.FeatureView

Packages that use FeatureView

Package	Description
com.logicalclocks.hsfs.spark
com.logicalclocks.hsfs.spark.engine

Uses of FeatureView in com.logicalclocks.hsfs.spark

Methods in com.logicalclocks.hsfs.spark that return FeatureView

Modifier and Type	Method	Description
FeatureView	FeatureView.FeatureViewBuilder.build()
FeatureView	FeatureStore.getFeatureView(@NonNull String name, @NonNull Integer version)	Get a feature view object from the selected feature store.
FeatureView	FeatureStore.getFeatureView(String name)	Get a feature view object with the default version `1` from the selected feature store.
FeatureView	FeatureStore.getOrCreateFeatureView(String name, Query query, Integer version)	Get feature view metadata object or create a new one if it doesn't exist.
FeatureView	FeatureStore.getOrCreateFeatureView(String name, Query query, Integer version, String description, List<String> labels)	Get feature view metadata object or create a new one if it doesn't exist.
FeatureView	FeatureView.update(FeatureView other)	Update the description of the feature view.

Methods in com.logicalclocks.hsfs.spark with parameters of type FeatureView

Modifier and Type	Method	Description
FeatureView	FeatureView.update(FeatureView other)	Update the description of the feature view.

Uses of FeatureView in com.logicalclocks.hsfs.spark.engine

Methods in com.logicalclocks.hsfs.spark.engine that return FeatureView

Modifier and Type	Method	Description
FeatureView	FeatureViewEngine.get(FeatureStore featureStore, String name, Integer version)
FeatureView	FeatureViewEngine.getOrCreateFeatureView(FeatureStore featureStore, String name, Integer version, Query query, String description, List<String> labels)
FeatureView	FeatureViewEngine.update(FeatureView featureView)

Methods in com.logicalclocks.hsfs.spark.engine with parameters of type FeatureView

Modifier and Type	Method	Description
Statistics	StatisticsEngine.computeAndSaveSplitStatistics(FeatureView featureView, TrainingDataset trainingDataset, Map<String,org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>> splitDatasets)
Statistics	FeatureViewEngine.computeStatistics(FeatureView featureView, TrainingDataset trainingDataset, org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>[] datasets)
Statistics	StatisticsEngine.computeStatistics(FeatureView featureView, TrainingDataset trainingDataset, org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> dataFrame)
TrainingDatasetBundle	FeatureViewEngine.createTrainingDataset(FeatureView featureView, TrainingDataset trainingDataset, Map<String,String> userWriteOptions)
org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>	FeatureViewEngine.getBatchData(FeatureView featureView, Date startTime, Date endTime, Map<String,String> readOptions, Integer trainingDataVersion)
Query	FeatureViewEngine.getBatchQuery(FeatureView featureView, Date startTime, Date endTime, Boolean withLabels, Integer trainingDataVersion)
String	FeatureViewEngine.getBatchQueryString(FeatureView featureView, Date startTime, Date endTime, Integer trainingDataVersion)
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)
TrainingDatasetBundle	FeatureViewEngine.getTrainingDataset(FeatureView featureView, Integer trainingDatasetVersion, List<String> requestedSplits, Map<String,String> userReadOptions)
void	FeatureViewEngine.recreateTrainingDataset(FeatureView featureView, Integer version, Map<String,String> userWriteOptions)
FeatureView	FeatureViewEngine.update(FeatureView featureView)
void	FeatureViewEngine.writeTrainingDataset(FeatureView featureView, TrainingDataset trainingDataset, Map<String,String> userWriteOptions)