Uses of Class
com.logicalclocks.hsfs.spark.TrainingDataset
Packages that use TrainingDataset
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Uses of TrainingDataset in com.logicalclocks.hsfs.spark
Methods in com.logicalclocks.hsfs.spark that return TrainingDatasetModifier and TypeMethodDescriptionFeatureStore.getTrainingDataset(@NonNull String name, @NonNull Integer version) Deprecated.FeatureStore.getTrainingDataset(String name) Deprecated.Methods in com.logicalclocks.hsfs.spark that return types with arguments of type TrainingDatasetModifier and TypeMethodDescriptionscala.collection.Seq<TrainingDataset>FeatureStore.getTrainingDatasets(@NonNull String name) Deprecated. -
Uses of TrainingDataset in com.logicalclocks.hsfs.spark.engine
Methods in com.logicalclocks.hsfs.spark.engine that return TrainingDatasetModifier and TypeMethodDescriptionTrainingDatasetEngine.save(TrainingDataset trainingDataset, Query query, Map<String, String> userWriteOptions, List<String> labels) Make a REST call to Hopsworks to create the metadata and write the data on the File System.Methods in com.logicalclocks.hsfs.spark.engine with parameters of type TrainingDatasetModifier and TypeMethodDescriptionStatisticsEngine.computeAndSaveSplitStatistics(FeatureView featureView, TrainingDataset trainingDataset, Map<String, org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>> splitDatasets) StatisticsEngine.computeAndSaveSplitStatistics(TrainingDataset trainingDataset) StatisticsEngine.computeSplitStatistics(TrainingDataset trainingDataset) StatisticsEngine.computeSplitStatistics(TrainingDataset trainingDataset, Map<String, org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>> splitDatasets) FeatureViewEngine.computeStatistics(FeatureView featureView, TrainingDataset trainingDataset, org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>[] datasets) StatisticsEngine.computeStatistics(FeatureView featureView, TrainingDataset trainingDataset, org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> dataFrame) StatisticsEngine.computeStatistics(TrainingDataset trainingDataset, org.apache.spark.sql.Dataset<org.apache.spark.sql.Row> dataFrame) FeatureViewEngine.createTrainingDataset(FeatureView featureView, TrainingDataset trainingDataset, Map<String, String> userWriteOptions) StatisticsEngine.get(TrainingDataset trainingDataset, String commitTime) StatisticsEngine.getLast(TrainingDataset trainingDataset) FeatureViewEngine.getTrainingDataset(FeatureView featureView, TrainingDataset trainingDataset, List<String> requestedSplits, Map<String, String> userReadOptions) FeatureViewEngine.getTrainingDataset(FeatureView featureView, TrainingDataset trainingDataset, Map<String, String> userReadOptions) org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>TrainingDatasetEngine.read(TrainingDataset trainingDataset, String split, Map<String, String> providedOptions) TrainingDatasetEngine.save(TrainingDataset trainingDataset, Query query, Map<String, String> userWriteOptions, List<String> labels) Make a REST call to Hopsworks to create the metadata and write the data on the File System.org.apache.spark.sql.Dataset<org.apache.spark.sql.Row>[]SparkEngine.splitDataset(TrainingDataset trainingDataset, Query query, Map<String, String> readOptions) 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.voidFeatureViewEngine.writeTrainingDataset(FeatureView featureView, TrainingDataset trainingDataset, Map<String, String> userWriteOptions)