content: /*
   * Copyright © 2018-2025 Commonwealth Scientific and Industrial Research
   * Organisation (CSIRO) ABN 41 687 119 230.
   *
   * Licensed under the Apache License, Version 2.0 (the "License");
   * you may not use this file except in compliance with the License.
   * You may obtain a copy of the License at
   *
   *     http://www.apache.org/licenses/LICENSE-2.0
   *
   * Unless required by applicable law or agreed to in writing, software
   * distributed under the License is distributed on an "AS IS" BASIS,
   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   * See the License for the specific language governing permissions and
   * limitations under the License.
   */
  
  package au.csiro.pathling.test.datasource;
  
  import static java.util.Objects.requireNonNull;
  import static java.util.stream.Collectors.groupingBy;
  
  import au.csiro.pathling.encoders.FhirEncoders;
  import au.csiro.pathling.io.source.DataSource;
  import jakarta.annotation.Nonnull;
  import jakarta.annotation.Nullable;
  import java.util.HashMap;
  import java.util.List;
  import java.util.Map;
  import java.util.Set;
  import org.apache.spark.sql.Dataset;
  import org.apache.spark.sql.Row;
  import org.apache.spark.sql.SparkSession;
  import org.apache.spark.sql.catalyst.encoders.ExpressionEncoder;
  import org.hl7.fhir.instance.model.api.IBase;
  import org.hl7.fhir.instance.model.api.IBaseResource;
  
  public class ObjectDataSource implements DataSource {
  
    @Nonnull
    private final Map<String, Dataset<Row>> data = new HashMap<>();
  
    public ObjectDataSource(@Nonnull final SparkSession spark, @Nonnull final FhirEncoders encoders,
        @Nonnull final List<IBaseResource> resources) {
      final Map<String, List<IBaseResource>> groupedResources = resources.stream()
          .collect(groupingBy(IBase::fhirType));
      groupedResources.forEach((resourceType, resourceList) -> {
        final ExpressionEncoder<IBaseResource> encoder = encoders.of(resourceType);
        final Dataset<Row> dataset = spark.createDataset(resourceList, encoder).toDF();
        data.put(resourceType, dataset);
      });
    }
  
    @Nonnull
    @Override
    public Dataset<Row> read(@Nullable final String resourceCode) {
      return requireNonNull(data.get(resourceCode));
    }
  
    @Override
    public @Nonnull Set<String> getResourceTypes() {
      return data.keySet();
    }
  
  }
  