private void projectDataset()

in contrib/format-hdf5/src/main/java/org/apache/drill/exec/store/hdf5/HDF5BatchReader.java [539:669]
118 lines of code
26 McCabe index (conditional complexity)

  private void projectDataset(RowSetLoader rowWriter, String datapath) {
    String fieldName = HDF5Utils.getNameFromPath(datapath);
    Dataset dataset= hdfFile.getDatasetByPath(datapath);

    // If the dataset is larger than 16MB, do not project the dataset
    if (dataset.getSizeInBytes() > MAX_DATASET_SIZE) {
      logger.warn("Dataset {} is greater than 16MB.  Data will be truncated in Metadata view.", datapath);
    }

    int[] dimensions = dataset.getDimensions();
    // Case for single dimensional data
    if (dimensions.length == 1) {
      MinorType currentDataType = HDF5Utils.getDataType(dataset.getDataType());

      Object data;
      try {
        data = dataset.getData();
      } catch (Exception e) {
        logger.debug("Error reading {}", datapath);
        return;
      }
      assert currentDataType != null;

      // Skip null datasets
      if (data == null) {
        return;
      }

      switch (currentDataType) {
        case GENERIC_OBJECT:
          logger.warn("Couldn't read {}", datapath );
          break;
        case VARCHAR:
          String[] stringData = (String[])data;
          writeStringListColumn(rowWriter, fieldName, stringData);
          break;
        case TIMESTAMP:
          long[] longList = (long[])data;
          writeTimestampListColumn(rowWriter, fieldName, longList);
          break;
        case INT:
          int[] intList = (int[])data;
          writeIntListColumn(rowWriter, fieldName, intList);
          break;
        case SMALLINT:
          short[] shortList = (short[])data;
          writeSmallIntColumn(rowWriter, fieldName, shortList);
          break;
        case TINYINT:
          byte[] byteList = (byte[])data;
          writeByteListColumn(rowWriter, fieldName, byteList);
          break;
        case FLOAT4:
          float[] tempFloatList = (float[])data;
          writeFloat4ListColumn(rowWriter, fieldName, tempFloatList);
          break;
        case FLOAT8:
          double[] tempDoubleList = (double[])data;
          writeFloat8ListColumn(rowWriter, fieldName, tempDoubleList);
          break;
        case BIGINT:
          long[] tempBigIntList = (long[])data;
          writeLongListColumn(rowWriter, fieldName, tempBigIntList);
          break;
        case MAP:
          try {
            getAndMapCompoundData(datapath, hdfFile, rowWriter);
          } catch (Exception e) {
            throw UserException
              .dataReadError()
              .message("Error writing Compound Field: " + e.getMessage())
              .addContext(errorContext)
              .build(logger);
          }
          break;
        default:
          // Case for data types that cannot be read
          logger.warn("{} not implemented.", currentDataType.name());
      }
    } else if (dimensions.length == 2) {
      // Case for 2D data sets. These are projected as lists of lists or maps of maps
      int cols = dimensions[1];
      int rows = dimensions[0];

      // TODO Add Boolean, Small and TinyInt data types
      switch (HDF5Utils.getDataType(dataset.getDataType())) {
        case INT:
          int[][] colData = (int[][])dataset.getData();
          mapIntMatrixField(colData, cols, rows, rowWriter);
          break;
        case FLOAT4:
          float[][] floatData = (float[][])dataset.getData();
          mapFloatMatrixField(floatData, cols, rows, rowWriter);
          break;
        case FLOAT8:
          double[][] doubleData = (double[][])dataset.getData();
          mapDoubleMatrixField(doubleData, cols, rows, rowWriter);
          break;
        case BIGINT:
          long[][] longData = (long[][])dataset.getData();
          mapBigIntMatrixField(longData, cols, rows, rowWriter);
          break;
        default:
          logger.warn("{} not implemented.", HDF5Utils.getDataType(dataset.getDataType()));
      }
    } else if (dimensions.length > 2){
      // Case for data sets with dimensions > 2
      int cols = dimensions[1];
      int rows = dimensions[0];
      switch (HDF5Utils.getDataType(dataset.getDataType())) {
        case INT:
          int[][] intMatrix = HDF5Utils.toIntMatrix((Object[]) dataset.getData());
          mapIntMatrixField(intMatrix, cols, rows, rowWriter);
          break;
        case FLOAT4:
          float[][] floatData = HDF5Utils.toFloatMatrix((Object[]) dataset.getData());
          mapFloatMatrixField(floatData, cols, rows, rowWriter);
          break;
        case FLOAT8:
          double[][] doubleData = HDF5Utils.toDoubleMatrix((Object[]) dataset.getData());
          mapDoubleMatrixField(doubleData, cols, rows, rowWriter);
          break;
        case BIGINT:
          long[][] longData = HDF5Utils.toLongMatrix((Object[]) dataset.getData());
          mapBigIntMatrixField(longData, cols, rows, rowWriter);
          break;
        default:
          logger.warn("{} not implemented.", HDF5Utils.getDataType(dataset.getDataType()));
      }
    }
  }