Method EvolveBatch

cpp/src/arrow/dataset/dataset.cc:418–446

  };

  Result<compute::ExecBatch> EvolveBatch(
      const std::shared_ptr<RecordBatch>& batch,
      const std::vector<FieldPath>& dataset_selection,
      const FragmentSelection& selection) const override {
    // In this simple evolution strategy every column is either missing from the fragment
    // or included in our load of the fragment.  For the columns that are missing we
    // populate a null array and the columns that we loaded we populate in the correct
    // spot.
    DCHECK_EQ(batch->num_columns(), static_cast<int>(selection.columns().size()));
    const BasicFragmentSelection& selection_cast =
        dynamic_cast<const BasicFragmentSelection&>(selection);
    std::size_t num_out_columns =
        selection_cast.columns().size() + selection_cast.missing_columns().size();
    std::vector<Datum> columns;
    columns.reserve(num_out_columns);
    auto missing_itr = selection_cast.missing_columns().begin();
    auto batch_itr = batch->columns().begin();
    for (std::size_t idx = 0; idx < num_out_columns; idx++) {
      if (missing_itr != selection_cast.missing_columns().end() &&
          missing_itr->idx == idx) {
        columns.push_back(MakeNullScalar(missing_itr->type));
        missing_itr++;
      } else {
        columns.push_back(*batch_itr);
        batch_itr++;
      }
    }
    return compute::ExecBatch(columns, batch->num_rows());
  }

  std::string ToString() const override { return "basic-fragment-evolution"; }