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package org.apache.iceberg.spark.source;

import org.apache.arrow.vector.NullCheckingForGet;
import org.apache.iceberg.CombinedScanTask;
import org.apache.iceberg.FileFormat;
import org.apache.iceberg.FileScanTask;
import org.apache.iceberg.Schema;
import org.apache.iceberg.encryption.EncryptionManager;
import org.apache.iceberg.io.CloseableIterable;
import org.apache.iceberg.io.CloseableIterator;
import org.apache.iceberg.io.FileIO;
import org.apache.iceberg.io.InputFile;
import org.apache.iceberg.mapping.NameMappingParser;
import org.apache.iceberg.parquet.Parquet;
import org.apache.iceberg.relocated.com.google.common.base.Preconditions;
import org.apache.iceberg.spark.data.vectorized.VectorizedSparkParquetReaders;
import org.apache.spark.sql.vectorized.ColumnarBatch;

class BatchDataReader extends BaseDataReader<ColumnarBatch> {
  private final Schema expectedSchema;
  private final String nameMapping;
  private final boolean caseSensitive;
  private final int batchSize;

      CombinedScanTask task, Schema expectedSchema, String nameMapping, FileIO fileIo,
      EncryptionManager encryptionManager, boolean caseSensitive, int size) {
    super(task, fileIo, encryptionManager);
    this.expectedSchema = expectedSchema;
    this.nameMapping = nameMapping;
    this.caseSensitive = caseSensitive;
    this.batchSize = size;

  CloseableIterator<ColumnarBatch> open(FileScanTask task) {
    CloseableIterable<ColumnarBatch> iter;
    InputFile location = getInputFile(task);
    Preconditions.checkNotNull(location, "Could not find InputFile associated with FileScanTask");
    if (task.file().format() == FileFormat.PARQUET) {
      Parquet.ReadBuilder builder = Parquet.read(location)
          .split(task.start(), task.length())
          .createBatchedReaderFunc(fileSchema -> VectorizedSparkParquetReaders.buildReader(expectedSchema,
              fileSchema, /* setArrowValidityVector */ NullCheckingForGet.NULL_CHECKING_ENABLED))
          // Spark eagerly consumes the batches. So the underlying memory allocated could be reused
          // without worrying about subsequent reads clobbering over each other. This improves
          // read performance as every batch read doesn't have to pay the cost of allocating memory.

      if (nameMapping != null) {

      iter = builder.build();
    } else {
      throw new UnsupportedOperationException(
          "Format: " + task.file().format() + " not supported for batched reads");
    return iter.iterator();