pypaimon/pynative/reader/pyarrow_dataset_reader.py

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from typing import Optional, List

import pyarrow.dataset as ds

from pypaimon import Predicate
from pypaimon.pynative.common.row.internal_row import InternalRow
from pypaimon.pynative.reader.core.columnar_row_iterator import ColumnarRowIterator
from pypaimon.pynative.reader.core.file_record_iterator import FileRecordIterator
from pypaimon.pynative.reader.core.file_record_reader import FileRecordReader
from pypaimon.pynative.util.predicate_converter import convert_predicate


class PyArrowDatasetReader(FileRecordReader[InternalRow]):
    """
    A PyArrowDatasetReader that reads data from a dataset file using PyArrow,
    and filters it based on the provided predicate and projection.
    """

    def __init__(self, format, file_path, batch_size, projection,
                 predicate: Predicate, primary_keys: List[str], fields: List[str]):

        if primary_keys is not None:
            # TODO: utilize predicate to improve performance
            predicate = None

        if predicate is not None:
            predicate = convert_predicate(predicate)

        self._file_path = file_path
        self.dataset = ds.dataset(file_path, format=format)
        self.scanner = self.dataset.scanner(
            columns=fields,
            filter=predicate,
            batch_size=batch_size
        )
        self.batch_iterator = self.scanner.to_batches()

    def read_batch(self) -> Optional[FileRecordIterator[InternalRow]]:
        try:
            record_batch = next(self.batch_iterator, None)
            if record_batch is None:
                return None

            return ColumnarRowIterator(
                self._file_path,
                record_batch
            )
        except Exception as e:
            print(f"Error reading batch: {e}")
            raise

    def close(self):
        pass