Source code for apache_beam.io.filebasedsource

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"""A framework for developing sources for new file types.

To create a source for a new file type a sub-class of ``FileBasedSource`` should
be created. Sub-classes of ``FileBasedSource`` must implement the method
``FileBasedSource.read_records()``. Please read the documentation of that method
for more details.

For an example implementation of ``FileBasedSource`` see ``avroio.AvroSource``.
"""

from apache_beam.internal import pickler
from apache_beam.io import concat_source
from apache_beam.io import iobase
from apache_beam.io import range_trackers
from apache_beam.io.filesystem import CompressionTypes
from apache_beam.io.filesystems import FileSystems
from apache_beam.transforms.display import DisplayDataItem
from apache_beam.options.value_provider import ValueProvider
from apache_beam.options.value_provider import StaticValueProvider
from apache_beam.options.value_provider import check_accessible

MAX_NUM_THREADS_FOR_SIZE_ESTIMATION = 25

__all__ = ['FileBasedSource']


[docs]class FileBasedSource(iobase.BoundedSource): """A ``BoundedSource`` for reading a file glob of a given type.""" MIN_NUMBER_OF_FILES_TO_STAT = 100 MIN_FRACTION_OF_FILES_TO_STAT = 0.01 def __init__(self, file_pattern, min_bundle_size=0, compression_type=CompressionTypes.AUTO, splittable=True, validate=True): """Initializes ``FileBasedSource``. Args: file_pattern: the file glob to read a string or a ValueProvider (placeholder to inject a runtime value). min_bundle_size: minimum size of bundles that should be generated when performing initial splitting on this source. compression_type: compression type to use splittable: whether FileBasedSource should try to logically split a single file into data ranges so that different parts of the same file can be read in parallel. If set to False, FileBasedSource will prevent both initial and dynamic splitting of sources for single files. File patterns that represent multiple files may still get split into sources for individual files. Even if set to True by the user, FileBasedSource may choose to not split the file, for example, for compressed files where currently it is not possible to efficiently read a data range without decompressing the whole file. validate: Boolean flag to verify that the files exist during the pipeline creation time. Raises: TypeError: when compression_type is not valid or if file_pattern is not a string or a ValueProvider. ValueError: when compression and splittable files are specified. IOError: when the file pattern specified yields an empty result. """ if not isinstance(file_pattern, (basestring, ValueProvider)): raise TypeError('%s: file_pattern must be of type string' ' or ValueProvider; got %r instead' % (self.__class__.__name__, file_pattern)) if isinstance(file_pattern, basestring): file_pattern = StaticValueProvider(str, file_pattern) self._pattern = file_pattern self._concat_source = None self._min_bundle_size = min_bundle_size if not CompressionTypes.is_valid_compression_type(compression_type): raise TypeError('compression_type must be CompressionType object but ' 'was %s' % type(compression_type)) self._compression_type = compression_type if compression_type in (CompressionTypes.UNCOMPRESSED, CompressionTypes.AUTO): self._splittable = splittable else: # We can't split compressed files efficiently so turn off splitting. self._splittable = False if validate and file_pattern.is_accessible(): self._validate()
[docs] def display_data(self): return {'file_pattern': DisplayDataItem(str(self._pattern), label="File Pattern"), 'compression': DisplayDataItem(str(self._compression_type), label='Compression Type')}
@check_accessible(['_pattern']) def _get_concat_source(self): if self._concat_source is None: pattern = self._pattern.get() single_file_sources = [] match_result = FileSystems.match([pattern])[0] files_metadata = match_result.metadata_list # We create a reference for FileBasedSource that will be serialized along # with each _SingleFileSource. To prevent this FileBasedSource from having # a reference to ConcatSource (resulting in quadratic space complexity) # we clone it here. file_based_source_ref = pickler.loads(pickler.dumps(self)) for file_metadata in files_metadata: file_name = file_metadata.path file_size = file_metadata.size_in_bytes if file_size == 0: continue # Ignoring empty file. # We determine splittability of this specific file. splittable = self.splittable if (splittable and self._compression_type == CompressionTypes.AUTO): compression_type = CompressionTypes.detect_compression_type( file_name) if compression_type != CompressionTypes.UNCOMPRESSED: splittable = False single_file_source = _SingleFileSource( file_based_source_ref, file_name, 0, file_size, min_bundle_size=self._min_bundle_size, splittable=splittable) single_file_sources.append(single_file_source) self._concat_source = concat_source.ConcatSource(single_file_sources) return self._concat_source
[docs] def open_file(self, file_name): return FileSystems.open( file_name, 'application/octet-stream', compression_type=self._compression_type)
@check_accessible(['_pattern']) def _validate(self): """Validate if there are actual files in the specified glob pattern """ pattern = self._pattern.get() # Limit the responses as we only want to check if something exists match_result = FileSystems.match([pattern], limits=[1])[0] if len(match_result.metadata_list) <= 0: raise IOError( 'No files found based on the file pattern %s' % pattern)
[docs] def split( self, desired_bundle_size=None, start_position=None, stop_position=None): return self._get_concat_source().split( desired_bundle_size=desired_bundle_size, start_position=start_position, stop_position=stop_position)
@check_accessible(['_pattern'])
[docs] def estimate_size(self): pattern = self._pattern.get() match_result = FileSystems.match([pattern])[0] return sum([f.size_in_bytes for f in match_result.metadata_list])
[docs] def read(self, range_tracker): return self._get_concat_source().read(range_tracker)
[docs] def get_range_tracker(self, start_position, stop_position): return self._get_concat_source().get_range_tracker(start_position, stop_position)
[docs] def read_records(self, file_name, offset_range_tracker): """Returns a generator of records created by reading file 'file_name'. Args: file_name: a ``string`` that gives the name of the file to be read. Method ``FileBasedSource.open_file()`` must be used to open the file and create a seekable file object. offset_range_tracker: a object of type ``OffsetRangeTracker``. This defines the byte range of the file that should be read. See documentation in ``iobase.BoundedSource.read()`` for more information on reading records while complying to the range defined by a given ``RangeTracker``. Returns: an iterator that gives the records read from the given file. """ raise NotImplementedError
@property def splittable(self): return self._splittable
class _SingleFileSource(iobase.BoundedSource): """Denotes a source for a specific file type.""" def __init__(self, file_based_source, file_name, start_offset, stop_offset, min_bundle_size=0, splittable=True): if not isinstance(start_offset, (int, long)): raise TypeError( 'start_offset must be a number. Received: %r' % start_offset) if stop_offset != range_trackers.OffsetRangeTracker.OFFSET_INFINITY: if not isinstance(stop_offset, (int, long)): raise TypeError( 'stop_offset must be a number. Received: %r' % stop_offset) if start_offset >= stop_offset: raise ValueError( 'start_offset must be smaller than stop_offset. Received %d and %d ' 'for start and stop offsets respectively' % (start_offset, stop_offset)) self._file_name = file_name self._is_gcs_file = file_name.startswith('gs://') if file_name else False self._start_offset = start_offset self._stop_offset = stop_offset self._min_bundle_size = min_bundle_size self._file_based_source = file_based_source self._splittable = splittable def split(self, desired_bundle_size, start_offset=None, stop_offset=None): if start_offset is None: start_offset = self._start_offset if stop_offset is None: stop_offset = self._stop_offset if self._splittable: bundle_size = max(desired_bundle_size, self._min_bundle_size) bundle_start = start_offset while bundle_start < stop_offset: bundle_stop = min(bundle_start + bundle_size, stop_offset) yield iobase.SourceBundle( bundle_stop - bundle_start, _SingleFileSource( # Copying this so that each sub-source gets a fresh instance. pickler.loads(pickler.dumps(self._file_based_source)), self._file_name, bundle_start, bundle_stop, min_bundle_size=self._min_bundle_size, splittable=self._splittable), bundle_start, bundle_stop) bundle_start = bundle_stop else: # Returning a single sub-source with end offset set to OFFSET_INFINITY (so # that all data of the source gets read) since this source is # unsplittable. Choosing size of the file as end offset will be wrong for # certain unsplittable source, e.g., compressed sources. yield iobase.SourceBundle( stop_offset - start_offset, _SingleFileSource( self._file_based_source, self._file_name, start_offset, range_trackers.OffsetRangeTracker.OFFSET_INFINITY, min_bundle_size=self._min_bundle_size, splittable=self._splittable ), start_offset, range_trackers.OffsetRangeTracker.OFFSET_INFINITY ) def estimate_size(self): return self._stop_offset - self._start_offset def get_range_tracker(self, start_position, stop_position): if start_position is None: start_position = self._start_offset if stop_position is None: # If file is unsplittable we choose OFFSET_INFINITY as the default end # offset so that all data of the source gets read. Choosing size of the # file as end offset will be wrong for certain unsplittable source, for # e.g., compressed sources. stop_position = ( self._stop_offset if self._splittable else range_trackers.OffsetRangeTracker.OFFSET_INFINITY) range_tracker = range_trackers.OffsetRangeTracker( start_position, stop_position) if not self._splittable: range_tracker = range_trackers.UnsplittableRangeTracker(range_tracker) return range_tracker def read(self, range_tracker): return self._file_based_source.read_records(self._file_name, range_tracker) def default_output_coder(self): return self._file_based_source.default_output_coder()