def __init__(self,
file_pattern,
min_bundle_size=0,
compression_type=CompressionTypes.AUTO,
splittable=True,
validate=True):
"""Initializes :class:`FileBasedSource`.
Args:
file_pattern (str): the file glob to read a string or a
:class:`~apache_beam.options.value_provider.ValueProvider`
(placeholder to inject a runtime value).
min_bundle_size (str): minimum size of bundles that should be generated
when performing initial splitting on this source.
compression_type (str): Used to handle compressed output files.
Typical value is :attr:`CompressionTypes.AUTO
<apache_beam.io.filesystem.CompressionTypes.AUTO>`,
in which case the final file path's extension will be used to detect
the compression.
splittable (bool): whether :class:`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 :data:`False`,
:class:`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
:data:`True` by the user, :class:`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 (bool): Boolean flag to verify that the files exist during the
pipeline creation time.
Raises:
~exceptions.TypeError: when **compression_type** is not valid or if
**file_pattern** is not a :class:`str` or a
:class:`~apache_beam.options.value_provider.ValueProvider`.
~exceptions.ValueError: when compression and splittable files are
specified.
~exceptions.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
self._splittable = splittable
if validate and file_pattern.is_accessible():
self._validate()
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()
def __init__(self,
reader,
file_patterns,
min_bundle_size=0,
compression_type=CompressionTypes.AUTO,
splittable=True,
validate=True):
if not isinstance(file_patterns, ValueProvider):
file_patterns = StaticValueProvider(list, file_patterns)
self._patterns = file_patterns
self._pickle_reader = pickler.dumps(reader)
self._reader = None
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
self._splittable = splittable
if validate and file_patterns.is_accessible():
self._validate()
