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# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from itertools import count
from numbers import Integral
from pyarrow import types
from pyarrow.lib import Schema
import pyarrow._orc as _orc
def _is_map(typ):
return (types.is_list(typ) and
types.is_struct(typ.value_type) and
typ.value_type.num_fields == 2 and
typ.value_type[0].name == 'key' and
typ.value_type[1].name == 'value')
def _traverse(typ, counter):
if isinstance(typ, Schema) or types.is_struct(typ):
for field in typ:
path = (field.name,)
yield path, next(counter)
for sub, c in _traverse(field.type, counter):
yield path + sub, c
elif _is_map(typ):
yield from _traverse(typ.value_type, counter)
elif types.is_list(typ):
# Skip one index for list type, since this can never be selected
# directly
next(counter)
yield from _traverse(typ.value_type, counter)
elif types.is_union(typ):
# Union types not supported, just skip the indexes
for dtype in typ:
next(counter)
for sub_c in _traverse(dtype, counter):
pass
def _schema_to_indices(schema):
return {'.'.join(i): c for i, c in _traverse(schema, count(1))}
[docs]class ORCFile:
"""
Reader interface for a single ORC file
Parameters
----------
source : str or pyarrow.io.NativeFile
Readable source. For passing Python file objects or byte buffers,
see pyarrow.io.PythonFileInterface or pyarrow.io.BufferReader.
"""
[docs] def __init__(self, source):
self.reader = _orc.ORCReader()
self.reader.open(source)
self._column_index_lookup = _schema_to_indices(self.schema)
@property
def schema(self):
"""The file schema, as an arrow schema"""
return self.reader.schema()
@property
def nrows(self):
"""The number of rows in the file"""
return self.reader.nrows()
@property
def nstripes(self):
"""The number of stripes in the file"""
return self.reader.nstripes()
def _select_indices(self, columns=None):
if columns is None:
return None
schema = self.schema
indices = []
for col in columns:
if isinstance(col, Integral):
col = int(col)
if 0 <= col < len(schema):
col = schema[col].name
else:
raise ValueError("Column indices must be in 0 <= ind < %d,"
" got %d" % (len(schema), col))
if col in self._column_index_lookup:
indices.append(self._column_index_lookup[col])
else:
raise ValueError("Unknown column name %r" % col)
return indices
[docs] def read_stripe(self, n, columns=None):
"""Read a single stripe from the file.
Parameters
----------
n : int
The stripe index
columns : list
If not None, only these columns will be read from the stripe. A
column name may be a prefix of a nested field, e.g. 'a' will select
'a.b', 'a.c', and 'a.d.e'
Returns
-------
pyarrow.lib.RecordBatch
Content of the stripe as a RecordBatch.
"""
include_indices = self._select_indices(columns)
return self.reader.read_stripe(n, include_indices=include_indices)
[docs] def read(self, columns=None):
"""Read the whole file.
Parameters
----------
columns : list
If not None, only these columns will be read from the file. A
column name may be a prefix of a nested field, e.g. 'a' will select
'a.b', 'a.c', and 'a.d.e'
Returns
-------
pyarrow.lib.Table
Content of the file as a Table.
"""
include_indices = self._select_indices(columns)
return self.reader.read(include_indices=include_indices)