code
string | signature
string | docstring
string | loss_without_docstring
float64 | loss_with_docstring
float64 | factor
float64 |
|---|---|---|---|---|---|
self._shard_state.counters_map.increment(counter_name, delta)
|
def increment(self, counter_name, delta=1)
|
Increment counter value.
Args:
counter_name: name of the counter as string.
delta: increment delta as int.
| 15.057514
| 12.848257
| 1.17195
|
cursor = self._cursor
if self._query is not None:
if isinstance(self._query, db.Query):
cursor = self._query.cursor()
else:
cursor = self._query.cursor_after()
if cursor is None or isinstance(cursor, basestring):
cursor_object = False
else:
cursor_object = True
cursor = cursor.to_websafe_string()
return {"property_range": self._property_range.to_json(),
"query_spec": self._query_spec.to_json(),
"cursor": cursor,
"ns_range": self._ns_range.to_json_object(),
"name": self.__class__.__name__,
"cursor_object": cursor_object}
|
def to_json(self)
|
Inherit doc.
| 3.539522
| 3.283406
| 1.078003
|
obj = cls(property_range.PropertyRange.from_json(json["property_range"]),
namespace_range.NamespaceRange.from_json_object(json["ns_range"]),
model.QuerySpec.from_json(json["query_spec"]))
cursor = json["cursor"]
# lint bug. Class method can access protected fields.
# pylint: disable=protected-access
if cursor and json["cursor_object"]:
obj._cursor = datastore_query.Cursor.from_websafe_string(cursor)
else:
obj._cursor = cursor
return obj
|
def from_json(cls, json)
|
Inherit doc.
| 6.556374
| 6.379225
| 1.02777
|
json = {"name": self.__class__.__name__,
"num_ranges": len(self._iters)}
for i in xrange(len(self._iters)):
json_item = self._iters[i].to_json()
query_spec = json_item["query_spec"]
item_name = json_item["name"]
# Delete and move one level up
del json_item["query_spec"]
del json_item["name"]
json[str(i)] = json_item
# Store once to save space
json["query_spec"] = query_spec
json["item_name"] = item_name
return json
|
def to_json(self)
|
Inherit doc.
| 4.353416
| 4.169125
| 1.044204
|
num_ranges = int(json["num_ranges"])
query_spec = json["query_spec"]
item_name = json["item_name"]
p_range_iters = []
for i in xrange(num_ranges):
json_item = json[str(i)]
# Place query_spec, name back into each iterator
json_item["query_spec"] = query_spec
json_item["name"] = item_name
p_range_iters.append(_PropertyRangeModelIterator.from_json(json_item))
obj = cls(p_range_iters)
return obj
|
def from_json(cls, json)
|
Inherit doc.
| 4.497386
| 4.3466
| 1.034691
|
current_iter = None
if self._current_iter:
current_iter = self._current_iter.to_json()
return {"key_ranges": self._key_ranges.to_json(),
"query_spec": self._query_spec.to_json(),
"current_iter": current_iter,
"key_range_iter_cls": self._key_range_iter_cls.__name__,
"name": self.__class__.__name__}
|
def to_json(self)
|
Inherit doc.
| 3.522787
| 3.333812
| 1.056684
|
key_range_iter_cls = _KEY_RANGE_ITERATORS[json["key_range_iter_cls"]]
obj = cls(key_ranges.KeyRangesFactory.from_json(json["key_ranges"]),
model.QuerySpec.from_json(json["query_spec"]),
key_range_iter_cls)
current_iter = None
if json["current_iter"]:
current_iter = key_range_iter_cls.from_json(json["current_iter"])
# pylint: disable=protected-access
obj._current_iter = current_iter
return obj
|
def from_json(cls, json)
|
Inherit doc.
| 3.535228
| 3.425673
| 1.031981
|
cursor = self._get_cursor()
cursor_object = False
if cursor and isinstance(cursor, datastore_query.Cursor):
cursor = cursor.to_websafe_string()
cursor_object = True
return {"key_range": self._key_range.to_json(),
"query_spec": self._query_spec.to_json(),
"cursor": cursor,
"cursor_object": cursor_object}
|
def to_json(self)
|
Serializes all states into json form.
Returns:
all states in json-compatible map.
| 3.626827
| 3.563128
| 1.017877
|
obj = cls(key_range.KeyRange.from_json(json["key_range"]),
model.QuerySpec.from_json(json["query_spec"]))
cursor = json["cursor"]
# lint bug. Class method can access protected fields.
# pylint: disable=protected-access
if cursor and json["cursor_object"]:
obj._cursor = datastore_query.Cursor.from_websafe_string(cursor)
else:
obj._cursor = cursor
return obj
|
def from_json(cls, json)
|
Reverse of to_json.
| 6.384538
| 5.97815
| 1.067979
|
checked = set()
yaml = _find_mapreduce_yaml(os.path.dirname(status_file), checked)
if not yaml:
yaml = _find_mapreduce_yaml(os.getcwd(), checked)
return yaml
|
def find_mapreduce_yaml(status_file=__file__)
|
Traverse directory trees to find mapreduce.yaml file.
Begins with the location of status.py and then moves on to check the working
directory.
Args:
status_file: location of status.py, overridable for testing purposes.
Returns:
the path of mapreduce.yaml file or None if not found.
| 3.166582
| 3.667056
| 0.863522
|
dir = start
while dir not in checked:
checked.add(dir)
for mr_yaml_name in MR_YAML_NAMES:
yaml_path = os.path.join(dir, mr_yaml_name)
if os.path.exists(yaml_path):
return yaml_path
dir = os.path.dirname(dir)
return None
|
def _find_mapreduce_yaml(start, checked)
|
Traverse the directory tree identified by start until a directory already
in checked is encountered or the path of mapreduce.yaml is found.
Checked is present both to make loop termination easy to reason about and so
that the same directories do not get rechecked.
Args:
start: the path to start in and work upward from
checked: the set of already examined directories
Returns:
the path of mapreduce.yaml file or None if not found.
| 2.245196
| 2.4223
| 0.926886
|
try:
builder = yaml_object.ObjectBuilder(MapReduceYaml)
handler = yaml_builder.BuilderHandler(builder)
listener = yaml_listener.EventListener(handler)
listener.Parse(contents)
mr_info = handler.GetResults()
except (ValueError, yaml_errors.EventError), e:
raise errors.BadYamlError(e)
if len(mr_info) < 1:
raise errors.BadYamlError("No configs found in mapreduce.yaml")
if len(mr_info) > 1:
raise errors.MultipleDocumentsInMrYaml("Found %d YAML documents" %
len(mr_info))
jobs = mr_info[0]
job_names = set(j.name for j in jobs.mapreduce)
if len(jobs.mapreduce) != len(job_names):
raise errors.BadYamlError(
"Overlapping mapreduce names; names must be unique")
return jobs
|
def parse_mapreduce_yaml(contents)
|
Parses mapreduce.yaml file contents.
Args:
contents: mapreduce.yaml file contents.
Returns:
MapReduceYaml object with all the data from original file.
Raises:
errors.BadYamlError: when contents is not a valid mapreduce.yaml file.
| 3.703231
| 3.696481
| 1.001826
|
mr_yaml_path = find_mapreduce_yaml()
if not mr_yaml_path:
raise errors.MissingYamlError()
mr_yaml_file = open(mr_yaml_path)
try:
return parse(mr_yaml_file.read())
finally:
mr_yaml_file.close()
|
def get_mapreduce_yaml(parse=parse_mapreduce_yaml)
|
Locates mapreduce.yaml, loads and parses its info.
Args:
parse: Used for testing.
Returns:
MapReduceYaml object.
Raises:
errors.BadYamlError: when contents is not a valid mapreduce.yaml file or the
file is missing.
| 2.614231
| 2.976456
| 0.878303
|
all_configs = []
for config in mapreduce_yaml.mapreduce:
out = {
"name": config.name,
"mapper_input_reader": config.mapper.input_reader,
"mapper_handler": config.mapper.handler,
}
if config.mapper.params_validator:
out["mapper_params_validator"] = config.mapper.params_validator
if config.mapper.params:
param_defaults = {}
for param in config.mapper.params:
param_defaults[param.name] = param.default or param.value
out["mapper_params"] = param_defaults
if config.params:
param_defaults = {}
for param in config.params:
param_defaults[param.name] = param.default or param.value
out["params"] = param_defaults
if config.mapper.output_writer:
out["mapper_output_writer"] = config.mapper.output_writer
all_configs.append(out)
return all_configs
|
def to_dict(mapreduce_yaml)
|
Converts a MapReduceYaml file into a JSON-encodable dictionary.
For use in user-visible UI and internal methods for interfacing with
user code (like param validation). as a list
Args:
mapreduce_yaml: The Pyton representation of the mapreduce.yaml document.
Returns:
A list of configuration dictionaries.
| 1.950501
| 1.921273
| 1.015213
|
if job_config.input_reader_cls != cls:
raise errors.BadReaderParamsError(
"Expect input reader class %r, got %r." %
(cls, job_config.input_reader_cls))
|
def validate(cls, job_config)
|
Validates relevant parameters.
This method can validate fields which it deems relevant.
Args:
job_config: an instance of map_job.JobConfig.
Raises:
errors.BadReaderParamsError: required parameters are missing or invalid.
| 4.630408
| 3.831753
| 1.208431
|
ctx = context.get()
l = len(records)
key_records = [None] * l
logging.debug("Parsing")
for i in range(l):
proto = kv_pb.KeyValue()
proto.ParseFromString(records[i])
key_records[i] = (proto.key(), records[i])
logging.debug("Sorting")
key_records.sort(cmp=_compare_keys)
logging.debug("Writing")
mapper_spec = ctx.mapreduce_spec.mapper
params = input_readers._get_params(mapper_spec)
bucket_name = params.get("bucket_name")
filename = (ctx.mapreduce_spec.name + "/" + ctx.mapreduce_id + "/output-" +
ctx.shard_id + "-" + str(int(time.time())))
full_filename = "/%s/%s" % (bucket_name, filename)
filehandle = cloudstorage.open(full_filename, mode="w")
with output_writers.GCSRecordsPool(filehandle, ctx=ctx) as pool:
for key_record in key_records:
pool.append(key_record[1])
logging.debug("Finalizing")
filehandle.close()
entity = _OutputFile(key_name=full_filename,
parent=_OutputFile.get_root_key(ctx.mapreduce_id))
entity.put()
|
def _sort_records_map(records)
|
Map function sorting records.
Converts records to KeyValue protos, sorts them by key and writes them
into new GCS file. Creates _OutputFile entity to record resulting
file name.
Args:
records: list of records which are serialized KeyValue protos.
| 3.906863
| 3.491388
| 1.119
|
proto = kv_pb.KeyValues()
proto.set_key(key)
proto.value_list().extend(values)
yield proto.Encode()
|
def _merge_map(key, values, partial)
|
A map function used in merge phase.
Stores (key, values) into KeyValues proto and yields its serialization.
Args:
key: values key.
values: values themselves.
partial: True if more values for this key will follow. False otherwise.
Yields:
The proto.
| 7.980831
| 6.6367
| 1.20253
|
proto = kv_pb.KeyValue()
proto.ParseFromString(binary_record)
yield (proto.key(), proto.value())
|
def _hashing_map(binary_record)
|
A map function used in hash phase.
Reads KeyValue from binary record.
Args:
binary_record: The binary record.
Yields:
The (key, value).
| 6.959962
| 5.292609
| 1.315034
|
filelists = mapper_spec.params[cls.FILES_PARAM]
max_values_count = mapper_spec.params.get(cls.MAX_VALUES_COUNT_PARAM, -1)
max_values_size = mapper_spec.params.get(cls.MAX_VALUES_SIZE_PARAM, -1)
return [cls([0] * len(files), max_values_count, max_values_size)
for files in filelists]
|
def split_input(cls, mapper_spec)
|
Split input into multiple shards.
| 2.994281
| 2.95544
| 1.013142
|
if mapper_spec.input_reader_class() != cls:
raise errors.BadReaderParamsError("Input reader class mismatch")
params = mapper_spec.params
if cls.FILES_PARAM not in params:
raise errors.BadReaderParamsError("Missing files parameter.")
|
def validate(cls, mapper_spec)
|
Validate reader parameters in mapper_spec.
| 4.549973
| 3.529092
| 1.289276
|
if mapper_spec.output_writer_class() != cls:
raise errors.BadWriterParamsError("Output writer class mismatch")
params = output_writers._get_params(mapper_spec)
# Bucket Name is required
if cls.BUCKET_NAME_PARAM not in params:
raise errors.BadWriterParamsError(
"%s is required for the _HashingGCSOutputWriter" %
cls.BUCKET_NAME_PARAM)
|
def validate(cls, mapper_spec)
|
Validates mapper specification.
Args:
mapper_spec: an instance of model.MapperSpec to validate.
Raises:
BadWriterParamsError: when Output writer class mismatch.
| 5.498181
| 4.829538
| 1.138449
|
# Use the member variable (since we don't have access to the context) to
# flush each pool to minimize the size of each filehandle before we
# serialize it.
for pool in self._pools:
if pool is not None:
pool.flush(True)
return {"filehandles": pickle.dumps(self._filehandles)}
|
def to_json(self)
|
Returns writer state to serialize in json.
Returns:
A json-izable version of the OutputWriter state.
| 12.600418
| 11.832302
| 1.064917
|
mapper_spec = mr_spec.mapper
params = output_writers._get_params(mapper_spec)
bucket_name = params.get(cls.BUCKET_NAME_PARAM)
shards = mapper_spec.shard_count
filehandles = []
filename = (mr_spec.name + "/" + mr_spec.mapreduce_id +
"/shard-" + str(shard_number) + "-bucket-")
for i in range(shards):
full_filename = "/%s/%s%d" % (bucket_name, filename, i)
filehandles.append(cloudstorage.open(full_filename, mode="w"))
return cls(filehandles)
|
def create(cls, mr_spec, shard_number, shard_attempt, _writer_state=None)
|
Inherit docs.
| 4.134168
| 4.065105
| 1.016989
|
shards = mapreduce_state.mapreduce_spec.mapper.shard_count
filenames = []
for _ in range(shards):
filenames.append([None] * shards)
shard_states = model.ShardState.find_all_by_mapreduce_state(mapreduce_state)
for x, shard_state in enumerate(shard_states):
shard_filenames = shard_state.writer_state["shard_filenames"]
for y in range(shards):
filenames[y][x] = shard_filenames[y]
return filenames
|
def get_filenames(cls, mapreduce_state)
|
See parent class.
| 2.963938
| 2.85229
| 1.039143
|
filenames = []
for filehandle in self._filehandles:
filenames.append(filehandle.name)
filehandle.close()
shard_state.writer_state = {"shard_filenames": filenames}
|
def finalize(self, ctx, shard_state)
|
See parent class.
| 6.254956
| 5.468154
| 1.143888
|
ctx = context.get()
if len(data) != 2:
logging.error("Got bad tuple of length %d (2-tuple expected): %s",
len(data), data)
try:
key = str(data[0])
value = str(data[1])
except TypeError:
logging.error("Expecting a tuple, but got %s: %s",
data.__class__.__name__, data)
file_index = key.__hash__() % len(self._filehandles)
# Work-around: Since we don't have access to the context in the to_json()
# function, but we need to flush each pool before we serialize the
# filehandle, we rely on a member variable instead of using context for
# pool management.
pool = self._pools[file_index]
if pool is None:
filehandle = self._filehandles[file_index]
pool = output_writers.GCSRecordsPool(filehandle=filehandle, ctx=ctx)
self._pools[file_index] = pool
proto = kv_pb.KeyValue()
proto.set_key(key)
proto.set_value(value)
pool.append(proto.Encode())
|
def write(self, data)
|
Write data.
Args:
data: actual data yielded from handler. Type is writer-specific.
| 4.924861
| 4.885136
| 1.008132
|
reader_params = self.input_reader_cls.params_to_json(
self.input_reader_params)
# TODO(user): Do the same for writer params.
return {"input_reader": reader_params,
"output_writer": self.output_writer_params}
|
def _get_mapper_params(self)
|
Converts self to model.MapperSpec.params.
| 5.111381
| 4.570985
| 1.118223
|
# pylint: disable=g-import-not-at-top
from mapreduce import model
return model.MapperSpec(
handler_spec=util._obj_to_path(self.mapper),
input_reader_spec=util._obj_to_path(self.input_reader_cls),
params=self._get_mapper_params(),
shard_count=self.shard_count,
output_writer_spec=util._obj_to_path(self.output_writer_cls))
|
def _get_mapper_spec(self)
|
Converts self to model.MapperSpec.
| 2.904243
| 2.597773
| 1.117974
|
return {"force_writes": self._force_writes,
"done_callback": self.done_callback_url,
"user_params": self.user_params,
"shard_max_attempts": self.shard_max_attempts,
"task_max_attempts": self._task_max_attempts,
"task_max_data_processing_attempts":
self._task_max_data_processing_attempts,
"queue_name": self.queue_name,
"base_path": self._base_path,
"app_id": self._app,
"api_version": self._api_version}
|
def _get_mr_params(self)
|
Converts self to model.MapreduceSpec.params.
| 3.792789
| 3.279894
| 1.156376
|
cfg = cls(_lenient=True)
mr_params = cfg._get_mr_params()
mr_params["api_version"] = 0
return mr_params
|
def _get_default_mr_params(cls)
|
Gets default values for old API.
| 8.779027
| 6.49613
| 1.351424
|
mapper_spec = mr_spec.mapper
# 0 means all the old APIs before api_version is introduced.
api_version = mr_spec.params.get("api_version", 0)
old_api = api_version == 0
# Deserialize params from json if input_reader/output_writer are new API.
input_reader_cls = mapper_spec.input_reader_class()
input_reader_params = input_readers._get_params(mapper_spec)
if issubclass(input_reader_cls, input_reader.InputReader):
input_reader_params = input_reader_cls.params_from_json(
input_reader_params)
output_writer_cls = mapper_spec.output_writer_class()
output_writer_params = output_writers._get_params(mapper_spec)
# TODO(user): Call json (de)serialization for writer.
# if (output_writer_cls and
# issubclass(output_writer_cls, output_writer.OutputWriter)):
# output_writer_params = output_writer_cls.params_from_json(
# output_writer_params)
# We can not always convert MapreduceSpec generated by older API
# to JobConfig. Thus, mr framework should use/expose the returned JobConfig
# object with caution when a job is started with an old API.
# In this case, this method only tries not to blow up and assemble a
# JobConfig object as accurate as possible.
return cls(_lenient=old_api,
job_name=mr_spec.name,
job_id=mr_spec.mapreduce_id,
# handler_spec from older API may not have map_job.Mapper type.
mapper=util.for_name(mapper_spec.handler_spec),
input_reader_cls=input_reader_cls,
input_reader_params=input_reader_params,
output_writer_cls=output_writer_cls,
output_writer_params=output_writer_params,
shard_count=mapper_spec.shard_count,
queue_name=queue_name,
user_params=mr_spec.params.get("user_params"),
shard_max_attempts=mr_spec.params.get("shard_max_attempts"),
done_callback_url=mr_spec.params.get("done_callback"),
_force_writes=mr_spec.params.get("force_writes"),
_base_path=mr_spec.params["base_path"],
_task_max_attempts=mr_spec.params.get("task_max_attempts"),
_task_max_data_processing_attempts=(
mr_spec.params.get("task_max_data_processing_attempts")),
_hooks_cls=util.for_name(mr_spec.hooks_class_name),
_app=mr_spec.params.get("app_id"),
_api_version=api_version)
|
def _to_map_job_config(cls,
mr_spec,
# TODO(user): Remove this parameter after it can be
# read from mr_spec.
queue_name)
|
Converts model.MapreduceSpec back to JobConfig.
This method allows our internal methods to use JobConfig directly.
This method also allows us to expose JobConfig as an API during execution,
despite that it is not saved into datastore.
Args:
mr_spec: model.MapreduceSpec.
queue_name: queue name.
Returns:
The JobConfig object for this job.
| 3.759404
| 3.741456
| 1.004797
|
length = len(data)
crc = crc32c.crc_update(crc32c.CRC_INIT, [record_type])
crc = crc32c.crc_update(crc, data)
crc = crc32c.crc_finalize(crc)
self.__writer.write(
struct.pack(_HEADER_FORMAT, _mask_crc(crc), length, record_type))
self.__writer.write(data)
self.__position += _HEADER_LENGTH + length
|
def __write_record(self, record_type, data)
|
Write single physical record.
| 3.491799
| 3.37601
| 1.034297
|
block_remaining = _BLOCK_SIZE - self.__position % _BLOCK_SIZE
if block_remaining < _HEADER_LENGTH:
# Header won't fit into remainder
self.__writer.write('\x00' * block_remaining)
self.__position += block_remaining
block_remaining = _BLOCK_SIZE
if block_remaining < len(data) + _HEADER_LENGTH:
first_chunk = data[:block_remaining - _HEADER_LENGTH]
self.__write_record(_RECORD_TYPE_FIRST, first_chunk)
data = data[len(first_chunk):]
while True:
block_remaining = _BLOCK_SIZE - self.__position % _BLOCK_SIZE
if block_remaining >= len(data) + _HEADER_LENGTH:
self.__write_record(_RECORD_TYPE_LAST, data)
break
else:
chunk = data[:block_remaining - _HEADER_LENGTH]
self.__write_record(_RECORD_TYPE_MIDDLE, chunk)
data = data[len(chunk):]
else:
self.__write_record(_RECORD_TYPE_FULL, data)
|
def write(self, data)
|
Write single record.
Args:
data: record data to write as string, byte array or byte sequence.
| 2.492768
| 2.520821
| 0.988872
|
pad_length = _BLOCK_SIZE - self.__position % _BLOCK_SIZE
if pad_length and pad_length != _BLOCK_SIZE:
self.__writer.write('\x00' * pad_length)
self.__position += pad_length
|
def _pad_block(self)
|
Pad block with 0.
Pad current block with 0. Reader will simply treat these as corrupted
record and skip the block.
This method is idempotent.
| 3.83283
| 4.226447
| 0.906868
|
block_remaining = _BLOCK_SIZE - self.__reader.tell() % _BLOCK_SIZE
if block_remaining < _HEADER_LENGTH:
return ('', _RECORD_TYPE_NONE)
header = self.__reader.read(_HEADER_LENGTH)
if len(header) != _HEADER_LENGTH:
raise EOFError('Read %s bytes instead of %s' %
(len(header), _HEADER_LENGTH))
(masked_crc, length, record_type) = struct.unpack(_HEADER_FORMAT, header)
crc = _unmask_crc(masked_crc)
if length + _HEADER_LENGTH > block_remaining:
# A record can't be bigger than one block.
raise errors.InvalidRecordError('Length is too big')
data = self.__reader.read(length)
if len(data) != length:
raise EOFError('Not enough data read. Expected: %s but got %s' %
(length, len(data)))
if record_type == _RECORD_TYPE_NONE:
return ('', record_type)
actual_crc = crc32c.crc_update(crc32c.CRC_INIT, [record_type])
actual_crc = crc32c.crc_update(actual_crc, data)
actual_crc = crc32c.crc_finalize(actual_crc)
if actual_crc != crc:
raise errors.InvalidRecordError('Data crc does not match')
return (data, record_type)
|
def __try_read_record(self)
|
Try reading a record.
Returns:
(data, record_type) tuple.
Raises:
EOFError: when end of file was reached.
InvalidRecordError: when valid record could not be read.
| 2.697778
| 2.555226
| 1.055789
|
pad_length = _BLOCK_SIZE - self.__reader.tell() % _BLOCK_SIZE
if pad_length and pad_length != _BLOCK_SIZE:
data = self.__reader.read(pad_length)
if len(data) != pad_length:
raise EOFError('Read %d bytes instead of %d' %
(len(data), pad_length))
|
def __sync(self)
|
Skip reader to the block boundary.
| 3.46023
| 2.843129
| 1.21705
|
data = None
while True:
last_offset = self.tell()
try:
(chunk, record_type) = self.__try_read_record()
if record_type == _RECORD_TYPE_NONE:
self.__sync()
elif record_type == _RECORD_TYPE_FULL:
if data is not None:
logging.warning(
"Ordering corruption: Got FULL record while already "
"in a chunk at offset %d", last_offset)
return chunk
elif record_type == _RECORD_TYPE_FIRST:
if data is not None:
logging.warning(
"Ordering corruption: Got FIRST record while already "
"in a chunk at offset %d", last_offset)
data = chunk
elif record_type == _RECORD_TYPE_MIDDLE:
if data is None:
logging.warning(
"Ordering corruption: Got MIDDLE record before FIRST "
"record at offset %d", last_offset)
else:
data += chunk
elif record_type == _RECORD_TYPE_LAST:
if data is None:
logging.warning(
"Ordering corruption: Got LAST record but no chunk is in "
"progress at offset %d", last_offset)
else:
result = data + chunk
data = None
return result
else:
raise errors.InvalidRecordError(
"Unsupported record type: %s" % record_type)
except errors.InvalidRecordError, e:
logging.warning("Invalid record encountered at %s (%s). Syncing to "
"the next block", last_offset, e)
data = None
self.__sync()
|
def read(self)
|
Reads record from current position in reader.
Returns:
original bytes stored in a single record.
| 2.526111
| 2.515201
| 1.004338
|
if shards is None:
shards = parameters.config.SHARD_COUNT
if base_path is None:
base_path = parameters.config.BASE_PATH
mapreduce_id = control.start_map(
job_name,
handler_spec,
input_reader_spec,
params or {},
mapreduce_parameters={
"done_callback": self.get_callback_url(),
"done_callback_method": "GET",
"pipeline_id": self.pipeline_id,
"base_path": base_path,
},
shard_count=shards,
output_writer_spec=output_writer_spec,
queue_name=self.queue_name,
)
self.fill(self.outputs.job_id, mapreduce_id)
self.set_status(console_url="%s/detail?mapreduce_id=%s" % (
(base_path, mapreduce_id)))
|
def run(self,
job_name,
handler_spec,
input_reader_spec,
output_writer_spec=None,
params=None,
shards=None,
base_path=None)
|
Start a mapreduce job.
Args:
job_name: mapreduce name. Only for display purpose.
handler_spec: fully qualified name to your map function/class.
input_reader_spec: fully qualified name to input reader class.
output_writer_spec: fully qualified name to output writer class.
params: a dictionary of parameters for input reader and output writer
initialization.
shards: number of shards. This provides a guide to mapreduce. The real
number of shards is determined by how input are splited.
| 3.259929
| 3.45792
| 0.942743
|
if self.was_aborted:
return
mapreduce_id = self.outputs.job_id.value
mapreduce_state = model.MapreduceState.get_by_job_id(mapreduce_id)
if mapreduce_state.result_status != model.MapreduceState.RESULT_SUCCESS:
self.retry("Job %s had status %s" % (
mapreduce_id, mapreduce_state.result_status))
return
mapper_spec = mapreduce_state.mapreduce_spec.mapper
outputs = []
output_writer_class = mapper_spec.output_writer_class()
if (output_writer_class and
mapreduce_state.result_status == model.MapreduceState.RESULT_SUCCESS):
outputs = output_writer_class.get_filenames(mapreduce_state)
self.fill(self.outputs.result_status, mapreduce_state.result_status)
self.fill(self.outputs.counters, mapreduce_state.counters_map.to_dict())
self.complete(outputs)
|
def callback(self)
|
Callback after this async pipeline finishes.
| 3.001325
| 2.912655
| 1.030443
|
if shard_count is None:
shard_count = parameters.config.SHARD_COUNT
if mapper_parameters:
mapper_parameters = dict(mapper_parameters)
# Make sure this old API fill all parameters with default values.
mr_params = map_job.JobConfig._get_default_mr_params()
if mapreduce_parameters:
mr_params.update(mapreduce_parameters)
# Override default values if user specified them as arguments.
if base_path:
mr_params["base_path"] = base_path
mr_params["queue_name"] = util.get_queue_name(queue_name)
mapper_spec = model.MapperSpec(handler_spec,
reader_spec,
mapper_parameters,
shard_count,
output_writer_spec=output_writer_spec)
if in_xg_transaction and not db.is_in_transaction():
logging.warning("Expects an opened xg transaction to start mapreduce "
"when transactional is True.")
return handlers.StartJobHandler._start_map(
name,
mapper_spec,
mr_params,
# TODO(user): Now that "queue_name" is part of mr_params.
# Remove all the other ways to get queue_name after one release.
queue_name=mr_params["queue_name"],
eta=eta,
countdown=countdown,
hooks_class_name=hooks_class_name,
_app=_app,
in_xg_transaction=in_xg_transaction)
|
def start_map(name,
handler_spec,
reader_spec,
mapper_parameters,
shard_count=None,
output_writer_spec=None,
mapreduce_parameters=None,
base_path=None,
queue_name=None,
eta=None,
countdown=None,
hooks_class_name=None,
_app=None,
in_xg_transaction=False)
|
Start a new, mapper-only mapreduce.
Deprecated! Use map_job.start instead.
If a value can be specified both from an explicit argument and from
a dictionary, the value from the explicit argument wins.
Args:
name: mapreduce name. Used only for display purposes.
handler_spec: fully qualified name of mapper handler function/class to call.
reader_spec: fully qualified name of mapper reader to use
mapper_parameters: dictionary of parameters to pass to mapper. These are
mapper-specific and also used for reader/writer initialization.
Should have format {"input_reader": {}, "output_writer":{}}. Old
deprecated style does not have sub dictionaries.
shard_count: number of shards to create.
mapreduce_parameters: dictionary of mapreduce parameters relevant to the
whole job.
base_path: base path of mapreduce library handler specified in app.yaml.
"/mapreduce" by default.
queue_name: taskqueue queue name to be used for mapreduce tasks.
see util.get_queue_name.
eta: absolute time when the MR should execute. May not be specified
if 'countdown' is also supplied. This may be timezone-aware or
timezone-naive.
countdown: time in seconds into the future that this MR should execute.
Defaults to zero.
hooks_class_name: fully qualified name of a hooks.Hooks subclass.
in_xg_transaction: controls what transaction scope to use to start this MR
job. If True, there has to be an already opened cross-group transaction
scope. MR will use one entity group from it.
If False, MR will create an independent transaction to start the job
regardless of any existing transaction scopes.
Returns:
mapreduce id as string.
| 3.500737
| 3.687196
| 0.949431
|
self.__update_state()
if self._state.active:
return self.RUNNING
else:
return self._state.result_status
|
def get_status(self)
|
Get status enum.
Returns:
One of the status enum.
| 9.355903
| 10.72814
| 0.87209
|
self.__update_state()
return self._state.counters_map.get(counter_name, default)
|
def get_counter(self, counter_name, default=0)
|
Get the value of the named counter from this job.
When a job is running, counter values won't be very accurate.
Args:
counter_name: name of the counter in string.
default: default value if the counter doesn't exist.
Returns:
Value in int of the named counter.
| 7.577941
| 10.53075
| 0.719601
|
assert self.SUCCESS == self.get_status()
ss = model.ShardState.find_all_by_mapreduce_state(self._state)
for s in ss:
yield iter(s.writer_state.get("outs", []))
|
def get_outputs(self)
|
Get outputs of this job.
Should only call if status is SUCCESS.
Yields:
Iterators, one for each shard. Each iterator is
from the argument of map_job.output_writer.commit_output.
| 14.807792
| 10.484276
| 1.412381
|
cls.__validate_job_config(job_config)
mapper_spec = job_config._get_mapper_spec()
# Create mr spec.
mapreduce_params = job_config._get_mr_params()
mapreduce_spec = model.MapreduceSpec(
job_config.job_name,
job_config.job_id,
mapper_spec.to_json(),
mapreduce_params,
util._obj_to_path(job_config._hooks_cls))
# Save states and enqueue task.
if in_xg_transaction:
propagation = db.MANDATORY
else:
propagation = db.INDEPENDENT
state = None
@db.transactional(propagation=propagation)
def _txn():
state = cls.__create_and_save_state(job_config, mapreduce_spec)
cls.__add_kickoff_task(job_config, mapreduce_spec)
return state
state = _txn()
return cls(state)
|
def submit(cls, job_config, in_xg_transaction=False)
|
Submit the job to run.
Args:
job_config: an instance of map_job.MapJobConfig.
in_xg_transaction: controls what transaction scope to use to start this MR
job. If True, there has to be an already opened cross-group transaction
scope. MR will use one entity group from it.
If False, MR will create an independent transaction to start the job
regardless of any existing transaction scopes.
Returns:
a Job instance representing the submitted job.
| 4.150525
| 4.168872
| 0.995599
|
# Only if the job was not in a terminal state.
if self._state.active:
self._state = self.__get_state_by_id(self.job_config.job_id)
|
def __update_state(self)
|
Fetches most up to date state from db.
| 9.202238
| 7.402293
| 1.24316
|
state = model.MapreduceState.get_by_job_id(job_id)
if state is None:
raise ValueError("Job state for job %s is missing." % job_id)
return state
|
def __get_state_by_id(cls, job_id)
|
Get job state by id.
Args:
job_id: job id.
Returns:
model.MapreduceState for the job.
Raises:
ValueError: if the job state is missing.
| 4.243301
| 3.168998
| 1.339004
|
state = model.MapreduceState.create_new(job_config.job_id)
state.mapreduce_spec = mapreduce_spec
state.active = True
state.active_shards = 0
state.app_id = job_config._app
config = datastore_rpc.Configuration(force_writes=job_config._force_writes)
state.put(config=config)
return state
|
def __create_and_save_state(cls, job_config, mapreduce_spec)
|
Save map job state to datastore.
Save state to datastore so that UI can see it immediately.
Args:
job_config: map_job.JobConfig.
mapreduce_spec: model.MapreduceSpec.
Returns:
model.MapreduceState for this job.
| 3.770304
| 4.114815
| 0.916275
|
params = {"mapreduce_id": job_config.job_id}
# Task is not named so that it can be added within a transaction.
kickoff_task = taskqueue.Task(
# TODO(user): Perhaps make this url a computed field of job_config.
url=job_config._base_path + "/kickoffjob_callback/" + job_config.job_id,
headers=util._get_task_headers(job_config.job_id),
params=params)
if job_config._hooks_cls:
hooks = job_config._hooks_cls(mapreduce_spec)
try:
hooks.enqueue_kickoff_task(kickoff_task, job_config.queue_name)
return
except NotImplementedError:
pass
kickoff_task.add(job_config.queue_name, transactional=True)
|
def __add_kickoff_task(cls, job_config, mapreduce_spec)
|
Add kickoff task to taskqueue.
Args:
job_config: map_job.JobConfig.
mapreduce_spec: model.MapreduceSpec,
| 4.394909
| 4.612523
| 0.952821
|
_json = self.to_json()
try:
return json.dumps(_json, sort_keys=True, cls=JsonEncoder)
except:
logging.exception("Could not serialize JSON: %r", _json)
raise
|
def to_json_str(self)
|
Convert data to json string representation.
Returns:
json representation as string.
| 4.195897
| 4.506641
| 0.931047
|
return cls.from_json(json.loads(json_str, cls=JsonDecoder))
|
def from_json_str(cls, json_str)
|
Convert json string representation into class instance.
Args:
json_str: json representation as string.
Returns:
New instance of the class with data loaded from json string.
| 4.53682
| 8.210345
| 0.552574
|
value = super(JsonProperty, self).get_value_for_datastore(model_instance)
if not value:
return None
json_value = value
if not isinstance(value, dict):
json_value = value.to_json()
if not json_value:
return None
return datastore_types.Text(json.dumps(
json_value, sort_keys=True, cls=JsonEncoder))
|
def get_value_for_datastore(self, model_instance)
|
Gets value for datastore.
Args:
model_instance: instance of the model class.
Returns:
datastore-compatible value.
| 2.732436
| 3.093827
| 0.88319
|
if value is None:
return None
_json = json.loads(value, cls=JsonDecoder)
if self.data_type == dict:
return _json
return self.data_type.from_json(_json)
|
def make_value_from_datastore(self, value)
|
Convert value from datastore representation.
Args:
value: datastore value.
Returns:
value to store in the model.
| 5.282518
| 5.270368
| 1.002305
|
if value is not None and not isinstance(value, self.data_type):
raise datastore_errors.BadValueError(
"Property %s must be convertible to a %s instance (%s)" %
(self.name, self.data_type, value))
return super(JsonProperty, self).validate(value)
|
def validate(self, value)
|
Validate value.
Args:
value: model value.
Returns:
Whether the specified value is valid data type value.
Raises:
BadValueError: when value is not of self.data_type type.
| 3.404284
| 3.406548
| 0.999335
|
task = self.to_task()
task.add(queue_name, transactional)
|
def add(self, queue_name, transactional=False)
|
Add task to the queue.
| 8.34599
| 5.757287
| 1.449639
|
# Never pass params to taskqueue.Task. Use payload instead. Otherwise,
# it's up to a particular taskqueue implementation to generate
# payload from params. It could blow up payload size over limit.
return taskqueue.Task(
url=self.url,
payload=self._payload,
name=self.name,
eta=self.eta,
countdown=self.countdown,
headers=self._headers)
|
def to_task(self)
|
Convert to a taskqueue task.
| 8.245244
| 7.078018
| 1.164909
|
# TODO(user): Pass mr_id into headers. Otherwise when payload decoding
# failed, we can't abort a mr.
if request.headers.get(cls.PAYLOAD_VERSION_HEADER) != cls.PAYLOAD_VERSION:
raise DeprecationWarning(
"Task is generated by an older incompatible version of mapreduce. "
"Please kill this job manually")
return cls._decode_payload(request.body)
|
def decode_payload(cls, request)
|
Decode task payload.
HugeTask controls its own payload entirely including urlencoding.
It doesn't depend on any particular web framework.
Args:
request: a webapp Request instance.
Returns:
A dict of str to str. The same as the params argument to __init__.
Raises:
DeprecationWarning: When task payload constructed from an older
incompatible version of mapreduce.
| 13.189553
| 9.198361
| 1.433902
|
current_value = self.counters.get(counter_name, 0)
new_value = current_value + delta
self.counters[counter_name] = new_value
return new_value
|
def increment(self, counter_name, delta)
|
Increment counter value.
Args:
counter_name: counter name as String.
delta: increment delta as Integer.
Returns:
new counter value.
| 2.101744
| 2.310487
| 0.909654
|
for counter_name in counters_map.counters:
self.increment(counter_name, counters_map.counters[counter_name])
|
def add_map(self, counters_map)
|
Add all counters from the map.
For each counter in the passed map, adds its value to the counter in this
map.
Args:
counters_map: CounterMap instance to add.
| 4.299105
| 3.846082
| 1.117788
|
for counter_name in counters_map.counters:
self.increment(counter_name, -counters_map.counters[counter_name])
|
def sub_map(self, counters_map)
|
Subtracts all counters from the map.
For each counter in the passed map, subtracts its value to the counter in
this map.
Args:
counters_map: CounterMap instance to subtract.
| 4.978383
| 4.012544
| 1.240705
|
result = {
"mapper_handler_spec": self.handler_spec,
"mapper_input_reader": self.input_reader_spec,
"mapper_params": self.params,
"mapper_shard_count": self.shard_count
}
if self.output_writer_spec:
result["mapper_output_writer"] = self.output_writer_spec
return result
|
def to_json(self)
|
Serializes this MapperSpec into a json-izable object.
| 3.206843
| 2.591647
| 1.237377
|
if self.__hooks is None and self.hooks_class_name is not None:
hooks_class = util.for_name(self.hooks_class_name)
if not isinstance(hooks_class, type):
raise ValueError("hooks_class_name must refer to a class, got %s" %
type(hooks_class).__name__)
if not issubclass(hooks_class, hooks.Hooks):
raise ValueError(
"hooks_class_name must refer to a hooks.Hooks subclass")
self.__hooks = hooks_class(self)
return self.__hooks
|
def get_hooks(self)
|
Returns a hooks.Hooks class or None if no hooks class has been set.
| 2.486602
| 2.184706
| 1.138186
|
mapper_spec = self.mapper.to_json()
return {
"name": self.name,
"mapreduce_id": self.mapreduce_id,
"mapper_spec": mapper_spec,
"params": self.params,
"hooks_class_name": self.hooks_class_name,
}
|
def to_json(self)
|
Serializes all data in this mapreduce spec into json form.
Returns:
data in json format.
| 3.53133
| 3.444908
| 1.025087
|
mapreduce_spec = cls(json["name"],
json["mapreduce_id"],
json["mapper_spec"],
json.get("params"),
json.get("hooks_class_name"))
return mapreduce_spec
|
def from_json(cls, json)
|
Create new MapreduceSpec from the json, encoded by to_json.
Args:
json: json representation of MapreduceSpec.
Returns:
an instance of MapreduceSpec with all data deserialized from json.
| 5.972353
| 5.887987
| 1.014328
|
key = 'GAE-MR-spec: %s' % mr_id
spec_json = memcache.get(key)
if spec_json:
return cls.from_json(spec_json)
state = MapreduceState.get_by_job_id(mr_id)
spec = state.mapreduce_spec
spec_json = spec.to_json()
memcache.set(key, spec_json)
return spec
|
def _get_mapreduce_spec(cls, mr_id)
|
Get Mapreduce spec from mr id.
| 2.725979
| 2.518561
| 1.082356
|
return db.Key.from_path(cls.kind(), str(mapreduce_id))
|
def get_key_by_job_id(cls, mapreduce_id)
|
Retrieves the Key for a Job.
Args:
mapreduce_id: The job to retrieve.
Returns:
Datastore Key that can be used to fetch the MapreduceState.
| 3.573607
| 7.721068
| 0.462838
|
chart = google_chart_api.BarChart()
def filter_status(status_to_filter):
return [count if status == status_to_filter else 0
for count, status in zip(shards_processed, shards_status)]
if shards_status:
# Each index will have only one non-zero count, so stack them to color-
# code the bars by status
# These status values are computed in _update_state_from_shard_states,
# in mapreduce/handlers.py.
chart.stacked = True
chart.AddBars(filter_status("unknown"), color="404040")
chart.AddBars(filter_status("success"), color="00ac42")
chart.AddBars(filter_status("running"), color="3636a9")
chart.AddBars(filter_status("aborted"), color="e29e24")
chart.AddBars(filter_status("failed"), color="f6350f")
else:
chart.AddBars(shards_processed)
shard_count = len(shards_processed)
if shard_count > 95:
# Auto-spacing does not work for large numbers of shards.
pixels_per_shard = 700.0 / shard_count
bar_thickness = int(pixels_per_shard * .9)
chart.style = bar_chart.BarChartStyle(bar_thickness=bar_thickness,
bar_gap=0.1, use_fractional_gap_spacing=True)
if shards_processed and shard_count <= 95:
# Adding labels puts us in danger of exceeding the URL length, only
# do it when we have a small amount of data to plot.
# Only 16 labels on the whole chart.
stride_length = max(1, shard_count / 16)
chart.bottom.labels = []
for x in xrange(shard_count):
if (x % stride_length == 0 or
x == shard_count - 1):
chart.bottom.labels.append(x)
else:
chart.bottom.labels.append("")
chart.left.labels = ["0", str(max(shards_processed))]
chart.left.min = 0
self.chart_width = min(700, max(300, shard_count * 20))
self.chart_url = chart.display.Url(self.chart_width, 200)
|
def set_processed_counts(self, shards_processed, shards_status)
|
Updates a chart url to display processed count for each shard.
Args:
shards_processed: list of integers with number of processed entities in
each shard
| 4.859759
| 4.98882
| 0.97413
|
if not mapreduce_id:
mapreduce_id = MapreduceState.new_mapreduce_id()
state = MapreduceState(key_name=mapreduce_id,
last_poll_time=gettime())
state.set_processed_counts([], [])
return state
|
def create_new(mapreduce_id=None,
gettime=datetime.datetime.now)
|
Create a new MapreduceState.
Args:
mapreduce_id: Mapreduce id as string.
gettime: Used for testing.
| 4.056563
| 4.159254
| 0.97531
|
self.input_reader = self.initial_input_reader
self.slice_id = 0
self.retries += 1
self.output_writer = output_writer
self.handler = self.mapreduce_spec.mapper.handler
|
def reset_for_retry(self, output_writer)
|
Reset self for shard retry.
Args:
output_writer: new output writer that contains new output files.
| 6.379719
| 6.77839
| 0.941185
|
if recovery_slice:
self.slice_id += 2
# Restore input reader to the beginning of the slice.
self.input_reader = self.input_reader.from_json(self._input_reader_json)
else:
self.slice_id += 1
|
def advance_for_next_slice(self, recovery_slice=False)
|
Advance relavent states for next slice.
Args:
recovery_slice: True if this slice is running recovery logic.
See handlers.MapperWorkerCallbackHandler._attempt_slice_recovery
for more info.
| 5.425477
| 5.523311
| 0.982287
|
result = {"mapreduce_spec": self.mapreduce_spec.to_json_str(),
"shard_id": self.shard_id,
"slice_id": str(self.slice_id),
"input_reader_state": self.input_reader.to_json_str(),
"initial_input_reader_state":
self.initial_input_reader.to_json_str(),
"retries": str(self.retries)}
if self.output_writer:
result["output_writer_state"] = self.output_writer.to_json_str()
serialized_handler = util.try_serialize_handler(self.handler)
if serialized_handler:
result["serialized_handler"] = serialized_handler
return result
|
def to_dict(self)
|
Convert state to dictionary to save in task payload.
| 2.883094
| 2.760095
| 1.044564
|
mapreduce_spec = MapreduceSpec.from_json_str(request.get("mapreduce_spec"))
mapper_spec = mapreduce_spec.mapper
input_reader_spec_dict = json.loads(request.get("input_reader_state"),
cls=json_util.JsonDecoder)
input_reader = mapper_spec.input_reader_class().from_json(
input_reader_spec_dict)
initial_input_reader_spec_dict = json.loads(
request.get("initial_input_reader_state"), cls=json_util.JsonDecoder)
initial_input_reader = mapper_spec.input_reader_class().from_json(
initial_input_reader_spec_dict)
output_writer = None
if mapper_spec.output_writer_class():
output_writer = mapper_spec.output_writer_class().from_json(
json.loads(request.get("output_writer_state", "{}"),
cls=json_util.JsonDecoder))
assert isinstance(output_writer, mapper_spec.output_writer_class()), (
"%s.from_json returned an instance of wrong class: %s" % (
mapper_spec.output_writer_class(),
output_writer.__class__))
handler = util.try_deserialize_handler(request.get("serialized_handler"))
if not handler:
handler = mapreduce_spec.mapper.handler
return cls(mapreduce_spec.params["base_path"],
mapreduce_spec,
str(request.get("shard_id")),
int(request.get("slice_id")),
input_reader,
initial_input_reader,
output_writer=output_writer,
retries=int(request.get("retries")),
handler=handler)
|
def from_request(cls, request)
|
Create new TransientShardState from webapp request.
| 2.309356
| 2.247946
| 1.027318
|
self.retries += 1
self.last_work_item = ""
self.active = True
self.result_status = None
self.input_finished = False
self.counters_map = CountersMap()
self.slice_id = 0
self.slice_start_time = None
self.slice_request_id = None
self.slice_retries = 0
self.acquired_once = False
|
def reset_for_retry(self)
|
Reset self for shard retry.
| 5.573263
| 5.323893
| 1.04684
|
self.slice_start_time = None
self.slice_request_id = None
self.slice_retries = 0
self.acquired_once = False
if recovery_slice:
self.slice_id += 2
else:
self.slice_id += 1
|
def advance_for_next_slice(self, recovery_slice=False)
|
Advance self for next slice.
Args:
recovery_slice: True if this slice is running recovery logic.
See handlers.MapperWorkerCallbackHandler._attempt_slice_recovery
for more info.
| 3.901522
| 4.072349
| 0.958052
|
for prop in self.properties().values():
setattr(self, prop.name, getattr(other_state, prop.name))
|
def copy_from(self, other_state)
|
Copy data from another shard state entity to self.
| 4.11611
| 3.898881
| 1.055716
|
keys = cls.calculate_keys_by_mapreduce_state(mapreduce_state)
i = 0
while i < len(keys):
@db.non_transactional
def no_tx_get(i):
return db.get(keys[i:i+cls._MAX_STATES_IN_MEMORY])
# We need a separate function to so that we can mix non-transactional and
# use be a generator
states = no_tx_get(i)
for s in states:
i += 1
if s is not None:
yield s
|
def find_all_by_mapreduce_state(cls, mapreduce_state)
|
Find all shard states for given mapreduce.
Args:
mapreduce_state: MapreduceState instance
Yields:
shard states sorted by shard id.
| 5.390713
| 5.780981
| 0.932491
|
if mapreduce_state is None:
return []
keys = []
for i in range(mapreduce_state.mapreduce_spec.mapper.shard_count):
shard_id = cls.shard_id_from_number(mapreduce_state.key().name(), i)
keys.append(cls.get_key_by_shard_id(shard_id))
return keys
|
def calculate_keys_by_mapreduce_state(cls, mapreduce_state)
|
Calculate all shard states keys for given mapreduce.
Args:
mapreduce_state: MapreduceState instance
Returns:
A list of keys for shard states, sorted by shard id.
The corresponding shard states may not exist.
| 2.812648
| 2.96787
| 0.947699
|
shard_id = cls.shard_id_from_number(mapreduce_id, shard_number)
state = cls(key_name=shard_id,
mapreduce_id=mapreduce_id)
return state
|
def create_new(cls, mapreduce_id, shard_number)
|
Create new shard state.
Args:
mapreduce_id: unique mapreduce id as string.
shard_number: shard number for which to create shard state.
Returns:
new instance of ShardState ready to put into datastore.
| 3.064193
| 3.765728
| 0.813705
|
return db.Key.from_path(cls.kind(), "%s:%s" % (mapreduce_id, cls._KEY_NAME))
|
def get_key_by_job_id(cls, mapreduce_id)
|
Retrieves the Key for a mapreduce ID.
Args:
mapreduce_id: The job to fetch.
Returns:
Datastore Key for the command for the given job ID.
| 4.295803
| 7.117618
| 0.603545
|
cls(key_name="%s:%s" % (mapreduce_id, cls._KEY_NAME),
command=cls.ABORT).put(**kwargs)
|
def abort(cls, mapreduce_id, **kwargs)
|
Causes a job to abort.
Args:
mapreduce_id: The job to abort. Not verified as a valid job.
| 7.284751
| 11.14943
| 0.653374
|
super(DatastoreInputReader, cls).validate(job_config)
params = job_config.input_reader_params
entity_kind = params[cls.ENTITY_KIND_PARAM]
# Check for a "." in the entity kind.
if "." in entity_kind:
logging.warning(
". detected in entity kind %s specified for reader %s."
"Assuming entity kind contains the dot.",
entity_kind, cls.__name__)
# Validate the filters parameters.
if cls.FILTERS_PARAM in params:
filters = params[cls.FILTERS_PARAM]
for f in filters:
if f[1] != "=":
raise errors.BadReaderParamsError(
"Only equality filters are supported: %s", f)
|
def validate(cls, job_config)
|
Inherit docs.
| 3.906967
| 3.754467
| 1.040618
|
super(TaskQueueHandler, self).initialize(request, response)
# Check request is from taskqueue.
if "X-AppEngine-QueueName" not in self.request.headers:
logging.error(self.request.headers)
logging.error("Task queue handler received non-task queue request")
self.response.set_status(
403, message="Task queue handler received non-task queue request")
return
# Check task has not been retried too many times.
if self.task_retry_count() + 1 > parameters.config.TASK_MAX_ATTEMPTS:
logging.error(
"Task %s has been attempted %s times. Dropping it permanently.",
self.request.headers["X-AppEngine-TaskName"],
self.task_retry_count() + 1)
self._drop_gracefully()
return
try:
self._preprocess()
self._preprocess_success = True
# pylint: disable=bare-except
except:
self._preprocess_success = False
logging.error(
"Preprocess task %s failed. Dropping it permanently.",
self.request.headers["X-AppEngine-TaskName"])
self._drop_gracefully()
|
def initialize(self, request, response)
|
Initialize.
1. call webapp init.
2. check request is indeed from taskqueue.
3. check the task has not been retried too many times.
4. run handler specific processing logic.
5. run error handling logic if precessing failed.
Args:
request: a webapp.Request instance.
response: a webapp.Response instance.
| 2.816096
| 2.540222
| 1.108602
|
self.response.set_status(httplib.SERVICE_UNAVAILABLE, "Retry task")
self.response.clear()
|
def retry_task(self)
|
Ask taskqueue to retry this task.
Even though raising an exception can cause a task retry, it
will flood logs with highly visible ERROR logs. Handlers should uses
this method to perform controlled task retries. Only raise exceptions
for those deserve ERROR log entries.
| 6.550064
| 5.922943
| 1.10588
|
path = self.request.path
base_path = path[:path.rfind("/")]
if not base_path.endswith("/command"):
raise BadRequestPathError(
"Json handlers should have /command path prefix")
return base_path[:base_path.rfind("/")]
|
def base_path(self)
|
Base path for all mapreduce-related urls.
JSON handlers are mapped to /base_path/command/command_name thus they
require special treatment.
Raises:
BadRequestPathError: if the path does not end with "/command".
Returns:
The base path.
| 7.664159
| 3.920131
| 1.955077
|
if self.request.headers.get("X-Requested-With") != "XMLHttpRequest":
logging.error("Got JSON request with no X-Requested-With header")
self.response.set_status(
403, message="Got JSON request with no X-Requested-With header")
return
self.json_response.clear()
try:
self.handle()
except errors.MissingYamlError:
logging.debug("Could not find 'mapreduce.yaml' file.")
self.json_response.clear()
self.json_response["error_class"] = "Notice"
self.json_response["error_message"] = "Could not find 'mapreduce.yaml'"
except Exception, e:
logging.exception("Error in JsonHandler, returning exception.")
# TODO(user): Include full traceback here for the end-user.
self.json_response.clear()
self.json_response["error_class"] = e.__class__.__name__
self.json_response["error_message"] = str(e)
self.response.headers["Content-Type"] = "text/javascript"
try:
output = json.dumps(self.json_response, cls=json_util.JsonEncoder)
# pylint: disable=broad-except
except Exception, e:
logging.exception("Could not serialize to JSON")
self.response.set_status(500, message="Could not serialize to JSON")
return
else:
self.response.out.write(output)
|
def _handle_wrapper(self)
|
The helper method for handling JSON Post and Get requests.
| 2.765071
| 2.669392
| 1.035843
|
if self._EOF:
return ""
while self._seg_index <= self._last_seg_index:
result = self._read_from_seg(n)
if result != "":
return result
else:
self._next_seg()
self._EOF = True
return ""
|
def read(self, n)
|
Read data from file segs.
Args:
n: max bytes to read. Must be positive.
Returns:
some bytes. May be smaller than n bytes. "" when no more data is left.
| 4.935452
| 3.995227
| 1.235337
|
if self._seg:
self._seg.close()
self._seg_index += 1
if self._seg_index > self._last_seg_index:
self._seg = None
return
filename = self._seg_prefix + str(self._seg_index)
stat = cloudstorage.stat(filename)
writer = output_writers._GoogleCloudStorageOutputWriter
if writer._VALID_LENGTH not in stat.metadata:
raise ValueError(
"Expect %s in metadata for file %s." %
(writer._VALID_LENGTH, filename))
self._seg_valid_length = int(stat.metadata[writer._VALID_LENGTH])
if self._seg_valid_length > stat.st_size:
raise ValueError(
"Valid length %s is too big for file %s of length %s" %
(self._seg_valid_length, filename, stat.st_size))
self._seg = cloudstorage.open(filename)
|
def _next_seg(self)
|
Get next seg.
| 3.213564
| 3.070625
| 1.04655
|
result = self._seg.read(size=n)
if result == "":
return result
offset = self._seg.tell()
if offset > self._seg_valid_length:
extra = offset - self._seg_valid_length
result = result[:-1*extra]
self._offset += len(result)
return result
|
def _read_from_seg(self, n)
|
Read from current seg.
Args:
n: max number of bytes to read.
Returns:
valid bytes from the current seg. "" if no more is left.
| 4.256155
| 3.93261
| 1.082272
|
now_descending = int((_FUTURE_TIME - gettime()) * 100)
request_id_hash = os.environ.get("REQUEST_ID_HASH")
if not request_id_hash:
request_id_hash = str(random.getrandbits(32))
return "%d%s" % (now_descending, request_id_hash)
|
def _get_descending_key(gettime=time.time)
|
Returns a key name lexically ordered by time descending.
This lets us have a key name for use with Datastore entities which returns
rows in time descending order when it is scanned in lexically ascending order,
allowing us to bypass index building for descending indexes.
Args:
gettime: Used for testing.
Returns:
A string with a time descending key.
| 3.445218
| 3.88734
| 0.886266
|
version = os.environ["CURRENT_VERSION_ID"].split(".")[0]
default_host = os.environ["DEFAULT_VERSION_HOSTNAME"]
module = os.environ["CURRENT_MODULE_ID"]
if os.environ["CURRENT_MODULE_ID"] == "default":
return "%s.%s" % (version, default_host)
return "%s.%s.%s" % (version, module, default_host)
|
def _get_task_host()
|
Get the Host header value for all mr tasks.
Task Host header determines which instance this task would be routed to.
Current version id format is: v7.368834058928280579
Current module id is just the module's name. It could be "default"
Default version hostname is app_id.appspot.com
Returns:
A complete host name is of format version.module.app_id.appspot.com
If module is the default module, just version.app_id.appspot.com. The reason
is if an app doesn't have modules enabled and the url is
"version.default.app_id", "version" is ignored and "default" is used as
version. If "default" version doesn't exist, the url is routed to the
default version.
| 3.030124
| 2.024034
| 1.497072
|
if queue_name:
return queue_name
queue_name = os.environ.get("HTTP_X_APPENGINE_QUEUENAME",
parameters.config.QUEUE_NAME)
if len(queue_name) > 1 and queue_name[0:2] == "__":
# We are currently in some special queue. E.g. __cron.
return parameters.config.QUEUE_NAME
else:
return queue_name
|
def get_queue_name(queue_name)
|
Determine which queue MR should run on.
How to choose the queue:
1. If user provided one, use that.
2. If we are starting a mr from taskqueue, inherit that queue.
If it's a special queue, fall back to the default queue.
3. Default queue.
If user is using any MR pipeline interface, pipeline.start takes a
"queue_name" argument. The pipeline will run on that queue and MR will
simply inherit the queue_name.
Args:
queue_name: queue_name from user. Maybe None.
Returns:
The queue name to run on.
| 4.356284
| 4.274179
| 1.019209
|
secs = td.seconds + td.days * 24 * 3600
if td.microseconds:
secs += 1
return secs
|
def total_seconds(td)
|
convert a timedelta to seconds.
This is patterned after timedelta.total_seconds, which is only
available in python 27.
Args:
td: a timedelta object.
Returns:
total seconds within a timedelta. Rounded up to seconds.
| 4.097479
| 4.391144
| 0.933123
|
resolved_name = for_name(fq_name)
if isinstance(resolved_name, (type, types.ClassType)):
# create new instance if this is type
return resolved_name()
elif isinstance(resolved_name, types.MethodType):
# bind the method
return getattr(resolved_name.im_class(), resolved_name.__name__)
else:
return resolved_name
|
def handler_for_name(fq_name)
|
Resolves and instantiates handler by fully qualified name.
First resolves the name using for_name call. Then if it resolves to a class,
instantiates a class, if it resolves to a method - instantiates the class and
binds method to the instance.
Args:
fq_name: fully qualified name of something to find.
Returns:
handler instance which is ready to be called.
| 4.252308
| 3.486405
| 1.219683
|
if (isinstance(handler, types.InstanceType) or # old style class
(isinstance(handler, object) and # new style class
not inspect.isfunction(handler) and
not inspect.ismethod(handler)) and
hasattr(handler, "__call__")):
return pickle.dumps(handler)
return None
|
def try_serialize_handler(handler)
|
Try to serialize map/reduce handler.
Args:
handler: handler function/instance. Handler can be a function or an
instance of a callable class. In the latter case, the handler will
be serialized across slices to allow users to save states.
Returns:
serialized handler string or None.
| 3.513979
| 3.709946
| 0.947178
|
if isinstance(obj, types.GeneratorType):
return True
CO_GENERATOR = 0x20
return bool(((inspect.isfunction(obj) or inspect.ismethod(obj)) and
obj.func_code.co_flags & CO_GENERATOR))
|
def is_generator(obj)
|
Return true if the object is generator or generator function.
Generator function objects provides same attributes as functions.
See isfunction.__doc__ for attributes listing.
Adapted from Python 2.6.
Args:
obj: an object to test.
Returns:
true if the object is generator function.
| 3.249876
| 3.709716
| 0.876044
|
if type(obj) is str:
TRUTH_VALUE_SET = ["true", "1", "yes", "t", "on"]
return obj.lower() in TRUTH_VALUE_SET
else:
return bool(obj)
|
def parse_bool(obj)
|
Return true if the object represents a truth value, false otherwise.
For bool and numeric objects, uses Python's built-in bool function. For
str objects, checks string against a list of possible truth values.
Args:
obj: object to determine boolean value of; expected
Returns:
Boolean value according to 5.1 of Python docs if object is not a str
object. For str objects, return True if str is in TRUTH_VALUE_SET
and False otherwise.
http://docs.python.org/library/stdtypes.html
| 3.601803
| 2.597528
| 1.386627
|
force_writes = parse_bool(mapreduce_spec.params.get("force_writes", "false"))
if force_writes:
return datastore_rpc.Configuration(force_writes=force_writes)
else:
# dev server doesn't support force_writes.
return datastore_rpc.Configuration()
|
def create_datastore_write_config(mapreduce_spec)
|
Creates datastore config to use in write operations.
Args:
mapreduce_spec: current mapreduce specification as MapreduceSpec.
Returns:
an instance of datastore_rpc.Configuration to use for all write
operations in the mapreduce.
| 4.418692
| 3.987028
| 1.108267
|
ndb_ctx = ndb.get_context()
ndb_ctx.set_cache_policy(lambda key: False)
ndb_ctx.set_memcache_policy(lambda key: False)
|
def _set_ndb_cache_policy()
|
Tell NDB to never cache anything in memcache or in-process.
This ensures that entities fetched from Datastore input_readers via NDB
will not bloat up the request memory size and Datastore Puts will avoid
doing calls to memcache. Without this you get soft memory limit exits,
which hurts overall throughput.
| 2.540584
| 2.320629
| 1.094783
|
if obj is None:
return obj
if inspect.isclass(obj) or inspect.isfunction(obj):
fetched = getattr(sys.modules[obj.__module__], obj.__name__, None)
if fetched is None:
raise ValueError(
"Object %r must be defined on the top level of a module." % obj)
return "%s.%s" % (obj.__module__, obj.__name__)
raise TypeError("Unexpected type %s." % type(obj))
|
def _obj_to_path(obj)
|
Returns the fully qualified path to the object.
Args:
obj: obj must be a new style top level class, or a top level function.
No inner function or static method.
Returns:
Fully qualified path to the object.
Raises:
TypeError: when argument obj has unsupported type.
ValueError: when obj can't be discovered on the top level.
| 3.424649
| 3.060434
| 1.119008
|
items_no_prefix = []
for item in items:
if item.startswith(prefix):
items_no_prefix.append(item[len(prefix):])
else:
items_no_prefix.append(item)
return items_no_prefix
|
def strip_prefix_from_items(prefix, items)
|
Strips out the prefix from each of the items if it is present.
Args:
prefix: the string for that you wish to strip from the beginning of each
of the items.
items: a list of strings that may or may not contain the prefix you want
to strip out.
Returns:
items_no_prefix: a copy of the list of items (same order) without the
prefix (if present).
| 1.669446
| 1.990879
| 0.838547
|
if hooks is not None:
try:
getattr(hooks, method)(task, queue_name)
except NotImplementedError:
# Use the default task addition implementation.
return False
return True
return False
|
def _run_task_hook(hooks, method, task, queue_name)
|
Invokes hooks.method(task, queue_name).
Args:
hooks: A hooks.Hooks instance or None.
method: The name of the method to invoke on the hooks class e.g.
"enqueue_kickoff_task".
task: The taskqueue.Task to pass to the hook method.
queue_name: The name of the queue to pass to the hook method.
Returns:
True if the hooks.Hooks instance handled the method, False otherwise.
| 6.76999
| 7.244551
| 0.934494
|
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