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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/model_datastore_input_reader.py | ModelDatastoreInputReader.split_input | def split_input(cls, job_config):
"""Inherit docs."""
params = job_config.input_reader_params
shard_count = job_config.shard_count
query_spec = cls._get_query_spec(params)
if not property_range.should_shard_by_property_range(query_spec.filters):
return super(ModelDatastoreInputReader, cls).sp... | python | def split_input(cls, job_config):
"""Inherit docs."""
params = job_config.input_reader_params
shard_count = job_config.shard_count
query_spec = cls._get_query_spec(params)
if not property_range.should_shard_by_property_range(query_spec.filters):
return super(ModelDatastoreInputReader, cls).sp... | [
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/model_datastore_input_reader.py | ModelDatastoreInputReader.validate | def validate(cls, job_config):
"""Inherit docs."""
super(ModelDatastoreInputReader, cls).validate(job_config)
params = job_config.input_reader_params
entity_kind = params[cls.ENTITY_KIND_PARAM]
# Fail fast if Model cannot be located.
try:
model_class = util.for_name(entity_kind)
except... | python | def validate(cls, job_config):
"""Inherit docs."""
super(ModelDatastoreInputReader, cls).validate(job_config)
params = job_config.input_reader_params
entity_kind = params[cls.ENTITY_KIND_PARAM]
# Fail fast if Model cannot be located.
try:
model_class = util.for_name(entity_kind)
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/model_datastore_input_reader.py | ModelDatastoreInputReader._validate_filters | def _validate_filters(cls, filters, model_class):
"""Validate user supplied filters.
Validate filters are on existing properties and filter values
have valid semantics.
Args:
filters: user supplied filters. Each filter should be a list or tuple of
format (<property_name_as_str>, <query_o... | python | def _validate_filters(cls, filters, model_class):
"""Validate user supplied filters.
Validate filters are on existing properties and filter values
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filters: user supplied filters. Each filter should be a list or tuple of
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/model_datastore_input_reader.py | ModelDatastoreInputReader._validate_filters_ndb | def _validate_filters_ndb(cls, filters, model_class):
"""Validate ndb.Model filters."""
if not filters:
return
properties = model_class._properties
for f in filters:
prop, _, val = f
if prop not in properties:
raise errors.BadReaderParamsError(
"Property %s is not... | python | def _validate_filters_ndb(cls, filters, model_class):
"""Validate ndb.Model filters."""
if not filters:
return
properties = model_class._properties
for f in filters:
prop, _, val = f
if prop not in properties:
raise errors.BadReaderParamsError(
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _normalize_entity | def _normalize_entity(value):
"""Return an entity from an entity or model instance."""
if ndb is not None and isinstance(value, ndb.Model):
return None
if getattr(value, "_populate_internal_entity", None):
return value._populate_internal_entity()
return value | python | def _normalize_entity(value):
"""Return an entity from an entity or model instance."""
if ndb is not None and isinstance(value, ndb.Model):
return None
if getattr(value, "_populate_internal_entity", None):
return value._populate_internal_entity()
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _normalize_key | def _normalize_key(value):
"""Return a key from an entity, model instance, key, or key string."""
if ndb is not None and isinstance(value, (ndb.Model, ndb.Key)):
return None
if getattr(value, "key", None):
return value.key()
elif isinstance(value, basestring):
return datastore.Key(value)
else:
... | python | def _normalize_key(value):
"""Return a key from an entity, model instance, key, or key string."""
if ndb is not None and isinstance(value, (ndb.Model, ndb.Key)):
return None
if getattr(value, "key", None):
return value.key()
elif isinstance(value, basestring):
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _ItemList.append | def append(self, item):
"""Add new item to the list.
If needed, append will first flush existing items and clear existing items.
Args:
item: an item to add to the list.
"""
if self.should_flush():
self.flush()
self.items.append(item) | python | def append(self, item):
"""Add new item to the list.
If needed, append will first flush existing items and clear existing items.
Args:
item: an item to add to the list.
"""
if self.should_flush():
self.flush()
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _ItemList.flush | def flush(self):
"""Force a flush."""
if not self.items:
return
retry = 0
options = {"deadline": DATASTORE_DEADLINE}
while retry <= self.__timeout_retries:
try:
self.__flush_function(self.items, options)
self.clear()
break
except db.Timeout, e:
logg... | python | def flush(self):
"""Force a flush."""
if not self.items:
return
retry = 0
options = {"deadline": DATASTORE_DEADLINE}
while retry <= self.__timeout_retries:
try:
self.__flush_function(self.items, options)
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _MutationPool.put | def put(self, entity):
"""Registers entity to put to datastore.
Args:
entity: an entity or model instance to put.
"""
actual_entity = _normalize_entity(entity)
if actual_entity is None:
return self.ndb_put(entity)
self.puts.append(actual_entity) | python | def put(self, entity):
"""Registers entity to put to datastore.
Args:
entity: an entity or model instance to put.
"""
actual_entity = _normalize_entity(entity)
if actual_entity is None:
return self.ndb_put(entity)
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _MutationPool.ndb_put | def ndb_put(self, entity):
"""Like put(), but for NDB entities."""
assert ndb is not None and isinstance(entity, ndb.Model)
self.ndb_puts.append(entity) | python | def ndb_put(self, entity):
"""Like put(), but for NDB entities."""
assert ndb is not None and isinstance(entity, ndb.Model)
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _MutationPool.delete | def delete(self, entity):
"""Registers entity to delete from datastore.
Args:
entity: an entity, model instance, or key to delete.
"""
key = _normalize_key(entity)
if key is None:
return self.ndb_delete(entity)
self.deletes.append(key) | python | def delete(self, entity):
"""Registers entity to delete from datastore.
Args:
entity: an entity, model instance, or key to delete.
"""
key = _normalize_key(entity)
if key is None:
return self.ndb_delete(entity)
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _MutationPool.ndb_delete | def ndb_delete(self, entity_or_key):
"""Like delete(), but for NDB entities/keys."""
if ndb is not None and isinstance(entity_or_key, ndb.Model):
key = entity_or_key.key
else:
key = entity_or_key
self.ndb_deletes.append(key) | python | def ndb_delete(self, entity_or_key):
"""Like delete(), but for NDB entities/keys."""
if ndb is not None and isinstance(entity_or_key, ndb.Model):
key = entity_or_key.key
else:
key = entity_or_key
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _MutationPool.flush | def flush(self):
"""Flush(apply) all changed to datastore."""
self.puts.flush()
self.deletes.flush()
self.ndb_puts.flush()
self.ndb_deletes.flush() | python | def flush(self):
"""Flush(apply) all changed to datastore."""
self.puts.flush()
self.deletes.flush()
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _MutationPool._flush_puts | def _flush_puts(self, items, options):
"""Flush all puts to datastore."""
datastore.Put(items, config=self._create_config(options)) | python | def _flush_puts(self, items, options):
"""Flush all puts to datastore."""
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _MutationPool._flush_deletes | def _flush_deletes(self, items, options):
"""Flush all deletes to datastore."""
datastore.Delete(items, config=self._create_config(options)) | python | def _flush_deletes(self, items, options):
"""Flush all deletes to datastore."""
datastore.Delete(items, config=self._create_config(options)) | [
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _MutationPool._flush_ndb_puts | def _flush_ndb_puts(self, items, options):
"""Flush all NDB puts to datastore."""
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ndb.put_multi(items, config=self._create_config(options)) | python | def _flush_ndb_puts(self, items, options):
"""Flush all NDB puts to datastore."""
assert ndb is not None
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _MutationPool._flush_ndb_deletes | def _flush_ndb_deletes(self, items, options):
"""Flush all deletes to datastore."""
assert ndb is not None
ndb.delete_multi(items, config=self._create_config(options)) | python | def _flush_ndb_deletes(self, items, options):
"""Flush all deletes to datastore."""
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"""Creates datastore Config.
Returns:
A datastore_rpc.Configuration instance.
"""
return datastore.CreateConfig(deadline=options["deadline"],
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/context.py | _Counters.increment | def increment(self, counter_name, delta=1):
"""Increment counter value.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/datastore_range_iterators.py | _PropertyRangeModelIterator.to_json | def to_json(self):
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cursor = self._query.cursor()
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cursor = self._query.cursor_after()
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cursor = self._cursor
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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 m... | python | def from_json(cls, json):
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obj = cls(property_range.PropertyRange.from_json(json["property_range"]),
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/datastore_range_iterators.py | _MultiPropertyRangeModelIterator.to_json | def to_json(self):
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/datastore_range_iterators.py | _MultiPropertyRangeModelIterator.from_json | def from_json(cls, json):
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/datastore_range_iterators.py | _KeyRangesIterator.to_json | def to_json(self):
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current_iter = None
if self._current_iter:
current_iter = self._current_iter.to_json()
return {"key_ranges": self._key_ranges.to_json(),
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/datastore_range_iterators.py | _KeyRangesIterator.from_json | def from_json(cls, json):
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obj = cls(key_ranges.KeyRangesFactory.from_json(json["key_ranges"]),
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current_iter = None
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obj = cls(key_ranges.KeyRangesFactory.from_json(json["key_ranges"]),
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/datastore_range_iterators.py | AbstractKeyRangeIterator.to_json | def to_json(self):
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/datastore_range_iterators.py | AbstractKeyRangeIterator.from_json | def from_json(cls, json):
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/status.py | find_mapreduce_yaml | def find_mapreduce_yaml(status_file=__file__):
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Args:
status_file: location of status.py, overridable for testing purposes.
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Raises:
errors.BadYamlError: when contents is not a valid mapreduce.yaml file.
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mapreduce_yaml: The Pyton representation of the mapreduce.yaml document.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/input_reader.py | InputReader.validate | def validate(cls, job_config):
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Args:
job_config: an instance of map_job.JobConfig.
Raises:
errors.BadReaderParamsError: required parameters are missing or invalid.
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if job_config.input_re... | python | def validate(cls, job_config):
"""Validates relevant parameters.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _sort_records_map | 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.
"""
ctx = context.... | python | def _sort_records_map(records):
"""Map function sorting records.
Converts records to KeyValue protos, sorts them by key and writes them
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Args:
records: list of records which are serialized KeyValue protos.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _merge_map | 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:
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"""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.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _hashing_map | 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).
"""
proto = kv_pb.KeyValue()
proto.ParseFromString(binary_record)
yield (proto.key(), proto.value()) | python | def _hashing_map(binary_record):
"""A map function used in hash phase.
Reads KeyValue from binary record.
Args:
binary_record: The binary record.
Yields:
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"""
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _MergingReader.split_input | def split_input(cls, mapper_spec):
"""Split input into multiple shards."""
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), m... | python | def split_input(cls, mapper_spec):
"""Split input into multiple shards."""
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)
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _MergingReader.validate | def validate(cls, mapper_spec):
"""Validate reader parameters in mapper_spec."""
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:
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"""Validate reader parameters in mapper_spec."""
if mapper_spec.input_reader_class() != cls:
raise errors.BadReaderParamsError("Input reader class mismatch")
params = mapper_spec.params
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _HashingGCSOutputWriter.validate | 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.
"""
if mapper_spec.output_writer_class() != cls:
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"""Validates mapper specification.
Args:
mapper_spec: an instance of model.MapperSpec to validate.
Raises:
BadWriterParamsError: when Output writer class mismatch.
"""
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _HashingGCSOutputWriter.to_json | def to_json(self):
"""Returns writer state to serialize in json.
Returns:
A json-izable version of the OutputWriter state.
"""
# 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
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f... | python | def to_json(self):
"""Returns writer state to serialize in json.
Returns:
A json-izable version of the OutputWriter state.
"""
# Use the member variable (since we don't have access to the context) to
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _HashingGCSOutputWriter.create | def create(cls, mr_spec, shard_number, shard_attempt, _writer_state=None):
"""Inherit docs."""
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.... | python | def create(cls, mr_spec, shard_number, shard_attempt, _writer_state=None):
"""Inherit docs."""
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.... | [
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _HashingGCSOutputWriter.get_filenames | def get_filenames(cls, mapreduce_state):
"""See parent class."""
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)
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"""See parent class."""
shards = mapreduce_state.mapreduce_spec.mapper.shard_count
filenames = []
for _ in range(shards):
filenames.append([None] * shards)
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _HashingGCSOutputWriter.finalize | def finalize(self, ctx, shard_state):
"""See parent class."""
filenames = []
for filehandle in self._filehandles:
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filehandle.close()
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/shuffler.py | _HashingGCSOutputWriter.write | def write(self, data):
"""Write data.
Args:
data: actual data yielded from handler. Type is writer-specific.
"""
ctx = context.get()
if len(data) != 2:
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"""Write data.
Args:
data: actual data yielded from handler. Type is writer-specific.
"""
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if len(data) != 2:
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_config.py | JobConfig._get_mapper_params | def _get_mapper_params(self):
"""Converts self to model.MapperSpec.params."""
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,
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"""Converts self to model.MapperSpec.params."""
reader_params = self.input_reader_cls.params_to_json(
self.input_reader_params)
# TODO(user): Do the same for writer params.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_config.py | JobConfig._get_mapper_spec | def _get_mapper_spec(self):
"""Converts self to model.MapperSpec."""
# pylint: disable=g-import-not-at-top
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"""Converts self to model.MapperSpec."""
# pylint: disable=g-import-not-at-top
from mapreduce import model
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_config.py | JobConfig._get_mr_params | def _get_mr_params(self):
"""Converts self to model.MapreduceSpec.params."""
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": s... | python | def _get_mr_params(self):
"""Converts self to model.MapreduceSpec.params."""
return {"force_writes": self._force_writes,
"done_callback": self.done_callback_url,
"user_params": self.user_params,
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_config.py | JobConfig._get_default_mr_params | def _get_default_mr_params(cls):
"""Gets default values for old API."""
cfg = cls(_lenient=True)
mr_params = cfg._get_mr_params()
mr_params["api_version"] = 0
return mr_params | python | def _get_default_mr_params(cls):
"""Gets default values for old API."""
cfg = cls(_lenient=True)
mr_params = cfg._get_mr_params()
mr_params["api_version"] = 0
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_config.py | JobConfig._to_map_job_config | 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 metho... | python | 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 metho... | [
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/records.py | RecordsWriter.__write_record | def __write_record(self, record_type, data):
"""Write single physical record."""
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),... | python | def __write_record(self, record_type, data):
"""Write single physical record."""
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(
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/records.py | RecordsWriter.write | def write(self, data):
"""Write single record.
Args:
data: record data to write as string, byte array or byte sequence.
"""
block_remaining = _BLOCK_SIZE - self.__position % _BLOCK_SIZE
if block_remaining < _HEADER_LENGTH:
# Header won't fit into remainder
self.__writer.write('\x... | python | def write(self, data):
"""Write single record.
Args:
data: record data to write as string, byte array or byte sequence.
"""
block_remaining = _BLOCK_SIZE - self.__position % _BLOCK_SIZE
if block_remaining < _HEADER_LENGTH:
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/records.py | RecordsWriter._pad_block | def _pad_block(self):
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Pad current block with 0. Reader will simply treat these as corrupted
record and skip the block.
This method is idempotent.
"""
pad_length = _BLOCK_SIZE - self.__position % _BLOCK_SIZE
if pad_length and pad_length != _BLOCK_SIZE:
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"""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.
"""
pad_length = _BLOCK_SIZE - self.__position % _BLOCK_SIZE
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/records.py | RecordsReader.__try_read_record | 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.
"""
block_remaining = _BLOCK_SIZE - self.__reader.tell() % _BLOCK_SIZE
if block_re... | python | 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.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/records.py | RecordsReader.__sync | def __sync(self):
"""Skip reader to the block boundary."""
pad_length = _BLOCK_SIZE - self.__reader.tell() % _BLOCK_SIZE
if pad_length and pad_length != _BLOCK_SIZE:
data = self.__reader.read(pad_length)
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"""Skip reader to the block boundary."""
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/records.py | RecordsReader.read | def read(self):
"""Reads record from current position in reader.
Returns:
original bytes stored in a single record.
"""
data = None
while True:
last_offset = self.tell()
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(chunk, record_type) = self.__try_read_record()
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Returns:
original bytes stored in a single record.
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data = None
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/mapper_pipeline.py | MapperPipeline.run | 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 ... | python | 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.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/mapper_pipeline.py | MapperPipeline.callback | def callback(self):
"""Callback after this async pipeline finishes."""
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.re... | python | def callback(self):
"""Callback after this async pipeline finishes."""
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:
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/control.py | start_map | 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,
c... | python | 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,
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_control.py | Job.get_status | def get_status(self):
"""Get status enum.
Returns:
One of the status enum.
"""
self.__update_state()
if self._state.active:
return self.RUNNING
else:
return self._state.result_status | python | def get_status(self):
"""Get status enum.
Returns:
One of the status enum.
"""
self.__update_state()
if self._state.active:
return self.RUNNING
else:
return self._state.result_status | [
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_control.py | Job.get_counter | 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 i... | python | 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.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_control.py | Job.get_outputs | 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.
"""
assert self.SUCCESS == self.get_status()
ss = model.ShardState.find_all_by... | python | 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.
"""
assert self.SUCCESS == self.get_status()
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_control.py | Job.submit | 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
s... | python | 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
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_control.py | Job.__update_state | def __update_state(self):
"""Fetches most up to date state from db."""
# 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) | python | def __update_state(self):
"""Fetches most up to date state from db."""
# 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) | [
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_control.py | Job.__get_state_by_id | 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.
"""
state = model.MapreduceState.get_by_job_id(job_id)
if state is None:
raise ValueError("... | python | 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.
"""
state = model.MapreduceState.get_by_job_id(job_id)
if state is None:
raise ValueError("... | [
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_control.py | Job.__create_and_save_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.
"""
... | python | 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.
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model.MapreduceState for this job.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/map_job_control.py | Job.__add_kickoff_task | def __add_kickoff_task(cls, job_config, mapreduce_spec):
"""Add kickoff task to taskqueue.
Args:
job_config: map_job.JobConfig.
mapreduce_spec: model.MapreduceSpec,
"""
params = {"mapreduce_id": job_config.job_id}
# Task is not named so that it can be added within a transaction.
kic... | python | def __add_kickoff_task(cls, job_config, mapreduce_spec):
"""Add kickoff task to taskqueue.
Args:
job_config: map_job.JobConfig.
mapreduce_spec: model.MapreduceSpec,
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/json_util.py | JsonMixin.to_json_str | def to_json_str(self):
"""Convert data to json string representation.
Returns:
json representation as string.
"""
_json = self.to_json()
try:
return json.dumps(_json, sort_keys=True, cls=JsonEncoder)
except:
logging.exception("Could not serialize JSON: %r", _json)
raise | python | def to_json_str(self):
"""Convert data to json string representation.
Returns:
json representation as string.
"""
_json = self.to_json()
try:
return json.dumps(_json, sort_keys=True, cls=JsonEncoder)
except:
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/json_util.py | JsonMixin.from_json_str | 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.
"""
return cls.from_json(json.loads(json_str, cls=JsonDecoder)) | python | def from_json_str(cls, json_str):
"""Convert json string representation into class instance.
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json_str: json representation as string.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/json_util.py | JsonProperty.get_value_for_datastore | def get_value_for_datastore(self, model_instance):
"""Gets value for datastore.
Args:
model_instance: instance of the model class.
Returns:
datastore-compatible value.
"""
value = super(JsonProperty, self).get_value_for_datastore(model_instance)
if not value:
return None
... | python | def get_value_for_datastore(self, model_instance):
"""Gets value for datastore.
Args:
model_instance: instance of the model class.
Returns:
datastore-compatible value.
"""
value = super(JsonProperty, self).get_value_for_datastore(model_instance)
if not value:
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/json_util.py | JsonProperty.make_value_from_datastore | def make_value_from_datastore(self, value):
"""Convert value from datastore representation.
Args:
value: datastore value.
Returns:
value to store in the model.
"""
if value is None:
return None
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r... | python | def make_value_from_datastore(self, value):
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value: datastore value.
Returns:
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if value is None:
return None
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/json_util.py | JsonProperty.validate | 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.
"""
if value is not None and not isinstance(value, self.data_type):
r... | python | def validate(self, value):
"""Validate value.
Args:
value: model value.
Returns:
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | HugeTask.add | def add(self, queue_name, transactional=False):
"""Add task to the queue."""
task = self.to_task()
task.add(queue_name, transactional) | python | def add(self, queue_name, transactional=False):
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task = self.to_task()
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | HugeTask.to_task | def to_task(self):
"""Convert to a taskqueue task."""
# Never pass params to taskqueue.Task. Use payload instead. Otherwise,
# it's up to a particular taskqueue implementation to generate
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return taskqueue.Task(
url=self.url,
... | python | def to_task(self):
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# Never pass params to taskqueue.Task. Use payload instead. Otherwise,
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | HugeTask.decode_payload | def decode_payload(cls, request):
"""Decode task payload.
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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 __... | python | def decode_payload(cls, request):
"""Decode task payload.
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request: a webapp Request instance.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | CountersMap.increment | 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.
"""
current_value = self.counters.get(counter_name, 0)
new_value = current_value + delta
self.c... | python | def increment(self, counter_name, delta):
"""Increment counter value.
Args:
counter_name: counter name as String.
delta: increment delta as Integer.
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new counter value.
"""
current_value = self.counters.get(counter_name, 0)
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | CountersMap.add_map | def add_map(self, counters_map):
"""Add all counters from the map.
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map.
Args:
counters_map: CounterMap instance to add.
"""
for counter_name in counters_map.counters:
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counters_map: CounterMap instance to add.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | CountersMap.sub_map | def sub_map(self, counters_map):
"""Subtracts all counters from the map.
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Args:
counters_map: CounterMap instance to subtract.
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self.increment(counter_na... | python | def sub_map(self, counters_map):
"""Subtracts all counters from the map.
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counters_map: CounterMap instance to subtract.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | MapperSpec.to_json | def to_json(self):
"""Serializes this MapperSpec into a json-izable object."""
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_... | python | def to_json(self):
"""Serializes this MapperSpec into a json-izable object."""
result = {
"mapper_handler_spec": self.handler_spec,
"mapper_input_reader": self.input_reader_spec,
"mapper_params": self.params,
"mapper_shard_count": self.shard_count
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | MapreduceSpec.get_hooks | def get_hooks(self):
"""Returns a hooks.Hooks class or None if no hooks class has been set."""
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... | python | def get_hooks(self):
"""Returns a hooks.Hooks class or None if no hooks class has been set."""
if self.__hooks is None and self.hooks_class_name is not None:
hooks_class = util.for_name(self.hooks_class_name)
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | MapreduceSpec.to_json | def to_json(self):
"""Serializes all data in this mapreduce spec into json form.
Returns:
data in json format.
"""
mapper_spec = self.mapper.to_json()
return {
"name": self.name,
"mapreduce_id": self.mapreduce_id,
"mapper_spec": mapper_spec,
"params": self.para... | python | def to_json(self):
"""Serializes all data in this mapreduce spec into json form.
Returns:
data in json format.
"""
mapper_spec = self.mapper.to_json()
return {
"name": self.name,
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | MapreduceSpec.from_json | def from_json(cls, json):
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Args:
json: json representation of MapreduceSpec.
Returns:
an instance of MapreduceSpec with all data deserialized from json.
"""
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | MapreduceSpec._get_mapreduce_spec | def _get_mapreduce_spec(cls, mr_id):
"""Get Mapreduce spec from mr id."""
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()
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"""Get Mapreduce spec from mr id."""
key = 'GAE-MR-spec: %s' % mr_id
spec_json = memcache.get(key)
if spec_json:
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | MapreduceState.get_key_by_job_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.
"""
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | MapreduceState.set_processed_counts | 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
"""
chart = google_chart_api.BarChart()
def filter_status(status... | python | def set_processed_counts(self, shards_processed, shards_status):
"""Updates a chart url to display processed count for each shard.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | MapreduceState.create_new | 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.
"""
if not mapreduce_id:
mapreduce_id = MapreduceState.new_mapreduce_id()
state = MapreduceStat... | python | 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.
"""
if not mapreduce_id:
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | TransientShardState.reset_for_retry | def reset_for_retry(self, output_writer):
"""Reset self for shard retry.
Args:
output_writer: new output writer that contains new output files.
"""
self.input_reader = self.initial_input_reader
self.slice_id = 0
self.retries += 1
self.output_writer = output_writer
self.handler = s... | python | def reset_for_retry(self, output_writer):
"""Reset self for shard retry.
Args:
output_writer: new output writer that contains new output files.
"""
self.input_reader = self.initial_input_reader
self.slice_id = 0
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | TransientShardState.advance_for_next_slice | 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.
"""
if recovery_slice:
self.... | python | def advance_for_next_slice(self, recovery_slice=False):
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | TransientShardState.to_dict | def to_dict(self):
"""Convert state to dictionary to save in task payload."""
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"""Convert state to dictionary to save in task payload."""
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | TransientShardState.from_request | def from_request(cls, request):
"""Create new TransientShardState from webapp request."""
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"),
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"""Create new TransientShardState from webapp request."""
mapreduce_spec = MapreduceSpec.from_json_str(request.get("mapreduce_spec"))
mapper_spec = mapreduce_spec.mapper
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | ShardState.reset_for_retry | def reset_for_retry(self):
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self.slice_request_id ... | python | def reset_for_retry(self):
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | ShardState.advance_for_next_slice | def advance_for_next_slice(self, recovery_slice=False):
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recovery_slice: True if this slice is running recovery logic.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | ShardState.copy_from | def copy_from(self, other_state):
"""Copy data from another shard state entity to self."""
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | ShardState.find_all_by_mapreduce_state | def find_all_by_mapreduce_state(cls, mapreduce_state):
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Args:
mapreduce_state: MapreduceState instance
Yields:
shard states sorted by shard id.
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keys = cls.calculate_keys_by_mapreduce_state(mapreduce_state)
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Args:
mapreduce_state: MapreduceState instance
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shard states sorted by shard id.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | ShardState.calculate_keys_by_mapreduce_state | def calculate_keys_by_mapreduce_state(cls, mapreduce_state):
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mapreduce_state: MapreduceState instance
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A list of keys for shard states, sorted by shard id.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | ShardState.create_new | def create_new(cls, mapreduce_id, shard_number):
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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.
"""
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Args:
mapreduce_id: unique mapreduce id as string.
shard_number: shard number for which to create shard state.
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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. | [
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | MapreduceControl.get_key_by_job_id | 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.
"""
return db.Key.from_path(cls.kind(), "%s:%s" % (mapreduce_id, cls._KEY_NAME)) | python | 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.
"""
return db.Key.from_path(cls.kind(), "%s:%s" % (mapreduce_id, cls._KEY_NAME)) | [
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/model.py | MapreduceControl.abort | def abort(cls, mapreduce_id, **kwargs):
"""Causes a job to abort.
Args:
mapreduce_id: The job to abort. Not verified as a valid job.
"""
cls(key_name="%s:%s" % (mapreduce_id, cls._KEY_NAME),
command=cls.ABORT).put(**kwargs) | python | def abort(cls, mapreduce_id, **kwargs):
"""Causes a job to abort.
Args:
mapreduce_id: The job to abort. Not verified as a valid job.
"""
cls(key_name="%s:%s" % (mapreduce_id, cls._KEY_NAME),
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/api/map_job/datastore_input_reader.py | DatastoreInputReader.validate | def validate(cls, job_config):
"""Inherit docs."""
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 i... | python | def validate(cls, job_config):
"""Inherit docs."""
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.
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/base_handler.py | TaskQueueHandler.initialize | 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 ... | python | 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 ... | [
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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 webap... | [
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GoogleCloudPlatform/appengine-mapreduce | python/src/mapreduce/base_handler.py | TaskQueueHandler.retry_task | 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.
... | python | 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.
... | [
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Even though raising an exception can cause a task retry, it
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this method to perform controlled task retries. Only raise exceptions
for those deserve ERROR log entries. | [
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