def monitor_migration_status(migration_status, migration_history_obj):
"""
migration_history_obj must be pickled!
Takes a pipeline status result and uses it to update MigrationHistory
status as the migration runs.
Calling forget() on this result will free up the worker to work on
other tasks.
"""
# Set up a datastore client
project = PROJECT or 'meridianedit-staging'
client = apache_helper.get_datastore(project)
throttler = AdaptiveThrottler(window_ms=120000, bucket_ms=1000, overload_ratio=1.25)
if migration_status == 'DONE':
migration_history_obj.properties.get('status').string_value = Status.success
elif migration_status in ['FAILED', 'CANCELLED', 'CANCELLING']:
migration_history_obj.properties.get('status').string_value = Status.failed
elif migration_status in ['STARTING', 'RUNNING', 'UPDATED', 'DRAINING', 'DRAINED']:
migration_history_obj.properties.get('status').string_value = Status.running
elif migration_status in ['PENDING', 'STOPPED'] :
migration_history_obj.properties.get('status').string_value = Status.waiting
elif migration_status == 'UNKNOWN':
migration_history_obj.properties.get('status').string_value = Status.unknown
else:
# Sometimes migration status equals none of these things. Just assume success so
# we can kick off post-migration work. This is based on observation in the wild.
migration_history_obj.properties.get('status').string_value = Status.success
# Write the mutated entity to the datastore
mutations = [Mutation(update=migration_history_obj)]
apache_helper.write_mutations(client, project, mutations, throttler, rpc_stats_callback)
def get_namespaces(self):
# Skip auth-ing to db in test operations
if not self.argv:
return ['4952435991248896_1']
query_pb = query_pb2.Query()
helper.set_kind(query_pb, "__namespace__")
client = apache_helper.get_datastore(PROJECT)
namespace_entities = apache_helper.fetch_entities(
PROJECT, '', query_pb, client)
namespaces = []
for n in namespace_entities:
# Get namespace name or id
key_path = n.key.path[-1]
if key_path.HasField('id'):
name_or_id = key_path.id
else:
name_or_id = key_path.name
# Avoid duplicates and test namespaces
if len(str(name_or_id)) > 1 and name_or_id not in namespaces:
namespaces.append(name_or_id)
return namespaces
def start_bundle(self):
self._mutations = []
self._mutations_size = 0
self._datastore = helper.get_datastore(self._project)
if self._fixed_batch_size:
self._target_batch_size = self._fixed_batch_size
else:
self._batch_sizer = _Mutate._DynamicBatchSizer()
self._target_batch_size = self._batch_sizer.get_batch_size(time.time())
def start_bundle(self):
self._datastore = helper.get_datastore(self._project)
def start_bundle(self): self._datastore = helper.get_datastore(self._project)
def start_bundle(self): self._mutations = [] self._datastore = helper.get_datastore(self._project)
def start_bundle(self):
self._mutations = []
self._datastore = helper.get_datastore(self._project)
def run_data_migration():
request_data = json.loads(request.get_data())
# Required fields
fields = [
'name',
'function_kwargs',
'user'
]
# Some basic validation
for f in fields:
if f not in request_data:
resp_data = json.dumps(
{
'error': 'The ' + f + ' field is required.'
}
)
resp = Response(resp_data, status=400, mimetype='application/json')
return resp
if request_data['name'] not in migration.choices:
resp_data = json.dumps(
{
'error': 'The migration name is not valid.'
}
)
resp = Response(resp_data, status=400, mimetype='application/json')
return resp
migration_name = request_data['name']
function_kwargs = request_data['function_kwargs'] or {}
user = request_data['user']
function_kwargs.update({'name': migration_name})
# Create a MigrationHistory entity to keep track of the migration status
# set the project
project = PROJECT or 'meridianedit-staging'
# Create entity key
partition_id = entity_pb2.PartitionId(project_id=project, namespace_id="")
migration_history_obj_id = datetime.now().strftime("%Y%m%d%H%M%S")
path_element = entity_pb2.Key.PathElement(kind="MigrationHistory", name=migration_history_obj_id)
key = entity_pb2.Key(partition_id=partition_id, path=[path_element])
# Create entity and give it properties
entity = entity_pb2.Entity(key=key)
property_dict = {
'name': migration_name,
'function_kwargs': json.dumps(function_kwargs),
'started_by': user,
'status': 'running',
'created': datetime.now()
}
datastore_helper.add_properties(entity, property_dict)
# Add entity to datastore
mutations = [Mutation(insert=entity)]
client = apache_helper.get_datastore(project)
throttler = AdaptiveThrottler(window_ms=120000, bucket_ms=1000, overload_ratio=1.25)
apache_helper.write_mutations(client, project, mutations, throttler, rpc_stats_callback)
# Call the migration with any given function kwargs
migration_kwargs = {
'migration_history_obj': migration_history_obj_id,
}
migration_kwargs.update(function_kwargs)
# Run the migration in a celery task worker to prevent it timing
# out this connection. Also monitor the task so we can update
# migration status.
run_dataflow_migration.delay(pickle.dumps(entity), **migration_kwargs)
resp_data = {
'migration_history_obj_id': migration_history_obj_id
}
# A default 500 error message is returned if any of this breaks
return Response(json.dumps(resp_data), status=200, mimetype='application/json')
