def execute_case():
pool.create_actor(ClusterInfoActor,
[pool.cluster_info.address],
uid=ClusterInfoActor.default_name())
resource_ref = pool.create_actor(
ResourceActor, uid=ResourceActor.default_name())
pool.create_actor(ChunkMetaActor,
uid=ChunkMetaActor.default_name())
pool.create_actor(AssignerActor,
uid=AssignerActor.gen_name(session_id))
graph_ref = pool.create_actor(GraphActor,
session_id,
graph_key,
serialize_graph(graph),
uid=GraphActor.gen_name(
session_id, graph_key))
execution_ref = pool.create_actor(FakeExecutionActor, sleep=1)
# handle mock objects
OperandActor._get_raw_execution_ref.side_effect = lambda: execution_ref
mock_resource = dict(
hardware=dict(cpu=4, cpu_total=4, memory=512))
def write_mock_meta():
resource_ref.set_worker_meta('localhost:12345',
mock_resource)
resource_ref.set_worker_meta('localhost:23456',
mock_resource)
v = gevent.spawn(write_mock_meta)
v.join()
graph_ref.prepare_graph()
fetched_graph = graph_ref.get_chunk_graph()
graph_ref.scan_node()
graph_ref.place_initial_chunks()
final_keys = set()
for c in fetched_graph:
if fetched_graph.count_successors(c) == 0:
final_keys.add(c.op.key)
graph_ref.create_operand_actors()
graph_meta_ref = pool.actor_ref(
GraphMetaActor.gen_name(session_id, graph_key))
start_time = time.time()
cancel_called = False
while True:
gevent.sleep(0.1)
if not cancel_called and time.time() > start_time + 0.8:
cancel_called = True
graph_ref.stop_graph(_tell=True)
if time.time() - start_time > 30:
raise SystemError('Wait for execution finish timeout')
if graph_meta_ref.get_state() in (GraphState.SUCCEEDED,
GraphState.FAILED,
GraphState.CANCELLED):
break
def execute_case():
pool.create_actor(ClusterInfoActor,
[pool.cluster_info.address],
uid=ClusterInfoActor.default_name())
resource_ref = pool.create_actor(
ResourceActor, uid=ResourceActor.default_name())
kv_store_ref = pool.create_actor(
KVStoreActor, uid=KVStoreActor.default_name())
pool.create_actor(AssignerActor,
uid=AssignerActor.gen_name(session_id))
graph_ref = pool.create_actor(GraphActor,
session_id,
graph_key,
serialize_graph(graph),
uid=GraphActor.gen_name(
session_id, graph_key))
execution_ref = execution_creator(pool)
# handle mock objects
OperandActor._get_raw_execution_ref.side_effect = lambda: execution_ref
mock_resource = dict(
hardware=dict(cpu=4, cpu_total=4, memory=512))
def write_mock_meta():
resource_ref.set_worker_meta('localhost:12345',
mock_resource)
resource_ref.set_worker_meta('localhost:23456',
mock_resource)
v = gevent.spawn(write_mock_meta)
v.join()
graph_ref.prepare_graph()
graph_data = kv_store_ref.read(
'/sessions/%s/graphs/%s/chunk_graph' %
(session_id, graph_key)).value
fetched_graph = deserialize_graph(graph_data)
graph_ref.scan_node()
graph_ref.place_initial_chunks()
final_keys = set()
for c in fetched_graph:
if fetched_graph.count_successors(c) == 0:
final_keys.add(c.op.key)
graph_ref.create_operand_actors()
start_time = time.time()
while True:
gevent.sleep(0.1)
if time.time() - start_time > 30:
raise SystemError('Wait for execution finish timeout')
if kv_store_ref.read('/sessions/%s/graph/%s/state' % (session_id, graph_key)).value.lower() \
in ('succeeded', 'failed', 'cancelled'):
break
def testGraphActor(self):
session_id = str(uuid.uuid4())
graph_key = str(uuid.uuid4())
arr = mt.random.randint(10, size=(10, 8), chunk_size=4)
arr_add = mt.random.randint(10, size=(10, 8), chunk_size=4)
arr2 = arr + arr_add
graph = arr2.build_graph(compose=False)
serialized_graph = serialize_graph(graph)
chunked_graph = arr2.build_graph(compose=False, tiled=True)
addr = '127.0.0.1:%d' % get_next_port()
with create_actor_pool(n_process=1, backend='gevent',
address=addr) as pool:
pool.create_actor(ClusterInfoActor, [pool.cluster_info.address],
uid=ClusterInfoActor.default_name())
resource_ref = pool.create_actor(ResourceActor,
uid=ResourceActor.default_name())
pool.create_actor(ChunkMetaActor,
uid=ChunkMetaActor.default_name())
pool.create_actor(AssignerActor,
uid=AssignerActor.gen_name(session_id))
graph_ref = pool.create_actor(GraphActor,
session_id,
graph_key,
serialized_graph,
uid=GraphActor.gen_name(
session_id, graph_key))
graph_ref.prepare_graph(compose=False)
fetched_graph = graph_ref.get_chunk_graph()
self.assertIsNotNone(fetched_graph)
self.assertEqual(len(chunked_graph), len(fetched_graph))
graph_ref.scan_node()
op_infos = graph_ref.get_operand_info()
for n in fetched_graph:
depth = op_infos[n.op.key]['optimize']['depth']
self.assertIsNotNone(depth)
successor_size = op_infos[
n.op.key]['optimize']['successor_size']
self.assertIsNotNone(successor_size)
descendant_size = op_infos[
n.op.key]['optimize']['descendant_size']
self.assertIsNotNone(descendant_size)
resource_ref.set_worker_meta('localhost:12345',
dict(hardware=dict(cpu_total=4)))
resource_ref.set_worker_meta('localhost:23456',
dict(hardware=dict(cpu_total=4)))
graph_ref.place_initial_chunks()
op_infos = graph_ref.get_operand_info()
for n in fetched_graph:
if fetched_graph.count_predecessors(n) != 0:
continue
target_worker = op_infos[n.op.key]['target_worker']
self.assertIsNotNone(target_worker)
graph_ref.create_operand_actors(_clean_io_meta=False)
op_infos = graph_ref.get_operand_info()
for n in fetched_graph:
self.assertEqual(op_infos[n.op.key]['op_name'],
type(n.op).__name__)
io_meta = op_infos[n.op.key]['io_meta']
orig_io_meta = dict(
predecessors=list(
set(pn.op.key
for pn in fetched_graph.iter_predecessors(n))),
successors=list(
set(sn.op.key
for sn in fetched_graph.iter_successors(n))),
input_chunks=list(
set(pn.key
for pn in fetched_graph.iter_predecessors(n))),
chunks=list(c.key for c in n.op.outputs),
)
self.assertSetEqual(set(io_meta['predecessors']),
set(orig_io_meta['predecessors']))
self.assertSetEqual(set(io_meta['successors']),
set(orig_io_meta['successors']))
self.assertSetEqual(set(io_meta['input_chunks']),
set(orig_io_meta['input_chunks']))
self.assertSetEqual(set(io_meta['chunks']),
set(orig_io_meta['chunks']))
self.assertEqual(op_infos[n.op.key]['output_size'],
sum(ch.nbytes for ch in n.op.outputs))
def testSameKey(self, *_):
session_id = str(uuid.uuid4())
graph_key = str(uuid.uuid4())
arr = mt.ones((5, 5), chunks=3)
arr2 = mt.concatenate((arr, arr))
graph = arr2.build_graph(compose=False)
serialized_graph = serialize_graph(graph)
chunked_graph = arr2.build_graph(compose=False, tiled=True)
with create_actor_pool(n_process=1, backend='gevent') as pool:
pool.create_actor(ClusterInfoActor, [pool.cluster_info.address],
uid=ClusterInfoActor.default_name())
resource_ref = pool.create_actor(ResourceActor,
uid=ResourceActor.default_name())
kv_store_ref = pool.create_actor(KVStoreActor,
uid=KVStoreActor.default_name())
pool.create_actor(AssignerActor,
uid=AssignerActor.gen_name(session_id))
graph_ref = pool.create_actor(GraphActor,
session_id,
graph_key,
serialized_graph,
uid=GraphActor.gen_name(
session_id, graph_key))
graph_ref.prepare_graph(compose=False)
graph_data = kv_store_ref.read(
'/sessions/%s/graphs/%s/chunk_graph' %
(session_id, graph_key)).value
self.assertIsNotNone(graph_data)
fetched_graph = deserialize_graph(graph_data)
self.assertEqual(len(chunked_graph), len(fetched_graph))
graph_ref.scan_node()
op_infos = graph_ref.get_operand_info()
for n in fetched_graph:
depth = op_infos[n.op.key]['optimize']['depth']
self.assertIsNotNone(depth)
successor_size = op_infos[
n.op.key]['optimize']['successor_size']
self.assertIsNotNone(successor_size)
descendant_size = op_infos[
n.op.key]['optimize']['descendant_size']
self.assertIsNotNone(descendant_size)
def write_mock_meta():
resource_ref.set_worker_meta('localhost:12345',
dict(hardware=dict(cpu_total=4)))
resource_ref.set_worker_meta('localhost:23456',
dict(hardware=dict(cpu_total=4)))
v = gevent.spawn(write_mock_meta)
v.join()
graph_ref.place_initial_chunks()
op_infos = graph_ref.get_operand_info()
for n in fetched_graph:
if fetched_graph.count_predecessors(n) != 0:
continue
target_worker = op_infos[n.op.key]['target_worker']
self.assertIsNotNone(target_worker)
graph_ref.create_operand_actors()
op_infos = graph_ref.get_operand_info()
for n in fetched_graph:
self.assertEqual(op_infos[n.op.key]['op_name'],
type(n.op).__name__)
io_meta = op_infos[n.op.key]['io_meta']
orig_io_meta = dict(
predecessors=list(
set(pn.op.key
for pn in fetched_graph.iter_predecessors(n))),
successors=list(
set(sn.op.key
for sn in fetched_graph.iter_successors(n))),
input_chunks=list(
set(pn.key
for pn in fetched_graph.iter_predecessors(n))),
chunks=list(c.key for c in n.op.outputs),
)
self.assertSetEqual(set(io_meta['predecessors']),
set(orig_io_meta['predecessors']))
self.assertSetEqual(set(io_meta['successors']),
set(orig_io_meta['successors']))
self.assertSetEqual(set(io_meta['input_chunks']),
set(orig_io_meta['input_chunks']))
self.assertSetEqual(set(io_meta['chunks']),
set(orig_io_meta['chunks']))
self.assertEqual(op_infos[n.op.key]['output_size'],
sum(ch.nbytes for ch in n.op.outputs))