def testReExecuteExisting(self):
pool_address = '127.0.0.1:%d' % get_next_port()
session_id = str(uuid.uuid4())
mock_data = np.array([1, 2, 3, 4])
with create_actor_pool(n_process=1,
backend='gevent',
address=pool_address,
distributor=MarsDistributor(2, 'w:0:')) as pool:
self.create_standard_actors(pool,
pool_address,
with_daemon=False,
with_status=False)
pool.create_actor(CpuCalcActor, uid='w:1:cpu-calc')
pool.create_actor(InProcHolderActor, uid='w:1:inproc-holder')
import mars.tensor as mt
arr = mt.ones((4, ), chunk_size=4)
arr_add = mt.array(mock_data)
result_tensor = arr + arr_add
graph = result_tensor.build_graph(compose=False, tiled=True)
result_tensor = get_tiled(result_tensor)
def _validate(*_):
data = test_actor.shared_store.get(session_id,
result_tensor.chunks[0].key)
assert_array_equal(data, mock_data + np.ones((4, )))
with self.run_actor_test(pool) as test_actor:
graph_key = str(uuid.uuid4())
execution_ref = test_actor.promise_ref(
ExecutionActor.default_uid())
execution_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
dict(chunks=[result_tensor.chunks[0].key]), None, _promise=True) \
.then(_validate) \
.then(lambda *_: test_actor.set_result(None)) \
.catch(lambda *exc: test_actor.set_result(exc, False))
self.get_result()
with self.run_actor_test(pool) as test_actor:
execution_ref = test_actor.promise_ref(
ExecutionActor.default_uid())
execution_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
dict(chunks=[result_tensor.chunks[0].key]), None, _promise=True) \
.then(_validate) \
.then(lambda *_: test_actor.set_result(None)) \
.catch(lambda *exc: test_actor.set_result(exc, False))
self.get_result()
def testStopGraphCalc(self):
pool_address = '127.0.0.1:%d' % get_next_port()
session_id = str(uuid.uuid4())
mock_data = np.array([1, 2, 3, 4])
with create_actor_pool(n_process=2, backend='gevent',
address=pool_address, distributor=MarsDistributor(2, 'w:0:')) as pool:
self.create_standard_actors(pool, pool_address, with_status=False)
daemon_ref = pool.actor_ref(WorkerDaemonActor.default_uid())
execution_ref = pool.actor_ref(ExecutionActor.default_uid())
calc_ref = daemon_ref.create_actor(
MockCpuCalcActor, session_id, mock_data, 10, uid='w:1:cpu-calc-a')
daemon_ref.create_actor(ProcessHelperActor, uid='w:1:proc-helper-a')
test_actor = pool.create_actor(ExecutionTestActor, uid='w:0:test_actor')
test_actor.run_simple_calc(session_id, _tell=True)
pool.sleep(2)
proc_id = pool.distributor.distribute(calc_ref.uid)
execution_ref.stop_execution(session_id, test_actor.get_graph_key(), _tell=True)
while daemon_ref.is_actor_process_alive(calc_ref):
pool.sleep(0.1)
pool.restart_process(proc_id)
daemon_ref.handle_process_down([proc_id])
with self.assertRaises(ExecutionInterrupted):
self.wait_for_result(pool, test_actor)
def testEstimateGraphFinishTime(self):
pool_address = '127.0.0.1:%d' % get_next_port()
session_id = str(uuid.uuid4())
with create_actor_pool(n_process=1, backend='gevent', address=pool_address) as pool:
self.create_standard_actors(pool, pool_address, with_daemon=False)
status_ref = pool.actor_ref(StatusActor.default_uid())
execution_ref = pool.actor_ref(ExecutionActor.default_uid())
pool.create_actor(CpuCalcActor)
import mars.tensor as mt
arr = mt.ones((10, 8), chunk_size=10)
graph = arr.build_graph(compose=False, tiled=True)
arr = get_tiled(arr)
graph_key = str(uuid.uuid4())
for _ in range(options.optimize.min_stats_count + 1):
status_ref.update_mean_stats(
'calc_speed.' + type(arr.chunks[0].op).__name__, 10)
status_ref.update_mean_stats('disk_read_speed', 10)
status_ref.update_mean_stats('disk_write_speed', 10)
status_ref.update_mean_stats('net_transfer_speed', 10)
execution_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
dict(chunks=[arr.chunks[0].key]), None)
execution_ref.estimate_graph_finish_time(session_id, graph_key)
stats_dict = status_ref.get_stats(['min_est_finish_time', 'max_est_finish_time'])
self.assertIsNotNone(stats_dict.get('min_est_finish_time'))
self.assertIsNotNone(stats_dict.get('max_est_finish_time'))
def testSendTargets(self):
pool_address = f'127.0.0.1:{get_next_port()}'
session_id = str(uuid.uuid4())
mock_data = np.array([1, 2, 3, 4])
with create_actor_pool(n_process=1,
backend='gevent',
address=pool_address,
distributor=MarsDistributor(2, 'w:0:')) as pool:
self.create_standard_actors(pool,
pool_address,
with_daemon=False,
with_status=False)
pool.create_actor(CpuCalcActor)
pool.create_actor(InProcHolderActor)
import mars.tensor as mt
arr = mt.ones((4, ), chunk_size=4)
arr_add = mt.array(mock_data)
result_tensor = arr + arr_add
graph = result_tensor.build_graph(fuse_enabled=False, tiled=True)
result_tensor = get_tiled(result_tensor)
result_key = result_tensor.chunks[0].key
pool.create_actor(MockSenderActor, [mock_data + np.ones((4, ))],
'out',
uid='w:mock_sender')
with self.run_actor_test(pool) as test_actor:
def _validate(*_):
data = test_actor.shared_store.get(
session_id, result_tensor.chunks[0].key)
assert_array_equal(data, mock_data + np.ones((4, )))
graph_key = str(uuid.uuid4())
execution_ref = test_actor.promise_ref(
ExecutionActor.default_uid())
execution_ref.execute_graph(
session_id,
graph_key,
serialize_graph(graph),
dict(chunks=[result_tensor.chunks[0].key]),
None,
_tell=True)
execution_ref.send_data_to_workers(
session_id,
graph_key, {result_key: (pool_address, )},
_tell=True)
execution_ref.add_finish_callback(session_id, graph_key, _promise=True) \
.then(_validate) \
.then(lambda *_: test_actor.set_result(None)) \
.catch(lambda *exc: test_actor.set_result(exc, False))
self.get_result()
def run_simple_calc(self, session_id):
self._session_id = session_id
import mars.tensor as mt
arr = mt.ones((4,), chunk_size=4) + 1
graph = arr.build_graph(compose=False, tiled=True)
arr = get_tiled(arr)
self._array_key = arr.chunks[0].key
graph_key = self._graph_key = str(uuid.uuid4())
execution_ref = self.promise_ref(ExecutionActor.default_uid())
execution_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
dict(chunks=[arr.chunks[0].key]), None, _tell=True)
execution_ref.add_finish_callback(session_id, graph_key, _promise=True) \
.then(lambda *_: self._results.append((True,))) \
.catch(lambda *exc: self._results.append((False, exc)))
def run_test(self, worker):
import mars.tensor as mt
from mars.worker import ExecutionActor
session_id = str(uuid.uuid4())
a = mt.random.rand(100, 50, chunk_size=30)
b = mt.random.rand(50, 200, chunk_size=30)
result = a.dot(b)
graph = result.build_graph(tiled=True)
executor_ref = self.promise_ref(ExecutionActor.default_uid(),
address=worker)
io_meta = dict(chunks=[c.key for c in result.chunks])
graph_key = str(id(graph))
executor_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
io_meta, None, _promise=True) \
.then(lambda *_: setattr(self, '_replied', True))
def create_standard_actors(cls,
pool,
address,
quota_size=None,
with_daemon=True,
with_status=True,
with_resource=False):
quota_size = quota_size or (1024 * 1024)
pool.create_actor(SchedulerClusterInfoActor, [address],
uid=SchedulerClusterInfoActor.default_uid())
pool.create_actor(WorkerClusterInfoActor, [address],
uid=WorkerClusterInfoActor.default_uid())
pool.create_actor(PlasmaKeyMapActor,
uid=PlasmaKeyMapActor.default_uid())
pool.create_actor(StorageManagerActor,
uid=StorageManagerActor.default_uid())
if with_resource:
pool.create_actor(ResourceActor, uid=ResourceActor.default_uid())
if with_daemon:
pool.create_actor(WorkerDaemonActor,
uid=WorkerDaemonActor.default_uid())
if with_status:
pool.create_actor(StatusActor,
address,
uid=StatusActor.default_uid())
pool.create_actor(SharedHolderActor,
cls.plasma_storage_size,
uid=SharedHolderActor.default_uid())
pool.create_actor(ChunkMetaActor, uid=ChunkMetaActor.default_uid())
pool.create_actor(DispatchActor, uid=DispatchActor.default_uid())
pool.create_actor(QuotaActor,
quota_size,
uid=MemQuotaActor.default_uid())
pool.create_actor(ExecutionActor, uid=ExecutionActor.default_uid())
def testFetchRemoteData(self):
pool_address = '127.0.0.1:%d' % get_next_port()
session_id = str(uuid.uuid4())
mock_data = np.array([1, 2, 3, 4])
with create_actor_pool(n_process=1, backend='gevent',
address=pool_address, distributor=MarsDistributor(2, 'w:0:')) as pool:
self.create_standard_actors(pool, pool_address, with_daemon=False, with_status=False,
with_resource=True)
pool.create_actor(CpuCalcActor)
pool.create_actor(InProcHolderActor)
pool.create_actor(MockSenderActor, [mock_data], 'in', uid='w:mock_sender')
import mars.tensor as mt
from mars.tensor.fetch import TensorFetch
arr = mt.ones((4,), chunk_size=4)
arr_add = mt.array(mock_data)
result_tensor = arr + arr_add
graph = result_tensor.build_graph(compose=False, tiled=True)
arr_add = get_tiled(arr_add)
result_tensor = get_tiled(result_tensor)
modified_chunk = arr_add.chunks[0]
arr_add.chunks[0]._op = TensorFetch(
dtype=modified_chunk.dtype, _outputs=[weakref.ref(o) for o in modified_chunk.op.outputs],
_key=modified_chunk.op.key)
with self.run_actor_test(pool) as test_actor:
graph_key = str(uuid.uuid4())
execution_ref = test_actor.promise_ref(ExecutionActor.default_uid())
execution_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
dict(chunks=[result_tensor.chunks[0].key]), None, _tell=True)
execution_ref.add_finish_callback(session_id, graph_key, _promise=True) \
.then(lambda *_: test_actor.set_result(None)) \
.catch(lambda *exc: test_actor.set_result(exc, False))
with self.assertRaises(DependencyMissing):
self.get_result()
metas = {modified_chunk.key: WorkerMeta(mock_data.nbytes, mock_data.shape, ('0.0.0.0:1234',))}
with self.run_actor_test(pool) as test_actor:
graph_key = str(uuid.uuid4())
execution_ref = test_actor.promise_ref(ExecutionActor.default_uid())
execution_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
dict(chunks=[result_tensor.chunks[0].key]), metas, _tell=True)
execution_ref.add_finish_callback(session_id, graph_key, _promise=True) \
.then(lambda *_: test_actor.set_result(None)) \
.catch(lambda *exc: test_actor.set_result(exc, False))
with self.assertRaises(DependencyMissing):
self.get_result()
metas[modified_chunk.key] = WorkerMeta(
mock_data.nbytes, mock_data.shape,
('0.0.0.0:1234', pool_address.replace('127.0.0.1', 'localhost')))
with self.run_actor_test(pool) as test_actor:
def _validate(_):
data = test_actor.shared_store.get(session_id, result_tensor.chunks[0].key)
assert_array_equal(data, mock_data + np.ones((4,)))
graph_key = str(uuid.uuid4())
execution_ref = test_actor.promise_ref(ExecutionActor.default_uid())
execution_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
dict(chunks=[result_tensor.chunks[0].key]), metas, _tell=True)
execution_ref.add_finish_callback(session_id, graph_key, _promise=True) \
.then(_validate) \
.then(lambda *_: test_actor.set_result(None)) \
.catch(lambda *exc: test_actor.set_result(exc, False))
self.get_result()
def testPrepareSpilled(self):
pool_address = '127.0.0.1:%d' % get_next_port()
session_id = str(uuid.uuid4())
mock_data = np.array([1, 2, 3, 4])
options.worker.spill_directory = tempfile.mkdtemp(prefix='mars_worker_prep_spilled-')
with create_actor_pool(n_process=1, backend='gevent', address=pool_address) as pool:
self.create_standard_actors(pool, pool_address, with_daemon=False, with_status=False)
pool.create_actor(IORunnerActor)
pool.create_actor(CpuCalcActor)
pool.create_actor(InProcHolderActor)
import mars.tensor as mt
from mars.tensor.fetch import TensorFetch
arr = mt.ones((4,), chunk_size=4)
arr_add = mt.array(mock_data)
result_tensor = arr + arr_add
graph = result_tensor.build_graph(compose=False, tiled=True)
arr_add = get_tiled(arr_add)
result_tensor = get_tiled(result_tensor)
modified_chunk = arr_add.chunks[0]
arr_add.chunks[0]._op = TensorFetch(
dtype=modified_chunk.dtype, _outputs=[weakref.ref(o) for o in modified_chunk.op.outputs],
_key=modified_chunk.op.key)
# test meta missing
with self.run_actor_test(pool) as test_actor:
graph_key = str(uuid.uuid4())
execution_ref = test_actor.promise_ref(ExecutionActor.default_uid())
execution_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
dict(chunks=[result_tensor.chunks[0].key]), None, _promise=True) \
.then(lambda *_: test_actor.set_result(None)) \
.catch(lambda *exc: test_actor.set_result(exc, False))
with self.assertRaises(DependencyMissing):
self.get_result()
metas = {modified_chunk.key: WorkerMeta(
mock_data.nbytes, mock_data.shape, ('0.0.0.0:1234', pool_address))}
# test read from spilled file
with self.run_actor_test(pool) as test_actor:
self.waitp(
test_actor.storage_client.put_objects(
session_id, [modified_chunk.key], [mock_data], [DataStorageDevice.PROC_MEMORY])
.then(lambda *_: test_actor.storage_client.copy_to(
session_id, [modified_chunk.key], [DataStorageDevice.DISK]))
)
test_actor.storage_client.delete(session_id, [modified_chunk.key],
[DataStorageDevice.PROC_MEMORY])
def _validate(_):
data = test_actor.shared_store.get(session_id, result_tensor.chunks[0].key)
assert_array_equal(data, mock_data + np.ones((4,)))
graph_key = str(uuid.uuid4())
execution_ref = test_actor.promise_ref(ExecutionActor.default_uid())
execution_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
dict(chunks=[result_tensor.chunks[0].key]), metas, _promise=True) \
.then(_validate) \
.then(lambda *_: test_actor.set_result(None)) \
.catch(lambda *exc: test_actor.set_result(exc, False))
self.get_result()
def testPrepareQuota(self, *_):
pinned = True
orig_pin = SharedHolderActor.pin_data_keys
def _mock_pin(self, session_id, chunk_keys, token):
from mars.errors import PinDataKeyFailed
if pinned:
raise PinDataKeyFailed
return orig_pin(self, session_id, chunk_keys, token)
pool_address = '127.0.0.1:%d' % get_next_port()
session_id = str(uuid.uuid4())
mock_data = np.array([1, 2, 3, 4])
with patch_method(SharedHolderActor.pin_data_keys, new=_mock_pin), \
create_actor_pool(n_process=1, backend='gevent', address=pool_address) as pool:
self.create_standard_actors(pool, pool_address, with_daemon=False, with_status=False)
pool.create_actor(MockSenderActor, [mock_data], 'in', uid='w:mock_sender')
pool.create_actor(CpuCalcActor)
pool.create_actor(InProcHolderActor)
pool.actor_ref(WorkerClusterInfoActor.default_uid())
import mars.tensor as mt
from mars.tensor.fetch import TensorFetch
arr = mt.ones((4,), chunk_size=4)
arr_add = mt.array(mock_data)
result_tensor = arr + arr_add
graph = result_tensor.build_graph(compose=False, tiled=True)
arr_add = get_tiled(arr_add)
result_tensor = get_tiled(result_tensor)
modified_chunk = arr_add.chunks[0]
arr_add.chunks[0]._op = TensorFetch(
dtype=modified_chunk.dtype, _outputs=[weakref.ref(o) for o in modified_chunk.op.outputs],
_key=modified_chunk.op.key)
metas = {modified_chunk.key: WorkerMeta(
mock_data.nbytes, mock_data.shape,
('0.0.0.0:1234', pool_address.replace('127.0.0.1', 'localhost')))}
with self.run_actor_test(pool) as test_actor:
graph_key = str(uuid.uuid4())
execution_ref = test_actor.promise_ref(ExecutionActor.default_uid())
start_time = time.time()
execution_ref.execute_graph(
session_id, graph_key, serialize_graph(graph),
dict(chunks=[result_tensor.chunks[0].key]), metas, _tell=True)
execution_ref.add_finish_callback(session_id, graph_key, _promise=True) \
.then(lambda *_: test_actor.set_result(time.time())) \
.catch(lambda *exc: test_actor.set_result(exc, False))
def _delay_fun():
nonlocal pinned
time.sleep(0.5)
pinned = False
threading.Thread(target=_delay_fun).start()
finish_time = self.get_result()
self.assertGreaterEqual(finish_time, start_time + 0.5)
def testSimpleExecution(self):
pool_address = '127.0.0.1:%d' % get_next_port()
with create_actor_pool(n_process=1, backend='gevent', address=pool_address) as pool:
self.create_standard_actors(pool, pool_address, with_daemon=False)
pool.create_actor(CpuCalcActor, uid='w:1:calc-a')
pool.create_actor(InProcHolderActor)
import mars.tensor as mt
from mars.tensor.datasource import TensorOnes
from mars.tensor.fetch import TensorFetch
arr = mt.ones((10, 8), chunk_size=10)
arr_add = mt.ones((10, 8), chunk_size=10)
arr2 = arr + arr_add
graph = arr2.build_graph(compose=False, tiled=True)
arr = get_tiled(arr)
arr2 = get_tiled(arr2)
metas = dict()
for chunk in graph:
if isinstance(chunk.op, TensorOnes):
chunk._op = TensorFetch(
dtype=chunk.dtype, _outputs=[weakref.ref(o) for o in chunk.op.outputs],
_key=chunk.op.key)
metas[chunk.key] = WorkerMeta(chunk.nbytes, chunk.shape, pool_address)
with self.run_actor_test(pool) as test_actor:
session_id = str(uuid.uuid4())
storage_client = test_actor.storage_client
self.waitp(
storage_client.put_objects(session_id, [arr.chunks[0].key], [np.ones((10, 8), dtype=np.int16)],
[DataStorageDevice.SHARED_MEMORY]),
)
execution_ref = test_actor.promise_ref(ExecutionActor.default_uid())
def _validate(_):
data = test_actor.shared_store.get(session_id, arr2.chunks[0].key)
assert_array_equal(data, 2 * np.ones((10, 8)))
graph_key = str(uuid.uuid4())
execution_ref.execute_graph(session_id, graph_key, serialize_graph(graph),
dict(chunks=[arr2.chunks[0].key]), metas, _promise=True) \
.then(_validate) \
.then(lambda *_: test_actor.set_result(None)) \
.catch(lambda *exc: test_actor.set_result(exc, False))
self.get_result()
with self.run_actor_test(pool) as test_actor:
execution_ref = test_actor.promise_ref(ExecutionActor.default_uid())
def _validate(_):
data = test_actor.shared_store.get(session_id, arr2.chunks[0].key)
assert_array_equal(data, 2 * np.ones((10, 8)))
execution_ref.add_finish_callback(session_id, graph_key, _promise=True) \
.then(_validate) \
.then(lambda *_: test_actor.set_result(None)) \
.catch(lambda *exc: test_actor.set_result(exc, False))
self.get_result()