def test__futures_to_collection(s, a, b):
e = Executor((s.ip, s.port), start=False)
yield e._start()
remote_dfs = e.map(identity, dfs)
ddf = yield _futures_to_collection(remote_dfs, divisions=True)
ddf2 = yield _futures_to_dask_dataframe(remote_dfs, divisions=True)
assert isinstance(ddf, dd.DataFrame)
assert ddf.dask == ddf2.dask
remote_arrays = e.map(np.arange, range(3, 5))
x = yield _futures_to_collection(remote_arrays)
y = yield _futures_to_dask_array(remote_arrays)
assert type(x) == type(y)
assert x.dask == y.dask
remote_lists = yield e._scatter([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
b = yield _futures_to_collection(remote_lists)
c = yield _futures_to_dask_bag(remote_lists)
assert type(b) == type(c)
assert b.dask == b.dask
yield e._shutdown()
def test__dask_array_collections(s, a, b):
import dask.array as da
e = Executor((s.ip, s.port), start=False)
yield e._start()
x_dsk = {('x', i, j): np.random.random((3, 3))
for i in range(3) for j in range(2)}
y_dsk = {('y', i, j): np.random.random((3, 3))
for i in range(2) for j in range(3)}
x_futures = yield e._scatter(x_dsk)
y_futures = yield e._scatter(y_dsk)
dt = np.random.random(0).dtype
x_local = da.Array(x_dsk, 'x', ((3, 3, 3), (3, 3)), dt)
y_local = da.Array(y_dsk, 'y', ((3, 3), (3, 3, 3)), dt)
x_remote = da.Array(x_futures, 'x', ((3, 3, 3), (3, 3)), dt)
y_remote = da.Array(y_futures, 'y', ((3, 3), (3, 3, 3)), dt)
exprs = [
lambda x, y: x.T + y, lambda x, y: x.mean() + y.mean(),
lambda x, y: x.dot(y).std(axis=0),
lambda x, y: x - x.mean(axis=1)[:, None]
]
for expr in exprs:
local = expr(x_local, y_local).compute(get=dask.get)
remote, = e.compute(expr(x_remote, y_remote))
remote = yield remote._result()
assert np.all(local == remote)
yield e._shutdown()
def test_with_data(s, a, b):
ss = HTTPScheduler(s)
ss.listen(0)
e = Executor((s.ip, s.port), start=False)
yield e._start()
L = e.map(inc, [1, 2, 3])
L2 = yield e._scatter(['Hello', 'world!'])
yield _wait(L)
client = AsyncHTTPClient()
response = yield client.fetch('http://localhost:%s/memory-load.json' %
ss.port)
out = json.loads(response.body.decode())
assert all(isinstance(v, int) for v in out.values())
assert set(out) == {a.address_string, b.address_string}
assert sum(out.values()) == sum(
map(sys.getsizeof, [1, 2, 3, 'Hello', 'world!']))
response = yield client.fetch(
'http://localhost:%s/memory-load-by-key.json' % ss.port)
out = json.loads(response.body.decode())
assert set(out) == {a.address_string, b.address_string}
assert all(isinstance(v, dict) for v in out.values())
assert all(k in {'inc', 'data'} for d in out.values() for k in d)
assert all(isinstance(v, int) for d in out.values() for v in d.values())
assert sum(v for d in out.values() for v in d.values()) == \
sum(map(sys.getsizeof, [1, 2, 3, 'Hello', 'world!']))
ss.stop()
yield e._shutdown()
def test__dask_array_collections(s, a, b):
import dask.array as da
e = Executor((s.ip, s.port), start=False)
yield e._start()
x_dsk = {('x', i, j): np.random.random((3, 3)) for i in range(3)
for j in range(2)}
y_dsk = {('y', i, j): np.random.random((3, 3)) for i in range(2)
for j in range(3)}
x_futures = yield e._scatter(x_dsk)
y_futures = yield e._scatter(y_dsk)
dt = np.random.random(0).dtype
x_local = da.Array(x_dsk, 'x', ((3, 3, 3), (3, 3)), dt)
y_local = da.Array(y_dsk, 'y', ((3, 3), (3, 3, 3)), dt)
x_remote = da.Array(x_futures, 'x', ((3, 3, 3), (3, 3)), dt)
y_remote = da.Array(y_futures, 'y', ((3, 3), (3, 3, 3)), dt)
exprs = [lambda x, y: x.T + y,
lambda x, y: x.mean() + y.mean(),
lambda x, y: x.dot(y).std(axis=0),
lambda x, y: x - x.mean(axis=1)[:, None]]
for expr in exprs:
local = expr(x_local, y_local).compute(get=dask.get)
remote = e.compute(expr(x_remote, y_remote))
remote = yield remote._result()
assert np.all(local == remote)
yield e._shutdown()
def test__futures_to_dask_bag(s, a, b):
import dask.bag as db
e = Executor((s.ip, s.port), start=False)
yield e._start()
L = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
futures = yield e._scatter(L)
rb = yield _futures_to_dask_bag(futures)
assert isinstance(rb, db.Bag)
assert rb.npartitions == len(L)
lb = db.from_sequence([1, 2, 3, 4, 5, 6, 7, 8, 9], npartitions=3)
exprs = [lambda x: x.map(lambda x: x + 1).sum(),
lambda x: x.filter(lambda x: x % 2)]
for expr in exprs:
local = expr(lb).compute(get=dask.get)
remote = e.compute(expr(rb))
remote = yield remote._result()
assert local == remote
yield e._shutdown()
def test_with_data(s, a, b):
ss = HTTPScheduler(s)
ss.listen(0)
e = Executor((s.ip, s.port), start=False)
yield e._start()
L = e.map(inc, [1, 2, 3])
L2 = yield e._scatter(['Hello', 'world!'])
yield _wait(L)
client = AsyncHTTPClient()
response = yield client.fetch('http://localhost:%s/memory-load.json' %
ss.port)
out = json.loads(response.body.decode())
assert all(isinstance(v, int) for v in out.values())
assert set(out) == {a.address_string, b.address_string}
assert sum(out.values()) == sum(map(sys.getsizeof,
[1, 2, 3, 'Hello', 'world!']))
response = yield client.fetch('http://localhost:%s/memory-load-by-key.json'
% ss.port)
out = json.loads(response.body.decode())
assert set(out) == {a.address_string, b.address_string}
assert all(isinstance(v, dict) for v in out.values())
assert all(k in {'inc', 'data'} for d in out.values() for k in d)
assert all(isinstance(v, int) for d in out.values() for v in d.values())
assert sum(v for d in out.values() for v in d.values()) == \
sum(map(sys.getsizeof, [1, 2, 3, 'Hello', 'world!']))
ss.stop()
yield e._shutdown()
def test__futures_to_collection(s, a, b):
e = Executor((s.ip, s.port), start=False)
yield e._start()
remote_dfs = e.map(identity, dfs)
ddf = yield _futures_to_collection(remote_dfs, divisions=True)
ddf2 = yield _futures_to_dask_dataframe(remote_dfs, divisions=True)
assert isinstance(ddf, dd.DataFrame)
assert ddf.dask == ddf2.dask
remote_arrays = e.map(np.arange, range(3, 5))
x = yield _futures_to_collection(remote_arrays)
y = yield _futures_to_dask_array(remote_arrays)
assert type(x) == type(y)
assert x.dask == y.dask
remote_lists = yield e._scatter([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
b = yield _futures_to_collection(remote_lists)
c = yield _futures_to_dask_bag(remote_lists)
assert type(b) == type(c)
assert b.dask == b.dask
yield e._shutdown()
def test__futures_to_dask_bag(s, a, b):
import dask.bag as db
e = Executor((s.ip, s.port), start=False)
yield e._start()
L = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
futures = yield e._scatter(L)
rb = yield _futures_to_dask_bag(futures)
assert isinstance(rb, db.Bag)
assert rb.npartitions == len(L)
lb = db.from_sequence([1, 2, 3, 4, 5, 6, 7, 8, 9], npartitions=3)
exprs = [
lambda x: x.map(lambda x: x + 1).sum(),
lambda x: x.filter(lambda x: x % 2)
]
for expr in exprs:
local = expr(lb).compute(get=dask.get)
remote = e.compute(expr(rb))
remote = yield remote._result()
assert local == remote
yield e._shutdown()
def f(c, a, b):
e = Executor((c.ip, c.port), start=False, loop=loop)
yield e._start()
x_dsk = {('x', i, j): np.random.random((3, 3)) for i in range(3)
for j in range(2)}
y_dsk = {('y', i, j): np.random.random((3, 3)) for i in range(2)
for j in range(3)}
x_futures = yield e._scatter(x_dsk)
y_futures = yield e._scatter(y_dsk)
dt = np.random.random(0).dtype
x_local = da.Array(x_dsk, 'x', ((3, 3, 3), (3, 3)), dt)
y_local = da.Array(y_dsk, 'y', ((3, 3), (3, 3, 3)), dt)
x_remote = da.Array(x_futures, 'x', ((3, 3, 3), (3, 3)), dt)
y_remote = da.Array(y_futures, 'y', ((3, 3), (3, 3, 3)), dt)
exprs = [lambda x, y: x.T + y,
lambda x, y: x.mean() + y.mean(),
lambda x, y: x.dot(y).std(axis=0),
lambda x, y: x - x.mean(axis=1)[:, None]]
for expr in exprs:
local = expr(x_local, y_local)
local_results = dask.get(local.dask, local._keys())
local_result = da.Array._finalize(local, local_results)
remote = expr(x_remote, y_remote)
remote_results = yield e._get(remote.dask, remote._keys())
remote_result = da.Array._finalize(remote, remote_results)
assert np.all(local_result == remote_result)
yield e._shutdown()
def test_write_bytes(s, a, b):
with make_hdfs() as hdfs:
e = Executor((s.ip, s.port), start=False)
yield e._start()
data = [b'123', b'456', b'789']
remote_data = yield e._scatter(data)
futures = write_bytes('/tmp/test/data/file.*.dat', remote_data, hdfs=hdfs)
yield _wait(futures)
assert len(hdfs.ls('/tmp/test/data/')) == 3
with hdfs.open('/tmp/test/data/file.1.dat') as f:
assert f.read() == b'456'
futures = write_bytes('/tmp/test/data2/', remote_data, hdfs=hdfs)
yield _wait(futures)
assert len(hdfs.ls('/tmp/test/data2/')) == 3
def test_write_binary(s, a, b):
with make_hdfs() as hdfs:
e = Executor((s.ip, s.port), start=False)
yield e._start()
data = [b'123', b'456', b'789']
remote_data = yield e._scatter(data)
futures = write_binary('/tmp/test/data/file.*.dat',
remote_data,
hdfs=hdfs)
yield _wait(futures)
assert len(hdfs.ls('/tmp/test/data/')) == 3
with hdfs.open('/tmp/test/data/file.1.dat') as f:
assert f.read() == b'456'
futures = write_binary('/tmp/test/data2/', remote_data, hdfs=hdfs)
yield _wait(futures)
assert len(hdfs.ls('/tmp/test/data2/')) == 3
