def test_allocations(self):
"""Tests allocations report."""
df = reports.allocations(self.cell)
# cpu disk max_utilization memory rank
# name
# t2/a1 10 10 inf 10 100
# t1/t3/a2 10 10 inf 10 100
self.assertEqual(df.ix['-', 't2/a1']['cpu'], 10)
self.assertEqual(df.ix['-', 't1/t3/a2']['cpu'], 10)
def test_allocations(self):
"""Tests allocations report."""
report = reports.allocations(self.cell)
pd.util.testing.assert_frame_equal(
report,
pd.DataFrame(
[['_default', 't1/t11/a1', 10, 10, 10, 100, 0, 0, np.inf],
['part', 't2/a2', 10, 10, 10, 100, 0, 3, np.inf]],
columns=[
'partition', 'name', 'mem', 'cpu', 'disk', 'rank',
'rank_adj', 'traits', 'max_util'
]).sort_values(by=['partition', 'name']))
def test_empty_cell_reports(self):
"""Tests all reports for an empty cell."""
empty_cell = _construct_cell(empty=True)
servers = reports.servers(empty_cell, self.trait_codes)
empty_servers = pd.DataFrame(columns=[
'name', 'location', 'partition', 'traits', 'state', 'valid_until',
'mem', 'cpu', 'disk', 'mem_free', 'cpu_free', 'disk_free'
]).astype({
'mem': 'int',
'cpu': 'int',
'disk': 'int',
'mem_free': 'int',
'cpu_free': 'int',
'disk_free': 'int'
}).reset_index(drop=True)
pd.util.testing.assert_frame_equal(servers, empty_servers)
allocations = reports.allocations(empty_cell, self.trait_codes)
empty_allocations = pd.DataFrame(columns=[
'partition', 'name', 'mem', 'cpu', 'disk', 'rank', 'rank_adj',
'traits', 'max_util'
]).astype({
'mem': 'int',
'cpu': 'int',
'disk': 'int'
}).reset_index(drop=True)
pd.util.testing.assert_frame_equal(allocations, empty_allocations)
apps = reports.apps(empty_cell, self.trait_codes)
empty_apps = pd.DataFrame(columns=[
'instance', 'allocation', 'rank', 'affinity', 'partition',
'identity_group', 'identity', 'order', 'lease', 'expires',
'data_retention', 'pending', 'server', 'util0', 'util1', 'mem',
'cpu', 'disk'
]).astype({
'mem': 'int',
'cpu': 'int',
'disk': 'int',
'order': 'int',
'expires': 'int',
'data_retention': 'int',
'identity': 'int'
}).reset_index(drop=True)
pd.util.testing.assert_frame_equal(apps, empty_apps)
def scheduler(view, reschedule, csv):
"""Manage Treadmill server configuration."""
treadmill_sched.DIMENSION_COUNT = 3
cell_master = master.Master(context.GLOBAL.zk.conn,
context.GLOBAL.cell)
cell_master.load_buckets()
cell_master.load_cell()
cell_master.load_servers(readonly=True)
cell_master.load_allocations()
cell_master.load_strategies()
cell_master.load_apps()
if reschedule:
cell_master.cell.schedule()
output = None
if view == 'servers':
output = reports.servers(cell_master.cell)
if view == 'features':
output = reports.node_features(cell_master.cell)
if view == 'allocs':
allocs = reports.allocations(cell_master.cell)
features = reports.allocation_features(cell_master.cell)
# TODO: investigate why pd.concat returns series not df.
# pylint: disable=R0204
output = pd.concat([allocs, features], axis=1)
if view == 'apps':
output = reports.apps(cell_master.cell)
if view == 'util':
apps = reports.apps(cell_master.cell)
output = reports.utilization(None, apps)
if output is not None and len(output):
if csv:
print output.to_csv()
else:
print output
def allocs():
"""View allocation report"""
cell_master = make_readonly_master(ctx['run_scheduler'])
allocs = reports.allocations(cell_master.cell, cell_master.trait_codes)
_print(allocs)
def allocs():
"""View allocation report"""
cell_master = _load()
allocs = reports.allocations(cell_master.cell)
_print_frame(allocs)
def allocs():
"""View allocation report"""
cell_master = make_readonly_master(ctx['run_scheduler'])
allocs = reports.allocations(cell_master.cell)
_print(allocs, allocs_formatter)
