def test_calculate_utilization_median_result(self):
rt = ResultTrace()
self.addCleanup(self._del_table, "usage_values")
rt._get_utilization_result().create_table(self._db)
self._db.insertListValues("usage_values", [
"trace_id", "type", "utilization", "waste", "corrected_utilization"
], [[1, "usage", 0.5, 10, 0.4], [2, "usage", 0.2, 11, 0.2],
[3, "usage", 0.6, 9, 0.5], [4, "usage", 0.7, 13, 0.7]])
rt.calculate_utilization_median_result([1, 2, 3, 4], True, self._db, 5)
new_rt = ResultTrace()
new_rt.load_utilization_results(self._db, 5)
self.assertEqual(new_rt._acc_waste, 10.5)
self.assertEqual(new_rt._integrated_ut, 0.55)
self.assertEqual(new_rt._corrected_integrated_ut, 0.45)
def extract_usage(db_obj,
trace_id_rows,
fill_none=True,
factor=1.0,
mean=False):
"""Takes a list of lists of trace_is and produces a list of lists of results
corresponding to them.
Args:
- db_obj: DBManager object connted to a db where the results will be pulled
from.
"""
exp_rows = []
my = ResultTrace()
res_type = "usage"
if mean:
res_type = "usage_mean"
for row in trace_id_rows:
new_row = []
exp_rows.append(new_row)
for trace_id in row:
exp = ExperimentDefinition()
exp.load(db_obj, trace_id)
result = my._get_utilization_result()
if exp.is_analysis_done():
result.load(db_obj, trace_id, res_type)
else:
result._set("utilization", 0)
result._set("waste", 0)
result._set("corrected_utilization", 0)
result.apply_factor(factor)
new_row.append(result)
return exp_rows
def test_utlization_sotre_load(self):
rt = ResultTrace()
self.addCleanup(self._del_table, "usage_values")
rt._get_utilization_result().create_table(self._db)
rt._lists_start = {
"job_db_inx": [2, 1],
"account": ["account2", "account1"],
"cpus_req": [96, 48],
"cpus_alloc": [96, 48],
"job_name": ["jobName2", "jobName1"],
"id_job": [2, 1],
"id_qos": [3, 2],
"id_resv": [4, 3],
"id_user": [5, 4],
"nodes_alloc": [4, 2],
"partition": ["partition2", "partition1"],
"priority": [199, 99],
"state": [2, 3],
"timelimit": [200, 100],
"time_submit": [3000, 3000],
"time_start": [3001, 3003],
"time_end": [3005, 3010]
}
rt._wf_extractor = FakeWFExtractor()
(integrated_ut, utilization_timestamps, utilization_values, acc_waste,
corrected_ut) = (rt.calculate_utilization(144,
do_preload_until=3003,
endCut=3010,
store=True,
db_obj=self._db,
trace_id=1))
self.assertEqual(acc_waste, 24)
self.assertEqual(utilization_timestamps,
[3003, 3005, 3006, 3007, 3008, 3010])
self.assertEqual(utilization_values, [144, 48, 36, 24, 48, 0])
rt_2 = ResultTrace()
rt_2.load_utilization_results(self._db, 1)
new_ut, new_acc, new_corrected_ut = rt_2.get_utilization_values()
self.assertAlmostEqual(integrated_ut, new_ut)
self.assertEqual(acc_waste, new_acc)
print("new_corrected_ut", new_corrected_ut)
self.assertAlmostEqual(corrected_ut, new_corrected_ut)
