public
/
ottertune
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

fix first normalized_db_time unequal to raw_db_time

This commit is contained in:
yangdsh 2020-04-22 15:21:23 +00:00 committed by Dana Van Aken
parent 93d6fa5339
commit 5df71fb436
1 changed files with 5 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
server/website/website/views.py
View File

@ -645,6 +645,7 @@ def handle_result_files(session, files, execution_times=None):
metric_data = MetricData.objects.create_metric_data( metric_data = MetricData.objects.create_metric_data(
session, JSONUtil.dumps(metric_dict, pprint=True, sort=True), session, JSONUtil.dumps(metric_dict, pprint=True, sort=True),
JSONUtil.dumps(numeric_metric_dict, pprint=True, sort=True), dbms) JSONUtil.dumps(numeric_metric_dict, pprint=True, sort=True), dbms)
if 'status' in summary and summary['status'] == "range_test": if 'status' in summary and summary['status'] == "range_test":
# The metric should not be used for learning because the driver did not run workload # The metric should not be used for learning because the driver did not run workload
# We tag the metric as invalid, so later they will be set to the worst result # We tag the metric as invalid, so later they will be set to the worst result
@ -659,6 +660,10 @@ def handle_result_files(session, files, execution_times=None):
metric = MetricCatalog.objects.get(dbms=dbms, name=name) metric = MetricCatalog.objects.get(dbms=dbms, name=name)
metric.default = numeric_metric_dict[name] metric.default = numeric_metric_dict[name]
metric.save() metric.save()
numeric_metric_dict = parser.convert_dbms_metrics(
dbms.pk, metric_dict, observation_time, session.target_objective)
metric_data.data = JSONUtil.dumps(numeric_metric_dict)
metric_data.save()
# Normalize metrics by the amount of work # Normalize metrics by the amount of work
if '*' not in metric_data.name and 'transaction_counter' in numeric_metric_dict.keys(): if '*' not in metric_data.name and 'transaction_counter' in numeric_metric_dict.keys():
# Find the first valid result as the base # Find the first valid result as the base