make dba_hist backward compatible; add dba_hist in fixtures
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@ -22,14 +22,17 @@ class CustomDBTime(BaseTargetObjective):
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def compute(self, metrics, observation_time):
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def compute(self, metrics, observation_time):
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total_wait_time = 0.
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total_wait_time = 0.
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# dba_hist db_time will be 0 after cleaning if & only if it does not exist before cleaning
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has_dba_hist = metrics['global.dba_hist_sys_time_model.db time'] > 0
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for name, value in metrics.items():
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for name, value in metrics.items():
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if 'dba_hist_' not in name:
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if has_dba_hist and 'dba_hist_' not in name:
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continue
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continue
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if 'db cpu' in name:
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if 'db cpu' in name:
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total_wait_time += float(value)
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total_wait_time += float(value)
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elif 'time_waited_micro_fg' in name:
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elif 'time_waited_micro_fg' in name:
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wait_time = float(value)
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wait_time = float(value)
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elif name.endswith('wait_class'):
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elif name.endswith('wait_class'):
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# wait_class#:
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# 0: Other; 1: Application; 2: Configuration; 3: Administrative; 4: Concurrency;
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# 0: Other; 1: Application; 2: Configuration; 3: Administrative; 4: Concurrency;
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# 5: Commit; 6: Idle; 7: Network; 8: User I/O; 9: System I/O
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# 5: Commit; 6: Idle; 7: Network; 8: User I/O; 9: System I/O
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if value == 'Idle':
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if value == 'Idle':
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@ -50,8 +53,9 @@ class NormalizedDBTime(BaseTargetObjective):
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total_wait_time = 0.
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total_wait_time = 0.
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# This target objective is designed for Oracle v12.2.0.1.0
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# This target objective is designed for Oracle v12.2.0.1.0
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dbms = DBMSCatalog.objects.get(type=DBMSType.ORACLE, version='12.2.0.1.0')
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dbms = DBMSCatalog.objects.get(type=DBMSType.ORACLE, version='12.2.0.1.0')
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has_dba_hist = metrics['global.dba_hist_sys_time_model.db time'] > 0
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for name, value in metrics.items():
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for name, value in metrics.items():
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if 'dba_hist_' not in name:
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if has_dba_hist and 'dba_hist_' not in name:
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continue
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continue
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if 'db cpu' in name:
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if 'db cpu' in name:
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total_wait_time += float(value)
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total_wait_time += float(value)
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@ -79,11 +83,14 @@ class NormalizedDBTime(BaseTargetObjective):
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class RawDBTime(BaseTargetObjective):
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class RawDBTime(BaseTargetObjective):
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def __init__(self):
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def __init__(self):
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super().__init__(name='raw_db_time', pprint='DB Time (from sys_time_model)',
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super().__init__(name='raw_db_time', pprint='Raw DB Time',
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unit='seconds', short_unit='s', improvement=LESS_IS_BETTER)
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unit='seconds', short_unit='s', improvement=LESS_IS_BETTER)
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def compute(self, metrics, observation_time):
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def compute(self, metrics, observation_time):
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return metrics['global.dba_hist_sys_time_model.db time'] / 1000000.
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has_dba_hist = metrics['global.dba_hist_sys_time_model.db time'] > 0
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if has_dba_hist:
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return metrics['global.dba_hist_sys_time_model.db time'] / 1000000.
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return metrics['global.sys_time_model.db time'] / 1000000.
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class TransactionCounter(BaseTargetObjective):
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class TransactionCounter(BaseTargetObjective):
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@ -93,8 +100,8 @@ class TransactionCounter(BaseTargetObjective):
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unit='transactions', short_unit='txn', improvement=MORE_IS_BETTER)
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unit='transactions', short_unit='txn', improvement=MORE_IS_BETTER)
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def compute(self, metrics, observation_time):
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def compute(self, metrics, observation_time):
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num_txns = sum(metrics[ctr] for ctr in ('global.dba_hist_sysstat.user commits',
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num_txns = sum(metrics[ctr] for ctr in ('global.sysstat.user commits',
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'global.dba_hist_sysstat.user rollbacks'))
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'global.sysstat.user rollbacks'))
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return num_txns
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return num_txns
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@ -109,8 +116,8 @@ class ElapsedTime(BaseTargetObjective):
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target_objective_list = tuple((DBMSType.ORACLE, target_obj) for target_obj in [ # pylint: disable=invalid-name
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target_objective_list = tuple((DBMSType.ORACLE, target_obj) for target_obj in [ # pylint: disable=invalid-name
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BaseThroughput(transactions_counter=('global.dba_hist_sysstat.user commits',
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BaseThroughput(transactions_counter=('global.sysstat.user commits',
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'global.dba_hist_sysstat.user rollbacks')),
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'global.sysstat.user rollbacks')),
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CustomDBTime(),
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CustomDBTime(),
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NormalizedDBTime(),
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NormalizedDBTime(),
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RawDBTime(),
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RawDBTime(),
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File diff suppressed because it is too large
Load Diff
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@ -665,7 +665,8 @@ def handle_result_files(session, files, execution_times=None):
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transaction_counter = numeric_metric_dict['transaction_counter']
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transaction_counter = numeric_metric_dict['transaction_counter']
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ratio = transaction_counter / first_transaction_counter
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ratio = transaction_counter / first_transaction_counter
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for name in numeric_metric_dict.keys():
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for name in numeric_metric_dict.keys():
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numeric_metric_dict[name] = numeric_metric_dict[name] / ratio
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if not any(n in name for n in ['transaction_counter', 'throughput_txn_per_sec']):
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numeric_metric_dict[name] = numeric_metric_dict[name] / ratio
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metric_data.data = JSONUtil.dumps(numeric_metric_dict)
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metric_data.data = JSONUtil.dumps(numeric_metric_dict)
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metric_data.save()
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metric_data.save()
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