def queryData(self, idx):
data = []
intv = int(hp.CalcMinutes4Period(self.dateFrom, self.dateTo) / 60)
time_list = hp.GetTimeRanges(self.dateFrom, self.dateTo, intv)
for i in range(len(time_list) - 1):
data.extend(qrs.query4Avg(idx, time_list[i], time_list[i + 1]))
return data
def queryData(dateFrom, dateTo):
data = []
# query in portions since ES does not allow aggregations with more than 10000 bins
intv = int(hp.CalcMinutes4Period(dateFrom, dateTo) / 60)
time_list = hp.GetTimeRanges(dateFrom, dateTo, intv)
for i in range(len(time_list) - 1):
data.extend(query4Avg(time_list[i], time_list[i + 1]))
return data
def loadPacketLossData(dateFrom, dateTo):
data = []
intv = int(hp.CalcMinutes4Period(dateFrom, dateTo) / 60)
time_list = hp.GetTimeRanges(dateFrom, dateTo, intv)
for i in range(len(time_list) - 1):
data.extend(
qrs.query4Avg('ps_packetloss', time_list[i], time_list[i + 1]))
return pd.DataFrame(data)
def getPercentageMeasuresDone(grouped, tempdf):
measures_done = tempdf.groupby('pair').agg({'doc_count': 'sum'})
def findRatio(row, total_minutes):
if pd.isna(row['doc_count']):
count = '0'
else:
count = str(round((row['doc_count'] / total_minutes) * 100)) + '%'
return count
one_test_per_min = hp.CalcMinutes4Period(dateFrom, dateTo)
measures_done['tests_done'] = measures_done.apply(
lambda x: findRatio(x, one_test_per_min), axis=1)
grouped = pd.merge(grouped, measures_done, on='pair', how='left')
return grouped