def insert_into_postgres(localtzone, gb_bldg_canonical_id, gb_mtr_id, gb_energy_type_id, gb_timestamp, gb_agg_reading,
tsMonthStart, tsMonthEnd):
# retrieve meter_id from seed_meter using buildingsnapshot_id, green_button_meter_id, energy_type
res = Meter.objects.filter(custom_meter_id=gb_mtr_id, energy_type=gb_energy_type_id).select_related().filter(
canonical_building=gb_bldg_canonical_id)
# insert in seed_timeseries
for row in res:
mtr_id = row.id
begintime = tsMonthStart.strftime("%Y-%m-%d %H:%M:%S%z")
endtime = tsMonthEnd.strftime("%Y-%m-%d %H:%M:%S%z")
ts = TimeSeries.objects.filter(begin_time=begintime, meter_id=mtr_id)
if not ts:
new_ts = TimeSeries(begin_time=begintime, end_time=endtime, reading=gb_agg_reading, meter_id=mtr_id)
new_ts.save()
else:
_log.info(
'Skipping for ' + str(mtr_id) + ' ts ' + datetime.datetime.fromtimestamp(gb_timestamp / 1000).strftime(
'%Y-%m-%d'))
else:
_log.info('Insertion Loop ended for building id %s', gb_bldg_canonical_id)
def data_analyse(ts_data, name):
finer_ts = []
monthly_ts = []
cache = {}
today_date = date.today()
today_str = today_date.strftime("%m/%d/%Y")
today_month = int(today_date.month)
today_year = int(today_date.year)
immediate_aggregate = False
for ts_cell in ts_data:
if name == "Energy Template" or name == "PM":
# convert to seconds
ts_cell["start"] = int(ts_cell["start"]) / 1000
ts_cell["interval"] = int(ts_cell["interval"]) / 1000
try:
ts_cell["canonical_id"] = str(int(float(ts_cell["canonical_id"])))
except ValueError:
continue
custom_meter_id = ts_cell["custom_meter_id"]
try:
ts_cell["custom_meter_id"] = str(int(float(ts_cell["custom_meter_id"])))
except ValueError:
ts_cell["custom_meter_id"] = custom_meter_id
interval = int(ts_cell["interval"])
building_id = str(ts_cell["canonical_id"])
custom_meter_id = str(ts_cell["custom_meter_id"])
if interval < interval_threshold:
ts_cell["insert_date"] = today_str
ts_dateObj = get_month_from_ts(ts_cell["start"])
if ts_dateObj["month"] != today_month or ts_dateObj["year"] != today_year:
# has back filling
immediate_aggregate = True
finer_ts.append(ts_cell)
else:
monthly_ts.append(ts_cell)
# create or retrieve seed_meter_id
if not building_id + "_" + custom_meter_id in cache:
res = (
Meter.objects.filter(custom_meter_id=custom_meter_id)
.select_related()
.filter(canonical_building=building_id)
)
if not res:
# create new meter record
new_meter = Meter(
name=(name + " METER"),
energy_type=ts_cell["energy_type_int"],
energy_units=ts_cell["uom_int"],
custom_meter_id=ts_cell["custom_meter_id"],
)
new_meter.save()
new_meter.canonical_building.add(CanonicalBuilding.objects.get(id=building_id))
seed_meter_id = int(new_meter.id)
else:
seed_meter_id = int(res[0].id)
cache[building_id + "_" + custom_meter_id] = seed_meter_id
for ts_cell in monthly_ts:
building_id = str(ts_cell["canonical_id"])
custom_meter_id = str(ts_cell["custom_meter_id"])
seed_meter_id = int(cache[building_id + "_" + custom_meter_id])
# save record to timeseries table
begin_ts = int(ts_cell["start"])
interval = int(ts_cell["interval"])
new_ts = TimeSeries(
begin_time=datetime.fromtimestamp(begin_ts),
end_time=datetime.fromtimestamp(begin_ts + interval),
reading=float(ts_cell["value"]),
meter_id=seed_meter_id,
)
new_ts.save()
_log.info("insert monthly data into postgresql finished")
insert_flag = tsdb.insert(finer_ts)
_log.info("insert ts data into KairosDB finished: " + str(insert_flag))
if insert_flag and immediate_aggregate:
_log.info("Having back filling data, aggregate immediately")
tasks.aggregate_monthly_data(ts_data[0]["canonical_id"])
_log.info("Immediate aggregation finished")