def getAllStations():
initEnvironment()
loadStations()
timestamp = time.time()
stationsJson = generalFunctions.dataFrameToJsonStr(stations)
stopEnvironment(sc)
return stationsJson
def getMeasurement():
initEnvironment()
loadCleanDaily()
date = request.args.get('date')
station_id = request.args.get('station_id')
getAllStations = request.args.get('allStations')
weatherData = sparkFunctions.getConcreteWeatherData(clean_daily, station_id, date, getAllStations)
weatherJson = generalFunctions.dataFrameToJsonStr(weatherData)
stopEnvironment(sc)
return jsonify(weatherJson)
def getStats():
initEnvironment()
data = request.data
dataStr = str(data, 'utf-8')
dataDict = json.loads(dataStr)
allStations = dataDict['allStations']
allTime = dataDict['allTime']
dateFrom = dataDict['dateFrom']
dateTo = dataDict['dateTo']
station_id = dataDict['station_id']
try:
if allTime:
loadGlobalWeatherStats()
if allStations:
returnJson = generalFunctions.dataFrameToJsonStr(stations_limits)
stopEnvironment(sc)
return jsonify(returnJson)
else:
tmpDf = sparkFunctions.getLimitsForStation(stations_limits, station_id)
returnJson = generalFunctions.dataFrameToJsonStr(tmpDf)
stopEnvironment(sc)
return jsonify(returnJson)
else:
loadCleanDaily()
if (allStations):
tmpDf = sparkFunctions.getLimitsAllStationsWithInterval(clean_daily, dateFrom, dateTo)
returnJson = generalFunctions.dataFrameToJsonStr(tmpDf)
stopEnvironment(sc)
return jsonify(returnJson)
else:
tmpDf = sparkFunctions.getLimitsStationWithInterval(clean_daily, station_id, dateFrom, dateTo)
returnJson = generalFunctions.dataFrameToJsonStr(tmpDf)
stopEnvironment(sc)
return jsonify(returnJson)
except:
logger.error("Ooops, something went wrong getting the stats")
stopEnvironment(sc)
def getEarthquakes():
initEnvironment()
loadEarthquakes()
date = request.args.get('date')
max_lat = request.args.get('max_lat')
min_lat = request.args.get('min_lat')
max_lon = request.args.get('max_lon')
min_lon = request.args.get('min_lon')
start_time = time.time()
earthquakesData = sparkFunctions.getConcreteEarhquakesData(earthquakes, date, max_lat, min_lat, max_lon, min_lon)
logger.info("--- %s seconds getting the data ---" % (time.time() - start_time))
start_time = time.time()
earthquakesJson = generalFunctions.dataFrameToJsonStr(earthquakesData)
logger.info("--- %s seconds parsing the data to json---" % (time.time() - start_time))
stopEnvironment(sc)
return jsonify(earthquakesJson)
def getEarthquakesIntervalWithQuadrants():
initEnvironment()
loadEarthquakes()
dateFrom = request.args.get('dateFrom')
dateTo = request.args.get('dateTo')
max_y = request.args.get('maxY')
min_y = request.args.get('minY')
max_x = request.args.get('maxX')
min_x = request.args.get('minX')
start_time = time.time()
earthquakesData = sparkFunctions.getConcreteEarhquakesIntervalDataWithQuadrants(earthquakes, dateFrom, dateTo, max_y, min_y, max_x, min_x)
logger.info("--- %s seconds getting the data ---" % (time.time() - start_time))
start_time = time.time()
earthquakesJson = generalFunctions.dataFrameToJsonStr(earthquakesData)
logger.info("--- %s seconds parsing the data to json---" % (time.time() - start_time))
stopEnvironment(sc)
return jsonify(earthquakesJson)
def getWeatherDataInterval():
initEnvironment()
data = request.data
dataStr = str(data, 'utf-8')
dataDict = json.loads(dataStr)
dateFrom = dataDict['dateFrom']
dateTo = dataDict['dateTo']
logger.info("From: " + str(dateFrom))
logger.info("To: " + str(dateTo))
station_id = dataDict['station_id']
try:
loadCleanDaily()
tmpDf = sparkFunctions.getWeatherDataInterval(clean_daily, station_id, dateFrom, dateTo)
returnJson = generalFunctions.dataFrameToJsonStr(tmpDf)
stopEnvironment(sc)
return jsonify(returnJson)
except:
logger.error("Ooops, something went wrong getting the stats")
stopEnvironment(sc)
def getPredictionStats():
try:
data = request.data
dataStr = str(data, 'utf-8')
dataDict = json.loads(dataStr)
initEnvironment()
loadCleanDaily()
station_id = dataDict["station_id"]
fecha = dataDict['fecha']
station_daily = clean_daily.filter(clean_daily.station_id == station_id)
weatherPrediction = sparkFunctions.predictStats(fecha, station_id, station_daily)
if (weatherPrediction):
predictionJson = generalFunctions.dataFrameToJsonStr(weatherPrediction)
else:
predictionJson = "No Prediction"
stopEnvironment(sc)
return jsonify(predictionJson)
except KeyError as ke:
logger.error(ke)
stopEnvironment(sc)
