print('spark finalizado')
print(spark)
kinesis = spark \
.readStream \
.format("kinesis") \
.option("streamName", streamName) \
.option("endpointUrl", endpointUrl)\
.option("region", regionName) \
.option("startingPosition", "earliest")\
.load()\
schema = StructType([
StructField("message_type", StringType()),
StructField("count", IntegerType())
])
print(schema.__str__())
print(schema)
print("teste de stream")
def convertCtoF(temp):
return (temp * 1.8) + 32
def convertFtoC(temp):
return ((temp - 32) * 5) / 9
def calculate_heat_index(data):
heat_index_list = []
for i in range(len(data)):
if ((data[i]["TEM_MAX"] != None and data[i]["TEM_MIN"] != None) or
(data[i]["UMD_MAX"] != None and data[i]["UMD_MAX"] != None)):
temp_media = 1.0
