def __init__(self):
self.et = ElectricTransformation()
self.dt = DataTransformation()
self.bf = BarsimAlgorithm(q_size=100, )
self.pq = CustomBuffer()
self.kc = KafkaConsumer()
self.kp = KafkaProducer()
def __init__(self):
self.et = ElectricTransformation()
self.dt = DataTransformation()
self.bf = BarsimAlgorithm(q_size=100, )
self.bm = LatencyBenchmark()
self.kp = KafkaProducer()
self.hc = HttpConnector(protocol="HTTP",
host="localhost",
port=8000,
path="data/1/")
class QueryOneWOKafka():
def __init__(self):
self.et = ElectricTransformation()
self.dt = DataTransformation()
self.bf = BarsimAlgorithm(q_size=100, )
self.bm = LatencyBenchmark()
self.kp = KafkaProducer()
self.hc = HttpConnector(protocol="HTTP",
host="localhost",
port=8000,
path="data/1/")
def run(self):
rx.create(lambda o, s: self.hc.connect(observer=o, scheduler=s)).pipe(
self.hc.transform_http_request(),
self.dt.transform_to_pandas(),
self.et.active_power(),
self.et.apparent_power(),
self.et.reactive_power(),
self.dt.remove_payload(keys=["records"]),
self.bf.build_window(),
self.bf.predict(),
self.bf.check_event_model_constraints(0.8),
self.bf.compute_loss(),
self.bf.process_detected_event(),
self.bf.prepare_result(),
# self.bm.append_kafka_metrics()
).subscribe(
on_next=lambda x: self.hc.submit(
x), # self.bm.calc_mean_latency(x),
on_error=lambda error: print(error),
on_completed=lambda: self.kp.show_benchmark_results(
start_time_dict=self.hc.start_time_dict))
class QueryOne():
def __init__(self):
self.et = ElectricTransformation()
self.dt = DataTransformation()
self.bf = BarsimAlgorithm(q_size=100, )
self.bm = LatencyBenchmark()
def run(self):
rx.create(lambda o, s: KafkaConsumer().create_subscription(
topics=[
"Input",
], observer=o, scheduler=s)).pipe(
split_payload(),
# self.bm.inject_time("start_time"),
self.dt.transform_to_pandas(),
self.et.active_power(),
self.et.apparent_power(),
self.et.reactive_power(),
self.dt.remove_payload(keys=["records"]),
self.bf.build_window(),
self.bf.predict(),
self.bf.check_event_model_constraints(0.8),
self.bf.compute_loss(),
self.bf.process_detected_event(),
self.bf.prepare_result(),
# self.bm.get_latency("start_time"),
self.bm.append_kafka_metrics()).subscribe(
on_next=lambda x: self.bm.measure_kafka(
x), # self.bm.calc_mean_latency(x),
on_error=lambda error: print(error),
on_completed=lambda: print("Query 1 done!"))
class QueryTwo():
def __init__(self):
self.et = ElectricTransformation()
self.dt = DataTransformation()
self.bf = BarsimAlgorithm(q_size=100, )
self.pq = CustomBuffer()
self.kc = KafkaConsumer()
self.kp = KafkaProducer()
def run(self):
rx.create(lambda o, s: self.kc.create_subscription(
topics=[
"Input_q2",
], observer=o, scheduler=s)).pipe(
split_payload(),
self.pq.buffer_and_manage(),
self.pq.sort_buffer(),
# self.pq.check_order(),
self.dt.transform_to_pandas(),
self.et.active_power(),
self.et.apparent_power(),
self.et.reactive_power(),
self.dt.remove_payload(keys=["records"]),
self.bf.build_window(),
self.bf.predict(),
self.bf.check_event_model_constraints(0.8),
self.bf.compute_loss(),
self.bf.process_detected_event(),
self.bf.prepare_result(),
).subscribe(on_next=lambda x: self.kp.benchmark_sink(x),
on_error=lambda error: print(error),
on_completed=lambda: self.kp.show_benchmark_results(
start_time_dict=self.kc.start_time_dict))
def __init__(self):
self.et = ElectricTransformation()
self.dt = DataTransformation()
self.bf = BarsimAlgorithm(q_size=100, )
self.bm = LatencyBenchmark()