DeepSeek进阶教程：实时数据分析与自动化决策系统 - 实践

进阶教程：实时数据分析与自动化决策系统

1. 实时数据流处理架构

class StreamProcessor:
def __init__(self):
self.window_size = 60 # 滑动窗口大小(秒)
self.analytics_engine = AnalyticsEngine() # 复用之前的分析引擎

def process_kafka_stream(self, topic):
"""从Kafka主题消费实时数据流"""
consumer = KafkaConsumer(
topic,
bootstrap_servers='localhost:9092',
value_deserializer=lambda x: json.loads(x.decode('utf-8'))
)

window_buffer = []
for message in consumer:
window_buffer.append(message.value)
# 滑动窗口处理
if len(window_buffer) >= self.window_size:
self._analyze_window(window_buffer