大数据消息处理12.12促销活动

from kafka import KafkaConsumer
from pyflink.datastream import StreamExecutionEnvironment
from pyflink.table import TableEnvironment, DataTypes
from pyflink.table.udf import udf

# Kafka消费者配置
consumer = KafkaConsumer(
    'promotion_events',
    bootstrap_servers=['localhost:9092'],
    auto_offset_reset='earliest',
    enable_auto_commit=True,
    group_id='promotion-group'
)

# Flink环境设置
env = StreamExecutionEnvironment.get_execution_environment()
t_env = TableEnvironment.create(env)

# 定义UDF处理消息
@udf(input_types=[DataTypes.STRING()], result_type=DataTypes.STRING())
def process_event(event):
    # 处理逻辑
    return event

# 创建数据流
ds = env.from_collection(consumer)

# 应用UDF
result = ds.apply(process_event)

# 输出结果
result.print()

# 执行任务
env.execute("Promotion Event Processing")