fromkafkaimportKafkaConsumerfromkafkaimportTopicPartition consumer= KafkaConsumer(group_id='group2', bootstrap_servers= ['localhost:9092']) consumer.assign([TopicPartition(topic='my_topic', partition=0)])formsginconsumer:print(msg) 超时处理 fromkafkaimportKafkaConsumer consumer= KafkaConsumer('my_topic...
from kafkaimportKafkaConsumer consumer=KafkaConsumer('test',bootstrap_servers=['127.0.0.1:9092'])#参数为接收主题和kafka服务器地址 # 这是一个永久堵塞的过程,生产者消息会缓存在消息队列中,并且不删除,所以每个消息在消息队列中都有偏移formessageinconsumer:# consumer是一个消息队列,当后台有消息时,这个消息...
from kafka import KafkaConsumer import time import threading from concurrent.futures import ThreadPoolExecutor from kafka.structs import TopicPartition class MultiThreadKafka(object): def __init__(self): self.seek = 0 # 偏移量 def operate(self): consumer = KafkaConsumer(bootstrap_servers='localhost...
说明:python 在操作 kafka 写入数据的时候,分为发送往已经存在的主题或者是不存在的主题,当主题不存在的时候,生产者会自动创建该主题,并将消息存贮在默认的 0 分区; 下面是将 kafka-python 库中生产者常用的方法进行封装,以便直接使用。更详细用法在下面第二节中import json import kafka class Producer(object):...
pip install kafka-python 生产者 from kafka import KafkaProducer producer = KafkaProducer(bootstrap_servers=['192.168.145.128:9092']) for i in range(3): msg = 'msg%d' % i producer.send('test', msg) producer.close() 消费者 from kafka import KafkaConsumer ...
from kafka import KafkaConsumer import logging,time from datetime import datetime #若需打印日志加加上logging.basicConfig logging.basicConfig(level=logging.DEBUG,#控制台打印的日志级别 filename='consumer.log', filemode='a',##模式,有w和a,w就是写模式,每次都会重新写日志,覆盖之前的日志 ...
import time from kafka import KafkaConsumer from kafka import TopicPartition bootstrap_servers = ['127.0.0.1:9092'] consumer = KafkaConsumer(group_id='test_consumer_group', bootstrap_servers=bootstrap_servers) consumer.assign([TopicPartition('test_topic', 0)]) for msg in consumer: time.sleep...
要连接Kafka,可以使用Kafka-Python库。以下是一个简单的示例代码,演示如何连接Kafka并发送消息: from kafka import KafkaProducer, KafkaConsumer # 连接Kafka生产者 producer = KafkaProducer(bootstrap_servers='localhost:9092') # 发送消息 producer.send('my_topic', b'Hello, Kafka!') # 关闭生产者连接 ...
subscribe(topics=['test', 'test0']) while True: msg = consumer.poll(timeout_ms=5) print msg time.sleep(1) 消费者-消息挂起与恢复 # -*- coding:utf-8 -*- import time from kafka import KafkaConsumer from kafka.structs import TopicPartition consumer = KafkaConsumer(bootstrap_servers=['...
要消费Kafka数据并将其写入数据库,可以按照以下步骤进行操作: 首先,确保已经安装了kafka-python库,可以使用以下命令安装: pip install kafka-python 复制代码 导入所需的模块: from kafka import KafkaConsumer import json import pymysql 复制代码 创建KafkaConsumer实例,指定要消费的topic和Kafka服务器地址: ...