RabbitMQ提供了三种类型的队列:
官方文档 对于流队列的描述是:高性能、可持久化、可复制、非破坏性消费、只追加写入的日志
使用场景:
生产消息:
import pika
from pika import BasicProperties
from pika.adapters.blocking_connection import BlockingChannel
from pika.spec import Basic
STREAM_QUEUE = "stream_queue"
connection = pika.BlockingConnection(pika.ConnectionParameters("localhost", 5672, "/"))
channel = connection.channel()
channel.queue_declare(queue=STREAM_QUEUE, durable=True, arguments={"x-queue-type": "stream"})
for i in range(500, 600):
msg = f"{i}".encode()
channel.basic_publish("", STREAM_QUEUE, msg)
channel.close()
connection.close()
消费消息:
import pika
from pika import BasicProperties
from pika.adapters.blocking_connection import BlockingChannel
from pika.spec import Basic
def msg_handler(channel: BlockingChannel, method: Basic.Deliver, properties: BasicProperties, body: bytes):
msg = f"获取消息:{body.decode()}"
print(msg)
channel.basic_ack(method.delivery_tag)
STREAM_QUEUE = "stream_queue"
connection = pika.BlockingConnection(pika.ConnectionParameters("localhost", 5672, "/"))
channel = connection.channel()
channel.queue_declare(queue=STREAM_QUEUE, durable=True, arguments={"x-queue-type": "stream"})
channel.basic_qos(prefetch_count=50)
channel.basic_consume(STREAM_QUEUE, on_message_callback=msg_handler, arguments={"x-stream-offset": 290})
channel.start_consuming()
channel.close()
connection.close()
可以通过x-stream-offset来控制读取消息的位置,对于改参数值的释义见下图,详情可参考:Offset Tracking with RabbitMQ Streams。
上图中有个chunk的概念,chunk就是stream队列中用于存储和传输消息的单元,一个chunk包含几条到几千条不等的消息。
以上只是对Stream类型队列的简单使用,API和普通队列没有差异。若要体验完整的Stream队列特性,如:服务端消息偏移量追踪,需要启用stream插件。
不启用和启用流插件功能特性对比,可参考: Stream Core vs Stream Plugin。
Stream提供了服务端消息偏移量追踪,客户端断开重连后可以从上次消费的下一个位置开始消费消息。
⚠️ 有些客户端不支持dedicated binary 协议,无法提供完整的流队列特性支持
使用docker启动一个rabbitmq服务并启用stream插件:
docker run \
-d --name rabbitmq \
--hostname=node1 \
--env=RABBITMQ_NODENAME=r1 \
--env=RABBITMQ_SERVER_ADDITIONAL_ERL_ARGS='-rabbitmq_stream advertised_host localhost' \
--volume=rabbit_erl:/var/lib/rabbitmq \
-p 15672:15672 -p 5672:5672 -p 5552:5552 \
rabbitmq:3-management
docker exec rabbitmq rabbitmq-plugins enable rabbitmq_stream
这里使用rstream客户端来收发消息:
import asyncio
from rstream import (
Producer
)
STREAM_QUEUE = "stream_queue"
CONSUMER_NAME = "py"
async def pub():
async with Producer("localhost", 5552, username="guest", password="guest") as producer:
await producer.create_stream(STREAM_QUEUE)
for i in range(100, 300):
await producer.send(STREAM_QUEUE, f"{i}".encode())
if __name__ == "__main__":
asyncio.run(pub())
消费消息:
import asyncio
from rstream import (
AMQPMessage,
Consumer,
ConsumerOffsetSpecification,
MessageContext,
OffsetType, OffsetNotFound
)
STREAM_QUEUE = "stream_queue"
CONSUMER_NAME = "py"
async def msg_handler(msg: AMQPMessage, context: MessageContext):
print(msg)
await context.consumer.store_offset(STREAM_QUEUE, CONSUMER_NAME, context.offset)
async def sub():
consumer = Consumer("localhost", 5552, username="guest", password="guest")
await consumer.start()
try:
offset = await consumer.query_offset(STREAM_QUEUE, CONSUMER_NAME)
except OffsetNotFound:
offset = 1
await consumer.subscribe(STREAM_QUEUE, msg_handler,
offset_specification=ConsumerOffsetSpecification(OffsetType.OFFSET, offset),
subscriber_name=CONSUMER_NAME)
await consumer.run()
if __name__ == "__main__":
asyncio.run(sub())
rabbitmq | kafka | |
---|---|---|
生产/消费者 | queue | topic |
底层消息存储 | chunk | partition |