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Introduction to python’s message queue framework

爱喝马黛茶的安东尼
爱喝马黛茶的安东尼Original
2019-06-14 13:34:249318browse

Introduction to python’s message queue framework

#What are the python message queue frameworks? Here are some useful message queue frameworks:

RabbitMQ

is an open source message queue written in Erlang. It supports many protocols: AMQP, XMPP, SMTP, STOMP. This makes it very heavyweight and more suitable for enterprise-level development. At the same time, a broker (Broker) architecture is implemented, which means that messages are first queued in the central queue when sent to the client. It has good support for routing, load balance or data persistence.

Introduction to python’s message queue framework

Redis

is a Key-Value NoSQL database. Development and maintenance are very active, although it is a Key-Value database. Storage system, but it itself supports MQ function, so it can be used as a lightweight queue service. For the enqueuing and dequeuing operations of RabbitMQ and Redis, each is executed 1 million times, and the execution time is recorded every 100,000 times. The test data is divided into four different sizes of 128Bytes, 512Bytes, 1K and 10K. Experiments show that when entering the queue, the performance of Redis is higher than that of RabbitMQ when the data is relatively small, but if the data size exceeds 10K, Redis is unbearably slow; when leaving the queue, Redis shows very good performance regardless of the size of the data. , and the dequeue performance of RabbitMQ is much lower than that of Redis.

Introduction to python’s message queue framework

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ZeroMQ

is known as the most Fast message queue system, especially for large throughput demand scenarios. ZMQ can implement advanced/complex queues that RabbitMQ is not good at, but developers need to combine multiple technical frameworks themselves. The technical complexity is a challenge to the successful application of MQ. ZeroMQ has a unique non-middleware model, you do not need to install and run a message server or middleware, because your application will play this service role. You just need to simply reference the ZeroMQ library, which can be installed using NuGet, and then you can happily send messages between applications. But ZeroMQ only provides non-persistent queues, which means that if the machine goes down, the data will be lost. Among them, Twitter's Storm uses ZeroMQ as the data stream transmission.

Introduction to python’s message queue framework

ActiveMQ

is a sub-project under Apache. Similar to ZeroMQ, it can implement queues with broker and peer-to-peer technology. At the same time, similar to RabbitMQ, it can efficiently implement advanced application scenarios with a small amount of code. RabbitMQ, ZeroMQ, and ActiveMQ all support commonly used multi-language clients C, Java, .Net, Python, Php, Ruby, etc.

Introduction to python’s message queue framework

Jafka/Kafka

is a high-performance cross-language distributed Publish/Subscribe message queue system, and Jafka is based on Kafka Incubated above, it is an upgraded version of Kafka. It has the following characteristics: fast persistence, which can persist messages with O(1) system overhead; high throughput, which can reach a throughput rate of 10W/s on an ordinary server; a completely distributed system, Broker , Producer, and Consumer all natively and automatically support distribution and automatically achieve complex balance; support parallel loading of Hadoop data, which is a feasible solution for log data and offline analysis systems like Hadoop that require real-time processing limitations. . Kafka unifies online and offline message processing through Hadoop's parallel loading mechanism, which is also what the system studied in this project values. Apache Kafka is a very lightweight messaging system compared to ActiveMQ. In addition to very good performance, it is also a well-working distributed system.

Introduction to python’s message queue framework

Rocketmq

RocketMQ is a distributed messaging middleware open sourced by Alibaba in 2012 and has been donated to the Apache Software Foundation. , and became a top-level project of Apache on September 25, 2017. As a domestic middleware that has experienced many "super projects" such as Alibaba's Double Eleven and has achieved stable and outstanding performance, it has been used by more and more people in recent years due to its high performance, low latency and high reliability. used by domestic enterprises.

Introduction to python’s message queue framework

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