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introduction

What is MQ? Why use MQ?

MQ is the abbreviation of Message Queue. Message queue is a method of passing messages between application systems. It implements the mechanism of asynchronous communication and decouples the direct dependencies between different components or systems. By sending messages to the message queue, the sender and receiver of the message can process independently, improving the reliability, scalability and performance of the system.

Message queues have the following features and advantages:

1. Asynchronous task processing: In many applications, some tasks may take a long time and do not require immediate response, such as image or video processing, sending emails, generating reports, etc. At this time, these tasks can be encapsulated as messages and sent to the message queue, and processed asynchronously in the background, rather than blocking user requests. For example, after a user places an order on an e-commerce platform, the order processing process can be performed by sending order information to a message queue and then processing inventory deductions, logistics operations, etc. asynchronously.

2. Application decoupling: In complex distributed systems, communication interactions are required between components, but direct point-to-point calls will lead to tight coupling between systems, reducing system flexibility and maintainability. By introducing a message queue, communication between components is implemented through publishing and subscribing to messages. Each component only needs to pay attention to the business logic it is responsible for, without knowing the implementation details of other components. For example, in the microservice architecture, each microservice communicates asynchronously through a message queue, realizing the decoupling of the system and the loose coupling between the microservices.

3. Broadcasting and notification: In some scenarios, messages need to be broadcast to multiple consumers for processing, such as real-time push, subscription notifications, etc. Message queues provide a broadcast mechanism that can send messages to a switch (Exchange). Multiple queues bound to the switch will receive the same message. For example, after publishing a news on a social media platform, the news is broadcast to all users who follow the user through a message queue.

4. Flow peak cutting: In high concurrent systems, a sudden surge in traffic can cause system crashes or performance degradation. Traffic peaks can be processed smoothly by forwarding requests to a message queue and then consumed by consumers according to their own processing capabilities. For example, in a flash sale activity, the user's flash sale request is placed into the message queue, and then limited resources can process the request one by one, avoiding system overload.

5. Data buffering and data synchronization: The message queue can serve as a data buffer to help optimize data transmission between different systems. For example, when the data formats between two systems are inconsistent or the transmission speeds do not match, the data producer and data consumer can be redirected through the message queue, allowing data producers and data consumers to convert and adapt data formats. In addition, message queues can also be used to implement asynchronous replication and synchronization of data to ensure consistency between different systems.

Common message queue systems include RabbitMQ, Apache Kafka, ActiveMQ, RocketMQ, etc. They all provide rich functions and features, suitable for different application scenarios. By using message queues, highly reliable, scalable and decoupled distributed systems can be built.

Disadvantages of MQ

1. Single point of failure: In some MQ implementations, there may be a problem of single point of failure. If the message queue fails, the entire system may be affected and the message delivery and processing cannot be carried out normally. Therefore, when designing and selecting MQ, high availability and fault tolerance mechanisms need to be considered to ensure the stability of the system.

2. Risk of data loss: In some cases, message queues may be at risk of data loss. For example, MQ fails or unexpectedly shuts down before the message is sent to the message queue but has not been consumed by the consumer, which can cause some messages to be lost. In order to ensure the reliability of the data, a persistence mechanism is required to ensure that messages are not lost during the sending and receiving process.

3. Increased system complexity: Introducing message queues increases system complexity. The system needs to manage and maintain information such as status, connection, and configuration of the message queue. At the same time, it also needs to consider issues such as message serialization and deserialization, message routing, and message confirmation. This will increase certain learning and development costs for developers.

4. Message order issue: In some scenarios, the order of messages can be very important. However, some MQs cannot guarantee strict orderliness of messages in distributed environments, because messages may be processed through different routing, network transmission and consumer processing. If the business requires that the order of messages be kept forced, additional design and processing are required.

5. System availability decreases: if the external dependencies introduced by the system increase, the stability of the system will become worse. Once MQ goes down, it will have an impact on the business. This requires consideration of how to ensure high availability of MQ.

Comparison of several major MQ product features

Kafka, RabbitMQ and RocketMQ are common message queue (MQ) products that differ in design concepts, features and applicable scenarios. Here are some comparisons and introductions to their applicable scenarios:

1. Kafka:

   • Design philosophy: Kafka is a distributed stream processing platform, mainly used for high-throughput real-time data stream processing and message delivery. It aims at high performance, persistence, scalability, and fault tolerance, emphasizing the order and consistency of data flows.
   • Features:
     • High Throughput: Kafka achieves high throughput message processing capabilities through partitioning and distributed architectures.
     • Persistent storage: Kafka persists messages to disk, allowing consumers to get historical messages at any time.
     • Distributed architecture: Kafka adopts a distributed multi-replica replication mechanism to provide high availability and fault tolerance.
   • Applicable scenarios:
     • Large-scale real-time log processing: Kafka is suitable for processing large amounts of real-time log data, such as application logs, access logs, etc.
     • Streaming processing: Kafka supports streaming processing frameworks, such as Apache Storm, Apache Flink, etc.
     • Building a Message-Driven Architecture (MDA): Kafka is an event bus and can be used to build distributed systems and microservice architectures.

2. RabbitMQ:

   • Design philosophy: RabbitMQ is an open source, AMQP (Advanced Message Queuing Protocol)-based messaging middleware. It features flexibility, reliability and ease of use, and supports a wide range of messaging modes and protocols.
   • Features:
     • Flexible message routing: RabbitMQ supports a variety of message routing strategies, including direct connection, theme, fan, etc., which can meet different messaging needs.
     • Message confirmation mechanism: RabbitMQ provides a message confirmation mechanism to ensure the reliability of messages during sending and receiving.
     • Plug-in system: RabbitMQ has a rich plug-in system that can extend its functions, such as delayed messages, priority queues, etc.
   • Applicable scenarios:
     • Highly reliable messaging: RabbitMQ is suitable for scenarios that need to emphasize message reliability and stability, such as financial systems, e-commerce order processing, etc.
     • Multiple messaging modes: RabbitMQ supports multiple messaging modes, suitable for complex message routing requirements, such as publish/subscribe, peer-to-peer, etc.
     • Asynchronous task processing: RabbitMQ can be used as a task queue for decoupling and asynchronous processing of tasks.

3. RocketMQ:

   • Design philosophy: RocketMQ is Alibaba's open source distributed messaging middleware, focusing on high performance, reliability and scalability. It has sequential messages and distributed transactions as its core features and is suitable for large-scale distributed systems.
   • Features:
     • Sequential message: RocketMQ supports strict and orderly message delivery, ensuring that messages are consumed in the order of sending.
     • Distributed Transactions: RocketMQ provides distributed transaction message functionality, supporting atomic messaging across multiple operations.
     • Horizontal scaling: RocketMQ adopts a scalable distributed architecture that supports horizontal scaling and load balancing.
   • Applicable scenarios:
     • High throughput sequence message: RocketMQ is suitable for scenarios that need to ensure message sequence, such as e-commerce order processing, process approval, etc.
     • Distributed transaction message: RocketMQ can be used in distributed transaction scenarios that require operations across multiple resources, such as distributed payments, inventory management, etc.
     • Large-scale real-time data processing: RocketMQ is an infrastructure for large-scale data processing and is suitable for scenarios such as log collection, monitoring data analysis, etc.

Introduction to RabbitMQ and Installation

RabbitMQ is an open source message broker middleware for reliable messaging between applications. It implements the AMQP (Advanced Message Queuing Protocol) standard and provides rich functionality and flexibility to enable developers to build scalable and reliable distributed systems.

Features and advantages of RabbitMQ

1. reliability: RabbitMQ adopts a message confirmation mechanism to ensure that messages can be safely delivered and processed. It also supports persistent messages, and messages are not lost even after a failure or restart.

2. flexibility: RabbitMQ supports multiple messaging modes, such as point-to-point, publish/subscribe and message routing. Developers can choose the most suitable mode according to application needs.

3. Scalability: RabbitMQ can build a distributed message broker system by adding multiple nodes to meet the needs of high concurrency and large-scale applications.

4. Message persistence: RabbitMQ can save messages on disk to ensure messages are still available after failure or restart.

5. Plug-in system: RabbitMQ has a rich plug-in ecosystem that can expand its functions such as management interface, authentication and authorization, message conversion, etc.

RabbitMQ is a powerful and flexible message broker middleware that provides reliable messaging mechanisms and rich features. Through simple installation steps (RabbitMQ installation guide), you can easily deploy and get started with RabbitMQ on a variety of operating systems.

References:

• RabbitMQ official website:RabbitMQ: easy to use, flexible messaging and streaming — RabbitMQ
• RabbitMQ Documentation:Documentation: Table of Contents — RabbitMQ