A distributed system, as the name suggests, is a system that distributes computing tasks and data storage to multiple computers to work together. Through this distributed architecture, it effectively improves the system's processing power, reliability and availability, and solves the bottleneck of single-machine systems in processing large-scale data and high concurrent requests. The editor of Downcodes will explain in detail the core concepts and key technologies of distributed systems in terms of working principles, problems solved, advantages and disadvantages, etc. This article aims to help readers fully understand the advantages and challenges of distributed systems and provide reference for practical applications.
A distributed system is a collection of independent computers that appear to users as a single, consistent system. In a popular understanding, a distributed system works by distributing computing tasks and data storage across multiple computers, enabling the system to handle larger-scale data and computing tasks, improving system reliability and availability, and improving resource utilization. . These systems address issues in data processing capabilities, system scalability, and the ability to deal with single points of failure. Among them, the ability to improve system availability is particularly important.
When we talk about distributed systems improving system availability, we mean that by spreading servers across multiple geographical locations, the system as a whole can continue to function even if one server or network fails. This design also improves the system's fault tolerance and disaster recovery capabilities, ensuring that critical data and services can remain accessible and available in the face of hardware failures, natural disasters, or other emergencies.
The basic principle behind distributed systems is to split complex and resource-intensive tasks into multiple small tasks and distribute them to multiple computers (nodes) in the network. These nodes each complete the assigned tasks or data storage roles, and communicate and collaborate with each other through the network to achieve a common goal.
Distributed computing: In a distributed system, the computing process is split into multiple small parts, and each part is assigned to a different node for processing. This method not only speeds up calculations, but also allows the calculation process to be performed at different physical locations, thereby enhancing the flexibility and reliability of the calculation process.
Data distribution and replication: To increase data accessibility and fault tolerance, data in a distributed system is replicated and distributed among multiple nodes. This means that even if a node fails, the system can still continue to work through data copies on other nodes, thus ensuring data integrity and continuous availability of the system.
Distributed systems mainly solve problems in three aspects: limitations of computing power, system scalability, and system reliability and availability.
Limitations of computing power: As the amount of data and computing requirements continue to grow, the processing power of a single computer can no longer meet the needs of modern applications. Distributed systems effectively break through the limitations of a single computer's computing power by allocating tasks to multiple computers for processing.
System scalability: Distributed systems support horizontal expansion, that is, increasing the processing capabilities of the system by adding more nodes. This approach is more cost-effective and flexible than traditional vertical expansion (upgrading existing hardware).
System reliability and availability: By deploying distributed nodes in different geographical locations, even if some nodes fail, the system as a whole can still work normally. In addition, distributed systems can be maintained and upgraded without affecting services, further improving system availability.
Improved processing and storage capabilities: By processing and storing data in parallel across multiple nodes, distributed systems significantly improve data processing and storage capabilities.
Improved system reliability and availability: Even if some nodes or networks fail, the system can still keep running, reducing the risk of business interruption.
Scalability and flexibility: According to business needs, the number of nodes can be flexibly increased or reduced to cope with different load conditions.
Increased complexity: The complexity of managing and maintaining distributed systems is significantly higher than that of monolithic systems, requiring professional knowledge and skills to ensure that the system works properly.
Consistency issues: Data may experience delays when synchronizing across multiple nodes, leading to data consistency issues. Although there are various algorithms (such as CAP theorem, Paxos, Raft, etc.) to solve this problem, it is still a challenge in practical applications.
Network dependency: Distributed systems are highly dependent on network connectivity. Network latency and instability can severely impact system performance and availability.
Through the above analysis, we can see that distributed systems solve the problems of computing power, system scalability, and coping with single points of failure by distributing computing tasks and data storage on multiple computers. It also brings new challenges, such as Increased system complexity, consistency issues and network dependencies. Nevertheless, as technology continues to advance, the design and management techniques of distributed systems are also constantly improving, making their role in modern applications increasingly important.
What is a distributed system? How to understand distributed systems in a popular way?
A distributed system is a system composed of multiple independent computer nodes connected through a network. Each node has certain computing power and storage capacity, and carries out information transmission and coordination through network communication. You can think of a distributed system as a brain, with different nodes like its neurons working together to complete various tasks.
What problems do distributed systems solve?
Distributed systems solve many of the problems faced by traditional centralized systems. First, it provides greater reliability and fault tolerance. Since there are multiple nodes in a distributed system, when one node fails, other nodes can take over the work and the system can still continue to run. Secondly, distributed systems provide better performance and scalability. Since tasks can be distributed to different nodes for parallel processing, larger data volumes and higher concurrent requests can be processed. Finally, distributed systems provide better availability. Distributed system nodes can back up and replicate data to each other, and can distribute requests to the nearest node through load balancing, thereby improving the response speed and availability of the system.
What are the advantages and disadvantages of distributed systems?
The advantages of distributed systems are: high reliability and fault tolerance; good performance and scalability; high availability and fast response; strong flexibility and easy maintenance and upgrades.
The shortcomings of distributed systems mainly include: building and maintaining distributed systems requires complex design and development work; the overall complexity of the system is high and the technical requirements for developers are high; the architecture and design of the system need to consider the challenges in a distributed environment Consistency and concurrency issues; the deployment and management of distributed systems require more resources and costs.
In general, while distributed systems solve many problems of traditional centralized systems, they also bring some new challenges and complexities, which require comprehensive consideration of various factors to effectively apply and manage them.
In summary, distributed systems play a vital role in modern information technology, with both advantages and challenges. Understanding its working principles and characteristics is crucial for both developers and users. I hope this analysis by the editor of Downcodes can help readers better master the knowledge of distributed systems.