Author: Zen and the Art of Computer Programming
With the explosive growth of various applications such as the Internet and mobile Internet, data processing has increasingly become a common issue faced by enterprises. As we all know, one of the challenges brought by the surge in data volume is how to efficiently store and quickly retrieve massive data. When the scale of data reaches a certain level, a single computer cannot completely store the data. Therefore, a distributed system is needed as a solution that can provide better storage performance and query speed than a single machine. Distributed systems are usually composed of multiple nodes, each node can save part of the data, and complete the overall storage and retrieval of data through cooperation.
For distributed systems, how to effectively handle large-scale data is a very important issue. The emergence of data sharding, distributed file systems, MapReduce, NoSQL and other technologies in distributed systems has greatly promoted the development of this field. This article will start from the perspective of arrays, introduce array data types and their processing methods in distributed systems, and elaborate on related technologies.
2. Explanation of basic concepts and terms
2.1 Distributed system
A distributed system refers to a system environment composed of multiple independent computers. Through network connection, a computer system can realize resource sharing and task scheduling. The distributed system consists of a service provider and a service requester. The service requester sends a request to the service provider through the network. The service provider allocates computing resources, storage resources, network resources and other resources according to the request, and finally returns the results to the service requester. A distributed system can be viewed as a collection of multiple independent computer nodes that cooperate with each other to complete tasks through a communication network. The main characteristics of distributed systems are as follows:
- Distribution: The resources of each node in a distributed system are independent of each other;
- Parallelism: Each node in a distributed system can work at the same time;
- Transparency: users can use the distributed system just like a local system;
- Scalability: Distributed systems can improve performance by adding nodes;
- limitation