At present, the amount of information accessible on the Internet is close to 1 trillion (1024). Undoubtedly, various large websites also store massive amounts of data, and how to effectively store this massive amount of data is a problem that every architect of a large website must solve. Distributed storage technology is a technology developed to solve this problem. Below, we will introduce this technology and its applications in detail< Br/>
The concept of distributed storage
Unlike the commonly used centralized storage technologies, distributed storage technology does not store data on one or more specific nodes. Instead, it utilizes the disk space on each machine in the enterprise through the network, and forms a virtual storage device with these dispersed storage resources. Data is stored in various corners of the enterprise< Br/>
Specific technologies and applications:
Massive data can be roughly divided into structured data, unstructured data, and semi-structured data based on the degree of structuring< Br/>
Next, this article will introduce how these three types of data are stored in a distributed manner< Br/>
Storage and Application of Structured Data
Structured data is a user-defined data type that contains a series of attributes, each of which has a data type, stored in a relational database, and can be expressed using a two-dimensional table structure to implement the data< Br/>
Most systems have a large amount of structured data, usually stored in relational databases such as Oracle or MySQL. When the system size is too large for a single node database to support, there are generally two methods: vertical scaling and horizontal scaling< Br/>
Vertical scaling: Vertical scaling is easy to understand, simply put, it means dividing the database according to its functions, storing data of different functions in different databases, so that a large database is divided into multiple small databases, thereby achieving database expansion. A well-designed application system generally consists of many loosely coupled functional modules, and the data required by each functional module corresponds to one or more tables in the database. The less interaction and unity between various functional modules, the lower the coupling degree of the system, making it easier to achieve vertical segmentation< Br/>
Horizontal scaling: Simply put, horizontal partitioning of data can be understood as dividing data by rows, which means dividing certain rows in a table into one database, while others are further divided into other databases. In order to easily determine which database each row of data is segmented into, segmentation always needs to follow certain specific rules, such as the range of a certain number field, the range of a certain time type field, or the hash value of a certain field< Br/>
Vertical expansion and horizontal expansion each have their own advantages and disadvantages. Generally, a large system will combine horizontal and vertical expansion< Br/>
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