What is the abbreviation of sno in the database?

In the database, sno is the abbreviation of "student number", "cno" is the abbreviation of course number, "sdept" is the abbreviation of department name, "cpno" is the abbreviation of prerequisite course, and "ccredit" is the abbreviation of credit; the database is A warehouse that organizes, stores, and manages data according to a data structure is a collection of large amounts of data that is stored in a computer for a long time, is organized, shareable, and unified management.

#The operating environment of this tutorial: Windows 10 system, Dell G3 computer.

What is the abbreviation of sno in the database?

In the database, sno is the abbreviation of student number. cno is the course number, sdept is the department name, cpno is the prerequisite course, and ccredit is the credit.

A database is a warehouse that organizes, stores and manages data according to the data structure. It is a collection of large amounts of data that is stored in a computer for a long time, is organized, shareable, and unified management. The database storage space is large and can store millions, tens of millions, or hundreds of millions of data. However, the database does not store data arbitrarily, there are certain rules, otherwise the query efficiency will be very low. Today's world is an Internet world full of data, filled with a lot of data. That is, this Internet world is the data world. There are many sources of data, such as travel records, consumption records, web pages browsed, messages sent, etc. In addition to text type data, images, music, and sounds are all data.

The database management system is a computer software system designed for managing databases. It generally has basic functions such as storage, interception, security, and backup. Database management systems can be classified according to the database models they support, such as relational, XML; or according to the types of computers they support, such as server clusters, mobile phones; or according to the query languages ​​used, such as SQL , XQuery; or classify according to the focus of performance impulse, such as maximum scale, maximum running speed; or other classification methods. Regardless of the classification scheme used, some DBMSs are able to span categories, for example, supporting multiple query languages ​​simultaneously.

Database type

• Relational database

Relational database, the storage format can be intuitively Reflect the relationship between entities. Relational databases are similar to common tables. There are many complex relationships between tables in relational databases. Common relational databases include Mysql, SqlServer, etc. In lightweight or small applications, using different relational databases has little impact on the performance of the system. However, when building large applications, you need to choose an appropriate relational database based on the business needs and performance requirements of the application.

Standard SQL statements

Although there are many relational databases, most of them follow the SQL (Structured Query Language) standard. Common operations include query, add, update, delete, sum, sort, etc.

Query statement: SELECT param FROM table WHERE condition This statement can be understood as querying the field param that meets the condition condition from the table.

New statement: INSERT INTO table (param1, param2, param3) VALUES (value1, value2, value3) This statement can be understood as inserting value1, value2 into the param1, param2, and param3 fields in the table respectively. value3.

Update statement: UPDATE table SET param=new_value WHERE condition This statement can be understood as updating the field param that meets the condition condition to the new_value value.

Delete statement: DELETE FROM table WHERE condition This statement can be understood as deleting all data that meets the condition condition.

Deduplication query: SELECT DISTINCT param FROM table WHERE condition This statement can be understood as querying the field param that meets the condition from the table, but the repeated value in param can only appear once.

Sort query: SELECT param FROM table WHERE condition ORDER BY param1 This statement can be understood as querying the params that meet the condition condition from the table, and sorting them in ascending order of param1.

Generally speaking, the SELECT, INSERT, UPDATE, and DELETE of the database correspond to the four commonly used operations of addition, deletion, modification, and query.

Relational databases are more suitable for processing structured data, such as student grades, addresses, etc. Such data generally require structured queries, such as join. In this case, relational databases are It will have better performance and higher accuracy than NoSQL database. Since the size of structured data is not too large and the growth of data size is usually predictable, it is better to use a relational database for structured data. Relational databases pay great attention to the transactionality and consistency of data operations. If these requirements are met, relational databases can undoubtedly satisfy them.

• Non-relational database (NoSQL)

With the continuous expansion of technology directions in recent years, a large number of NoSql databases such as MongoDB, Redis Memcache is designed to simplify the database structure, avoid redundant and performance-impacting table connections, and abandon complex distribution.

refers to a distributed, non-relational data storage system that does not guarantee compliance with ACID principles. NoSQL database technology is closely related to CAP theory and consistent hashing algorithm. The so-called CAP theory simply means that it is impossible for a distributed system to meet the three requirements of availability, consistency, and partition tolerance. Meeting two requirements at once is the upper limit of the system. The consistent hashing algorithm refers to a data algorithm produced under normal circumstances in order to meet work needs during the application process of NoSQL databases. This algorithm can effectively solve many work-related problems, but it also has disadvantages, that is, work The quality of completion will fluctuate with changes in nodes. When there are too many nodes, the related work results will not be so accurate. This problem affects the work efficiency of the entire system, causing the data garbled code and error rate of the entire database system to greatly increase. The content of data nodes may even be migrated, resulting in erroneous code information. But despite this, NoSQL database technology still has very obvious application advantages. For example, the database structure is relatively simple, and its read and write performance is good under large amounts of data. It can meet the needs of storing customized data formats at any time, and is very suitable for big data processing work.

NoSQL database is suitable for application scenarios that pursue speed, scalability, and business changes. It is more suitable for the processing of unstructured data, such as articles and comments. These data, such as full-text search and machine learning, are usually only used for fuzzy processing and do not require precise queries like structured data. Moreover, the data size of this type of data is It is often massive, and the growth in data scale is often impossible to predict. The expansion capabilities of NoSQL databases are almost unlimited, so NoSQL databases can well meet the storage of this type of data. NoSQL databases can use key-value to obtain a large amount of unstructured data, and the data acquisition efficiency is very high, but the effect of using it to query structured data is relatively poor.

Currently there is still no unified standard for NoSQL databases. It now has four major categories:

(1) Key-value storage (key-value): represents the software Redis, its The advantage is that it can quickly query data, but the disadvantage is that it needs to store the relationship between data.

(2) Column storage: represents the software Hbase. Its advantage is that it can quickly query data and has strong scalability of data storage. The disadvantage is that the functionality of the database is limited.

(3) Document database storage: represents the software MongoDB. Its advantage is that it does not have particularly strict requirements on data structure. The disadvantages are poor query performance and the lack of a unified query language.

(4) Graph database storage: represents the software InfoGrid, which has the advantage of being able to easily use graph structure-related algorithms for calculations. The disadvantage is that in order to obtain results, the entire graph must be calculated, and graph databases are difficult to use when encountering unsuitable data models.

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