Usage of decimal in sql
The DECIMAL data type in SQL is used to store exact decimal numbers. It has the following syntax: DECIMAL(precision, scale), where precision is the total number of digits and scale is the number of digits after the decimal point. DECIMAL is used to store financial data, monetary values, and other numbers that require high precision. Unlike FLOAT and DOUBLE, DECIMAL stores exact values without using scientific notation. It takes up more storage space than FLOAT or DOUBLE. You should use = and <> operators when comparing. If you need greater precision and range, you can use NUMER
##Usage of DECIMAL data type in SQL
The DECIMAL data type is used in SQL to store precise decimal numbers. It is similar to the NUMERIC data type in that it is used to store fixed-length and precision numbers.Syntax
The syntax of the DECIMAL data type is as follows:DECIMAL(precision, scale)
- precision: Total number of digits, including decimal point The number of digits after.
- scale: Number of digits after the decimal point.
Example
For example, to create a DECIMAL column that can store two decimal places and a total of 5 digits, you can use the following code:
CREATE TABLE my_table ( price DECIMAL(5, 2) );
Usage
The DECIMAL data type is mainly used to store financial data, monetary values and other numbers that require high precision. It's great for storing numbers that require precise calculations and comparisons.Differences from FLOAT and DOUBLE
DECIMAL is different from the FLOAT and DOUBLE data types, which are used to store approximate values. DECIMAL stores exact decimal numbers, while FLOAT and DOUBLE use scientific notation to store approximate values. FLOAT and DOUBLE are often used to store scientific data or other numbers that don't require high precision.Note
- The DECIMAL data type takes up more storage space than FLOAT or DOUBLE.
- When comparing DECIMAL values, use the
- =
and
<>operators instead of
>=and
<=operator.
If you need to store a large number of numbers, you can use the NUMERIC data type, which provides greater precision and range than DECIMAL.
The above is the detailed content of Usage of decimal in sql. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics











SQL commands are divided into five categories in MySQL: DQL, DDL, DML, DCL and TCL, and are used to define, operate and control database data. MySQL processes SQL commands through lexical analysis, syntax analysis, optimization and execution, and uses index and query optimizers to improve performance. Examples of usage include SELECT for data queries and JOIN for multi-table operations. Common errors include syntax, logic, and performance issues, and optimization strategies include using indexes, optimizing queries, and choosing the right storage engine.

SQL is a standard language for managing relational databases, while MySQL is a specific database management system. SQL provides a unified syntax and is suitable for a variety of databases; MySQL is lightweight and open source, with stable performance but has bottlenecks in big data processing.

SQL is a standard language for managing relational databases, while MySQL is a database management system that uses SQL. SQL defines ways to interact with a database, including CRUD operations, while MySQL implements the SQL standard and provides additional features such as stored procedures and triggers.

Advanced query skills in SQL include subqueries, window functions, CTEs and complex JOINs, which can handle complex data analysis requirements. 1) Subquery is used to find the employees with the highest salary in each department. 2) Window functions and CTE are used to analyze employee salary growth trends. 3) Performance optimization strategies include index optimization, query rewriting and using partition tables.

To become an SQL expert, you should master the following strategies: 1. Understand the basic concepts of databases, such as tables, rows, columns, and indexes. 2. Learn the core concepts and working principles of SQL, including parsing, optimization and execution processes. 3. Proficient in basic and advanced SQL operations, such as CRUD, complex queries and window functions. 4. Master debugging skills and use the EXPLAIN command to optimize query performance. 5. Overcome learning challenges through practice, utilizing learning resources, attaching importance to performance optimization and maintaining curiosity.

The difference between SQL and MySQL is that SQL is a language used to manage and operate relational databases, while MySQL is an open source database management system that implements these operations. 1) SQL allows users to define, operate and query data, and implement it through commands such as CREATETABLE, INSERT, SELECT, etc. 2) MySQL, as an RDBMS, supports these SQL commands and provides high performance and reliability. 3) The working principle of SQL is based on relational algebra, and MySQL optimizes performance through mechanisms such as query optimizers and indexes.

SQL's role in data management is to efficiently process and analyze data through query, insert, update and delete operations. 1.SQL is a declarative language that allows users to talk to databases in a structured way. 2. Usage examples include basic SELECT queries and advanced JOIN operations. 3. Common errors such as forgetting the WHERE clause or misusing JOIN, you can debug through the EXPLAIN command. 4. Performance optimization involves the use of indexes and following best practices such as code readability and maintainability.

In practical applications, SQL is mainly used for data query and analysis, data integration and reporting, data cleaning and preprocessing, advanced usage and optimization, as well as handling complex queries and avoiding common errors. 1) Data query and analysis can be used to find the most sales product; 2) Data integration and reporting generate customer purchase reports through JOIN operations; 3) Data cleaning and preprocessing can delete abnormal age records; 4) Advanced usage and optimization include using window functions and creating indexes; 5) CTE and JOIN can be used to handle complex queries to avoid common errors such as SQL injection.
