The choice of data type is important because it determines storage space, query efficiency, data integrity and accuracy. For example, using VARCHAR to store years will lead to low range query efficiency, while DECIMAL can avoid the problem of loss of accuracy in amount calculation; numerical types should choose TINYINT, SMALLINT, INT or BIGINT according to size to avoid wasting or overflow; char types should choose CHAR, VARCHAR or TEXT as required to avoid abuse of VARCHAR (255); date and time types should choose DATE, DATETIME, etc. according to accuracy and time zone requirements; common misunderstandings include using numbers as strings to cause sorting errors, ignoring character sets to cause storage problems, and not considering future scalability.

When defining SQL table structures, selecting the appropriate data type is the basis for building an efficient and stable database. Many people only think about "just use it" when building tables, but unreasonable data types not only waste storage space, but may also affect query performance and even lead to errors.

Why the choice of data type is important

You may think: "Isn't it over to choose VARCHAR(255)?" Actually, it's not the case. The data type determines:

• Storage space usage
• Query and indexing efficiency
• Data integrity and accuracy

For example, setting a year field to VARCHAR instead of SMALLINT can also be stored, but the efficiency will be much worse when doing range queries (such as finding records between 2010 and 2020).

Common data types classification and usage suggestions

Numerical type: choose the right size to avoid waste or overflow

• Use TINYINT or SMALLINT in small numbers, such as status codes and ages, etc.
• Only large integers use INT or BIGINT , such as user ID, counter, etc.
• Try to use DECIMAL as much as possible for floating point numbers, especially when the amount is involved, to avoid accuracy loss.

For example: If you use FLOAT to save the product price DECIMAL(10,2) errors like 9.999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999999

Character type: length control should be reasonable

• Use CHAR(n) for fixed-length strings, such as ID number, telephone area code, etc.
• VARCHAR(n) is used for variable length, suitable for most text content
• Only long text contents are considered TEXT type, such as the main text of the article

Be careful not to write VARCHAR(255) or VARCHAR(MAX) at any time, which will make it difficult for the optimizer to estimate the cost of the query and may also waste memory.

Date & Time: Is it accurate to milliseconds or is it only necessary for a date?

• If only year, month and day are needed, use DATE
• If the time part is required, use DATETIME or DATE-TIME combination
• Accurate to milliseconds or time zone requirements, consider DATETIME2 or TIMESTAMP WITH TIME ZONE

For example, when recording user registration time, you generally do not need to have a time stamp with a time zone, unless your system is a cross-border service.

Common misunderstandings in practical applications

Treat all numbers as strings

Sometimes, in order to "convenient splicing" or "compatible with null values", developers will also set the number field to VARCHAR . This approach seems flexible, but it actually poses hidden dangers. For example, if you want to sort by price, but because it is a string comparison, "100" is actually smaller than "20", which is embarrassing.

Ignore character sets and sorting rules

Especially in multi-language environments, if the character set (such as utf8mb4 ) is not set properly, some special characters may not be stored. At the same time, sorting rules (such as utf8mb4_unicode_ci ) will affect whether string comparisons are case-sensitive, which is also easy to be ignored.

No future expansion

For example, the ID number is initially used INT or BIGINT , but later it was found that some areas start with 0, and they can only convert strings. Therefore, at the beginning of design, the actual needs and possibility of change of the business must be taken into account.

Basically that's it. The data type selection looks simple, but it is easy to get stuck in details. As long as you make judgments based on actual data characteristics and usage scenarios, most problems can be avoided.

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