Wichtige Punkte, die Sie beim Erstellen von Tabellen in MySQL kennen müssen

Für Backend-Entwickler ist der Zugriff auf eine Datenbank von entscheidender Bedeutung.

Kernbenutzerdaten werden normalerweise sicher in Datenbanken wie MySQL oder Oracle gespeichert.

Tägliche Aufgaben umfassen oft die Erstellung von Datenbanken und Tabellen, um Geschäftsanforderungen zu erfüllen, aber Tabellen werden viel häufiger erstellt.

Dieser Artikel konzentriert sich auf die Tabellenerstellung, da das Ignorieren wichtiger Details zu kostspieligen Problemen bei der Wartung nach der Bereitstellung führen kann.

Übrigens können schlechte Datenbankdesignpraktiken auch dazu führen, dass Ihre API bei hoher Parallelität langsam reagiert. Das folgende Bild zeigt die Leistungstestergebnisse einer API mit dem EchoAPI-Tool.

Lassen Sie uns heute 18 Tipps zum Erstellen von Tabellen in einer Datenbank besprechen.

Viele der in diesem Artikel erwähnten Details stammen aus meinen eigenen Erfahrungen und Herausforderungen während der Arbeit und ich hoffe, dass sie für Sie hilfreich sein werden.

1. Benennung

Beim Erstellen von Tabellen, Feldern und Indizes ist es unglaublich wichtig, ihnen gute Namen zu geben.

1.1 Bedeutungsvolle Namen

Namen dienen als Gesicht von Tabellen, Feldern und Indizes und hinterlassen einen ersten Eindruck.

Gute Namen sind prägnant und selbsterklärend, was die Kommunikation und Wartung erleichtert.

Schlechte Namen sind mehrdeutig und verwirrend, was zu Chaos und Frustration führt.

Schlechte Beispiele:

Feldnamen wie abc, abc_name, name, user_name_123456789 werden Sie verwirren.

Gutes Beispiel:

Feldname als Benutzername.

Eine kleine Erinnerung: Namen sollten auch nicht zu lang sein, idealerweise nicht länger als 30 Zeichen.

1.2 Groß- und Kleinschreibung

Am besten verwenden Sie Kleinbuchstaben für Namen, da diese optisch leichter zu lesen sind.

Schlechte Beispiele:

Feldnamen wie PRODUCT_NAME, PRODUCT_name sind nicht intuitiv. Eine Mischung aus Groß- und Kleinschreibung ist weniger angenehm zu lesen.

Gutes Beispiel:

Feldname als Produktname sieht komfortabler aus.

1.3 Trennzeichen

Namen können zum besseren Verständnis oft mehrere Wörter enthalten.

Welches Trennzeichen sollte zwischen mehreren Wörtern verwendet werden?

Schlechte Beispiele:

Feldnamen wie Produktname, Produktname, Produktname oder Produkt@Name werden nicht empfohlen.

Gutes Beispiel:

Feldname als Produktname.

Die Verwendung eines Unterstrichs _ zwischen Wörtern wird dringend empfohlen.

1.4 Tabellennamen

Für Tabellennamen wird empfohlen, aussagekräftige, prägnante Namen zusammen mit einem Geschäftspräfix zu verwenden.

Für auftragsbezogene Tabellen stellen Sie dem Tabellennamen order_ voran, z. B. order_pay, order_pay_detail.

Für produktbezogene Tabellen stellen Sie „product_“ voran, z. B. „product_spu“ oder „product_sku“.

Diese Vorgehensweise hilft dabei, Tabellen, die sich auf dasselbe Unternehmen beziehen, schnell zusammenzufassen.

Wenn ein Nicht-Bestellunternehmen außerdem möglicherweise eine Tabelle mit dem Namen „pay“ erstellen muss, kann diese leicht als „finance_pay“ unterschieden werden, wodurch Namenskonflikte vermieden werden.

1.5 Feldnamen

Feldnamen ermöglichen maximale Flexibilität, können aber leicht zu Verwirrung führen.

Zum Beispiel kann die Verwendung eines Flags zur Angabe des Status in einer Tabelle und die Verwendung des Status in einer anderen Tabelle zu Inkonsistenzen führen.

Eine Standardisierung auf den Status zur Darstellung des Staates ist ratsam.

Wenn eine Tabelle den Primärschlüssel einer anderen Tabelle verwendet, hängen Sie _id oder _sys_no an das Ende des Feldnamens an, zum Beispiel „product_spu_id“ oder „product_spu_sys_no“.

Standardisieren Sie außerdem die Erstellungszeit als „create_time“ und die Änderungszeit als „update_time“, wobei der Löschstatus auf „delete_status“ festgelegt ist.

Andere gemeinsame Felder sollten zur besseren Übersichtlichkeit ebenfalls eine einheitliche Namenskonvention über verschiedene Tabellen hinweg beibehalten.

1.6 Indexnamen

In einer Datenbank gibt es verschiedene Arten von Indizes, darunter Primärschlüssel, reguläre Indizes, eindeutige Indizes und zusammengesetzte Indizes.

Eine Tabelle hat im Allgemeinen einen einzelnen Primärschlüssel, der normalerweise id oder sys_no genannt wird.

Reguläre und zusammengesetzte Indizes können das Präfix ix_ verwenden, zum Beispiel ix_product_status.

Eindeutige Indizes können das Präfix ux_ verwenden, z. B. ux_product_code.

2. Feldtypen

Beim Entwerfen von Tabellen besteht reichlich Freiheit bei der Auswahl der Feldtypen.

Zeitformatierte Felder können Datum, Datum/Uhrzeit oder Zeitstempel usw. sein.

Zu den Zeichendatentypen gehören Varchar, Char, Text usw.

Numerische Typen umfassen int, bigint, smallint und tinyint.

Die Auswahl eines geeigneten Feldtyps ist entscheidend.

Overestimating types (e.g., using bigint for a field that will only store values between 1 and 10) wastes space; tinyint would suffice.

Conversely, underestimating (e.g., using int for an 18-digit ID) will lead to data storage failures.

Here are some principles for choosing field types:

• Prefer small storage size while meeting normal business needs, selecting from small to large.
• Use char for fixed or similar string lengths, and varchar for varied lengths.
• Use bit for boolean fields.
• Use tinyint for enumeration fields.
• Choose bigint for primary key fields.
• Use decimal for monetary fields.
• Use timestamp or datetime for time fields.

3. Field Length

After defining field names and selecting appropriate field types, the focus should shift to field lengths, like varchar(20) or bigint(20).

What does varchar indicate in terms of length—bytes or characters?

The answer: In MySQL, varchar and char represent character length, while most other types represent byte length.

For example, bigint(4) specifies the display length, not the storage length, which remains 8 bytes.

If the zerofill property is set, numbers less than 4 bytes will be padded, but even if filled, the underlying data storage remains at 8 bytes.

4. Number of Fields

When designing a table, it’s crucial to limit the number of fields.

I’ve seen tables with dozens or even hundreds of fields, leading to large data volumes and low query efficiency.

If this situation arises, consider splitting large tables into smaller ones while retaining common primary keys.

As a rule of thumb, keep the number of fields per table below 20.

5. Primary Keys

Create a primary key when setting up a table.

Primary keys inherently come with primary key indexes, making queries more efficient, as they don’t require additional lookups.

In a single database, primary keys can use AUTO_INCREMENT for automatic growth.

For distributed databases, particularly in sharded architectures, it’s best to use external algorithms (like Snowflake) to ensure globally unique IDs.

Moreover, keep primary keys independent of business values to reduce coupling and facilitate future expansions.

However, for one-to-one relationships, such as user tables and user extension tables, it’s acceptable to directly use the primary key from the user table.

6. Storage Engine

Before MySQL 8, the default storage engine was MyISAM; from MySQL 8 onward, it’s now InnoDB.

Historically, there was much debate about which storage engine to choose.

MyISAM separates index and data storage, enhancing query performance but lacks support for transactions and foreign keys.

InnoDB, while slightly slower in queries, supports transactions and foreign keys, making it more robust.

It was previously advised to use MyISAM for read-heavy and InnoDB for write-heavy scenarios.

However, optimizations in MySQL have reduced performance differences, so using the default InnoDB storage engine in MySQL 8 and later is recommended without any additional modifications.

7. NOT NULL

When creating fields, decide whether they can be NULL.

Defining fields as NOT NULL whenever possible is advisable.

Why?

In InnoDB, storing NULL values requires extra space, and they can also lead to index failures.

NULL values can only be queried using IS NULL or IS NOT NULL, as using = always returns false.

Thus, define fields as NOT NULL wherever feasible.

However, when a field is directly defined as NOT NULL, and a value is forgotten during input, it will prevent data insertion.

This can be an acceptable situation when new fields are added and scripts run before deploying new code, leading to errors without default values.

For newly added NOT NULL fields, setting a default value is crucial:

ALTER TABLE product_sku ADD COLUMN brand_id INT(10) NOT NULL DEFAULT 0;

8. Foreign Keys

Foreign keys in MySQL serve to ensure data consistency and integrity.

For instance:

CREATE TABLE class (
  id INT(10) PRIMARY KEY AUTO_INCREMENT,
  cname VARCHAR(15)
);

This creates a class table.

Then, a student table can be constructed that references it:

CREATE TABLE student(
  id INT(10) PRIMARY KEY AUTO_INCREMENT,
  name VARCHAR(15) NOT NULL,
  gender VARCHAR(10) NOT NULL,
  cid INT,
  FOREIGN KEY (cid) REFERENCES class(id)
);

Here, cid in the student table references id in the class table.

Attempting to delete a record in student without removing the corresponding cid record in class will raise a foreign key constraint error:

a foreign key constraint fails.

Thus, consistency and integrity are preserved.

Note that foreign keys are only usable with the InnoDB storage engine.

If only two tables are linked, it might be manageable, but with several tables, deleting a parent record requires synchronously deleting many child records, which can impact performance.

Thus, for internet systems, it is generally advised to avoid using foreign keys to prioritize performance over absolute data consistency.

In addition to foreign keys, stored procedures and triggers are also discouraged due to their performance impact.

9. Indexes

When creating tables, beyond specifying primary keys, it’s essential to create additional indexes.

For example:

CREATE TABLE product_sku(
  id INT(10) PRIMARY KEY AUTO_INCREMENT,
  spu_id INT(10) NOT NULL,
  brand_id INT(10) NOT NULL,
  name VARCHAR(15) NOT NULL
);

This table includes spu_id (from the product group) and brand_id (from the brand table).

In situations that save IDs from other tables, a regular index can be added:

CREATE TABLE product_sku (
  id INT(10) PRIMARY KEY AUTO_INCREMENT,
  spu_id INT(10) NOT NULL,
  brand_id INT(10) NOT NULL,
  name VARCHAR(15) NOT NULL,
  KEY `ix_spu_id` (`spu_id`) USING BTREE,
  KEY `ix_brand_id` (`brand_id`) USING BTREE
);

Such indexes significantly enhance query efficiency.

However, do not create too many indexes as they can hinder data insertion efficiency due to additional storage requirements.

A single table should ideally have no more than five indexes.

If the number of indexes exceeds five during table creation, consider dropping some regular indexes in favor of composite indexes.

Also, when creating composite indexes, always apply the leftmost matching rule to ensure the indexes are effective.

For fields with high duplication rates (like status), avoid creating separate regular indexes. MySQL may skip the index and choose a full table scan instead if it’s more efficient.

I’ll address index inefficiency issues in a separate article later, so let’s hold off on that for now.

10. Time Fields

The range of types available for time fields in MySQL is fairly extensive: date, datetime, timestamp, and varchar.

Using varchar might be for API consistency where time data is represented as a string.

However, querying data by time ranges can be inefficient with varchar since it cannot utilize indexes.

Date is intended only for dates (e.g., 2020-08-20), while datetime and timestamp are suited for complete date and time.

There are subtle differences between them.

Timestamp: uses 4 bytes and spans from 1970-01-01 00:00:01 UTC to 2038-01-19 03:14:07. It’s also timezone-sensitive.

Datetime: occupies 8 bytes with a range from 1000-01-01 00:00:00 to 9999-12-31 23:59:59, independent of time zones.

Using datetime to save date and time is preferable for its wider range.

As a reminder, when setting default values for time fields, avoid using 0000-00-00 00:00:00, which can cause errors during queries.

11. Monetary Fields

MySQL provides several types for floating-point numbers: float, double, decimal, etc.

Given that float and double may lose precision, it’s recommended to use decimal for monetary values.

Typically, floating numbers are defined as decimal(m,n), where n represents the number of decimal places, and m is the total length of both integer and decimal portions.

For example, decimal(10,2) allows for 8 digits before the decimal point and 2 digits after it.

12. JSON Fields

During table structure design, you may encounter fields needing to store variable data values.

For example, in an asynchronous Excel export feature, a field in the async task table may need to save user-selected query conditions, which can vary per user.

Traditional database fields don’t handle this well.

Using MySQL’s json type enables structured data storage in JSON format for easy saving and querying.

MySQL also supports querying JSON data by field names or values.

13. Unique Indexes

Unique indexes are frequently used in practice.

You can apply unique indexes to individual fields, like an organization’s code, or create composite unique indexes for multiple fields, like category numbers, units, specifications, etc.

Unique indexes on individual fields are straightforward, but for composite unique indexes, if any field is NULL, the uniqueness constraint may fail.

Another common issue is having unique indexes while still producing duplicate data.

Due to its complexity, I’ll elaborate on unique index issues in a later article.

When creating unique indexes, ensure that none of the involved fields contain NULL values to maintain their uniqueness.

14. Character Set

MySQL supports various character sets, including latin1, utf-8, utf8mb4, etc.

Here’s a table summarizing MySQL character sets:

It’s advisable to set the character set to utf8mb4 during table creation to avoid potential issues.

15. Collation

When creating tables in MySQL, the COLLATE parameter can be configured.

For example:

CREATE TABLE `order` (
  `id` BIGINT NOT NULL AUTO_INCREMENT,
  `code` VARCHAR(20) COLLATE utf8mb4_bin NOT NULL,
  `name` VARCHAR(30) COLLATE utf8mb4_bin NOT NULL,
  PRIMARY KEY (`id`),
  UNIQUE KEY `un_code` (`code`),
  KEY `un_code_name` (`code`,`name`) USING BTREE,
  KEY `idx_name` (`name`)
) ENGINE=InnoDB AUTO_INCREMENT=5 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_bin;

The collation determines how character sorting and comparison are conducted.

Character collation depends on the character set, which for utf8mb4 would also start with utf8mb4_. Common types include utf8mb4_general_ci and utf8mb4_bin.

The utf8mb4_general_ci collation is case-insensitive for alphabetical characters, while utf8mb4_bin is case-sensitive.

This distinction is important. For example, if the order table contains a record with the name YOYO and you query it using lowercase yoyo under utf8mb4_general_ci, it retrieves the record. Under utf8mb4_bin, it will not.

Choose collation based on the actual business needs to avoid confusion.

16. Large Fields

Special attention is warranted for fields that consume substantial storage space, such as comments.

A user comment field might require limits, like a maximum of 500 characters.

Defining large fields as text can waste storage, thus it’s often better to use varchar for better efficiency.

For much larger data types, like contracts that can take up several MB, it may be unreasonable to store directly in MySQL.

Instead, such data could be stored in MongoDB, with the MySQL business table retaining the MongoDB ID.

17. Redundant Fields

To enhance performance and query speed, some fields can be redundantly stored.

For example, an order table typically contains a userId to identify users.

However, many order query pages also need to display the user ID along with the user’s name.

If both tables are small, a join is feasible, but for large datasets, it can degrade performance.

In that case, creating a redundant userName field in the order table can resolve performance issues.

While this adjustment allows direct querying from the order table without joins, it requires additional storage and may lead to inconsistency if user names change.

Therefore, carefully evaluate if the redundant fields strategy fits your particular business scenario.

18. Comments

When designing tables, ensure to add clear comments for tables and associated fields.

For example:

CREATE TABLE `sys_dept` (
  `id` BIGINT NOT NULL AUTO_INCREMENT COMMENT 'ID',
  `name` VARCHAR(30) NOT NULL COMMENT 'Name',
  `pid` BIGINT NOT NULL COMMENT 'Parent Department',
  `valid_status` TINYINT(1) NOT NULL DEFAULT 1 COMMENT 'Valid Status: 1=Valid, 0=Invalid',
  `create_user_id` BIGINT NOT NULL COMMENT 'Creator ID',
  `create_user_name` VARCHAR(30) NOT NULL COMMENT 'Creator Name',
  `create_time` DATETIME(3) DEFAULT NULL COMMENT 'Creation Date',
  `update_user_id` BIGINT DEFAULT NULL COMMENT 'Updater ID',
  `update_user_name` VARCHAR(30)  DEFAULT NULL COMMENT 'Updater Name',
  `update_time` DATETIME(3) DEFAULT NULL COMMENT 'Update Time',
  `is_del` TINYINT(1) DEFAULT '0' COMMENT 'Is Deleted: 1=Deleted, 0=Not Deleted',
  PRIMARY KEY (`id`) USING BTREE,
  KEY `index_pid` (`pid`) USING BTREE
) ENGINE=InnoDB AUTO_INCREMENT=1 DEFAULT CHARSET=utf8mb4 COMMENT='Department';

Detailed comments clarify the purpose of tables and fields.

Particularly for fields representing statuses (like valid_status), it immediately conveys the intent behind the data, such as indicating valid versus invalid.

Avoid situations where numerous status fields exist without comments, leading to confusion about what values like 1, 2, or 3 signify.

Initially, one might remember, but after a year of operation, it’s easy to forget, potentially leading to significant pitfalls.

Thus, when designing tables, meticulous commenting and regular updates of these comments are essential.

That wraps up the technical section of this article,If you have a different opinion, let me know?.

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