PostgreSQL computed columns: exploring alternatives
PostgreSQL users often ask about the availability of computed columns, a feature common in other database management systems such as MS SQL Server. Although PostgreSQL does not yet natively support computed columns, it provides various alternatives to achieve similar functionality.
Storing generated columns: PostgreSQL 12 and later
PostgreSQL 12 introduces the concept of storing generated columns, which is compliant with SQL standards and supported by other RDBMS such as DB2, MySQL and Oracle. These columns are created using the STORED keyword and are calculated when data is retrieved or inserted.
CREATE TABLE tbl ( int1 int , int2 int , product bigint GENERATED ALWAYS AS (int1 * int2) STORED );
Virtually generated columns: PostgreSQL 11 and earlier
For PostgreSQL 11 and earlier, true virtual generated columns are not supported. However, the user can simulate its behavior using functions with attribute notation. This method involves using the tbl.col syntax, which mimics the appearance and functionality of a virtually generated column.
CREATE FUNCTION col(tbl) ... AS ... -- 您的计算表达式在此处
SELECT tbl.*, col(tbl) FROM tbl;
Alternatives
In addition to the above methods, PostgreSQL users can also consider other methods to achieve similar functions:
- Views: Views can be used to create virtually generated columns, allowing users to select them in SELECT * queries.
- Expression indexes: These indexes can be created on functions that compute derived values, providing performance benefits for queries involving these values.
- Materialized View: Materialized view stores the results of a query, providing a snapshot of the data at a specific point in time.
- Triggers: Triggers can be used to update or insert derived values into a table.
While PostgreSQL may not currently support native computed columns, its flexible and powerful feature set provides various solutions to implement similar functionality to meet the various needs of its users.
The above is the detailed content of PostgreSQL Computed Columns: What Alternatives Exist?. For more information, please follow other related articles on the PHP Chinese website!

MySQL'sBLOBissuitableforstoringbinarydatawithinarelationaldatabase,whileNoSQLoptionslikeMongoDB,Redis,andCassandraofferflexible,scalablesolutionsforunstructureddata.BLOBissimplerbutcanslowdownperformancewithlargedata;NoSQLprovidesbetterscalabilityand

ToaddauserinMySQL,use:CREATEUSER'username'@'host'IDENTIFIEDBY'password';Here'showtodoitsecurely:1)Choosethehostcarefullytocontrolaccess.2)SetresourcelimitswithoptionslikeMAX_QUERIES_PER_HOUR.3)Usestrong,uniquepasswords.4)EnforceSSL/TLSconnectionswith

ToavoidcommonmistakeswithstringdatatypesinMySQL,understandstringtypenuances,choosetherighttype,andmanageencodingandcollationsettingseffectively.1)UseCHARforfixed-lengthstrings,VARCHARforvariable-length,andTEXT/BLOBforlargerdata.2)Setcorrectcharacters

MySQloffersechar, Varchar, text, Anddenumforstringdata.usecharforfixed-Lengthstrings, VarcharerForvariable-Length, text forlarger text, AndenumforenforcingdataAntegritywithaetofvalues.

Optimizing MySQLBLOB requests can be done through the following strategies: 1. Reduce the frequency of BLOB query, use independent requests or delay loading; 2. Select the appropriate BLOB type (such as TINYBLOB); 3. Separate the BLOB data into separate tables; 4. Compress the BLOB data at the application layer; 5. Index the BLOB metadata. These methods can effectively improve performance by combining monitoring, caching and data sharding in actual applications.

Mastering the method of adding MySQL users is crucial for database administrators and developers because it ensures the security and access control of the database. 1) Create a new user using the CREATEUSER command, 2) Assign permissions through the GRANT command, 3) Use FLUSHPRIVILEGES to ensure permissions take effect, 4) Regularly audit and clean user accounts to maintain performance and security.

ChooseCHARforfixed-lengthdata,VARCHARforvariable-lengthdata,andTEXTforlargetextfields.1)CHARisefficientforconsistent-lengthdatalikecodes.2)VARCHARsuitsvariable-lengthdatalikenames,balancingflexibilityandperformance.3)TEXTisidealforlargetextslikeartic

Best practices for handling string data types and indexes in MySQL include: 1) Selecting the appropriate string type, such as CHAR for fixed length, VARCHAR for variable length, and TEXT for large text; 2) Be cautious in indexing, avoid over-indexing, and create indexes for common queries; 3) Use prefix indexes and full-text indexes to optimize long string searches; 4) Regularly monitor and optimize indexes to keep indexes small and efficient. Through these methods, we can balance read and write performance and improve database efficiency.


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

SublimeText3 English version
Recommended: Win version, supports code prompts!

VSCode Windows 64-bit Download
A free and powerful IDE editor launched by Microsoft

SublimeText3 Linux new version
SublimeText3 Linux latest version

Dreamweaver CS6
Visual web development tools

Zend Studio 13.0.1
Powerful PHP integrated development environment
