


How Can I Handle Dynamic SQL Return Types in PostgreSQL with Varying Column Names and Types?
PostgreSQL dynamic SQL and return types
Handling custom return types with different column names and types
In your scenario, the return type will change due to different column names and types. To handle this, you can take advantage of PostgreSQL's ability to return anonymous record types:
CREATE FUNCTION data_of(integer) RETURNS SETOF record AS ...
However, this approach requires manually specifying column definitions in each function call:
SELECT * FROM data_of(17) AS foo (colum_name1 integer , colum_name2 text , colum_name3 real);
To avoid this tedious approach, you can use document data types like JSON or XML to store unstructured data:
CREATE FUNCTION data_of(integer) RETURNS JSONB AS ...
However, this approach will sacrifice the advantages of PostgreSQL structured data types.
Fixed return type using column conversion
If your data structure is consistent (except for column names), you can return a fixed number of correctly named and typed columns:
CREATE FUNCTION data_of(_id integer) RETURNS TABLE (datahora timestamp, col2 text, col3 text) AS $func$ ...
For simplicity, each column is explicitly converted to type TEXT.
Variable number of columns with the same type
If you have a variable number of columns of the same type, you can use an array to store the values:
CREATE FUNCTION data_of(_id integer) RETURNS TABLE (datahora timestamp, names text[], values float8[]) AS $func$ ...
Also, you can return the column names as an array:
CREATE FUNCTION data_of(_id integer) RETURNS TABLE (datahora timestamp, names text[], values float8[]) AS $func$ ...
Polymorphically return all columns of the table
To return all columns of a table, regardless of their structure, you can use the anyelement
pseudo data type:
CREATE FUNCTION data_of(_tbl_type anyelement, _id int) RETURNS SETOF anyelement AS $func$ BEGIN RETURN QUERY EXECUTE format(' SELECT * FROM %s -- pg_typeof returns regtype, quoted automatically WHERE id = ORDER BY datahora' , pg_typeof(_tbl_type)) USING _id; END $func$;
Call this function with NULL of the desired table type to dynamically determine the return type:
SELECT * FROM data_of(NULL::pcdmet, 17);
The above is the detailed content of How Can I Handle Dynamic SQL Return Types in PostgreSQL with Varying Column Names and Types?. 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

Full table scanning may be faster in MySQL than using indexes. Specific cases include: 1) the data volume is small; 2) when the query returns a large amount of data; 3) when the index column is not highly selective; 4) when the complex query. By analyzing query plans, optimizing indexes, avoiding over-index and regularly maintaining tables, you can make the best choices in practical applications.

Yes, MySQL can be installed on Windows 7, and although Microsoft has stopped supporting Windows 7, MySQL is still compatible with it. However, the following points should be noted during the installation process: Download the MySQL installer for Windows. Select the appropriate version of MySQL (community or enterprise). Select the appropriate installation directory and character set during the installation process. Set the root user password and keep it properly. Connect to the database for testing. Note the compatibility and security issues on Windows 7, and it is recommended to upgrade to a supported operating system.

InnoDB's full-text search capabilities are very powerful, which can significantly improve database query efficiency and ability to process large amounts of text data. 1) InnoDB implements full-text search through inverted indexing, supporting basic and advanced search queries. 2) Use MATCH and AGAINST keywords to search, support Boolean mode and phrase search. 3) Optimization methods include using word segmentation technology, periodic rebuilding of indexes and adjusting cache size to improve performance and accuracy.

The difference between clustered index and non-clustered index is: 1. Clustered index stores data rows in the index structure, which is suitable for querying by primary key and range. 2. The non-clustered index stores index key values and pointers to data rows, and is suitable for non-primary key column queries.

MySQL is an open source relational database management system. 1) Create database and tables: Use the CREATEDATABASE and CREATETABLE commands. 2) Basic operations: INSERT, UPDATE, DELETE and SELECT. 3) Advanced operations: JOIN, subquery and transaction processing. 4) Debugging skills: Check syntax, data type and permissions. 5) Optimization suggestions: Use indexes, avoid SELECT* and use transactions.

MySQL and MariaDB can coexist, but need to be configured with caution. The key is to allocate different port numbers and data directories to each database, and adjust parameters such as memory allocation and cache size. Connection pooling, application configuration, and version differences also need to be considered and need to be carefully tested and planned to avoid pitfalls. Running two databases simultaneously can cause performance problems in situations where resources are limited.

Data Integration Simplification: AmazonRDSMySQL and Redshift's zero ETL integration Efficient data integration is at the heart of a data-driven organization. Traditional ETL (extract, convert, load) processes are complex and time-consuming, especially when integrating databases (such as AmazonRDSMySQL) with data warehouses (such as Redshift). However, AWS provides zero ETL integration solutions that have completely changed this situation, providing a simplified, near-real-time solution for data migration from RDSMySQL to Redshift. This article will dive into RDSMySQL zero ETL integration with Redshift, explaining how it works and the advantages it brings to data engineers and developers.

In MySQL database, the relationship between the user and the database is defined by permissions and tables. The user has a username and password to access the database. Permissions are granted through the GRANT command, while the table is created by the CREATE TABLE command. To establish a relationship between a user and a database, you need to create a database, create a user, and then grant permissions.
