


How Can I Correctly Use PostgreSQL's DISTINCT ON with Different ORDER BY Clauses?
Jan 21, 2025 pm 12:14 PMUnderstanding PostgreSQL's DISTINCT ON and ORDER BY Interactions
PostgreSQL's DISTINCT ON
clause is designed to select the first row from each group of rows that have the same values in the specified expression(s). The crucial point is that the selection of the "first" row depends entirely on the ORDER BY
clause. They must align.
A common mistake is using a DISTINCT ON
clause with an ORDER BY
clause that doesn't include the DISTINCT ON
expression(s). This leads to unpredictable results because the database's choice of the "first" row becomes arbitrary.
Correcting Order Issues with DISTINCT ON
The error arises when the fields in DISTINCT ON
don't match the leading fields in ORDER BY
. To fix this, ensure the ORDER BY
clause starts with the same expressions as DISTINCT ON
. This guarantees a consistent and predictable selection of the first row within each group.
Alternative Approaches for "Greatest N Per Group" Problems
If the objective is to find the latest purchase for each address_id
, ordered by purchase date, this is a classic "greatest N per group" query. Here are two efficient solutions:
General SQL Solution:
This approach uses a subquery to find the maximum purchased_at
for each address_id
and then joins it back to the original table to retrieve the complete row.
SELECT t1.* FROM purchases t1 JOIN ( SELECT address_id, max(purchased_at) max_purchased_at FROM purchases WHERE product_id = 1 GROUP BY address_id ) t2 ON t1.address_id = t2.address_id AND t1.purchased_at = t2.max_purchased_at ORDER BY t1.purchased_at DESC
PostgreSQL-Specific Optimization:
PostgreSQL offers a more concise and potentially faster solution using a nested DISTINCT ON
query:
SELECT * FROM ( SELECT DISTINCT ON (address_id) * FROM purchases WHERE product_id = 1 ORDER BY address_id, purchased_at DESC ) t ORDER BY purchased_at DESC
These alternatives provide cleaner and more efficient solutions compared to relying solely on DISTINCT ON
when dealing with "greatest N per group" scenarios. They avoid unnecessary sorting and improve query performance.
The above is the detailed content of How Can I Correctly Use PostgreSQL's DISTINCT ON with Different ORDER BY Clauses?. For more information, please follow other related articles on the PHP Chinese website!

Hot AI Tools

Undress AI Tool
Undress images for free

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

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

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

MySQL transactions follow ACID characteristics to ensure the reliability and consistency of database transactions. First, atomicity ensures that transactions are executed as an indivisible whole, either all succeed or all fail to roll back. For example, withdrawals and deposits must be completed or not occur at the same time in the transfer operation; second, consistency ensures that transactions transition the database from one valid state to another, and maintains the correct data logic through mechanisms such as constraints and triggers; third, isolation controls the visibility of multiple transactions when concurrent execution, prevents dirty reading, non-repeatable reading and fantasy reading. MySQL supports ReadUncommitted and ReadCommi.

MySQL's default transaction isolation level is RepeatableRead, which prevents dirty reads and non-repeatable reads through MVCC and gap locks, and avoids phantom reading in most cases; other major levels include read uncommitted (ReadUncommitted), allowing dirty reads but the fastest performance, 1. Read Committed (ReadCommitted) ensures that the submitted data is read but may encounter non-repeatable reads and phantom readings, 2. RepeatableRead default level ensures that multiple reads within the transaction are consistent, 3. Serialization (Serializable) the highest level, prevents other transactions from modifying data through locks, ensuring data integrity but sacrificing performance;

To add MySQL's bin directory to the system PATH, it needs to be configured according to the different operating systems. 1. Windows system: Find the bin folder in the MySQL installation directory (the default path is usually C:\ProgramFiles\MySQL\MySQLServerX.X\bin), right-click "This Computer" → "Properties" → "Advanced System Settings" → "Environment Variables", select Path in "System Variables" and edit it, add the MySQLbin path, save it and restart the command prompt and enter mysql--version verification; 2.macOS and Linux systems: Bash users edit ~/.bashrc or ~/.bash_

TosecurelyconnecttoaremoteMySQLserver,useSSHtunneling,configureMySQLforremoteaccess,setfirewallrules,andconsiderSSLencryption.First,establishanSSHtunnelwithssh-L3307:localhost:3306user@remote-server-Nandconnectviamysql-h127.0.0.1-P3307.Second,editMyS

MySQLWorkbench stores connection information in the system configuration file. The specific path varies according to the operating system: 1. It is located in %APPDATA%\MySQL\Workbench\connections.xml in Windows system; 2. It is located in ~/Library/ApplicationSupport/MySQL/Workbench/connections.xml in macOS system; 3. It is usually located in ~/.mysql/workbench/connections.xml in Linux system or ~/.local/share/data/MySQL/Wor

Aconnectionpoolisacacheofdatabaseconnectionsthatarekeptopenandreusedtoimproveefficiency.Insteadofopeningandclosingconnectionsforeachrequest,theapplicationborrowsaconnectionfromthepool,usesit,andthenreturnsit,reducingoverheadandimprovingperformance.Co

Turn on MySQL slow query logs and analyze locationable performance issues. 1. Edit the configuration file or dynamically set slow_query_log and long_query_time; 2. The log contains key fields such as Query_time, Lock_time, Rows_examined to assist in judging efficiency bottlenecks; 3. Use mysqldumpslow or pt-query-digest tools to efficiently analyze logs; 4. Optimization suggestions include adding indexes, avoiding SELECT*, splitting complex queries, etc. For example, adding an index to user_id can significantly reduce the number of scanned rows and improve query efficiency.

mysqldump is a common tool for performing logical backups of MySQL databases. It generates SQL files containing CREATE and INSERT statements to rebuild the database. 1. It does not back up the original file, but converts the database structure and content into portable SQL commands; 2. It is suitable for small databases or selective recovery, and is not suitable for fast recovery of TB-level data; 3. Common options include --single-transaction, --databases, --all-databases, --routines, etc.; 4. Use mysql command to import during recovery, and can turn off foreign key checks to improve speed; 5. It is recommended to test backup regularly, use compression, and automatic adjustment.
