


How to Find Uncancelled Reservations Using SQL: `NOT IN` vs. `LEFT JOIN`?
SQL Techniques for Finding Uncancelled Reservations
This article explores two efficient SQL methods to retrieve uncancelled reservations from a database with reservation
and reservation_log
tables. The objective is to select only those reservations lacking a cancellation record.
Method 1: Using NOT IN
with a Subquery
This approach employs a subquery to identify reservation IDs present in the reservation_log
table with a change_type
of 'cancel'. The main query then selects reservations whose IDs are not in this list:
SELECT * FROM reservation WHERE id NOT IN (SELECT reservation_id FROM reservation_log WHERE change_type = 'cancel');
Method 2: Utilizing LEFT JOIN
A more efficient alternative uses a LEFT JOIN
to combine the reservation
and reservation_log
tables. A LEFT JOIN
returns all rows from the left table (reservation
), even if there's no match in the right table (reservation_log
). If a match is absent, the columns from the right table will be NULL
. Filtering for NULL
values in the change_type
column isolates uncancelled reservations:
SELECT r.* FROM reservation r LEFT JOIN reservation_log l ON r.id = l.reservation_id AND l.change_type = 'cancel' WHERE l.id IS NULL;
Both methods achieve the same outcome. However, the LEFT JOIN
approach is generally preferred for its improved performance, especially with larger datasets, as it avoids the potential performance issues associated with NOT IN
subqueries. Choose the method that best suits your database system and data volume.
The above is the detailed content of How to Find Uncancelled Reservations Using SQL: `NOT IN` vs. `LEFT JOIN`?. 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

AI Hentai Generator
Generate AI Hentai for free.

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



The article discusses using MySQL's ALTER TABLE statement to modify tables, including adding/dropping columns, renaming tables/columns, and changing column data types.

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.

Article discusses configuring SSL/TLS encryption for MySQL, including certificate generation and verification. Main issue is using self-signed certificates' security implications.[Character count: 159]

Article discusses popular MySQL GUI tools like MySQL Workbench and phpMyAdmin, comparing their features and suitability for beginners and advanced users.[159 characters]

Article discusses strategies for handling large datasets in MySQL, including partitioning, sharding, indexing, and query optimization.

The article discusses dropping tables in MySQL using the DROP TABLE statement, emphasizing precautions and risks. It highlights that the action is irreversible without backups, detailing recovery methods and potential production environment hazards.

The article discusses creating indexes on JSON columns in various databases like PostgreSQL, MySQL, and MongoDB to enhance query performance. It explains the syntax and benefits of indexing specific JSON paths, and lists supported database systems.

MySQL supports four index types: B-Tree, Hash, Full-text, and Spatial. 1.B-Tree index is suitable for equal value search, range query and sorting. 2. Hash index is suitable for equal value searches, but does not support range query and sorting. 3. Full-text index is used for full-text search and is suitable for processing large amounts of text data. 4. Spatial index is used for geospatial data query and is suitable for GIS applications.
