How to Design a Database for Efficient AND-Search on Tags?

Database Design for Tagging with Efficient AND-Search

To design a database for tagging that supports an efficient AND-search, we need to consider the following requirements:

• Large Number of Tags: Items can be associated with numerous tags.
• Quick Search by Multiple Tags: Queries for items tagged with all the specified tags should be fast.
• Slower Write Operations: Creating or modifying items can be slower to optimize read performance.

Traditionally, JOINs could be used to implement the tagging functionality, but that approach becomes impractical when dealing with a large number of tags. To overcome this limitation, consider the following solutions:

Entity-Attribute-Value (EAV) Model

The EAV model separates data into three tables:

• Entity: Stores the primary entities (e.g., items)
• Attribute: Defines the types of attributes (e.g., tags)
• Value: Contains the actual tag values for each item

This model allows for efficient search queries by creating a separate column for each tag in the Value table. Each item can have multiple rows in the Value table, one for each tag it has. To perform an AND-search, simply specify conditions on all the desired tag columns.

Bitset Approach

This approach uses a bitset to represent the presence or absence of tags for each item. A bit is allocated for each tag, and each item has a corresponding bitset. To perform an AND-search, binary operations (e.g., bitwise AND) can be used on the bitsets of the specified tags.

Reference to Performance Tests

For further insights, refer to the following resources:

• [Database Schemas for Tags](http://howto.philippkeller.com/2005/04/24/Tags-Database-schemas/)
• [Tag Systems Performance Tests](http://howto.philippkeller.com/2005/06/19/Tagsystems-performance-tests/)

Note that the cited sources provide specific performance evaluations for MySQL, which may have improved its full-text indexing capabilities since their publication.

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