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Entity-Attribute-Value Model

对象 - 属性 - 值模型(Entity-Attribute-Value Model, EAV Model),也叫开放架构(Open Schema)垂直数据库模型(Vertical Database Model),是一种针对属性、值分布稀疏(sparse)或特别的数据模型,专为空间高效存储而优化的,运行时数据模型是任意的、受用户变化影响。

该模型适用于不同实体的属性、值数量庞大且未知,但每一个实体的属性、值较少(也就是稀疏属性 [1])。




下面展示一个使用 EAV 模型 的临床数据库(Clinical database)表例子:

Entity Atrribute Value
⟨Patient XYZ, 1998-05-01 09:30⟩ ⟨Temperature in degrees Celsius⟩ "38.9"
⟨Patient XYZ, 1998-05-01 09:30⟩ ⟨Presence of cough⟩ "True"
⟨Patient ABC, 1998-05-01 09:30⟩ ⟨Type of Cough⟩ "With phlegm, yellowish, streaks of blood"
⟨Patient ABC, 1998-05-01 09:30⟩ ⟨Heart rate in beats per minute⟩ "98"

EAV 模型的优点

EAV 模型的缺点


An Entity–attribute–value model (EAV) is a data model optimized for the space-efficient storage of sparse—or ad-hoc—property or data values, intended for situations where runtime usage patterns are arbitrary, subject to user variation, or otherwise unforseeable using a fixed design. The use-case targets applications which offer a large or rich system of defined property types, which are in turn appropriate to a wide set of entities, but where typically only a small, specific selection of these are instantated (or persisted) for a given entity. Therefore, this type of data model relates to the mathematical notion of a sparse matrix.[2]

Entity-Attribute-Value (EAV) database model

EAV database model, as well known as ‘open schema’ or ‘vertical model’, describe entities where the number of all attributes in unknown and potentially significant, however number of attributes for a particular entity is small.[3]

Entity-Attribute-Value (EAV) database model

EAV Advantages:

  • Flexible mechanism, supports multiple projects, broad community.
  • Little consideration of DB structure at the initial design stage.
  • Database schema does not change, when model changes, allowing updates through for example web UI.[3:1]
Entity-Attribute-Value (EAV) database model

EAV Disadvantages:

  • Complexity - a high learning curve for new developers.
  • Loose data validation that needs to be implemented later in the code.
  • Performance - multiple join queries (though good cache system can improve it).
  • Does not provide a way for grouping of related entity types.
  • Does not provide a mechanism to create relationships between entities of different subtypes.
  • Developers have to recreate relational database technology (graphical system tools, data security, incremental back-up and restore, exception handling, etc.).
  • Often you cannot just use ORM, but write complex SQL queries.[3:2]

  1. ↩︎

  2.–attribute–value_model ↩︎

  3. ↩︎ ↩︎ ↩︎