Group items tagged

In an EAV data model, each attribute-value pair is a fact describing an entity, and a row in an EAV table stores a single fact

EAV tables are often described as "long and skinny": "long" refers to the number of rows, "skinny" to the few columns

Data is recorded as three columns: The entity: the item being described. The attribute or parameter: a foreign key into a table of attribute definitions. At the very least, the attribute definitions table would contain the following columns: an attribute ID, attribute name, description, data type, and columns assisting input validation

The value of the attribute

Row modeling, where facts about something (in this case, a sales transaction) are recorded as multiple rows rather than multiple columns

differences between row modeling and EAV (which may be considered a generalization of row-modeling) are:

A row-modeled table is homogeneous in the facts that it describes

The data type of the value column/s in a row-modeled table is pre-determined by the nature of the facts it records. By contrast, in an EAV table, the conceptual data type of a value in a particular row depend on the attribute in that row

In the EAV table itself, this is just an attribute ID, a foreign key into an Attribute Definitions table

The Attribute

The Value

Coercing all values into strings

larger systems use separate EAV tables for each data type (including binary large objects, "BLOBS"), with the metadata for a given attribute identifying the EAV table in which its data will be stored

Where an EAV system is implemented through RDF, the RDF Schema language may conveniently be used to express such metadata

access to metadata must be restricted, and an audit trail of accesses and changes put into place to deal with situations where multiple individuals have metadata access

quality of the annotation and documentation within the metadata (i.e., the narrative/explanatory text in the descriptive columns of the metadata sub-schema) must be much higher, in order to facilitate understanding by various members of the development team.

Attribute metadata

Validation metadata include data type, range of permissible values or membership in a set of values, regular expression match, default value, and whether the value is permitted to be null

Presentation metadata: how the attribute is to be displayed to the user

Grouping metadata: Attributes are typically presented as part of a higher-order group, e.g., a specialty-specific form. Grouping metadata includes information such as the order in which attributes are presented

Advanced validation metadata Dependency metadata:

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Caching: Spring Security optionally integrates with Spring's Ehcache factory. This flexibility means your database (or other authentication repository) is not repeatedly queried for authentication information when using Spring Security with stateless applications.

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