start on inheritance mapping

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Gavin 2023-05-10 17:28:07 +02:00 committed by Christian Beikov
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include::Configuration.adoc[] include::Configuration.adoc[]
include::Entities.adoc[] include::Entities.adoc[]
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[[object-relational-mapping]]
== Object/relational mapping
Given a domain model&mdash;that is, a collection of entity classes decorated with all the fancy annotations we <<entities-summary,just met>> in the previous chapter&mdash;Hibernate will happily go away and infer a complete relational schema, and even <<automatic-schema-export,export it to your database>> if you ask politely.
The resulting schema will be entirely sane and reasonable, though if you look closely, you'll find some flaws.
For example, every `VARCHAR` column will have the same length, `VARCHAR(255)`.
But the process I just described&mdash;which we call _top down_ mapping&mdash;simply doesn't fit the most common scenario for the use of O/R mapping.
It's only rarely that the Java classes precede the relational schema.
Usually, _we already have a relational schema_, and we're constructing our domain model around the schema.
This is called _bottom up_ mapping.
[NOTE]
."Legacy" data
====
Developers often refer to a pre-existing relational database as "legacy" data.
That's perhaps a bad word to use, conjuring images of bad old "legacy apps" written in COBOL or something.
But it's not "legacy" data&mdash;it's just your data.
And it's valuable.
So learning to work with "legacy" data is important.
====
Especially when mapping bottom up, we often need to customize the inferred object/relational mappings.
This is a somewhat tedious topic, and so we don't want to spend too many words on it.
Instead, we'll quickly skim the most important mapping annotations.
[[mapping-inheritance]]
=== Mapping entity inheritance hierarchies
In <<entity-inheritance>> we saw that entity classes may exist within an inheritance hierarchy.
There's three basic strategies for mapping an entity hierarchy to relational tables.
Let's put them in a table, so we can more easily compare the points of difference between them.
|===
| Strategy | Mapping | Polymorphic queries | Constraints | Normalization | When to use it
| `SINGLE_TABLE`
| Map every class in the hierarchy to the same table, and uses the value of a _discriminator column_ to determine which concrete class each row represents.
| To retrieve instances of a given class, we only need to query the one table.
| Attributes declared by subclasses map to columns without `NOT NULL` constraints. 💀
Any association may have a `FOREIGN KEY` constraint. 🤓
| Subclass data is denormalized. 🧐
| Works well when subclasses declare few or no additional attributes.
| `JOINED`
| Map every class in the hierarchy to a separate table, but each table only maps the attributes declared by the class itself.
Optionally, a discriminator column may be used.
a| To retrieve instances of a given class, we must `JOIN` the table mapped by the class with:
- all tables mapped by its superclasses and
- all tables mapped by its subclasses.
| Any attribute may map to a column with a `NOT NULL` constraint. 🤓
Any association may have a `FOREIGN KEY` constraint. 🤓
| The tables are normalized. 🤓
| The best option when we care a lot about constraints and normalization.
| `TABLE_PER_CLASS`
| Map every concrete class in the hierarchy to a separate table, but denormalize all inherited attributes into the table.
| To retrieve instances of a given class, we must take a `UNION` over the table mapped by the class and the tables mapped by its subclasses.
| Associations targeting a superclass cannot have a corresponding `FOREIGN KEY` constraint in the database. 💀💀
Any attribute may map to a column with a `NOT NULL` constraint. 🤓
| Superclass data is denormalized. 🧐
| Not very popular.
From a certain point of view, competes with `@MappedSuperclass`.