Developer guide

Jens Schauder edited this page Jun 16, 2017 · 4 revisions

Introduction

This guide targets developers that want to understand the internal workings of Spring Data, especially those that want to write their own modules or implement new features in existing modules.

How does Spring Data work?

As a user of a Spring Data module you do NOT implement interfaces as one is used to with most frameworks, but you at least start by specifying an interface and Spring Data will create the implementation internally for you.

This implementation is based on three sources:

  1. A basic implementation of standard interfaces provided by Spring Data. For example for the Mongo module there is SimpleMongoRepository implementing MongoRepository

  2. Analysis of the interface that is to be implemented. Spring Data analyses names of methods, their arguments and return value types and annotations on those methods and creates implementation strategies based on that information.

  3. Information about the Java classes to be persisted. This includes information that can be obtained through reflection, like class names, property names and types, and annotations on properties. It also includes store specific information. For example many stores provides some kind of metadata, which Spring Data will use.

For each module there is a *RepositoryFactory which creates repositories implementing the passed in interface, by creating a proxy which contains a chain of strategies for implementing methods. These strategies differ for each module, but often include

  • implementation based on some annotation on the method, so one can provide literal queries in a store dependent query language to use.
  • implementation based on the name of the method (so called query methods)
  • implementation by the basic repository implementation mentioned above. This strategy is the bare minimum and is available in all stores.

What is the role of Spring Data Commons?

The process outlined above has large parts that are independent of a specific store. For example most if not all stores need to access properties (i.e. getting and setting values) and meta data about properties (e.g. what annotations are present) abstracting over the exact implementation (i.e. is there a setter or do we access a potential private field directly; is an annotation on the field, the getter or the setter, or in a super class or interface). Also the structure of a repository and a repository factory is always the same, with surprisingly few pieces that are store dependent.

For all this there are implementations in Spring Data Commons and interfaces or abstract classes to fill in the store dependent blanks.

Mapping and conversion system

The Spring Data Commons module provides a sophisticated system to gather and use entity mapping and conversion functionality. The core model abstractions are PersistentEntity, PersistentProperty. These abstractions can be created and used through a MappingContext. In top of that we provide an EntityConverter abstraction consisting of EntityReader and EntityWriter.

Core mapping abstractions

MappingContext

The base of any mappings is the MappingContext each store has it's own implementation <Store>MappingContext which has the main purpose of providing a consistent set of instances of mapping related classes to the various pieces of the mapping infrastructure.

EntityWriter, EntityReader & EntityConverter

The main abstractions are EntityWriter and EntityReader which provide write/read methods that take a sink/source to write to / read from. If a store reads and writes from the same kind of object e.g. the DbObject of MongoDb, the two interfaces get combined into that of an EntityConverter.

For reading and writing the different pieces of an entity need to get converted into something that can be added to a sink or read from a 'source'. This is a process consisting of multiple steps:

ConversionService
  1. Figure out what conversion is required. For example, an entity might contain an attribute of type Enum but the store doesn't support enums directly, so it needs to get converted. What the conversion target is, depends on the source type, but also possibly on annotations or other configurations. You might want to consider annotations on the attribute to decide if you want to store an Enum as it's ordinal number (Integer), or its name (String). This decision is based on the <Store>PersistentProperty, which might also provide additional information about how to store attribute information, for example, the name of a column to use or the attribute name in a JSON format.

  2. Do the actual conversion. This is done through a ConversionService in most cases.

  3. If an attribute is itself an entity. The process typically gets applied recursively. The decision if an attribute is an entity is again made by the <Store>PersistentProperty and is by default based on a list of "simple types". Attributes that aren't compatible with one such simple type are considered an entity.

Entity instantiation

As an important part of the entity conversion on the reading side is creating instances of the domain class an EntityInstantiator API allows plugging custom code for

Storing type information

By default the conversion system inspects the properties of the type being read to find out which nested types it has to instantiate. So assume the following domain classes:

class Address { … }

class Person {
  Address address;
}

If the domain model works with type hierarchies, inspecting the property types might not be sufficient to read data into an object graph. Assume the domain model slightly modified and a Person instance created as follows:

class Address { … }

class Person {
  Object address;
}

Person person = new Person();
person.address = new Address();

In this case there are two important things to consider: first, the type information of the address has to be stored when persisting the Person instance. Second, when reading the object we need to detect the type to be instantiated for the data eventually forming the Address instance.

To achieve this, Spring Data Commons provides the TypeMapper API. The interface has to be typed to the actual store's native data representation (e.g. a DBObject in MongoDB). It's core responsibility is writing type information to the store object and read it back in in turn. We also ship a configurable DefaultTypeMapper that takes a TypeAliasAccessor, a MappingContext as well as TypeInformationMapper implementations to delegate to.

The TypeAliasAccessor is the core interface to implement how a type alias gets actually persisted to the store (through writeTypeTo(…))and read back in (through readTypeAlias(…)). It is not responsible to interpret the token written, it's solely encapsulating the reading and writing aspect and has to be implemented in a store-specific way.

The type alias is some arbitrary token which can be mapped to a Java type in a unique way. This can be the fully-qualified Java type name or another unique hash-like token.

The TypeInformationMapper is responsible for mapping the arbitrary alias into a TypeInformation instance, i.e. actually resolving the type. Spring Data Commons ships with a variety of implementations for that out of the box:

  • SimpleTypeInformationMapper - stores the fully-qualified class name on writing and interpreting the token returned by the TypeAliasAccessor as class name and trying to load the class.
  • MappingContextTypeInformationMapper - uses a MappingContext which inspects the entities persisted for the @TypeAlias annotation. It will return the value configured if annotated or null if no type alias information is present with the PersistentEntity (see PersistentEntity#getTypeAlias())
  • ConfigurableTypeInformationMapper - takes a Map<? extends Class<?>, String> to register a manual mapping from a type to a given alias.

These implementations can be configured as a chain on the DefaultTypeMapper. The class will then consult them in a row using the alias or type of the one returning a non-null value. This allows some types being mapped into aliases by @TypeAlias whereas all others fall back on the fully-qualified class name.

However, there a a few constructors on the DefaultTypeMapper that make the setup quite easy. The one taking a TypeAliasAccessor registers a SimpleTypeInformationMapper by default. Assume we have a TypeAliasAccessor for a Maplike this:

class MapTypeAliasAccessor implements TypeAliasAccessor<Map<String, Object>> {

  public static final String TYPE_ALIAS_KEY = "_class";

  public Object readAliasFrom(Map<String, Object> source) {
    return source.get(TYPE_ALIAS_KEY);
  }

  public void writeTypeTo(Map<String, Object> sink, Object alias) {
    sink.put(TYPE_ALIAS_KEY, alias);
  }
}

We could the setup a DefaultTypeMapper instance and use it as follows:

MapTypeAliasAccessor accessor = new MapTypeAliasAccessor();
TypeMapper<Map<String, Object> mapper = new DefaultTypeMapper<Map<String, Object>(accessor);

Map<String, Object> store = new HashMap<String, Object>();
mapper.writeType(HashMap.class, store);

// Make sure we have the type information captured
assertThat(store.get(TYPE_ALIAS_KEY), is(HashMap.class.getName()));

// Make sure we can obtain the type from the plain store source
assertThat(mapper.readType(store), is(ClassTypeInformation.from(HashMap.class)));

If we hand it a MappingContext and our Address is annotated with @TypeAlias("A"), then the DefaultTypeMapper would work as follows:

MapTypeAliasAccessor accessor = new MapTypeAliasAccessor();
MappingContext<?, ?> context =// obtain MappingContext
TypeMapper<Map<String, Object> mapper = new DefaultTypeMapper<Map<String, Object>(accessor, context, Collections.emptyList());

Map<String, Object> store = new HashMap<String, Object>();
mapper.writeType(Address.class, store);

// Make sure the alias is written, not the class name
assertThat(store.get(TYPE_ALIAS_KEY, is("A")));

// Make sure we discover Address to be the target ty
assertThat(mapper.readType(store), is(ClassTypeInformation.from(Address.class)));

Note, that storing type information for Person would still store the fully-qualified class name as the MappingContext does not find any type alias mapping information.

Implementation patterns

Usually EntityConverter implementations will setup a DefaultTypeMapper in their constructors and hand in a MappingContext so that type information is transparently stored as fully-qualified class names and consider the customization via @TypeAlias out-of-the box. The only store specific part is the TypeAliasAccessor implementation, which has to be adapted according to the store's data structure. Have a look at MongoDB's DBObjectTypeAliasAccessor for example.

Beyond that it's good practice to expose the TypeMapper as configurable property of the EntityConverter implementation so that uses gain full control over the type mapping setup if necessary.

Repository abstraction

Repository interfaces

We provide a set of repository interfaces that either declare a user's repository interface as a Spring Data interface or even pull in functionality that can be implemented generically.

  • Repository - A plain marker interface to let the Spring Data infrastructure pick up user defined repositories.
  • CrudRepository - Extends Repository and adds basic persistence methods like saving entities, finding entities and deleting them.
  • PagingAndSortingRepositories - Extends CrudRepository and adds method for access ing entities page by page and sorted by a given criteria.

Web integration

TODO

Building a store implementation

When building a store implementation for a data store we do not already support the most interesting parts are the mapping and conversion system as well as the repository abstraction. If the store you target already supports entity mapping (like JPA for example) you can implement the repository abstraction directly on top of it. Otherwise you need to integrate with the mapping and conversion system. The following sections will describe the important abstractions and classes you'll have to take a look and and extend/implement.

As example for an implementation of store support with Spring Data mapping have a look at Spring Data MongoDB, for a plain repository abstraction integration consider taking a look at Spring Data JPA.

Mapping and conversion system

TODO

Repository abstraction

Create a *RepositoryFactory extending from RepositoryFactorySupport

The very core of the repository abstraction is the factory to create repository instances. RepositoryFactorySupport requires the following methods to be implemented:

  • getEntityInformation(…) - returns the EntityInformation which encapsulates ways to determine whether an entity is new, lookup the identifier of the entity as well as the type of the id. PersistentEntityInformation is the class you'll probably want to extend. In order to do so you need a PersistentEntity. You get that by requesting it from a MappingContext. The mapping context will ensure that the PersistentEntity is properly initialized (e.g. all PersistentPropertys are found) and that the information gets memoized and not created over and over again. You can simply instantiate a MappingContext in your repository factory.
  • getRepositoryBaseClass(…) - returns the type of the backing instance of the repositories which usually implements CRUD methods etc. Needed to inspect the user's repository interface for query methods before actually creating the instance.
  • getTargetRepository(…) - returns an instance of the type returned by getRepositoryBaseClass(…). This instance will usually return one of the Spring Data Repository interfaces.

PersistentEntityInformation vs PersistentEntity The original idea was to have a separate interface for some use cases that need only very little information about an entity, so those could use the simpler PersistentEntityInformation. But currently it looks like this doesn't really work. So go ahead use mainly PersistentEntity and when you need the isNew() from PersistentEntityInformation just create one from your PersistentEntity.

There are considerations to merge these two classes in future.

Create a Simple*Repository implementing CrudRepository or PagingAndSortingRepository

There seem to be two kind of stores as far as the repository implementation is concerned:

  1. Those that read and write based on one class. For example Monge reads and writes DbObjects

  2. Those where reading and writing is asymmetrical or based on a mapping of the persistence layer. Examples for this are JDBC which needs PreparedStatements with parametersfor writing and produces ResultSets for reading, or JPA which takes and produces Pojos directly.

For the first kind you want to use the mapping and conversion system. For the second you will probably implement the necessary methods in the repository directly.

When creating domain model in your repositories, you want to use a ClassGeneratingEntityInstantiator. It creates instances and can handle constructor parameters, that set properties (if the names and types of the constructor parameters and the property match). So the users of your repository don't have to have parameterless constructors in their domain classes.

For manipulationg domain model instances, i.e. setting and getting property values, use an accessor that you can get from a PersistentEntity:

Object instance = ....; // the domain model instance
PersistentEntity entity = ....; the PersistentEntity for the class of the domain model instance
PersistentProperty property = entity.getPersistentProperty("Name"); // get the name property
entity.getPropertyAccessor(instance).setProperty(property, someValue); // set the name property to someValue

The PropertyAccessor will take care to use getter/setter/field access as required.

Query methods

TODO

Spring namespaces

TODO

Transaction handling

TODO