[[mapping-chapter]]
= Object Mapping

Rich mapping support is provided by the `MappingMongoConverter`.
The converter holds a metadata model that provides a full feature set to map domain objects to MongoDB documents.
The mapping metadata model is populated by using annotations on your domain objects.
However, the infrastructure is not limited to using annotations as the only source of metadata information.
The `MappingMongoConverter` also lets you map objects to documents without providing any additional metadata, by following a set of conventions.

This section describes the features of the `MappingMongoConverter`, including fundamentals, how to use conventions for mapping objects to documents and how to override those conventions with annotation-based mapping metadata.

include::{commons}@data-commons::page$object-mapping.adoc[leveloffset=+1]

[[mapping-conventions]]
== Convention-based Mapping

`MappingMongoConverter` has a few conventions for mapping objects to documents when no additional mapping metadata is provided.
The conventions are:

* The short Java class name is mapped to the collection name in the following manner.
The class `com.bigbank.SavingsAccount` maps to the `savingsAccount` collection name.
* All nested objects are stored as nested objects in the document and *not* as DBRefs.
* The converter uses any Spring Converters registered with it to override the default mapping of object properties to document fields and values.
* The fields of an object are used to convert to and from fields in the document.
Public `JavaBean` properties are not used.
* If you have a single non-zero-argument constructor whose constructor argument names match top-level field names of document, that constructor is used.Otherwise, the zero-argument constructor is used.If there is more than one non-zero-argument constructor, an exception will be thrown.

[[mapping.conventions.id-field]]
=== How the `_id` field is handled in the mapping layer.

MongoDB requires that you have an `_id` field for all documents.If you don't provide one the driver will assign a ObjectId with a generated value.The `_id` field can be of any type, other than arrays, so long as it is unique.The driver naturally supports all primitive types and Dates.When using the `MappingMongoConverter` there are certain rules that govern how properties from the Java class are mapped to the `_id` field.

The following outlines what field will be mapped to the `_id` document field:

* A field annotated with `@Id` (`org.springframework.data.annotation.Id`) will be mapped to the `_id` field. +
Additionally, the name of the document field can be customized via the `@Field` annotation, in which case the document will not contain a field `_id`.
* A field without an annotation but named `id` will be mapped to the `_id` field.

[cols="1,2",options="header"]
.Examples for the translation of `_id` field definitions
|===
| Field definition
| Resulting Id-Fieldname in MongoDB

| `String` id
| `_id`

| `@Field` `String` id
| `_id`

| `@Field("x")` `String` id
| `x`

| `@Id` `String` x
| `_id`

| `@Field("x")` `@Id` `String` y
| `_id` (`@Field(name)` is ignored, `@Id` takes precedence)
|===

The following outlines what type conversion, if any, will be done on the property mapped to the _id document field.

* If a field named `id` is declared as a String or BigInteger in the Java class it will be converted to and stored as an ObjectId if possible.
ObjectId as a field type is also valid.
If you specify a value for `id` in your application, the conversion to an ObjectId is done by the MongoDB driver.
If the specified `id` value cannot be converted to an ObjectId, then the value will be stored as is in the document's `_id` field.
This also applies if the field is annotated with `@Id`.
* If a field is annotated with `@MongoId` in the Java class it will be converted to and stored as using its actual type.
No further conversion happens unless `@MongoId` declares a desired field type.
If no value is provided for the `id` field, a new `ObjectId` will be created and converted to the properties type.
* If a field is annotated with `@MongoId(FieldType.…)` in the Java class it will be attempted to convert the value to the declared `FieldType`.
If no value is provided for the `id` field, a new `ObjectId` will be created and converted to the declared type.
* If a field named `id` is not declared as a String, BigInteger, or ObjectID in the Java class then you should assign it a value in your application so it can be stored 'as-is' in the document's `_id` field.
* If no field named `id` is present in the Java class then an implicit `_id` file will be generated by the driver but not mapped to a property or field of the Java class.

When querying and updating `MongoTemplate` will use the converter to handle conversions of the `Query` and `Update` objects that correspond to the above rules for saving documents so field names and types used in your queries will be able to match what is in your domain classes.

[[mapping-conversion]]
== Data Mapping and Type Conversion

Spring Data MongoDB supports all types that can be represented as BSON, MongoDB's internal document format.
In addition to these types, Spring Data MongoDB provides a set of built-in converters to map additional types.
You can provide your own converters to adjust type conversion.
See xref:mongodb/mapping/custom-conversions.adoc[Custom Conversions - Overriding Default Mapping] for further details.

.Built in Type conversions:
[%collapsible]
====
[cols="3,1,6",options="header"]
.Type
|===
| Type
| Type conversion
| Sample

| `String`
| native
| `{"firstname" : "Dave"}`

| `double`, `Double`, `float`, `Float`
| native
| `{"weight" : 42.5}`

| `int`, `Integer`, `short`, `Short`
| native +
32-bit integer
| `{"height" : 42}`

| `long`, `Long`
| native +
64-bit integer
| `{"height" : 42}`

| `Date`, `Timestamp`
| native
| `{"date" : ISODate("2019-11-12T23:00:00.809Z")}`

| `byte[]`
| native
| `{"bin" : { "$binary" : "AQIDBA==", "$type" : "00" }}`

| `java.util.UUID` (According to UuidRepresentation)
| native
| `{"uuid" : { "$binary" : "MEaf1CFQ6lSphaa3b9AtlA==", "$type" : "04" }}`

| `Date`
| native
| `{"date" : ISODate("2019-11-12T23:00:00.809Z")}`

| `ObjectId`
| native
| `{"_id" : ObjectId("5707a2690364aba3136ab870")}`

| Array, `List`, `BasicDBList`
| native
| `{"cookies" : [ … ]}`

| `boolean`, `Boolean`
| native
| `{"active" : true}`

| `null`
| native
| `{"value" : null}`

| `Document`
| native
| `{"value" : { … }}`

| `Decimal128`
| native
| `{"value" : NumberDecimal(…)}`

| `AtomicInteger` +
calling `get()` before the actual conversion
| converter +
32-bit integer
| `{"value" : "741" }`

| `AtomicLong` +
calling `get()` before the actual conversion
| converter +
64-bit integer
| `{"value" : "741" }`

| `BigInteger`
| native +
`NumberDecimal`, `String` (see `BigDecimalRepresentation`)
| `{"value" : NumberDecimal(741) }`, `{"value" : "741" }`

| `BigDecimal`
| native +
`NumberDecimal`, `String` (see `BigDecimalRepresentation`)
| `{"value" : NumberDecimal(741.99) }`, `{"value" : "741.99" }`

| `URL`
| converter
| `{"website" : "https://spring.io/projects/spring-data-mongodb/" }`

| `Locale`
| converter
| `{"locale : "en_US" }`

| `char`, `Character`
| converter
| `{"char" : "a" }`

| `NamedMongoScript`
| converter +
`Code`
| `{"_id" : "script name", value: (some javascript code)`}

| `java.util.Currency`
| converter
| `{"currencyCode" : "EUR"}`

| `Instant` +
(Java 8)
| native
| `{"date" : ISODate("2019-11-12T23:00:00.809Z")}`

| `Instant` +
(Java 8)
| converter
| `{"date" : ISODate("2019-11-12T23:00:00.809Z")}`

| `LocalDate` +
(Java 8)
| converter / native (Java 8)footnote:[Uses UTC zone offset. Configure via xref:mongodb/mapping/mapping.adoc#mapping-configuration[MongoConverterConfigurationAdapter]]
| `{"date" : ISODate("2019-11-12T00:00:00.000Z")}`

| `LocalDateTime`, `LocalTime` +
(Java 8)
| converter / native (Java 8)footnote:[Uses UTC zone offset. Configure via xref:mongodb/mapping/mapping.adoc#mapping-configuration[MongoConverterConfigurationAdapter]]
| `{"date" : ISODate("2019-11-12T23:00:00.809Z")}`

| `ZoneId` (Java 8)
| converter
| `{"zoneId" : "ECT - Europe/Paris"}`

| `Box`
| converter
| `{"box" : { "first" : { "x" : 1.0 , "y" : 2.0} , "second" : { "x" : 3.0 , "y" : 4.0}}`

| `Polygon`
| converter
| `{"polygon" : { "points" : [ { "x" : 1.0 , "y" : 2.0} , { "x" : 3.0 , "y" : 4.0} , { "x" : 4.0 , "y" : 5.0}]}}`

| `Circle`
| converter
| `{"circle" : { "center" : { "x" : 1.0 , "y" : 2.0} , "radius" : 3.0 , "metric" : "NEUTRAL"}}`

| `Point`
| converter
| `{"point" : { "x" : 1.0 , "y" : 2.0}}`

| `GeoJsonPoint`
| converter
| `{"point" : { "type" : "Point" , "coordinates" : [3.0 , 4.0] }}`

| `GeoJsonMultiPoint`
| converter
| `{"geoJsonLineString" : {"type":"MultiPoint", "coordinates": [ [ 0 , 0 ], [ 0 , 1 ], [ 1 , 1 ] ] }}`

| `Sphere`
| converter
| `{"sphere" : { "center" : { "x" : 1.0 , "y" : 2.0} , "radius" : 3.0 , "metric" : "NEUTRAL"}}`

| `GeoJsonPolygon`
| converter
| `{"polygon" : { "type" : "Polygon", "coordinates" : [[ [ 0 , 0 ], [ 3 , 6 ], [ 6 , 1 ], [ 0 , 0  ] ]] }}`

| `GeoJsonMultiPolygon`
| converter
| `{"geoJsonMultiPolygon" : { "type" : "MultiPolygon", "coordinates" : [
[ [ [ -73.958 , 40.8003 ] , [ -73.9498 , 40.7968 ] ] ],
[ [ [ -73.973 , 40.7648 ] , [ -73.9588 , 40.8003 ] ] ]
] }}`

| `GeoJsonLineString`
| converter
| `{ "geoJsonLineString" : { "type" : "LineString", "coordinates" : [ [ 40 , 5 ], [ 41 , 6 ] ] }}`

| `GeoJsonMultiLineString`
| converter
| `{"geoJsonLineString" : { "type" : "MultiLineString", coordinates: [
[ [ -73.97162 , 40.78205 ], [ -73.96374 , 40.77715 ] ],
[ [ -73.97880 , 40.77247 ], [ -73.97036 , 40.76811 ] ]
] }}`
|===
====

.Collection Handling
[NOTE]
====
Collection handling depends on the actual values returned by MongoDB.

* If a document does **not** contain a field mapped to a collection, the mapping will not update the property.
Which means the value will remain `null`, a java default or any value set during object creation.
* If a document contains a field to be mapped, but the field holds a `null` value (like: `{ 'list' : null }`), the property value is set to `null`.
* If a document contains a field to be mapped to a collection which is **not** `null` (like: `{ 'list' : [ ... ] }`), the collection is populated with the mapped values.

Generally, if you use constructor creation, then you can get hold of the value to be set.
Property population can make use of default initialization values if a property value is not being provided by a query response.
====

[[mapping-configuration]]
== Mapping Configuration

Unless explicitly configured, an instance of `MappingMongoConverter` is created by default when you create a `MongoTemplate`.
You can create your own instance of the `MappingMongoConverter`.
Doing so lets you dictate where in the classpath your domain classes can be found, so that Spring Data MongoDB can extract metadata and construct indexes.
Also, by creating your own instance, you can register Spring converters to map specific classes to and from the database.

You can configure the `MappingMongoConverter` as well as `com.mongodb.client.MongoClient` and MongoTemplate by using either Java-based or XML-based metadata.
The following example shows the configuration:

[tabs]
======
Java::
+
====
[source,java,indent=0,subs="verbatim,quotes",role="primary"]
----
@Configuration
public class MongoConfig extends AbstractMongoClientConfiguration {

  @Override
  public String getDatabaseName() {
    return "database";
  }

  // the following are optional

  @Override
  public String getMappingBasePackage() { <1>
    return "com.bigbank.domain";
  }

  @Override
  void configureConverters(MongoConverterConfigurationAdapter adapter) { <2>

  	adapter.registerConverter(new org.springframework.data.mongodb.test.PersonReadConverter());
  	adapter.registerConverter(new org.springframework.data.mongodb.test.PersonWriteConverter());
  }

  @Bean
  public LoggingEventListener<MongoMappingEvent> mappingEventsListener() {
    return new LoggingEventListener<MongoMappingEvent>();
  }
}
----

<1> The mapping base package defines the root path used to scan for entities used to pre initialize the `MappingContext`.
By default the configuration classes package is used.
<2> Configure additional custom converters for specific domain types that replace the default mapping procedure for those types with your custom implementation.
====

XML::
+
[source,xml,indent=0,subs="verbatim,quotes",role="secondary"]
----
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
  xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xmlns:mongo="http://www.springframework.org/schema/data/mongo"
  xsi:schemaLocation="
    http://www.springframework.org/schema/data/mongo https://www.springframework.org/schema/data/mongo/spring-mongo.xsd
    http://www.springframework.org/schema/beans https://www.springframework.org/schema/beans/spring-beans-3.0.xsd">

  <!-- Default bean name is 'mongo' -->
  <mongo:mongo-client host="localhost" port="27017"/>

  <mongo:db-factory dbname="database" mongo-ref="mongoClient"/>

  <!-- by default look for a Mongo object named 'mongo' - default name used for the converter is 'mappingConverter' -->
  <mongo:mapping-converter base-package="com.bigbank.domain">
    <mongo:custom-converters>
      <mongo:converter ref="readConverter"/>
      <mongo:converter>
        <bean class="org.springframework.data.mongodb.test.PersonWriteConverter"/>
      </mongo:converter>
    </mongo:custom-converters>
  </mongo:mapping-converter>

  <bean id="readConverter" class="org.springframework.data.mongodb.test.PersonReadConverter"/>

  <!-- set the mapping converter to be used by the MongoTemplate -->
  <bean id="mongoTemplate" class="org.springframework.data.mongodb.core.MongoTemplate">
    <constructor-arg name="mongoDbFactory" ref="mongoDbFactory"/>
    <constructor-arg name="mongoConverter" ref="mappingConverter"/>
  </bean>

  <bean class="org.springframework.data.mongodb.core.mapping.event.LoggingEventListener"/>

</beans>
----
======

`AbstractMongoClientConfiguration` requires you to implement methods that define a `com.mongodb.client.MongoClient` as well as provide a database name.
`AbstractMongoClientConfiguration` also has a method named  `getMappingBasePackage(…)` that you can override to tell the converter where to scan for classes annotated with the `@Document` annotation.

You can add additional converters to the converter by overriding the `customConversionsConfiguration` method.
MongoDB's native JSR-310 support can be enabled through `MongoConverterConfigurationAdapter.useNativeDriverJavaTimeCodecs()`.
Also shown in the preceding example is a `LoggingEventListener`, which logs `MongoMappingEvent` instances that are posted onto Spring's `ApplicationContextEvent` infrastructure.

[TIP]
====
.Java Time Types
We recommend using MongoDB's native JSR-310 support via `MongoConverterConfigurationAdapter.useNativeDriverJavaTimeCodecs()` as described above as it is using an `UTC` based approach.
The default JSR-310 support for `java.time` types inherited from Spring Data Commons uses the local machine timezone as reference and should only be used for backwards compatibility.
====

NOTE: `AbstractMongoClientConfiguration` creates a `MongoTemplate` instance and registers it with the container under the name `mongoTemplate`.

The `base-package` property tells it where to scan for classes annotated with the `@org.springframework.data.mongodb.core.mapping.Document` annotation.

[TIP]
====
If you want to rely on https://spring.io/projects/spring-boot[Spring Boot] to bootstrap Data MongoDB, but still want to override certain aspects of the configuration, you may want to expose beans of that type.
For custom conversions you may eg. choose to register a bean of type `MongoCustomConversions` that will be picked up the by the Boot infrastructure.
To learn more about this please make sure to read the Spring Boot https://docs.spring.io/spring-boot/docs/current/reference/htmlsingle/#data.nosql.mongodb[Reference Documentation].
====

[[mapping-usage]]
== Metadata-based Mapping

To take full advantage of the object mapping functionality inside the Spring Data MongoDB support, you should annotate your mapped objects with the `@Document` annotation.
Although it is not necessary for the mapping framework to have this annotation (your POJOs are mapped correctly, even without any annotations), it lets the classpath scanner find and pre-process your domain objects to extract the necessary metadata.
If you do not use this annotation, your application takes a slight performance hit the first time you store a domain object, because the mapping framework needs to build up its internal metadata model so that it knows about the properties of your domain object and how to persist them.
The following example shows a domain object:

.Example domain object
====
[source,java]
----
package com.mycompany.domain;

@Document
public class Person {

  @Id
  private ObjectId id;

  @Indexed
  private Integer ssn;

  private String firstName;

  @Indexed
  private String lastName;
}
----
====

IMPORTANT: The `@Id` annotation tells the mapper which property you want to use for the MongoDB `_id` property, and the `@Indexed` annotation tells the mapping framework to call `createIndex(…)` on that property of your document, making searches faster.
Automatic index creation is only done for types annotated with `@Document`.

WARNING: Auto index creation is **disabled** by default and needs to be enabled through the configuration (see xref:mongodb/mapping/mapping.adoc#mapping.index-creation[Index Creation]).

[[mapping-usage-annotations]]
=== Mapping Annotation Overview

The MappingMongoConverter can use metadata to drive the mapping of objects to documents.
The following annotations are available:

* `@Id`: Applied at the field level to mark the field used for identity purpose.
* `@MongoId`: Applied at the field level to mark the field used for identity purpose.
Accepts an optional `FieldType` to customize id conversion.
* `@Document`: Applied at the class level to indicate this class is a candidate for mapping to the database.
You can specify the name of the collection where the data will be stored.
* `@DBRef`: Applied at the field to indicate it is to be stored using a com.mongodb.DBRef.
* `@DocumentReference`: Applied at the field to indicate it is to be stored as a pointer to another document.
This can be a single value (the _id_ by default), or a `Document` provided via a converter.
* `@Indexed`: Applied at the field level to describe how to index the field.
* `@CompoundIndex` (repeatable): Applied at the type level to declare Compound Indexes.
* `@GeoSpatialIndexed`: Applied at the field level to describe how to geoindex the field.
* `@TextIndexed`: Applied at the field level to mark the field to be included in the text index.
* `@HashIndexed`: Applied at the field level for usage within a hashed index to partition data across a sharded cluster.
* `@Language`: Applied at the field level to set the language override property for text index.
* `@Transient`: By default, all fields are mapped to the document.
This annotation excludes the field where it is applied from being stored in the database.
Transient properties cannot be used within a persistence constructor as the converter cannot materialize a value for the constructor argument.
* `@PersistenceCreator`: Marks a given constructor or a `static` factory method - even a package protected one - to use when instantiating the object from the database.
Constructor arguments are mapped by name to the key values in the retrieved Document.
* `@Value`: This annotation is part of the Spring Framework . Within the mapping framework it can be applied to constructor arguments.
This lets you use a Spring Expression Language statement to transform a key's value retrieved in the database before it is used to construct a domain object.
In order to reference a property of a given document one has to use expressions like: `@Value("#root.myProperty")` where `root` refers to the root of the given document.
* `@Field`: Applied at the field level it allows to describe the name and type of the field as it will be represented in the MongoDB BSON document thus allowing the name and type to be different than the fieldname of the class as well as the property type.
* `@Version`: Applied at field level is used for optimistic locking and checked for modification on save operations.
The initial value is `zero` (`one` for primitive types) which is bumped automatically on every update.

The mapping metadata infrastructure is defined in a separate spring-data-commons project that is technology agnostic.
Specific subclasses are using in the MongoDB support to support annotation based metadata.
Other strategies are also possible to put in place if there is demand.

.Here is an example of a more complex mapping
[%collapsible]
====
[source,java]
----
@Document
@CompoundIndex(name = "age_idx", def = "{'lastName': 1, 'age': -1}")
public class Person<T extends Address> {

  @Id
  private String id;

  @Indexed(unique = true)
  private Integer ssn;

  @Field("fName")
  private String firstName;

  @Indexed
  private String lastName;

  private Integer age;

  @Transient
  private Integer accountTotal;

  @DBRef
  private List<Account> accounts;

  private T address;

  public Person(Integer ssn) {
    this.ssn = ssn;
  }

  @PersistenceCreator
  public Person(Integer ssn, String firstName, String lastName, Integer age, T address) {
    this.ssn = ssn;
    this.firstName = firstName;
    this.lastName = lastName;
    this.age = age;
    this.address = address;
  }

  public String getId() {
    return id;
  }

  // no setter for Id.  (getter is only exposed for some unit testing)

  public Integer getSsn() {
    return ssn;
  }

// other getters/setters omitted
}
----
====

[TIP]
====
`@Field(targetType=...)` can come in handy when the native MongoDB type inferred by the mapping infrastructure does not match the expected one.
Like for `BigDecimal`, which is represented as `String` instead of `Decimal128`, just because earlier versions of MongoDB Server did not have support for it.

[source,java]
----
public class Balance {

  @Field(targetType = STRING)
  private BigDecimal value;

  // ...
}
----

You may even consider your own, custom annotation.

[source,java]
----
@Target(ElementType.FIELD)
@Retention(RetentionPolicy.RUNTIME)
@Field(targetType = FieldType.STRING)
public @interface AsString { }

// ...

public class Balance {

  @AsString
  private BigDecimal value;

  // ...
}
----
====

=== Special Field Names

Generally speaking MongoDB uses the dot (`.`) character as a path separator for nested documents or arrays.
This means that in a query (or update statement) a key like `a.b.c` targets an object structure as outlined below:

[source,json]
----
{
    'a' : {
        'b' : {
            'c' : …
        }
    }
}
----

Therefore, up until MongoDB 5.0 field names must not contain dots (`.`). +
Using a `MappingMongoConverter#setMapKeyDotReplacement` allowed circumvent some of the limitations when storing `Map` structures by substituting dots on write with another character.

[source,java]
----
converter.setMapKeyDotReplacement("-");
// ...

source.map = Map.of("key.with.dot", "value")
converter.write(source,...) // -> map : { 'key-with-dot', 'value' }
----

With the release of MongoDB 5.0 this restriction on `Document` field names containing special characters was lifted.
We highly recommend reading more about limitations on using dots in field names in the https://www.mongodb.com/docs/manual/core/dot-dollar-considerations/[MongoDB Reference]. +
To allow dots in `Map` structures please set `preserveMapKeys` on the `MappingMongoConverter`.

Using `@Field` allows customizing the field name to consider dots in two ways.

. `@Field(name = "a.b")`: The name is considered to be a path.
Operations expect a structure of nested objects such as `{ a : { b : … } }`.
. `@Field(name = "a.b", fieldNameType = KEY)`: The names is considered a name as-is.
Operations expect a field with the given value as `{ 'a.b' : ….. }`

[WARNING]
====
Due to the special nature of the dot character in both MongoDB query and update statements field names containing dots cannot be targeted directly and therefore are excluded from being used in derived query methods.
Consider the following `Item` having a `categoryId` property that is mapped to the field named `cat.id`.

[source,java]
----
public class Item {

	@Field(name = "cat.id", fieldNameType = KEY)
	String categoryId;

	// ...
}
----

Its raw representation will look like

[source,json]
----
{
    'cat.id' : "5b28b5e7-52c2",
    ...
}
----

Since we cannot target the `cat.id` field directly (as this would be interpreted as a path) we need the help of the xref:mongodb/aggregation-framework.adoc#mongo.aggregation[Aggregation Framework].

.Query fields with a dot in its name
[source,java]
----
template.query(Item.class)
    // $expr : { $eq : [ { $getField : { input : '$$CURRENT', 'cat.id' }, '5b28b5e7-52c2' ] }
    .matching(expr(ComparisonOperators.valueOf(ObjectOperators.getValueOf("value")).equalToValue("5b28b5e7-52c2"))) <1>
    .all();
----

<1> The mapping layer takes care of translating the property name `value` into the actual field name.
It is absolutely valid to use the target field name here as well.

.Update fields with a dot in its name
[source,java]
----
template.update(Item.class)
    .matching(where("id").is("r2d2"))
    // $replaceWith: { $setField : { input: '$$CURRENT', field : 'cat.id', value : 'af29-f87f4e933f97' } }
    .apply(AggregationUpdate.newUpdate(ReplaceWithOperation.replaceWithValue(ObjectOperators.setValueTo("value", "af29-f87f4e933f97")))) <1>
    .first();
----

<1> The mapping layer takes care of translating the property name `value` into the actual field name.
It is absolutely valid to use the target field name here as well.

The above shows a simple example where the special field is present on the top document level.
Increased levels of nesting increase the complexity of the aggregation expression required to interact with the field.
====

[[mapping-custom-object-construction]]
=== Customized Object Construction

The mapping subsystem allows the customization of the object construction by annotating a constructor with the `@PersistenceCreator` annotation.
The values to be used for the constructor parameters are resolved in the following way:

* If a parameter is annotated with the `@Value` annotation, the given expression is evaluated and the result is used as the parameter value.
* If the Java type has a property whose name matches the given field of the input document, then it's property information is used to select the appropriate constructor parameter to pass the input field value to.
This works only if the parameter name information is present in the java `.class` files which can be achieved by compiling the source with debug information or using the new `-parameters` command-line switch for javac in Java 8.
* Otherwise, a `MappingException` will be thrown indicating that the given constructor parameter could not be bound.

[source,java]
----
class OrderItem {

  private @Id String id;
  private int quantity;
  private double unitPrice;

  OrderItem(String id, @Value("#root.qty ?: 0") int quantity, double unitPrice) {
    this.id = id;
    this.quantity = quantity;
    this.unitPrice = unitPrice;
  }

  // getters/setters ommitted
}

Document input = new Document("id", "4711");
input.put("unitPrice", 2.5);
input.put("qty",5);
OrderItem item = converter.read(OrderItem.class, input);
----

NOTE: The SpEL expression in the `@Value` annotation of the `quantity` parameter falls back to the value `0` if the given property path cannot be resolved.

Additional examples for using the `@PersistenceCreator` annotation can be found in the https://github.com/spring-projects/spring-data-mongodb/blob/master/spring-data-mongodb/src/test/java/org/springframework/data/mongodb/core/convert/MappingMongoConverterUnitTests.java[MappingMongoConverterUnitTests] test suite.

[[mapping-usage-events]]
=== Mapping Framework Events

Events are fired throughout the lifecycle of the mapping process.
This is described in the xref:mongodb/lifecycle-events.adoc[Lifecycle Events] section.

Declaring these beans in your Spring ApplicationContext causes them to be invoked whenever the event is dispatched.
