Skip to content

Latest commit

 

History

History
717 lines (554 loc) · 27.9 KB

File metadata and controls

717 lines (554 loc) · 27.9 KB

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.

{commons}@data-commons::page$object-mapping.adoc

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.

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.

Table 1. 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.

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 Custom Conversions - Overriding Default Mapping for further details.

Built in Type conversions:
Table 2. 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 (Legacy UUID)

native

{"uuid" : { "$binary" : "MEaf1CFQ6lSphaa3b9AtlA==", "$type" : "03" }}

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

converter
String

{"value" : "741" }

BigDecimal

converter
String

{"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
(Joda, JSR310-BackPort)

converter

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

LocalDate
(Joda, Java 8, JSR310-BackPort)

converter / native (Java8)[1]

{"date" : ISODate("2019-11-12T00:00:00.000Z")}

LocalDateTime, LocalTime
(Joda, Java 8, JSR310-BackPort)

converter / native (Java8)[2]

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

DateTime (Joda)

converter

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

ZoneId (Java 8, JSR310-BackPort)

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 ] ] ] }}

Note
Collection Handling

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

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:

Java
@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
<?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 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 Reference Documentation.

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 1. Example domain object
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 Index Creation).

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.

  • @PersistenceConstructor: Marks a given constructor - 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
@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;
  }

  @PersistenceConstructor
  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.

public class Balance {

  @Field(targetType = DECIMAL128)
  private BigDecimal value;

  // ...
}

You may even consider your own, custom annotation.

@Target(ElementType.FIELD)
@Retention(RetentionPolicy.RUNTIME)
@Field(targetType = FieldType.DECIMAL128)
public @interface Decimal128 { }

// ...

public class Balance {

  @Decimal128
  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:

{
    '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.

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 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.

  1. @Field(name = "a.b"): The name is considered to be a path. Operations expect a structure of nested objects such as { a : { b : … } }.

  2. @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.

public class Item {

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

	// ...
}

Its raw representation will look like

{
    '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 Aggregation Framework.

Query fields with a dot in its name
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
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.

Customized Object Construction

The mapping subsystem allows the customization of the object construction by annotating a constructor with the @PersistenceConstructor 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.

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 @PersistenceConstructor annotation can be found in the MappingMongoConverterUnitTests test suite.

Mapping Framework Events

Events are fired throughout the lifecycle of the mapping process. This is described in the Lifecycle Events section.

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


1. Uses UTC zone offset. Configure via MongoConverterConfigurationAdapter
2. Uses UTC zone offset. Configure via MongoConverterConfigurationAdapter