Remove duplicate JSON Schema section from reference documentation.
Closes: #3573 Original pull request: #3574.
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Christoph Strobl
committed by
Mark Paluch
Mark Paluch
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2ef9844219
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ffaa7cae6f
@@ -1904,8 +1904,6 @@ AggregationResults<TagCount> results = template.aggregate(aggregation, "tags", T
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WARNING: Indexes are only used if the collation used for the operation matches the index collation.
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include::./mongo-json-schema.adoc[leveloffset=+1]
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<<mongo.repositories>> support `Collations` via the `collation` attribute of the `@Query` annotation.
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.Collation support for Repositories
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@@ -1946,186 +1944,7 @@ as shown in (1) and (2), will be included when creating the index.
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TIP: The most specifc `Collation` outroules potentially defined others. Which means Method argument over query method annotation over doamin type annotation.
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====
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[[mongo.jsonSchema]]
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=== JSON Schema
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As of version 3.6, MongoDB supports collections that validate documents against a provided https://docs.mongodb.com/manual/core/schema-validation/#json-schema[JSON Schema].
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The schema itself and both validation action and level can be defined when creating the collection, as the following example shows:
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.Sample JSON schema
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====
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[source,json]
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----
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{
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"type": "object", <1>
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"required": [ "firstname", "lastname" ], <2>
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"properties": { <3>
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"firstname": { <4>
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"type": "string",
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"enum": [ "luke", "han" ]
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},
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"address": { <5>
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"type": "object",
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"properties": {
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"postCode": { "type": "string", "minLength": 4, "maxLength": 5 }
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}
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}
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}
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}
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----
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<1> JSON schema documents always describe a whole document from its root. A schema is a schema object itself that can contain
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embedded schema objects that describe properties and subdocuments.
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<2> `required` is a property that describes which properties are required in a document. It can be specified optionally, along with other
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schema constraints. See MongoDB's documentation on https://docs.mongodb.com/manual/reference/operator/query/jsonSchema/#available-keywords[available keywords].
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<3> `properties` is related to a schema object that describes an `object` type. It contains property-specific schema constraints.
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<4> `firstname` specifies constraints for the `firsname` field inside the document. Here, it is a string-based `properties` element declaring
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possible field values.
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<5> `address` is a subdocument defining a schema for values in its `postCode` field.
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====
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You can provide a schema either by specifying a schema document (that is, by using the `Document` API to parse or build a document object) or by building it with Spring Data's JSON schema utilities in `org.springframework.data.mongodb.core.schema`. `MongoJsonSchema` is the entry point for all JSON schema-related operations. The following example shows how use `MongoJsonSchema.builder()` to create a JSON schema:
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.Creating a JSON schema
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====
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[source,java]
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----
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MongoJsonSchema.builder() <1>
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.required("firstname", "lastname") <2>
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.properties(
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string("firstname").possibleValues("luke", "han"), <3>
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object("address")
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.properties(string("postCode").minLength(4).maxLength(5)))
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.build(); <4>
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----
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<1> Obtain a schema builder to configure the schema with a fluent API.
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<2> Configure required properties.
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<3> Configure the String-typed `firstname` field, allowing only `luke` and `han` values. Properties can be typed or untyped. Use a static import of `JsonSchemaProperty` to make the syntax slightly more compact and to get entry points such as `string(…)`.
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<4> Build the schema object. Use the schema to create either a collection or <<mongodb-template-query.criteria,query documents>>.
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====
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There are already some predefined and strongly typed schema objects (`JsonSchemaObject` and `JsonSchemaProperty`) available
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through static methods on the gateway interfaces.
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However, you may need to build custom property validation rules, which can be created through the builder API, as the following example shows:
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[source,java]
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----
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// "birthdate" : { "bsonType": "date" }
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JsonSchemaProperty.named("birthdate").ofType(Type.dateType());
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// "birthdate" : { "bsonType": "date", "description", "Must be a date" }
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JsonSchemaProperty.named("birthdate").with(JsonSchemaObject.of(Type.dateType()).description("Must be a date"));
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----
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The Schema builder also provides support for https://docs.mongodb.com/manual/core/security-client-side-encryption/[Client-Side Field Level Encryption]. Please refer to <<mongo.jsonSchema.encrypted-fields>> for more information,
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`CollectionOptions` provides the entry point to schema support for collections, as the following example shows:
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.Create collection with `$jsonSchema`
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====
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[source,java]
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----
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MongoJsonSchema schema = MongoJsonSchema.builder().required("firstname", "lastname").build();
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template.createCollection(Person.class, CollectionOptions.empty().schema(schema));
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----
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====
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You can use a schema to query any collection for documents that match a given structure defined by a JSON schema, as the following example shows:
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.Query for Documents matching a `$jsonSchema`
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====
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[source,java]
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----
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MongoJsonSchema schema = MongoJsonSchema.builder().required("firstname", "lastname").build();
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template.find(query(matchingDocumentStructure(schema)), Person.class);
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----
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====
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The following table shows the supported JSON schema types:
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[cols="3,1,6", options="header"]
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.Supported JSON schema types
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|===
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| Schema Type
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| Java Type
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| Schema Properties
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| `untyped`
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| -
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| `description`, generated `description`, `enum`, `allOf`, `anyOf`, `oneOf`, `not`
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| `object`
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| `Object`
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| `required`, `additionalProperties`, `properties`, `minProperties`, `maxProperties`, `patternProperties`
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| `array`
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| any array except `byte[]`
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| `uniqueItems`, `additionalItems`, `items`, `minItems`, `maxItems`
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| `string`
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| `String`
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| `minLength`, `maxLentgth`, `pattern`
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| `int`
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| `int`, `Integer`
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| `multipleOf`, `minimum`, `exclusiveMinimum`, `maximum`, `exclusiveMaximum`
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| `long`
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| `long`, `Long`
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| `multipleOf`, `minimum`, `exclusiveMinimum`, `maximum`, `exclusiveMaximum`
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| `double`
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| `float`, `Float`, `double`, `Double`
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| `multipleOf`, `minimum`, `exclusiveMinimum`, `maximum`, `exclusiveMaximum`
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| `decimal`
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| `BigDecimal`
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| `multipleOf`, `minimum`, `exclusiveMinimum`, `maximum`, `exclusiveMaximum`
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| `number`
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| `Number`
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| `multipleOf`, `minimum`, `exclusiveMinimum`, `maximum`, `exclusiveMaximum`
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| `binData`
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| `byte[]`
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| (none)
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| `boolean`
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| `boolean`, `Boolean`
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| (none)
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| `null`
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| `null`
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| (none)
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| `objectId`
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| `ObjectId`
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| (none)
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| `date`
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| `java.util.Date`
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| (none)
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| `timestamp`
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| `BsonTimestamp`
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| (none)
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| `regex`
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| `java.util.regex.Pattern`
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| (none)
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|===
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NOTE: `untyped` is a generic type that is inherited by all typed schema types. It provides all `untyped` schema properties to typed schema types.
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For more information, see https://docs.mongodb.com/manual/reference/operator/query/jsonSchema/#op._S_jsonSchema[$jsonSchema].
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include::./mongo-json-schema.adoc[leveloffset=+1]
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[[mongo.query.fluent-template-api]]
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=== Fluent Template API
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