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Fix small typos in documentation.
Signed-off-by: andrelmv <andrelmv@gmail.com>
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src/main/antora/modules/ROOT/pages/mongodb/mapping/mapping-index-management.adoc

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= Index Creation
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Spring Data MongoDB can automatically create indexes for entity types annotated with `@Document`.
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Index creation must be explicitly enabled since version 3.0 to prevent undesired effects with collection lifecyle and performance impact.
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Index creation must be explicitly enabled since version 3.0 to prevent undesired effects with collection lifecycle and performance impact.
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Indexes are automatically created for the initial entity set on application startup and when accessing an entity type for the first time while the application runs.
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We generally recommend explicit index creation for application-based control of indexes as Spring Data cannot automatically create indexes for collections that were recreated while the application was running.
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Hashed indexes can be created next to other index definitions like shown below, in that case both indices are created:
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.Example Hashed Index Usage togehter with simple index
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.Example Hashed Index Usage together with simple index
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====
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[source,java]
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----

src/main/antora/modules/ROOT/pages/mongodb/mapping/mapping-schema.adoc

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[[mongo.jsonSchema.generated]]
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== Generating a Schema
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Setting up a schema can be a time consuming task and we encourage everyone who decides to do so, to really take the time it takes.
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Setting up a schema can be a time-consuming task, and we encourage everyone who decides to do so, to really take the time it takes.
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It's important, schema changes can be hard.
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However, there might be times when one does not want to balked with it, and that is where `JsonSchemaCreator` comes into play.
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this.age = age;
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}
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// gettter / setter omitted
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// getter / setter omitted
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}
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MongoJsonSchema schema = MongoJsonSchemaCreator.create(mongoOperations.getConverter())
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}
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}
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----
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<1> Simple object properties are consideres regular properties.
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<1> Simple object properties are considers regular properties.
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<2> Primitive types are considered required properties
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<3> Enums are restricted to possible values.
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<4> Object type properties are inspected and represented as nested documents.
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unless there is more specific information available via the `@MongoId` annotation.
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[cols="2,2,6", options="header"]
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.Sepcial Schema Generation rules
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.Special Schema Generation rules
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|===
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| Java
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| Schema Type

src/main/antora/modules/ROOT/pages/mongodb/mapping/mapping.adoc

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this.unitPrice = unitPrice;
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}
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// getters/setters ommitted
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// getters/setters omitted
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}
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Document input = new Document("id", "4711");

src/main/antora/modules/ROOT/pages/mongodb/mapping/property-converters.adoc

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Make sure that neither the class nor the accessors are `final` as otherwise this approach doesn't work.
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====
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WARNING: Dot notation (such as `registerConverter(Person.class, "address.street", …)`) for nagivating across properties into subdocuments is *not* supported when registering converters.
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WARNING: Dot notation (such as `registerConverter(Person.class, "address.street", …)`) for navigating across properties into subdocuments is *not* supported when registering converters.
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TIP: `MongoValueConverter` offers a pre-typed `PropertyValueConverter` interface that uses `MongoConversionContext`.
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src/main/antora/modules/ROOT/pages/mongodb/mongo-encryption.adoc

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MongoDB Collection Info::
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====
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[source,json,indent=0,subs="verbatim,quotes",role="thrid"]
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[source,json,indent=0,subs="verbatim,quotes",role="third"]
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----
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{
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name: 'patient',

src/main/antora/modules/ROOT/pages/mongodb/mongo-mapreduce.adoc

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}
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----
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The follwing reduce function sums up the occurrence of each letter across all the documents:
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The following reduce function sums up the occurrence of each letter across all the documents:
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}
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The preceding exmaple produces the following output:
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The preceding example produces the following output:
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[source]
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src/main/antora/modules/ROOT/pages/mongodb/repositories/query-methods.adoc

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NOTE: In case you enabled the automatic index creation for repository finder methods a potential static collation definition,
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as shown in (1) and (2), will be included when creating the index.
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TIP: The most specifc `Collation` outrules potentially defined others. Which means Method argument over query method annotation over domain type annotation.
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TIP: The most specific `Collation` outrules potentially defined others. Which means Method argument over query method annotation over domain type annotation.
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====
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To streamline usage of collation attributes throughout the codebase it is also possible to use the `@Collation` annotation, which serves as a meta annotation for the ones mentioned above.

src/main/antora/modules/ROOT/pages/mongodb/tailable-cursors.adoc

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container.stop(); <7>
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----
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<1> Starting the container intializes the resources and starts `Task` instances for already registered `SubscriptionRequest` instances. Requests added after startup are ran immediately.
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<1> Starting the container initializes the resources and starts `Task` instances for already registered `SubscriptionRequest` instances. Requests added after startup are ran immediately.
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<2> Define the listener called when a `Message` is received. The `Message#getBody()` is converted to the requested domain type. Use `Document` to receive raw results without conversion.
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<3> Set the collection to listen to.
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<4> Provide an optional filter for documents to receive.

src/main/antora/modules/ROOT/pages/mongodb/template-api.adoc

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====
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A motivation to customize exception can be MongoDB's behavior during transactions where some failures (such as write conflicts) can become transient and where a retry could lead to a successful operation.
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In such a case, you could wrap exceptions with a specific MongoDB label and apply a different exception translation stragegy.
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In such a case, you could wrap exceptions with a specific MongoDB label and apply a different exception translation strategy.
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[[mongo-template.type-mapping]]
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== Domain Type Mapping

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