Streaming Live Updates From a Reactive Spring Data Repository

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Streaming Live Updates From a Reactive Spring Data Repository

Learn how to stream live updates from a reactive Spring Data repo.

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Here's an example implementation of streaming updates from a database to other components

This post details a naive implementation of streaming updates from a database to any other components that are interested in that data. More precisely, we look at how to alter a Spring Data R2DBC repository to emit events to relevant subscribers.

You may also like: Reactive Streams With Spring Data and MongoDB

A little bit of background knowledge of R2DBC and Spring will be helpful for this post. My previous writings: Asynchronous RDBMS access with Spring Data R2DBC and Spring Data R2DBC for Microsoft SQL Server — these should help in that regard.

As I mentioned, this will be a naive implementation. Therefore, the code will not be anything fancy.

To do this, I hijacked a SimpleR2dbcRepository to create a repository implementation that emits an event every time a new record is persisted. New events are added to a DirectProcessor and sent to any Publishers  subscribed to it. This looks like:

class PersonRepository(
  entity: RelationalEntityInformation<Person, Int>,
  databaseClient: DatabaseClient,
  converter: R2dbcConverter,
  accessStrategy: ReactiveDataAccessStrategy
) : SimpleR2dbcRepository<Person, Int>(entity, databaseClient, converter, accessStrategy) {

  private val source: DirectProcessor<Person> = DirectProcessor.create<Person>()
  val events: Flux<Person> = source

  override fun <S : Person> save(objectToSave: S): Mono<S> {
    return super.save(objectToSave).doOnNext(source::onNext)

The only function from SimpleR2dbcRepository  that needs to be overridden is save  (saveAll delegates to save ). doOnNext  is added to the original save call, which pushes a new event to the source  (the DirectorProcessor ) by calling onNext .

The source  is cast to a Flux to prevent classes from outside of the repository from adding new events. Technically they can still add events, but they will need to cast it themselves.

As you might have noticed, the repository is taking a load of parameters and passing them into SimpleR2dbcRepository. An instance of the repository needs to be created manually as some of its dependencies cannot be injected in automatically:

class RepositoryConfiguration {

  fun personRepository(
    databaseClient: DatabaseClient,
    dataAccessStrategy: ReactiveDataAccessStrategy
  ): PersonRepository {
    val entity: RelationalPersistentEntity<Person> = dataAccessStrategy
      .getRequiredPersistentEntity(Person::class.java) as RelationalPersistentEntity<Person>
    val relationEntityInformation: MappingRelationalEntityInformation<Person, Int> =
      MappingRelationalEntityInformation(entity, Int::class.java)
    return PersonRepository(

At this point, everything is set up and ready to use. Below is an example of it working:

  .doOnComplete { log.info("Events flux has closed") }
  .subscribe { log.info("From events stream - $it") }
// insert people records over time
  .delayElements(Duration.of(1, SECONDS))
  .concatMap { personRepository.save(it) }

Which outputs:

29-08-2019 09:08:27.674 [reactor-tcp-nio-1]  From events stream - Person(id=481, name=Spiderman, age=18)
29-08-2019 09:08:28.550 [reactor-tcp-nio-2]  From events stream - Person(id=482, name=Ironman, age=48)
29-08-2019 09:08:29.555 [reactor-tcp-nio-3]  From events stream - Person(id=483, name=Thor, age=1000)
29-08-2019 09:08:30.561 [reactor-tcp-nio-4]  From events stream - Person(id=484, name=Hulk, age=49)
29-08-2019 09:08:31.568 [reactor-tcp-nio-5]  From events stream - Person(id=485, name=Antman, age=49)
29-08-2019 09:08:32.571 [reactor-tcp-nio-6]  From events stream - Person(id=486, name=Blackwidow, age=34)
29-08-2019 09:08:33.576 [reactor-tcp-nio-7]  From events stream - Person(id=487, name=Starlord, age=38)
29-08-2019 09:08:34.581 [reactor-tcp-nio-8]  From events stream - Person(id=488, name=Captain America, age=100)
29-08-2019 09:08:35.585 [reactor-tcp-nio-9]  From events stream - Person(id=489, name=Warmachine, age=50)
29-08-2019 09:08:36.589 [reactor-tcp-nio-10] From events stream - Person(id=490, name=Wasp, age=26)
29-08-2019 09:08:37.596 [reactor-tcp-nio-11] From events stream - Person(id=491, name=Winter Soldier, age=101)
29-08-2019 09:08:38.597 [reactor-tcp-nio-12] From events stream - Person(id=492, name=Black Panther, age=42)
29-08-2019 09:08:39.604 [reactor-tcp-nio-1]  From events stream - Person(id=493, name=Doctor Strange, age=42)
29-08-2019 09:08:40.609 [reactor-tcp-nio-2]  From events stream - Person(id=494, name=Gamora, age=29)
29-08-2019 09:08:41.611 [reactor-tcp-nio-3]  From events stream - Person(id=495, name=Groot, age=4)
29-08-2019 09:08:42.618 [reactor-tcp-nio-4]  From events stream - Person(id=496, name=Hawkeye, age=47)
29-08-2019 09:08:43.620 [reactor-tcp-nio-5]  From events stream - Person(id=497, name=Pepper Potts, age=44)
29-08-2019 09:08:44.627 [reactor-tcp-nio-6]  From events stream - Person(id=498, name=Captain Marvel, age=59)
29-08-2019 09:08:45.631 [reactor-tcp-nio-7]  From events stream - Person(id=499, name=Rocket Raccoon, age=30)
29-08-2019 09:08:46.637 [reactor-tcp-nio-8]  From events stream - Person(id=500, name=Drax, age=49)
29-08-2019 09:08:47.639 [reactor-tcp-nio-9]  From events stream - Person(id=501, name=Nebula, age=30)

A record is saved every second which matches up to the events coming out of the repository.

Note, that the doOnComplete  event is never triggered. The source never closes and, therefore, never emits a completion event to any of its subscribers.

That’s all there is to it, at least for this basic implementation. I am sure there is a lot more that could be done, but I would need to figure out how to do that first… To summarise, with a few additions, you can stream data inserted into your database to components that are interested in the records being added.

If you enjoyed this post, or found it helpful (or both), then please feel free to follow me on Twitter at @LankyDanDev and remember to share with anyone else who might find this useful!

Further Reading

Reactive Streams With Spring Data and MongoDB

Introduction to Reactive APIs With Postgres, R2DBC, Spring Data JDBC, and Spring WebFlux

Reactive Streaming With Spring WebFlux

components, data, database, java, r2dbc, reactive, reactive programming, spring, spring data

Published at DZone with permission of Dan Newton , DZone MVB. See the original article here.

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