Why you should replace your return List with a Consumer parameter

It is common practice to have your Service layer, Dao layer etc… return a List or Collection as a result of the call.

List < T > getAllMyTs ()

but with the introduction of lambdas in java 8, the use of callback has become far cheaper and user a Consumer as a parameter

produceAllMyTs ( Consumer < T > consumer )

could make your code less couple, easier to maintain and more scalable.

A tale of 2 services

In our Classic Service

public class SClassicService { public List < String > getStrings () { // ... } }

we return a List that we get from our DAO. We make it the responsibility of the service to choose an appropriate data structure to store the result, ArrayList or LinkedList?, ImmutableList?

In our Producer Service

public class SProducerService { public void produceStrings ( Consumer <? super String > consumer ) { // ... } }

we use the Consumer interface as a way to communicate each element. It’s the responsibility of the caller to decide what to do with it. If we don’t need to have a List we won’t need to create one - when do we need it? some framework push you towards that but there is always a way to do without -.

For small amount of data it may not matter, but if you fetching a few 100 000s and don’t need to store them in a list it can make a big difference.

Let’s imagine a simple class that uses the service and output it to the console.

in Classic world

service . getStrings (). forEach ( System . out :: println );

in the Producer

service . produceStrings ( System . out :: println );

In the classic world we won’t start printing the data until they have all been put in the list.

So if we have use DSlowDAO nothing happens for a while and then all of a sudden we display all the data.

If the Consumer was slow, we would fetch all the data and keep them all in memory until the last is consumed.

In the producer world only the one currently being processed is alive. If the producer is slow we will output the value as soon as they arrive. If the consumer is slow we will not produce the next value until the consumer is ready to consume it. Those are great properties to have in your system.

A tale of 2 functional interfaces

The Consumer approach is also easier to compose.

When you use a Supplier

@FunctionalInterface public interface ListSupplier < T > { List < T > get (); default ListSupplier < T > compose ( ListSupplier <? extends T > composeWith ) { return () -> { List < T > composedList = new ArrayList <>( get ()); composedList . addAll ( composeWith . get ()); return composedList ; }; } }

you will need to create 3 Lists.

But using a producer

@FunctionalInterface public interface Producer < T > { void produce ( Consumer <? super T > consumer ); default Producer < T > compose ( Producer <? extends T > composeWith ) { return ( consumer ) -> { this . produce ( consumer ); composeWith . produce ( consumer ); }; } }

you just need to call on the first producer then the second. no more garbage created because it is not the responsibility of the producer to create the data structure to store the objects.

What if the consumer needs a list?

You can just use the List as a consumer

List < String > list = new ArrayList <>; service . produceStrings ( list: add );

you could also make the producer return the consumer with the actual type using the following generic signature

public < C extends Consumer < String >> produceString ( C consumer ) { ... return consumer ; }

then create generic ToListConsumer

class ToListConsumer < T > implements Consumer < T > { public static < T > ToListConsumer < T > toList () { return new ToListConsumer < T >(); } List < T > list = new ArrayList <>(); void accept ( T t ) { list . add ( t ); } List < T > get () { return list ; } }

you can now chain the consumer call with the list fetching.

List < String > list = service . produceStrings ( ToListConsumer . toList ()). get ();

My DAO layer return a List?

There is still some benefits if you can’t remove the List creation. The consumer is called inside the transaction, no need for the dreadful open session in view filter.

Unfortunately JPA does not seem to support ScrollablResults but Hibernate does so if you use that implementation you can change your code to fetch only a few items at a time.

If you use spring jdbc then just use the RowCallBackHandler, map the object and callback the consumer.

template . query ( sql , rs -> consumer . apply ( rowMapper . map ( rs )));

jOOQ and SimpleFlatMapper already support a consumer callback.

// jooq jooqQuery . fetchInto ( System . out :: println ); jooqQuery . fetchStream (). forEach ( System . out :: println ); // sfm mapper . forEach ( resultSet , System . out :: println ); mapper . stream ( resultSet ). forEach ( System . out :: println );

Using that pattern even when it return a single Entry?

The consumer can be use with 0 to n number of elements. It’s a good alternative to returning Optional .

service . getOptionalValue (). ifPresent ( consumer );

becomes

service . produceOptionalValue ( consumer );

Conclusion

Using a consumer allow you to build more flexible and more reactive interface without changing your design too much. It’s very straightforward and can help reduce the coupling of your application. There is nothing new there but java8 with the addition of Lambdas made it a lot cheaper on the dev side. It’s time to get back to message passing.