Stream records from DataBase using Akka Stream - akka

Question

I have a system using Akka which currently handles incoming streaming data over message queues. When a record arrives then it is processed, mq is acked and record is passed on for further handling within the system.
Now I would like to add support for using DBs as input.
What would be a way to go for the input source to be able to handle DB (should stream in > 100M records at the pace that the receiver can handle - so I presume reactive/akka-streams?)?

Answer 1

Slick Library
Slick streaming is how this is usually done.
Extending the slick documentation a bit to include akka streams:
//SELECT Name from Coffees
val q = for (c <- coffees) yield c.name
val action = q.result
type Name = String
val databasePublisher : DatabasePublisher[Name] = db stream action
import akka.stream.scaladsl.Source
val akkaSourceFromSlick : Source[Name, _] = Source fromPublisher databasePublisher
Now akkaSourceFromSlick is like any other akka stream Source.
"Old School" ResultSet
It is also possible to use a plain ResultSet, without slick, as the "engine" for an akka stream. We will utilize the fact that a stream Source can be instantiated from an Iterator.
First create the ResultSet using standard jdbc techniques:
import java.sql._
val resultSetGenerator : () => Try[ResultSet] = Try {
val statement : Statement = ???
statement executeQuery "SELECT Name from Coffees"
}
Of course all ResultSet instances have to move the cursor before the first row:
val adjustResultSetBeforeFirst : (ResultSet) => Try[ResultSet] =
(resultSet) => Try(resultSet.beforeFirst()) map (_ => resultSet)
Once we start iterating through rows we'll have to pull the value from the correct column:
val getNameFromResultSet : ResultSet => Name = _ getString "Name"
And now we can implement the Iterator Interface to create a Iterator[Name] from a ResultSet:
val convertResultSetToNameIterator : ResultSet => Iterator[Name] =
(resultSet) => new Iterator[Try[Name]] {
override def hasNext : Boolean = resultSet.next
override def next() : Try[Name] = Try(getNameFromResultSet(resultSet))
} flatMap (_.toOption)
And finally, glue all the pieces together to create the function we'll need to pass to Source.fromIterator:
val resultSetGenToNameIterator : (() => Try[ResultSet]) => () => Iterator[Name] =
(_ : () => Try[ResultSet])
.andThen(_ flatMap adjustResultSetBeforeFirst)
.andThen(_ map convertResultSetToNameIterator)
.andThen(_ getOrElse Iterator.empty)
This Iterator can now feed a Source:
val akkaSourceFromResultSet : Source[Name, _] =
Source fromIterator resultSetGenToNameIterator(resultSetGenerator)
This implementation is reactive all the way down to the database. Since the ResultSet pre-fetches a limited number of rows at a time, data will only come off the hard drive through the database as the stream Sink signals demand.

Answer 2

I find Alpakka documentation to be excellent and a much easier way to work with reactive-streams than than the Java Publisher interface.
The Alpakka project is an open source initiative to implement stream-aware, reactive, integration pipelines for Java and Scala. It is built on top of Akka Streams, and has been designed from the ground up to understand streaming natively and provide a DSL for reactive and stream-oriented programming, with built-in support for backpressure
Document for Alpakka with Slick: https://doc.akka.io/docs/alpakka/current/slick.html
Alpakka Github: https://github.com/akka/alpakka