RxJava: From Future to Observable
I first came across Reactive Extensions about 4 years ago on Matthew Podwysocki’s blog but then haven’t heard much about it until I saw Matthew give a talk at Code Mesh a few weeks ago.
It seems to have grown in popularity recently and I noticed that’s there’s now a Java version called RxJava written by Netflix.
I thought I’d give it a try by changing some code I wrote while exploring cypher’s MERGE function to expose an Observable instead of Futures.
To recap, we have 50 threads and we do 100 iterations where we create random (user, event) pairs. We create a maximum of 10 users and 50 events and the goal is to concurrently send requests for the same pairs.
In the example of my other post I was throwing away the result of each query whereas here I returned the result back so I had something to subscribe to.
The outline of the code looks like this:
public class MergeTimeRx
{
public static void main( final String[] args ) throws InterruptedException, IOException
{
String pathToDb = "/tmp/foo";
FileUtils.deleteRecursively( new File( pathToDb ) );
GraphDatabaseService db = new GraphDatabaseFactory().newEmbeddedDatabase( pathToDb );
final ExecutionEngine engine = new ExecutionEngine( db );
int numberOfThreads = 50;
int numberOfUsers = 10;
int numberOfEvents = 50;
int iterations = 100;
Observable<ExecutionResult> events = processEvents( engine, numberOfUsers, numberOfEvents, numberOfThreads, iterations );
events.subscribe( new Action1<ExecutionResult>()
{
@Override
public void call( ExecutionResult result )
{
for ( Map<String, Object> row : result )
{
}
}
} );
....
}
}The nice thing about using RxJava is that there’s no mention of how we got our collection of ExecutionResults, it’s not important. We just have a stream of them and by calling the subscribe function on the Observable we’ll be informed whenever another one is made available.
Most of the examples I found show how to generate events from a single thread but I wanted to use a thread pool so that I could fire off lots of requests at the same time. The processEvents method ended up looking like this:
private static Observable<ExecutionResult> processEvents( final ExecutionEngine engine, final int numberOfUsers, final int numberOfEvents, final int numberOfThreads, final int iterations )
{
final Random random = new Random();
final List<Integer> userIds = generateIds( numberOfUsers );
final List<Integer> eventIds = generateIds( numberOfEvents );
return Observable.create( new Observable.OnSubscribeFunc<ExecutionResult>()
{
@Override
public Subscription onSubscribe( final Observer<? super ExecutionResult> observer )
{
final ExecutorService executor = Executors.newFixedThreadPool( numberOfThreads );
List<Future<ExecutionResult>> jobs = new ArrayList<>();
for ( int i = 0; i < iterations; i++ )
{
Future<ExecutionResult> job = executor.submit( new Callable<ExecutionResult>()
{
@Override
public ExecutionResult call()
{
Integer userId = userIds.get( random.nextInt( numberOfUsers ) );
Integer eventId = eventIds.get( random.nextInt( numberOfEvents ) );
return engine.execute(
"MERGE (u:User {id: {userId}})\n" +
"MERGE (e:Event {id: {eventId}})\n" +
"MERGE (u)-[:HAS_EVENT]->(e)\n" +
"RETURN u, e",
MapUtil.map( "userId", userId, "eventId", eventId ) );
}
} );
jobs.add( job );
}
for ( Future<ExecutionResult> future : jobs )
{
try
{
observer.onNext( future.get() );
}
catch ( InterruptedException | ExecutionException ignored )
{
}
}
observer.onCompleted();
executor.shutdown();
return Subscriptions.empty();
}
} );
}I’m not sure if that’s the correct way of using Observables so please let me know in the comments if I’ve got it wrong.
I wasn’t sure what the proper way of handling errors was. I initially had a call to observer#onError in the catch block but that means that no further events are produced which wasn’t what I wanted.
The code is available as a gist if you want to play around with it. I added the following dependency to get the RxJava library: ~xml
About the author
I'm currently working on short form content at ClickHouse. I publish short 5 minute videos showing how to solve data problems on YouTube @LearnDataWithMark. I previously worked on graph analytics at Neo4j, where I also co-authored the O'Reilly Graph Algorithms Book with Amy Hodler.