[infinispan-dev] Further dist.exec and M/R API improvements
Hey guys,
As some of you might know we have received additional requirements from
community and internally to add a few things to dist.executors and
map/reduce API. On distributed executors front we need to enable
distributed executors to store results into cache directly rather than
returning them to invoker [1]. As soon as we introduce this API we also
need a asyc. mechanism to allow notifications of subtask
completion/failure. I was thinking we add a concept of
DistributedTaskExecutionListener which can be specified in
DistributedTaskBuilder:
DistributedTaskBuilder<T>
executionListener(DistributedTaskExecutionListener<K, T> listener);
We needed DistributedTaskExecutionListener anyway. All distributed tasks
might use some feedback about task progress, completion/failure and on.
My proposal is roughly:
public interface DistributedTaskExecutionListener<K, T> {
void subtaskSent(Address node, Set<K> inputKeys);
void subtaskFailed(Address node, Set<K> inputKeys, Exception e);
void subtaskSucceded(Address node, Set<K> inputKeys, T result);
void allSubtasksCompleted();
}
So much for that. If tasks do not use input keys these parameters would
be emply sets. Now for [1] we need to add additional methods to
DistributedExecutorService. We can not specify result cache in
DistributedTaskBuilder as we are still bound to only submit methods in
DistributedExecutorService that return futures and we don't want that.
We need two new void methods:
<T, K> void submitEverywhere(DistributedTask<T> task,
Cache<DistExecResultKey<K>, T> result);
<T, K > void submitEverywhere(DistributedTask<T> task,
Cache<DistExecResultKey<K>, T> result, K... input);
Now, why bother with DistExecResultKey? Well we have tasks that use
input keys and tasks that don't. So results cache could only be keyed by
either keys or execution address, or combination of those two.
Therefore, DistExecResultKey could be something like:
public interface DistExecResultKey<K> {
Address getExecutionAddress();
K getKey();
}
If you have a better idea how to address this aspect let us know. So
much for distributed executors.
For map/reduce we also have to enable storing of map reduce task results
into cache [2] and allow users to specify custom cache for intermediate
results[3]. Part of task [2] is to allow notification about map/reduce
task progress and completion. Just as in dist.executor I would add
MapReduceTaskExecutionListener interface:
public interface MapReduceTaskExecutionListener {
void mapTaskInitialized(Address executionAddress);
void mapTaskSucceeded(Address executionAddress);
void mapTaskFailed(Address executionTarget, Exception cause);
void mapPhaseCompleted();
void reduceTaskInitialized(Address executionAddress);
void reduceTaskSucceeded(Address executionAddress);
void reduceTaskFailed(Address address, Exception cause);
void reducePhaseCompleted();
}
while MapReduceTask would have an additional method:
public void execute(Cache<KOut, VOut> resultsCache);
MapReduceTaskExecutionListener could be specified using fluent
MapReduceTask API just as intermediate cache would be:
public MapReduceTask<KIn, VIn, KOut, VOut>
usingIntermediateCache(Cache<KOut, List<VOut>> tmpCache);
thus addressing issue [3].
Let me know what you think,
Vladimir
[1] https://issues.jboss.org/browse/ISPN-4030
[2] https://issues.jboss.org/browse/ISPN-4002
[3] https://issues.jboss.org/browse/ISPN-4021