Currently I have a process that is set up as follows:
1. Pulse every minute and see if a domain object should be changed,
1. If not then do nothing.
2. If there is an object that needs to be processed, find all child
objects remaining to process.
1. If this is empty, the domain object goes to the next state.
2. If there are child objects to process determine if any of them
are already in a Distributed Memcached map we will call "TaskMap". For
each
obect not in TaskMap figure out what needs to be done, generate a task
message and put them in TaskMap keyed by the id of the domain object
to
process.This could result in 1million entries getting added to
TaskMap. Its
a heavyweight process but happens infrequently. It is also not
avoidable.
2. Pulse every minute on another task.
1. If there are any objects in the task map that are distributed to
this node then process them one at a time until the map is empty of all
local entries.
I would like to convert this to Akka Actor based processing for a number of
reasons. The problem that I cant figure out how to handle is to know that
the tasks are already in the inbox. So if in step 1.2.2 I decide there are
200,000 objects that need to be processed, i dont want to resubmit them to
be processed if they are already queued up in the actor inbox. Although the
task protects itself against double execution, it would just hammer the
system with unnecessary load. Furthermore, its possible that a task might
get lost due to node failure or some other unforseen reason so if 5k of
those 200k tasks are missing, I want to add them to the map. Right now all
I have to do is check the key set of the map and remove the ids already in
the map. With an inbox I have no idea how this could be accomplished. The
closest thought I had was to still put them in the map and have the actor
pull them out of the map. However, if I could introspect the inbox then I
wouldnt have to duplicate the data.
Any ideas?
Thanks.
-- Robert
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