David, I have 3 comments:
1. The "ahead window" phrase you discussed above is really behind window. With Apex, the windows which are ahead are the windows with smaller window Id. smaller window ids are followed by bigger window ids. 2. ITERATION_WINDOW_COUNT sounds like a misnomer. IMO, It should be something akin to DELAY_BY_WINDOW_COUNT as you are delaying the events by those many windows. You are not iterating over them as many times. It also resonates with PortContext.SLIDE_BY_WINDOW_COUNT 3. Deduper has similar requirement where large amount of data (potentially even larger) needs to be partitioned. You can borrow the idea/code from there. And perhaps abstract the code to be reusable. HTH. -- Chetan On Wed, Sep 16, 2015 at 1:44 PM, David Yan <da...@datatorrent.com> wrote: > Hi all, > > One current disadvantage of Apex is the inability to do iterations and > machine learning algorithms because we don't allow loops in the application > DAG (hence the name DAG). I am proposing that we allow loops in the DAG if > the loop advances the window ID by a configured amount. A JIRA ticket has > been created: > > https://malhar.atlassian.net/browse/APEX-60 > > I have started this work in my fork at > https://github.com/davidyan74/incubator-apex-core/tree/APEX-60. > > The current progress is that a simple test case works. Major work still > needs to be done with respect to recovery and partitioning. > > The value ITERATION_WINDOW_COUNT is an attribute to an input port of an > operator. If the value of the attribute is greater than or equal to 1, any > tuples sent to the input port are treated to be ITERATION_WINDOW_COUNT > windows ahead of what they are. > > For recovery, we will need to checkpoint all the tuples between ports with > the to replay the looped tuples. During the recovery, if the operator has > an input port, with ITERATION_WINDOW_COUNT=2, is recovering from checkpoint > window 14, the tuples for that input port from window 13 and window 14 need > to be replayed to be treated as window 15 and window 16 respectively (13+2 > and 14+2). > > In other words, we need to store all the tuples from window with ID > committedWindowId minus ITERATION_WINDOW_COUNT for recovery and purge the > tuples earlier than that window. > We can optimize this by only storing the tuples for ITERATION_WINDOW_COUNT > windows prior to any checkpoint. > > For that, we need a storage mechanism for the tuples. Chandni already has > something that fits this usage case in Apex Malhar. The class is > IdempotentStorageManager. In order for this to be used in Apex core, we > need to deprecate the class in Apex Malhar and move it to Apex Core. > > A JIRA ticket has been created for this particular work: > > https://malhar.atlassian.net/browse/APEX-128 > > Some of the above has been discussed among Thomas, Chetan, Chandni, and > myself. > > For partitioning, we have not started any discussion or brainstorming. We > appreciate any feedback on this and any other aspect related to supporting > iterations in general. > > Thanks! > > David >
