+1 for 2nd approach. I have 2 reasons - 1. As a user this looks simpler. 2. I think it will benefit us to be able to specify multiple input ports.
On Thu, Oct 29, 2015 at 12:09 PM, Gaurav Gupta <gau...@datatorrent.com> wrote: > +1 for 1st approach as this Operator behaves just like an Unifier and > actual connection is between B->A > > Thanks > -Gaurav > > On Thu, Oct 29, 2015 at 11:11 AM, David Yan <da...@datatorrent.com> wrote: > > > This delay operator will act as an input operator for the first window > and > > act as a regular operator after that. > > The engine will increment the window id of the windows from all the > output > > ports of the delay operator. > > > > We will need a new interface for the delay operator, extending the > existing > > Operator interface. The interface will probably include: > > > > - Emitting the tuples for the first window > > - Emitting the tuples after recovery > > > > We will provide a default implementation of the delay operator with a > > write-ahead log that stores the tuples for the window before each > > checkpoint for recovery. We will also probably support the number of > > windows to delay using an operator property. > > > > Let's look at this DAG with an iteration loop: > > > > upstream --> A --> B --> downstream > > ^ | > > |-----| > > > > With the delay operator, the physical view of the DAG looks like this > with > > D being the delay operator: > > > > upstream --> A --> B --> downstream > > ^ | > > |-D<--| > > > > There are two approaches for specifying the delay operator. > > > > 1) As discussed earlier on this thread, the delay operator can be > specified > > as an *input port attribute* of A. The delay operator D will not appear > in > > the logical DAG. The engine will do the +1 on the window ID based on the > > presence of the input port attribute. In this case, the delay operator > > does not need to specify any input port, just like the unifier, with the > > process(tuple) method implicitly taking in the tuples from the output > port > > of B, which logically connects to the input port of A. > > > > 2) The delay operator is specified and connected *as any other operator* > in > > the logical DAG. The engine will do the +1 on the window ID if the > > operator implements the delay operator interface. In this case, the > delay > > operator D will need to specify at least one input port (just like a > > regular operator), and can actually have multiple input ports. > > > > I'm leaning toward the 2nd approach. > > > > Please share your thoughts. Which one you think is better? Or maybe > > suggest a different approach altogether? > > > > Thanks! > > > > David > > > > David > > > > On Wed, Oct 7, 2015 at 10:51 AM, Thomas Weise <tho...@datatorrent.com> > > wrote: > > > > > Why not set the the delay operator as attribute? We already support > > > partitioners and stream codecs as attribute. > > > > > > > > > On Wed, Oct 7, 2015 at 10:09 AM, Pramod Immaneni < > pra...@datatorrent.com > > > > > > wrote: > > > > > > > How about making just the window delay an attribute on the input > port. > > > The > > > > operator connection is just like a normal DAG stream creation. We > could > > > > also support connecting same operator to multiple input ports with > > > > different delay and handle fault recovery accordingly. > > > > > > > > On Wed, Oct 7, 2015 at 9:53 AM, David Yan <da...@datatorrent.com> > > wrote: > > > > > > > > > The iteration operator actually resembles the usage of unifiers. > We > > > have > > > > > getUnifier in the interface of OutputPort. > > > > > > > > > > But if we add getDelayOperator in the interface of InputPort, that > > > would > > > > > introduce backward incompatibility especially since we can't use > the > > > > > default implementation feature of interfaces that is in Java 8. > > > > > > > > > > Putting the class object as an attribute of the InputPort is not > good > > > > > either because you can't configure the delay operator itself. > > > > > > > > > > Thoughts? > > > > > > > > > > David > > > > > > > > > > On Fri, Sep 25, 2015 at 10:10 AM, David Yan <da...@datatorrent.com > > > > > > wrote: > > > > > > > > > > > This is a very good idea. This way, we can have a default > > > > implementation > > > > > > of that operator and the user can control how the tuples are > stored > > > by > > > > > > having his/her own implementation. How many windows the operator > > > > delays > > > > > is > > > > > > part of the implementation of that operator. > > > > > > > > > > > > I am thinking of getting rid of the ITERATION_WINDOW_OFFSET > > attribute > > > > and > > > > > > introduce a DELAY_OPERATOR_CLASS attribute so that the user can > > > specify > > > > > the > > > > > > delay operator class to be used. > > > > > > > > > > > > More thoughts? > > > > > > > > > > > > David > > > > > > > > > > > > On Thu, Sep 17, 2015 at 7:16 PM, Gaurav Gupta < > > > gau...@datatorrent.com> > > > > > > wrote: > > > > > > > > > > > >> Hey David, > > > > > >> > > > > > >> I was thinking can we add another operator in front of the input > > > port > > > > > that > > > > > >> has ITERATION_WINDOW_COUNT set. The new additional operator will > > > have > > > > > >> property whose value will be set equal to > ITERATION_WINDOW_COUNT > > > and > > > > it > > > > > >> will be responsible for caching the data for those many windows > > and > > > > > >> delaying the data. This operator can act as unifier cum iterator > > > > > operator. > > > > > >> For this you may not need any external storage agent as platform > > > > > >> checkpointing should help you here. > > > > > >> > > > > > >> We are doing something similar for Sliding window. > > > > > >> > > > > > >> Thanks > > > > > >> -Gaurav > > > > > >> > > > > > >> 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 > > > > > >> > > > > > > >> > > > > > > > > > > > > > > > > > > > > > > > > > > >
