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From Chandni Singh <chan...@datatorrent.com>
Subject Re: Supporting iterations in Apex
Date Thu, 29 Oct 2015 19:32:08 GMT
+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 <gaurav@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 <david@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 <thomas@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 <
> pramod@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 <david@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 <david@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 <
> > > gaurav@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 <
> david@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
> > > > > >> >
> > > > > >>
> > > > > >
> > > > > >
> > > > >
> > > >
> > >
> >
>

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