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From Gaurav Gupta <gaurav.gopi...@gmail.com>
Subject Re: load based stream partitioning
Date Fri, 12 Feb 2016 02:03:41 GMT
How will it work in following scenario

Say Operator O has two partitions P1 and P2. P1 was processing faster than
P2 and streamcodec decided to send more data to P1. P1 process some windows
and then P1 crashes and it came back to previous checkpoint. Now P1 comes
on a node which is slow and it processes slowly. So the streamcodec decides
to send less data to P1. In this case will application not loose data some
windows?

Similarly in a reverse scenario, I think there will be duplicate of data.



On Thu, Feb 11, 2016 at 5:46 PM, Pramod Immaneni <pramod@datatorrent.com>
wrote:

> Inline
>
> On Thu, Feb 11, 2016 at 4:32 PM, Timothy Farkas <tim@datatorrent.com>
> wrote:
>
> > Comments inline
> >
> > +1 Overall as well provided Apex-339 is implemented first and it is
> > documented that the mechanism should not be used with some stateful
> > operators.
> >
> > On Thu, Feb 11, 2016 at 4:20 PM, Pramod Immaneni <pramod@datatorrent.com
> >
> > wrote:
> >
> > > Comments inline
> > >
> > > On Thu, Feb 11, 2016 at 4:13 PM, Timothy Farkas <tim@datatorrent.com>
> > > wrote:
> > >
> > > > Hey Pramod,
> > > >
> > > > I agree if APEX-339 is in place then it would work without
> redeploying
> > > > containers for operators that are Stateless, or a subset of Stateful
> > > > operators.
> > > >
> > > > Addressing your previous questions.
> > > >
> > > > - The StatsListener can be used to see how far behind operators are.
> > You
> > > > could determine what window the operator is on, or the number of
> tuples
> > > > it's processed so far, or how long
> > > > it takes it to complete a window.
> > > >
> > >
> > > What if tuples are different sizes and number of tuples processed
> doesn't
> > > reflect how far ahead or behind a downstream partition is? How is the
> > > information from StatsListener made available to the upstream partition
> > > codecs.
> > >
> > What is the information Buffer Server can provide that the StatsListener
> > cannot?
> >
>
> The stats information would have to be relayed down to the upstream
> operators. It's possible.
>
>
> >
> > The StatsListener can trigger a repartition. The information in the
> > StatsListener can be shared
> > with the partitioner by setting the same object for both in populate Dag.
> > The partitioner can then
> > compute the new Stream Codec. The mechanism by which the upstream would
> be
> > updated with the new
> > Stream Codec would have to be implemented as it's currently not there.
> >
> > >
> > >
> > > >
> > > > - Some examples of Stateful operators that require repartitioning of
> > > state
> > > > are the following:
> > > >       - Deduper
> > > >            In this case after updating the stream codec the operator
> > may
> > > > allow a previously seen value to pass because the partition didn't
> > > receive
> > > > that value with the previous stream codec.
> > > >       - A key value store that holds aggregations for each key.
> > > >            In this case multiple partitions would hold partial
> > > aggregations
> > > > for a key, when they are expecting to hold the complete aggregation.
> > > >
> > >
> > > Agreed for deduper. For the second case a unifier is a better approach
> so
> > > that you are not affected by key skew in general.
> > >
> > This is not always possible. We can discuss this offline, since it won't
> > add much to the discussion here to go into the details.
> >
> >
> Yes not always.
>
>
> > >
> > >
> > > >
> > > > Tim
> > > >
> > > > On Thu, Feb 11, 2016 at 4:04 PM, Pramod Immaneni <
> > pramod@datatorrent.com
> > > >
> > > > wrote:
> > > >
> > > > > Additionally it can be treated as a non-idempotent stream for
> > recovery.
> > > > > Look at APEXCORE-339. In cases where the downstream partitions
> > require
> > > > some
> > > > > key based partitioning, what you are suggesting would be a good
> > > approach
> > > > > but it will require more complex logic in the StreamCodec to both
> key
> > > and
> > > > > load based partitioning.
> > > > >
> > > > > On Thu, Feb 11, 2016 at 3:49 PM, Pramod Immaneni <
> > > pramod@datatorrent.com
> > > > >
> > > > > wrote:
> > > > >
> > > > > > How would you know how far behind partitions are without
> > interacting
> > > > with
> > > > > > BufferServer like you were mentioning in the earlier email.
> > Secondly
> > > > why
> > > > > > would changing where the data is sent to based mandate
> > > re-partitioning
> > > > if
> > > > > > the downstream partitions can handle data with different keys.
> > > > > >
> > > > > > On Thu, Feb 11, 2016 at 3:43 PM, Timothy Farkas <
> > tim@datatorrent.com
> > > >
> > > > > > wrote:
> > > > > >
> > > > > >> Hey Pramod,
> > > > > >>
> > > > > >> I think in general and for recovery the existing Partitioning
> > > > machinery
> > > > > >> can
> > > > > >> be reused to update the Stream Codec.
> > > > > >> The reason why is because If the operator is Stateful and
> changes
> > > are
> > > > > made
> > > > > >> to the Stream Codec, the state of the partitions will also
have
> to
> > > be
> > > > > >> repartitioned.
> > > > > >> In this case the number of partitions will remain the same,
just
> > the
> > > > > state
> > > > > >> of the partitions is reshuffled. The implementation for
this
> state
> > > > > >> reshuffling in a fault tolerant way is already handled by
the
> > > Dynamic
> > > > > >> Partitioning logic, so it could be extended to update the
Stream
> > > Codec
> > > > > as
> > > > > >> well.
> > > > > >>
> > > > > >> If the operator is Stateless, it may be possible to do without
> > > > > redeploying
> > > > > >> any containers. But with the way I am envisioning it, I
think
> > there
> > > > > would
> > > > > >> be a lot of difficult to handle corner cases for recovery.
> > > > > >>
> > > > > >> Tim
> > > > > >>
> > > > > >> On Thu, Feb 11, 2016 at 3:07 PM, Pramod Immaneni <
> > > > > pramod@datatorrent.com>
> > > > > >> wrote:
> > > > > >>
> > > > > >> > Comment inline.
> > > > > >> >
> > > > > >> > On Thu, Feb 11, 2016 at 12:21 PM, Timothy Farkas <
> > > > tim@datatorrent.com
> > > > > >
> > > > > >> > wrote:
> > > > > >> >
> > > > > >> > > +1 for the idea.
> > > > > >> > >
> > > > > >> > > Gaurav, this could be done idempotently in the
same way that
> > > > dynamic
> > > > > >> > > repartitioning is done idempotently. All the partitions
are
> > > rolled
> > > > > >> back
> > > > > >> > to
> > > > > >> > > a common checkpoint and the new StreamCodec is
applied
> > starting
> > > > > then.
> > > > > >> The
> > > > > >> > > statistics that the Stream Codec are given are
the
> statistics
> > > for
> > > > > the
> > > > > >> > > windows computed before the common checkpoint
that the
> > > partitions
> > > > > are
> > > > > >> > > rolled back to.
> > > > > >> > >
> > > > > >> > > In fact I think this feature could be added easily
by
> avoiding
> > > > > buffer
> > > > > >> > > server entirely and by allowing the Partitioner
to redefine
> > the
> > > > > >> > StreamCodec
> > > > > >> > > for the operator when define partitions is called.
> > > > > >> > >
> > > > > >> >
> > > > > >> > Are you saying this in context of recovery or in general?
> > > > > >> >
> > > > > >> >
> > > > > >> > >
> > > > > >> > > Thanks,
> > > > > >> > > Tim
> > > > > >> > >
> > > > > >> > > On Thu, Feb 11, 2016 at 12:07 PM, Amol Kekre <
> > > > amol@datatorrent.com>
> > > > > >> > wrote:
> > > > > >> > >
> > > > > >> > > > Gaurav,
> > > > > >> > > > It would not be idempotent per partition,
but will be
> across
> > > all
> > > > > >> > > partitions
> > > > > >> > > > combined. In this case the user would have
explicitly
> asked
> > > for
> > > > > >> such a
> > > > > >> > > > pattern.
> > > > > >> > > >
> > > > > >> > > > Thks,
> > > > > >> > > > Amol
> > > > > >> > > >
> > > > > >> > > >
> > > > > >> > > > On Thu, Feb 11, 2016 at 12:04 PM, Gaurav
Gupta <
> > > > > >> > gaurav.gopi123@gmail.com
> > > > > >> > > >
> > > > > >> > > > wrote:
> > > > > >> > > >
> > > > > >> > > > > Pramod,
> > > > > >> > > > >
> > > > > >> > > > > How would it work with recovery? There
could be cases
> > where
> > > a
> > > > > >> tuple
> > > > > >> > > went
> > > > > >> > > > to
> > > > > >> > > > > P1 and post recovery it can go to P2
> > > > > >> > > > >
> > > > > >> > > > > Gaurav
> > > > > >> > > > >
> > > > > >> > > > > On Thu, Feb 11, 2016 at 11:56 AM, Pramod
Immaneni <
> > > > > >> > > > pramod@datatorrent.com>
> > > > > >> > > > > wrote:
> > > > > >> > > > >
> > > > > >> > > > > > Hi,
> > > > > >> > > > > >
> > > > > >> > > > > > There are scenarios where the downstream
partitions of
> > an
> > > > > >> upstream
> > > > > >> > > > > operator
> > > > > >> > > > > > are generally not performing uniformly
resulting in an
> > > > overall
> > > > > >> > > > > sub-optimal
> > > > > >> > > > > > performance dictated by the slowest
partitions. The
> > > reasons
> > > > > >> could
> > > > > >> > be
> > > > > >> > > > data
> > > > > >> > > > > > related such as some partitions
are receiving more
> data
> > to
> > > > > >> process
> > > > > >> > > than
> > > > > >> > > > > the
> > > > > >> > > > > > others or could be environment
related such as some
> > > > partitions
> > > > > >> are
> > > > > >> > > > > running
> > > > > >> > > > > > slower than others because they
are on heavily loaded
> > > nodes.
> > > > > >> > > > > >
> > > > > >> > > > > > A solution based on currently available
functionality
> in
> > > the
> > > > > >> engine
> > > > > >> > > > would
> > > > > >> > > > > > be to write a StreamCodec implementation
to distribute
> > > data
> > > > > >> among
> > > > > >> > the
> > > > > >> > > > > > partitions such that each partition
is receiving
> similar
> > > > > amount
> > > > > >> of
> > > > > >> > > data
> > > > > >> > > > > to
> > > > > >> > > > > > process. We should consider adding
StreamCodecs like
> > these
> > > > to
> > > > > >> the
> > > > > >> > > > library
> > > > > >> > > > > > but these however do not solve
the problem when it is
> > > > > >> environment
> > > > > >> > > > > related.
> > > > > >> > > > > >
> > > > > >> > > > > > For that a better and more comprehensive
approach
> would
> > be
> > > > > look
> > > > > >> at
> > > > > >> > > how
> > > > > >> > > > > data
> > > > > >> > > > > > is being consumed by the downstream
partitions from
> the
> > > > > >> > BufferServer
> > > > > >> > > > and
> > > > > >> > > > > > use that information to make decisions
on how to send
> > > future
> > > > > >> data.
> > > > > >> > If
> > > > > >> > > > > some
> > > > > >> > > > > > partitions are behind others in
consuming data then
> data
> > > can
> > > > > be
> > > > > >> > > > directed
> > > > > >> > > > > to
> > > > > >> > > > > > the other partitions. One way to
do this would be to
> > relay
> > > > > this
> > > > > >> > type
> > > > > >> > > of
> > > > > >> > > > > > statistical and positional information
from
> BufferServer
> > > to
> > > > > the
> > > > > >> > > > upstream
> > > > > >> > > > > > publishers. The publishers can
use this information in
> > > ways
> > > > > >> such as
> > > > > >> > > > > making
> > > > > >> > > > > > it available to StreamCodecs to
affect destination of
> > > future
> > > > > >> data.
> > > > > >> > > > > >
> > > > > >> > > > > > What do you think.
> > > > > >> > > > > >
> > > > > >> > > > > > Thanks
> > > > > >> > > > > >
> > > > > >> > > > >
> > > > > >> > > >
> > > > > >> > >
> > > > > >> >
> > > > > >>
> > > > > >
> > > > > >
> > > > >
> > > >
> > >
> >
>

Mime
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