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From Vinay Patil <vinay18.pa...@gmail.com>
Subject Re: [Discussion] Query regarding Join
Date Tue, 28 Jun 2016 15:13:44 GMT
Hi Aljoscha,

Thanks a lot for your inputs.

I still did not get you when you say you will not face this issue in case
of continuous stream, lets consider the following example :
Assume that the stream runs continuously from Monday  to Friday, and on
Friday it stops after 5.00 PM , will I still face this issue ?

I am actually not able to understand how it will differ in real time
streams.

Regards,
Vinay Patil

On Tue, Jun 28, 2016 at 5:07 PM, Aljoscha Krettek <aljoscha@apache.org>
wrote:

> Hi,
> ingestion time can only be used if you don't care about the timestamp in
> the elements. So if you have those you should probably use event time.
>
> If your timestamps really are strictly increasing then the ascending
> extractor is good. And if you have a continuous stream of incoming elements
> you will not see the behavior of not getting the last elements.
>
> By the way, when using Kafka you can also embed the timestamp extractor
> directly in the Kafka consumer. This is described here:
>
> https://ci.apache.org/projects/flink/flink-docs-master/apis/streaming/connectors/kafka.html#kafka-consumers-and-timestamp-extractionwatermark-emission
>
> Cheers,
> Aljoscha
>
> On Tue, 28 Jun 2016 at 11:44 Vinay Patil <vinay18.patil@gmail.com> wrote:
>
> > Hi Aljoscha,
> >
> > Thank you for your response.
> > So do you suggest to use different approach for extracting timestamp (as
> > given in document) instead of AscendingTimeStamp Extractor ?
> > Is that the reason I am seeing this unexpected behaviour ? in case of
> > continuous stream I would not see any data loss ?
> >
> > Also assuming that the records are always going to be in order , which is
> > the best approach : Ingestion Time or Event Time ?
> >
> >
> >
> > Regards,
> > Vinay Patil
> >
> > On Tue, Jun 28, 2016 at 2:41 PM, Aljoscha Krettek <aljoscha@apache.org>
> > wrote:
> >
> > > Hi,
> > > first regarding tumbling windows: even if you have 5 minute windows it
> > can
> > > happen that elements that are only seconds apart go into different
> > windows.
> > > Consider the following case:
> > >
> > > |                x | x                 |
> > >
> > > These are two 5-mintue windows and the two elements are only seconds
> > apart
> > > but go into different windows because windows are aligned to epoch.
> > >
> > > Now, for the ascending timestamp extractor. The reason this can behave
> in
> > > unexpected ways is that it emits a watermark that is "last timestamp -
> > 1",
> > > i.e. if it has seen timestamp t it can only emit watermark t-1 because
> > > there might be other elements with timestamp t arriving. If you have a
> > > continuous stream of elements you wouldn't notice this. Only in this
> > > constructed example does it become visible.
> > >
> > > Cheers,
> > > Aljoscha
> > >
> > > On Tue, 28 Jun 2016 at 06:04 Vinay Patil <vinay18.patil@gmail.com>
> > wrote:
> > >
> > > > Hi,
> > > >
> > > > Following is the timestamp I am getting from DTO, here is the
> timestamp
> > > > difference between the two records :
> > > > 1466115892162154279
> > > > 1466116026233613409
> > > >
> > > > So the time difference is roughly 3 min, even if I apply the window
> of
> > > 5min
> > > > , I am not getting the last record (last timestamp value above),
> > > > using ascending timestamp extractor for generating the timestamp
> > > (assuming
> > > > that the timestamp are always in order)
> > > >
> > > > I was at-least expecting data to reach the co-group function.
> > > > What could be the reason for the data loss ? The data we are getting
> is
> > > > critical, hence we cannot afford to loose any data
> > > >
> > > >
> > > > Regards,
> > > > Vinay Patil
> > > >
> > > > On Mon, Jun 27, 2016 at 11:31 PM, Vinay Patil <
> vinay18.patil@gmail.com
> > >
> > > > wrote:
> > > >
> > > > > Just an update, when I keep IngestionTime and remove the timestamp
> I
> > am
> > > > > generating, I am getting all the records, but for Event Time I am
> > > getting
> > > > > one less record, I checked the Time Difference between two records,
> > it
> > > > is 3
> > > > > min, I tried keeping the window time to 5 mins, but that even did
> not
> > > > work.
> > > > >
> > > > > Even when I try assigning timestamp for IngestionTime, I get one
> > record
> > > > > less, so should I safely use Ingestion Time or is it always
> advisable
> > > to
> > > > > use EventTime ?
> > > > >
> > > > > Regards,
> > > > > Vinay Patil
> > > > >
> > > > > On Mon, Jun 27, 2016 at 8:16 PM, Vinay Patil <
> > vinay18.patil@gmail.com>
> > > > > wrote:
> > > > >
> > > > >> Hi ,
> > > > >>
> > > > >> Actually I am only publishing 5 messages each to two different
> kafka
> > > > >> topics (using Junit), even if I keep the window to 500 seconds
the
> > > > result
> > > > >> is same.
> > > > >>
> > > > >> I am not understanding why it is not sending the 5th element
to
> > > co-group
> > > > >> operator even when the keys are same.
> > > > >>
> > > > >> I actually cannot share the actual client code.
> > > > >> But this is what the streams look like :
> > > > >> sourceStream.coGroup(destStream)
> > > > >> here the sourceStream and destStream is actually
> Tuple2<String,DTO>
> > ,
> > > > and
> > > > >> the ElementSelector returns tuple.f0 which is the key.
> > > > >>
> > > > >> I am generating the timestamp based on a field from the DTO which
> is
> > > > >> guaranteed to be in order.
> > > > >>
> > > > >> Will using the triggers help here ?
> > > > >>
> > > > >>
> > > > >> Regards,
> > > > >> Vinay Patil
> > > > >>
> > > > >> *+91-800-728-4749*
> > > > >>
> > > > >> On Mon, Jun 27, 2016 at 7:05 PM, Aljoscha Krettek <
> > > aljoscha@apache.org>
> > > > >> wrote:
> > > > >>
> > > > >>> Hi,
> > > > >>> what timestamps are you assigning? Is it guaranteed that
all of
> > them
> > > > >>> would
> > > > >>> fall into the same 30 second window?
> > > > >>>
> > > > >>> The issue with duplicate printing in the ElementSelector
is
> > strange?
> > > > >>> Could
> > > > >>> you post a more complete code example so that I can reproduce
the
> > > > >>> problem?
> > > > >>>
> > > > >>> Cheers,
> > > > >>> Aljoscha
> > > > >>>
> > > > >>> On Mon, 27 Jun 2016 at 13:21 Vinay Patil <
> vinay18.patil@gmail.com>
> > > > >>> wrote:
> > > > >>>
> > > > >>> > Hi ,
> > > > >>> >
> > > > >>> > I am able to get the matching and non-matching elements.
> > > > >>> >
> > > > >>> > However when I am unit testing the code , I am getting
one
> record
> > > > less
> > > > >>> > inside the overriden cogroup function.
> > > > >>> > Testing the following way :
> > > > >>> >
> > > > >>> > 1) Insert 5 messages into local kafka topic (test1)
> > > > >>> > 2) Insert different 5 messages into local kafka topic
(test2)
> > > > >>> > 3) Consume 1) and 2) and I have two different kafka
 streams
> > > > >>> > 4) Generate ascending timestamp(using Event Time) for
both
> > streams
> > > > and
> > > > >>> > create key(String)
> > > > >>> >
> > > > >>> > Now till 4) I am able to get all the records (checked
by
> printing
> > > the
> > > > >>> > stream in text file)
> > > > >>> >
> > > > >>> > However when I send the stream to co-group operator,
I am
> > receiving
> > > > one
> > > > >>> > less record, using the following syntax:
> > > > >>> >
> > > > >>> > sourceStream.coGroup(destStream)
> > > > >>> > .where(new ElementSelector())
> > > > >>> > .equalTo(new ElementSelector())
> > > > >>> > .window(TumblingEventTimeWindows.of(Time.seconds(30)))
> > > > >>> > .apply(new JoinStreams);
> > > > >>> >
> > > > >>> > Also in the Element Selector I have inserted a sysout,
I am
> > getting
> > > > 20
> > > > >>> > sysouts instead of 10 (10 sysouts for source and 10
for dest
> > > stream)
> > > > >>> >
> > > > >>> > Unable to understand why one record is coming less to
co-group
> > > > >>> >
> > > > >>> >
> > > > >>> >
> > > > >>> > Regards,
> > > > >>> > Vinay Patil
> > > > >>> >
> > > > >>> > On Wed, Jun 15, 2016 at 1:39 PM, Fabian Hueske <
> > fhueske@gmail.com>
> > > > >>> wrote:
> > > > >>> >
> > > > >>> > > Can you add a flag to each element emitted by the
> > CoGroupFunction
> > > > >>> that
> > > > >>> > > indicates whether it was joined or not?
> > > > >>> > > Then you can use split to distinguish between both
cases and
> > > handle
> > > > >>> both
> > > > >>> > > streams differently.
> > > > >>> > >
> > > > >>> > > Best, Fabian
> > > > >>> > >
> > > > >>> > > 2016-06-15 6:45 GMT+02:00 Vinay Patil <
> vinay18.patil@gmail.com
> > >:
> > > > >>> > >
> > > > >>> > > > Hi Jark,
> > > > >>> > > >
> > > > >>> > > > I am able to get the non-matching elements
in a stream :,
> > > > >>> > > >
> > > > >>> > > > Of-course we can collect the matching elements
in the same
> > > stream
> > > > >>> as
> > > > >>> > > well,
> > > > >>> > > > however I want to perform additional operations
on the
> joined
> > > > >>> stream
> > > > >>> > > before
> > > > >>> > > > writing it to S3, so I would have to include
a separate
> join
> > > > >>> operator
> > > > >>> > for
> > > > >>> > > > the same two streams, right ?
> > > > >>> > > > Correct me if I am wrong.
> > > > >>> > > >
> > > > >>> > > > I have pasted the dummy code which collects
the
> non-matching
> > > > >>> records (i
> > > > >>> > > > have to perform this on the actual data, correct
me if I am
> > > dong
> > > > >>> > wrong).
> > > > >>> > > >
> > > > >>> > > > sourceStream.coGroup(destStream).where(new
> > > > >>> > ElementSelector()).equalTo(new
> > > > >>> > > > ElementSelector())
> > > > >>> > > > .window(TumblingEventTimeWindows.of(Time.seconds(30)))
> > > > >>> > > > .apply(new CoGroupFunction<Integer, Integer,
Integer>() {
> > > > >>> > > >
> > > > >>> > > > private static final long serialVersionUID
=
> > > > 6408179761497497475L;
> > > > >>> > > >
> > > > >>> > > > @Override
> > > > >>> > > > public void coGroup(Iterable<Integer>
paramIterable,
> > > > >>> Iterable<Integer>
> > > > >>> > > > paramIterable1,
> > > > >>> > > > Collector<Integer> paramCollector) throws
Exception {
> > > > >>> > > > long exactSizeIfKnown =
> > > > >>> > > paramIterable.spliterator().getExactSizeIfKnown();
> > > > >>> > > > long exactSizeIfKnown2 =
> > > > >>> > > > paramIterable1.spliterator().getExactSizeIfKnown();
> > > > >>> > > > if(exactSizeIfKnown == 0 ) {
> > > > >>> > > > paramCollector.collect(paramIterable1.iterator().next());
> > > > >>> > > > } else if (exactSizeIfKnown2 == 0) {
> > > > >>> > > > paramCollector.collect(paramIterable.iterator().next());
> > > > >>> > > > }
> > > > >>> > > > }
> > > > >>> > > > }).print();
> > > > >>> > > >
> > > > >>> > > > Regards,
> > > > >>> > > > Vinay Patil
> > > > >>> > > >
> > > > >>> > > >
> > > > >>> > > > On Tue, Jun 14, 2016 at 1:37 PM, Vinay Patil
<
> > > > >>> vinay18.patil@gmail.com>
> > > > >>> > > > wrote:
> > > > >>> > > >
> > > > >>> > > > > You are right, debugged it for all elements
, I can do
> that
> > > > now.
> > > > >>> > > > > Thanks a lot.
> > > > >>> > > > >
> > > > >>> > > > > Regards,
> > > > >>> > > > > Vinay Patil
> > > > >>> > > > >
> > > > >>> > > > > On Tue, Jun 14, 2016 at 11:56 AM, Jark
Wu <
> > > > >>> > wuchong.wc@alibaba-inc.com>
> > > > >>> > > > > wrote:
> > > > >>> > > > >
> > > > >>> > > > >> In `coGroup(Iterable<Integer>
iter1, Iterable<Integer>
> > > iter2,
> > > > >>> > > > >> Collector<Integer> out)` ,
  when both iter1 and iter2
> are
> > > not
> > > > >>> > empty,
> > > > >>> > > it
> > > > >>> > > > >> means they are matched elements from
both stream.
> > > > >>> > > > >> When one of iter1 and iter2 is empty
, it means that
> they
> > > are
> > > > >>> > > unmatched.
> > > > >>> > > > >>
> > > > >>> > > > >>
> > > > >>> > > > >> - Jark Wu (wuchong)
> > > > >>> > > > >>
> > > > >>> > > > >> > 在 2016年6月14日,下午12:46,Vinay
Patil <
> > vinay18.patil@gmail.com
> > > >
> > > > >>> 写道:
> > > > >>> > > > >> >
> > > > >>> > > > >> > Hi Matthias ,
> > > > >>> > > > >> >
> > > > >>> > > > >> > I did not get you, even if we
use Co-Group we have to
> > > apply
> > > > >>> it on
> > > > >>> > a
> > > > >>> > > > key
> > > > >>> > > > >> >
> > > > >>> > > > >> > sourceStream.coGroup(destStream)
> > > > >>> > > > >> > .where(new ElementSelector())
> > > > >>> > > > >> > .equalTo(new ElementSelector())
> > > > >>> > > > >> > .window(TumblingEventTimeWindows.of(Time.seconds(30)))
> > > > >>> > > > >> > .apply(new CoGroupFunction<Integer,
Integer,
> Integer>()
> > {
> > > > >>> > > > >> > private static final long serialVersionUID
=
> > > > >>> 6408179761497497475L;
> > > > >>> > > > >> >
> > > > >>> > > > >> > @Override
> > > > >>> > > > >> > public void coGroup(Iterable<Integer>
paramIterable,
> > > > >>> > > Iterable<Integer>
> > > > >>> > > > >> > paramIterable1,
> > > > >>> > > > >> > Collector<Integer> paramCollector)
throws Exception {
> > > > >>> > > > >> > Iterator<Integer> iterator
= paramIterable.iterator();
> > > > >>> > > > >> > while(iterator.hasNext()) {
> > > > >>> > > > >> > }
> > > > >>> > > > >> > }
> > > > >>> > > > >> > });
> > > > >>> > > > >> >
> > > > >>> > > > >> > when I debug this ,only the
matched element from both
> > > stream
> > > > >>> will
> > > > >>> > > come
> > > > >>> > > > >> in
> > > > >>> > > > >> > the coGroup function.
> > > > >>> > > > >> >
> > > > >>> > > > >> > What I want is how do I check
for unmatched elements
> > from
> > > > both
> > > > >>> > > streams
> > > > >>> > > > >> and
> > > > >>> > > > >> > write it to sink.
> > > > >>> > > > >> >
> > > > >>> > > > >> > Regards,
> > > > >>> > > > >> > Vinay Patil
> > > > >>> > > > >> >
> > > > >>> > > > >> > *+91-800-728-4749*
> > > > >>> > > > >> >
> > > > >>> > > > >> > On Tue, Jun 14, 2016 at 2:07
AM, Matthias J. Sax <
> > > > >>> > mjsax@apache.org>
> > > > >>> > > > >> wrote:
> > > > >>> > > > >> >
> > > > >>> > > > >> >> You need to do an outer-join.
However, there is no
> > > build-in
> > > > >>> > support
> > > > >>> > > > for
> > > > >>> > > > >> >> outer-joins yet.
> > > > >>> > > > >> >>
> > > > >>> > > > >> >> You can use Window-CoGroup
to implement the
> outer-join
> > as
> > > > an
> > > > >>> own
> > > > >>> > > > >> operator.
> > > > >>> > > > >> >>
> > > > >>> > > > >> >>
> > > > >>> > > > >> >> -Matthias
> > > > >>> > > > >> >>
> > > > >>> > > > >> >> On 06/13/2016 06:53 PM,
Vinay Patil wrote:
> > > > >>> > > > >> >>> Hi,
> > > > >>> > > > >> >>>
> > > > >>> > > > >> >>> I have a question regarding
the join operation,
> > consider
> > > > the
> > > > >>> > > > following
> > > > >>> > > > >> >>> dummy example:
> > > > >>> > > > >> >>>
> > > > >>> > > > >> >>> StreamExecutionEnvironment
env =
> > > > >>> > > > >> >>>
> StreamExecutionEnvironment.getExecutionEnvironment();
> > > > >>> > > > >> >>>
> > > > >>> >
> > env.setStreamTimeCharacteristic(TimeCharacteristic.IngestionTime);
> > > > >>> > > > >> >>> DataStreamSource<Integer>
sourceStream =
> > > > >>> > > > >> >>> env.fromElements(10,20,23,25,30,33,102,18);
> > > > >>> > > > >> >>> DataStreamSource<Integer>
destStream =
> > > > >>> > > > >> >> env.fromElements(20,30,40,50,60,10);
> > > > >>> > > > >> >>>
> > > > >>> > > > >> >>> sourceStream.join(destStream)
> > > > >>> > > > >> >>> .where(new ElementSelector())
> > > > >>> > > > >> >>> .equalTo(new ElementSelector())
> > > > >>> > > > >> >>>
> > > > .window(TumblingEventTimeWindows.of(Time.milliseconds(10)))
> > > > >>> > > > >> >>> .apply(new JoinFunction<Integer,
Integer,
> Integer>() {
> > > > >>> > > > >> >>>
> > > > >>> > > > >> >>> private static final
long serialVersionUID = 1L;
> > > > >>> > > > >> >>>
> > > > >>> > > > >> >>> @Override
> > > > >>> > > > >> >>> public Integer join(Integer
paramIN1, Integer
> > paramIN2)
> > > > >>> throws
> > > > >>> > > > >> Exception
> > > > >>> > > > >> >> {
> > > > >>> > > > >> >>> return paramIN1;
> > > > >>> > > > >> >>> }
> > > > >>> > > > >> >>> }).print();
> > > > >>> > > > >> >>>
> > > > >>> > > > >> >>> I perfectly get the
elements that are matching in
> both
> > > the
> > > > >>> > > streams,
> > > > >>> > > > >> >> however
> > > > >>> > > > >> >>> my requirement is to
write these matched elements
> and
> > > also
> > > > >>> the
> > > > >>> > > > >> unmatched
> > > > >>> > > > >> >>> elements to sink(S3)
> > > > >>> > > > >> >>>
> > > > >>> > > > >> >>> How do I get the unmatched
elements from each
> stream ?
> > > > >>> > > > >> >>>
> > > > >>> > > > >> >>> Regards,
> > > > >>> > > > >> >>> Vinay Patil
> > > > >>> > > > >> >>>
> > > > >>> > > > >> >>
> > > > >>> > > > >> >>
> > > > >>> > > > >>
> > > > >>> > > > >>
> > > > >>> > > > >
> > > > >>> > > >
> > > > >>> > >
> > > > >>> >
> > > > >>>
> > > > >>
> > > > >>
> > > > >
> > > >
> > >
> >
>

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