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From Oleg Ruchovets <oruchov...@gmail.com>
Subject Re: how to model data based on "time bucket"
Date Thu, 31 Jan 2013 13:52:52 GMT
```Hi Rodrigo ,
As usual you have very intereting ! :-)

I am not sure that I understand exactly what do you mean and I try to
simulate:
Suppose we have such events in MAIN Table:
event1 | 10:07
event2 | 10:10
event3 | 10:12
Time window T=5 minutes.

=================on  map================ :

what should I emit for event1 and event2

For event1 in map phase will be (10:07 ,event1) , (10:06 ,event1) , (10:05
,event1), (10:04 ,event1), (10:03 ,event1).
For event2 in map phase will be (10:10 ,event2) , (10:09 ,event2) , (10:08
,event2), (10:07 ,event2), (10:06 ,event2).
For event3 in map phase will be (10:12 ,event3) , (10:11 ,event3) , (10:10
,event3), (10:09 ,event3), (10:08 ,event3).

I calculate from the event time T=5 steps back Is it correct?

==================on reduce =========:

10:03|event1
10:04|event1
10:05|event1
10:06|event1,event2
10:07|event1,event2
10:08|event2,event3
10:09|event2,event3
10:10|event2,event3
10:11|event3
10:12|event3

this output will be writtent to the second table. is it correct?

=============================================

How should I work with this table.Should I have to scan Main table : row by
row and for every row get event time and based on that time query second
table?

In case I will do so , i still need to execute 50 million request?

May be I need to work only with second table. How do I know what to query
(scan)?

I am sure I simply don't understand well what is your approach for solution.

Thanks
Oleg.

On Wed, Jan 30, 2013 at 8:34 PM, Rodrigo Ribeiro <
rodriguinho@jusbrasil.com.br> wrote:

> There is another option,
> You could do a MapReduce job that, for each row from the main table, emits
> all times that it would be in the window of time,
> For example, "event1" would emit {"10:06": event1}, {"10:05": event1} ...
> {"10:00": event1}. (also for "10:07" if you want to know those who happen
> in the same minute too)
> And in the Reduce step you aggregate and save in another table all events
> that are in the window of a given time.
>
> For:
> event_id | time
> =============
> event1 | 10:07
> event2 | 10:10
> event3 | 10:12
>
> The result table would look like:
> time   | events
> 10:00 | event1
> 10:01 | event1
> 10:02 | event1
> 10:03 | event1,event2
> 10:04 | event1,event2
> 10:05 | event1,event2,event3
> 10:06 | event1,event2,event3
> 10:07 | event2,event3
> 10:08 | event2,event3
> ...
>
> So that, knowing a time when a event happens, you can get the list of
> events after it.
> For event1, we only look in the this table for the key "10:07".
>
> Sorry any typo, writing in a bit of hurry.
>
> On Wed, Jan 30, 2013 at 6:57 AM, Oleg Ruchovets <oruchovets@gmail.com
> >wrote:
>
> > Hi Rodrigo.
> >     Using solution with 2 tables : one main and one as index.
> > I have ~50 Million records , in my case I need scan all table and as a
> > result I will have 50 Millions scans and It will kill all performance.
> >
> > Is there any other approach to model my usecase using hbase?
> >
> > Thanks
> > Oleg.
> >
> >
> > On Mon, Jan 28, 2013 at 6:27 PM, Rodrigo Ribeiro <
> > rodriguinho@jusbrasil.com.br> wrote:
> >
> > > In the approach that i mentioned, you would need a table to retrieve
> the
> > > time of a certain event(if this information can retrieve in another
> way,
> > > you may ignore this table). It would be like you posted:
> > > event_id | time
> > > =============
> > > event1 | 10:07
> > > event2 | 10:10
> > > event3 | 10:12
> > > event4 | 10:20
> > >
> > > And a secundary table would be like:
> > > rowkey
> > > ===========
> > > 10:07:event1
> > > 10:10:event2
> > > 10:12:event3
> > > 10:20:event4
> > >
> > > That way, for your first example, you first retrieve the time of the
> > > "event1" on the main table, and then scan starting from his position on
> > the
> > > secondary table("10:07:event1"), until the end of the window.
> > > In this case(T=7) the scan will range ["10:07:event1", "10:05").
> > >
> > > As Michel Segel mentioned, there is a hotspot problem on insertion
> using
> > > this approach alone.
> > > Using multiples buckets(could be a hash from the eventId) would
> > distribute
> > > it better, but requires to scan on all buckets from the second table to
> > get
> > > all events of the window of time.
> > >
> > > Assuming you use 3 buckets, it would look like:
> > > rowkey
> > > ===========
> > > *1_*10:07:event1
> > > *2_*10:10:event2
> > > *3_*10:12:event3
> > > *2_*10:20:event4
> > >
> > > The scans would be: ["*1*_10:07:event1", "1_10:15"),
> ["*2*_10:07:event1",
> > > "2_10:15"), and ["*3*_10:07:event1", "3_10:15"), you can then combine
> the
> > > results.
> > >
> > > Hope it helps.
> > >
> > > On Mon, Jan 28, 2013 at 12:49 PM, Oleg Ruchovets <oruchovets@gmail.com
> > > >wrote:
> > >
> > > > Hi Rodrigo.
> > > >   Can you please explain in more details your solution.You said that
> I
> > > will
> > > > have another table. How many table will I have? Will I have 2 tables?
> > > What
> > > > will be the schema of the tables?
> > > >
> > > > I try to explain what I try to achive:
> > > >     I have ~50 million records like {time|event}. I want to put the
> > data
> > > in
> > > > Hbase in such way :
> > > >     events of time X and all events what was after event X during
> time
> > > > T minutes (for example during 7 minutes).
> > > > So I will be able to scan all table and get groups like:
> > > >
> > > >   {event1:10:02} corresponds to events {event2:10:03} ,
> {event3:10:05}
> > ,
> > > > {event4:10:06}
> > > >   {event2:10:30} correnponds to events {events5:10:32} ,
> > {event3:10:33} ,
> > > > {event3:10:36}.
> > > >
> > > > Thanks
> > > > Oleg.
> > > >
> > > >
> > > > On Mon, Jan 28, 2013 at 5:17 PM, Rodrigo Ribeiro <
> > > > rodriguinho@jusbrasil.com.br> wrote:
> > > >
> > > > > You can use another table as a index, using a rowkey like
> > > > > '{time}:{event_id}', and then scan in the range ["10:07", "10:15").
> > > > >
> > > > > On Mon, Jan 28, 2013 at 10:06 AM, Oleg Ruchovets <
> > oruchovets@gmail.com
> > > > > >wrote:
> > > > >
> > > > > > Hi ,
> > > > > >
> > > > > > I have such row data structure:
> > > > > >
> > > > > > event_id | time
> > > > > > =============
> > > > > > event1 | 10:07
> > > > > > event2 | 10:10
> > > > > > event3 | 10:12
> > > > > >
> > > > > > event4 | 10:20
> > > > > > event5 | 10:23
> > > > > > event6 | 10:25
> > > > > >
> > > > > >
> > > > > > Numbers of records is 50-100 million.
> > > > > >
> > > > > >
> > > > > > Question:
> > > > > >
> > > > > > I need to find group of events starting form eventX and enters
to
> > the
> > > > > time
> > > > > > window bucket = T.
> > > > > >
> > > > > >
> > > > > > For example: if T=7 munutes.
> > > > > > Starting from event event1- {event1, event2 , event3} were
> detected
> > > > > durint
> > > > > > 7 minutes.
> > > > > >
> > > > > > Starting from event event2- {event2 , event3} were detected
> durint
> > 7
> > > > > > minutes.
> > > > > >
> > > > > > Starting from event event4 - {event4, event5 , event6} were
> > detected
> > > > > during
> > > > > > 7 minutes.
> > > > > > Is there a way to model the data in hbase to get?
> > > > > >
> > > > > > Thanks
> > > > > >
> > > > >
> > > > >
> > > > >
> > > > > --
> > > > >
> > > > > *Rodrigo Pereira Ribeiro*
> > > > > Software Developer
> > > > > www.jusbrasil.com.br
> > > > >
> > > >
> > >
> > >
> > >
> > > --
> > >
> > > *Rodrigo Pereira Ribeiro*
> > > Software Developer
> > > T (71) 3033-6371
> > > C (71) 8612-5847
> > > rodriguinho@jusbrasil.com.br
> > > www.jusbrasil.com.br
> > >
> >
>
>
>
> --
>
> *Rodrigo Pereira Ribeiro*
> Software Developer
> www.jusbrasil.com.br
>

```
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