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HBase >> mail # user >> how to model data based on "time bucket"


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Re: how to model data based on "time bucket"
Yes.
This is very interesting approach.

       Is it possible to read from main key and scan from another using
map/reduce? I don't want to read from single client. I use hbase version
0.94.2.21.

Thanks
Oleg.
On Mon, Jan 28, 2013 at 6:27 PM, Rodrigo Ribeiro <
[EMAIL PROTECTED]> 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 <[EMAIL PROTECTED]
> >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 <
> > [EMAIL PROTECTED]> 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 <[EMAIL PROTECTED]
> > > >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
NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB