How are you storing segments in a Bag? Can you forward the script.

2011/12/13 唐亮 <[email protected]>

> Then how can I transfer all the items in Bag to a Tuple?
>
>
> 2011/12/14 Jonathan Coveney <[email protected]>
>
> > It's funny, but if you look wayyyy in the past, I actually asked a bunch
> of
> > questions that circled around, literally, this exact problem.
> >
> > Dmitriy and Prahsant are correct: the best way is to make a UDF that can
> do
> > the lookup really efficiently. This is what the maxmind API does, for
> > example.
> >
> > 2011/12/13 Prashant Kommireddi <[email protected]>
> >
> > > I am lost when you say "If enumerate every IP, it will be more than
> > > 100000000 single IPs"
> > >
> > > If each bag is a collection of 30000 tuples it might not be too bad on
> > the
> > > memory if you used Tuple to store segments instead?
> > >
> > > (8 bytes long + 8 bytes long + 20 bytes for chararray ) = 36
> > > Lets say we incur an additional overhead 4X times this, which is ~160
> > bytes
> > > per tuple.
> > > Total per Bag = 30000 X 160 = ~5 MB
> > >
> > > You could probably store the ipsegments as Tuple and test it on your
> > > servers.
> > >
> > >
> > > On Tue, Dec 13, 2011 at 8:39 PM, Dmitriy Ryaboy <[email protected]>
> > > wrote:
> > >
> > > > Do you have many such bags or just one? If one, and you want to look
> up
> > > > many ups in it, might be more efficient to serialize this relation to
> > > hdfs,
> > > > and write a lookup udf that specifies the serialized data set as a
> file
> > > to
> > > > put in distributed cache. At init time, load up the file into memory,
> > > then
> > > > for every ip do the binary search in exec()
> > > >
> > > > On Dec 13, 2011, at 7:55 PM, 唐亮 <[email protected]> wrote:
> > > >
> > > > > Thank you all!
> > > > >
> > > > > The detail is:
> > > > > A bag contains many "IP Segments", whose schema is (ipStart:long,
> > > > > ipEnd:long, locName:chararray) and the number of tuples is about
> > 30000,
> > > > > and I want to check wheather an IP is belong to one segment in the
> > bag.
> > > > >
> > > > > I want to order the "IP Segments" by (ipStart, ipEnd) in MR,
> > > > > and then binary search wheather an IP is in the bag in UDF.
> > > > >
> > > > > If enumerate every IP, it will be more than 100000000 single IPs,
> > > > > I think it will also be time consuming by JOIN in PIG.
> > > > >
> > > > > Please help me how can I deal with it efficiently!
> > > > >
> > > > >
> > > > > 2011/12/14 Thejas Nair <[email protected]>
> > > > >
> > > > >> My assumption is that 唐亮 is trying to do binary search on bags
> > within
> > > > the
> > > > >> tuples in a relation (ie schema of the relation has a bag
> column). I
> > > > don't
> > > > >> think he is trying to treat the entire relation as one bag and do
> > > binary
> > > > >> search on that.
> > > > >>
> > > > >>
> > > > >> -Thejas
> > > > >>
> > > > >>
> > > > >>
> > > > >> On 12/13/11 2:30 PM, Andrew Wells wrote:
> > > > >>
> > > > >>> I don't think this could be done,
> > > > >>>
> > > > >>> pig is just a hadoop job, and the idea behind hadoop is to read
> all
> > > the
> > > > >>> data in a file.
> > > > >>>
> > > > >>> so by the time you put all the data into an array, you would have
> > > been
> > > > >>> better off just checking each element for the one you were
> looking
> > > for.
> > > > >>>
> > > > >>> So what you would get is [n + lg (n)], which will just be [n]
> after
> > > > >>> putting
> > > > >>> that into an array.
> > > > >>> Second, hadoop is all about large data analysis, usually more
> than
> > > > 100GB,
> > > > >>> so putting this into memory is out of the question.
> > > > >>> Third, hadoop is efficient because it processes this large amount
> > of
> > > > data
> > > > >>> by splitting it up into multiple processes. To do an efficient
> > binary
> > > > >>> search, you would need do this in one mapper or one reducer.
> > > > >>>
> > > > >>> My opinion is just don't fight hadoop/pig.
> > > > >>>
> > > > >>>
> > > > >>>
> > > > >>> On Tue, Dec 13, 2011 at 1:56 PM, Thejas Nair<
> > [email protected]>
> > > > >>> wrote:
> > > > >>>
> > > > >>> Bags can be very large might not fit into memory, and in such
> cases
> > > > some
> > > > >>>> or all of the bag might have to be stored on disk. In such
> cases,
> > it
> > > > is
> > > > >>>> not
> > > > >>>> efficient to do random access on the bag. That is why the
> DataBag
> > > > >>>> interface
> > > > >>>> does not support it.
> > > > >>>>
> > > > >>>> As Prashant suggested, storing it in a tuple would be a good
> > > > alternative,
> > > > >>>> if you want to have random access to do binary search.
> > > > >>>>
> > > > >>>> -Thejas
> > > > >>>>
> > > > >>>>
> > > > >>>>
> > > > >>>> On 12/12/11 7:54 PM, 唐亮 wrote:
> > > > >>>>
> > > > >>>> Hi all,
> > > > >>>>> How can I implement a binary search in pig?
> > > > >>>>>
> > > > >>>>> In one relation, there exists a bag whose items are sorted.
> > > > >>>>> And I want to check there exists a specific item in the bag.
> > > > >>>>>
> > > > >>>>> In UDF, I can't random access items in DataBag container.
> > > > >>>>> So I have to transfer the items in DataBag to an ArrayList, and
> > > this
> > > > is
> > > > >>>>> time consuming.
> > > > >>>>>
> > > > >>>>> How can I implement the binary search efficiently in pig?
> > > > >>>>>
> > > > >>>>>
> > > > >>>>>
> > > > >>>>
> > > > >>>
> > > > >>
> > > >
> > >
> >
>

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