hbase has nothing to do with distributed cache.
2011/12/14 唐亮 <[email protected]> > Now, I didn't use HBase, > so, maybe I can't use DistributedCache. > > And if FLATTEN DataBag, the results are Tuples, > then in UDF I can process only one Tuple, which can't implement > BinarySearch. > > So, please help and show me the detailed solution. > Thanks! > > 在 2011年12月14日 下午5:59，唐亮 <[email protected]>写道： > > > Hi Prashant Kommireddi， > > > > If I do 1. and 2. as you mentioned， > > the schema will be {tag, ipStart, ipEnd, locName}. > > > > BUT, how should I write the UDF, especially how should I set the type of > > the input parameter? > > > > Currently, the UDF codes are as below, whose input parameter is DataBag: > > > > public class GetProvinceNameFromIPNum extends EvalFunc<String> { > > > > public String exec(Tuple input) throws IOException { > > if (input == null || input.size() == 0) > > return UnknownIP; > > if (input.size() != 2) { > > throw new IOException("Expected input's size is 2, but is: " + > > input.size()); > > } > > > > Object o1 = input.get(0); * // This should be the IP you want to > > look up* > > if (!(o1 instanceof Long)) { > > throw new IOException("Expected input 1 to be Long, but got " > > + o1.getClass().getName()); > > } > > Object o2 = input.get(1); *// This is the Bag of IP segs* > > if (!(o2 instanceof *DataBag*)) { //* Should I change it to "(o2 > > instanceof Tuple)"?* > > throw new IOException("Expected input 2 to be DataBag, but > got > > " > > + o2.getClass().getName()); > > } > > > > ........... other codes ........... > > } > > > > } > > > > > > > > 在 2011年12月14日 下午3:16，Prashant Kommireddi <[email protected]>写道： > > > > Seems like at the end of this you have a Single bag with all the > elements, > >> and somehow you would like to check whether an element exists in it > based > >> on ipstart/end. > >> > >> > >> 1. Use FLATTEN http://pig.apache.org/docs/r0.9.1/basic.html#flatten - > >> this will convert the Bag to Tuple: to_tuple = FOREACH order_ip_segs > >> GENERATE tag, FLATTEN(order_seq); ---- This is O(n) > >> 2. Now write a UDF that can access the elements positionally for the > >> BinarySearch > >> 3. Dmitriy and Jonathan's ideas with DistributedCache could perform > >> better than the above approach, so you could go down that route too. > >> > >> > >> 2011/12/13 唐亮 <[email protected]> > >> > >> > The detailed PIG codes are as below: > >> > > >> > raw_ip_segment = load ... > >> > ip_segs = foreach raw_ip_segment generate ipstart, ipend, name; > >> > group_ip_segs = group ip_segs all; > >> > > >> > order_ip_segs = foreach group_ip_segs { > >> > order_seg = order ip_segs by ipstart, ipend; > >> > generate 't' as tag, order_seg; > >> > } > >> > describe order_ip_segs > >> > order_ip_segs: {tag: chararray,order_seg: {ipstart: long,ipend: > >> long,poid: > >> > chararray}} > >> > > >> > Here, the order_ip_segs::order_seg is a BAG, > >> > how can I transer it to a TUPLE? > >> > > >> > And can I access the TUPLE randomly in UDF? > >> > > >> > 在 2011年12月14日 下午2:41，唐亮 <[email protected]>写道： > >> > > >> > > 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? > >> > >> > > >>>>> > >> > >> > > >>>>> > >> > >> > > >>>>> > >> > >> > > >>>> > >> > >> > > >>> > >> > >> > > >> > >> > >> > > > >> > >> > > >> > >> > >> > > > >> > > > >> > > >> > > > > >
