Michael, This would have no benefit over using a DistributedCache. For a large cluster this would mean poor performance. If the file is static and needs to be looked-up across the cluster, DistributedCache would be a better approach.
Thanks, Prashant On Wed, Dec 14, 2011 at 11:18 AM, jiang licht <[email protected]> wrote: > If that list of ip pairs is pretty static most time and will be used > frequently, maybe just copy it in hdfs with a high replication factor. Then > use it as a look up table or some binary tree or treemap kind of thing by > reading it from hdfs instead of using distributed cache if that sounds an > easier thing to do. > > > Best regards, > Michael > > > ________________________________ > From: Dmitriy Ryaboy <[email protected]> > To: [email protected] > Sent: Wednesday, December 14, 2011 10:28 AM > Subject: Re: Implement Binary Search in PIG > > 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? > > >> > >> > > >>>>> > > >> > >> > > >>>>> > > >> > >> > > >>>>> > > >> > >> > > >>>> > > >> > >> > > >>> > > >> > >> > > >> > > >> > >> > > > > >> > >> > > > >> > >> > > >> > > > > >> > > > > >> > > > >> > > > > > > > > >
