Cool, James. I am very interested to contribute to this. I think group by, join and order by can been added to the examples.
On Thu, Jul 22, 2010 at 4:59 AM, James Seigel <ja...@tynt.com> wrote: > Oh yeah, it would help if I put the url: > > http://github.com/seigel/MRPatterns > > James > > On 2010-07-21, at 2:55 PM, James Seigel wrote: > > > Here is a skeleton project I stuffed up on github (feel free to offer > other suggestions/alternatives). There is a wiki, a place to commit code, a > place to fork around, etc.. > > > > Over the next couple of days I’ll try and put up some sample samples for > people to poke around with. Feel free to attack the wiki, contribute code, > etc... > > > > If anyone can derive some cool pseudo code to write map reduce type > algorithms that’d be great. > > > > Cheers > > James. > > > > > > On 2010-07-21, at 10:51 AM, James Seigel wrote: > > > >> Jeff, I agree that cascading looks cool and might/should have a place in > everyone’s tool box, however at some corps it takes a while to get those > kinds of changes in place and therefore they might have to hand craft some > java code before moving (if they ever can) to a different technology. > >> > >> I will get something up and going and post a link back for whomever is > interested. > >> > >> To answer Himanshu’s question, I am thinking something like this (with > some code): > >> > >> Hadoop M/R Patterns, and ones that match Pig Structures > >> > >> 1. COUNT: [Mapper] Spit out one key and the value of 1. [Combiner] Same > as reducer. [Reducer] count = count + next.value. [Emit] Single result. > >> 2. FREQ COUNT: [Mapper] Item, 1. [Combiner] Same as reducer. [Reducer] > count = count + next.value. [Emit] list of Key, count > >> 3. UNIQUE: [Mapper] Item, One. [Combiner] None. [Reducer + Emit] spit > out list of keys and no value. > >> > >> I think adding a description of why the technique works would be helpful > for people learning as well. I see some questions from people not > understanding what happens to the data between mappers and reducers, or what > data they will see when it gets to the reducer...etc... > >> > >> Cheers > >> James. > >> > > > > -- Best Regards Jeff Zhang
