@Rahul : I'm sorry as I am not aware of any such document. But you could use distcp for local to HDFS copy : *bin/hadoop distcp file:///home/tariq/in.txt hdfs://localhost:9000/* * * And yes. When you use distcp from local to HDFS, you can't take the pleasure of parallelism as the data is stored in a non distributed fashion.
Warm Regards, Tariq cloudfront.blogspot.com On Sat, May 11, 2013 at 11:07 PM, Mohammad Tariq <donta...@gmail.com> wrote: > Hello guys, > > My 2 cents : > > Actually no. of mappers is primarily governed by the no. of InputSplits > created by the InputFormat you are using and the no. of reducers by the no. > of partitions you get after the map phase. Having said that, you should > also keep the no of slots, available per slave, in mind, along with the > available memory. But as a general rule you could use this approach : > > Take the no. of virtual CPUs*.75 and that's the no. of slots you can > configure. For example, if you have 12 physical cores (or 24 virtual > cores), you would have (24*.75)=18 slots. Now, based on your requirement > you could choose how many mappers and reducers you want to use. With 18 MR > slots, you could have 9 mappers and 9 reducers or 12 mappers and 9 reducers > or whatever you think is OK with you. > > I don't know if it ,makes much sense, but it helps me pretty decently. > > Warm Regards, > Tariq > cloudfront.blogspot.com > > > On Sat, May 11, 2013 at 8:57 PM, Rahul Bhattacharjee < > rahul.rec....@gmail.com> wrote: > >> Hi, >> >> I am also new to Hadoop world , here is my take on your question , if >> there is something missing then others would surely correct that. >> >> For per-YARN , the slots are fixed and computed based on the crunching >> capacity of the datanode hardware , once the slots per data node is >> ascertained , they are divided into Map and reducer slots and that goes >> into the config files and remain fixed , until changed.In YARN , its >> decided at runtime based on the kind of requirement of particular task.Its >> very much possible that a datanode at certain point of time running 10 >> tasks and another similar datanode is only running 4 tasks. >> >> Coming to your question. Based of the data set size , block size of dfs >> and input formater , the number of map tasks are decided , generally for >> file based inputformats its one mapper per data block , however there are >> way to change this using configuration settings.Reduce tasks are set using >> job configuration. >> >> General rule as I have read from various documents is that Mappers should >> run atleast a minute , so you can run a sample to find out a good size of >> data block which would make you mapper run more than a minute. Now it again >> depends on your SLA , in case you are not looking for a very small SLA you >> can choose to run less mappers at the expense of higher runtime. >> >> But again its all theory , not sure how these things are handled in >> actual prod clusters. >> >> HTH, >> >> >> >> Thanks, >> Rahul >> >> >> On Sat, May 11, 2013 at 8:02 PM, Shashidhar Rao < >> raoshashidhar...@gmail.com> wrote: >> >>> Hi Users, >>> >>> I am new to Hadoop and confused about task slots in a cluster. How would >>> I know how many task slots would be required for a job. Is there any >>> empirical formula or on what basis should I set the number of task slots. >>> >>> Advanced Thanks >>> >> >> >
