that means you can only trace by log, and not possible to debug hadoop using step debug, haha distributed system always introduce extra complexity and confusing issues.
2010/8/15 Piyush Garg <[email protected]>: > Hi Rita, > > You can put log4j logger debug statements in the code. log4j library is > part of hadoop framework and there is already a log4j.properties file in > hadoop conf directory and all the output logs are saved in hadoop logs > directory. > > Thanks and Regards > Piyush Garg > > > On Sunday 15 August 2010 10:20 AM, Rita Liu wrote: >> Thank you very much, Piyush! :) May I know more about how to use "traces"? >> >> And -- yes, please teach me if possible, experts! :) >> >> Thanks a lot, >> -Rita :)) >> >> On Sat, Aug 14, 2010 at 9:42 PM, Piyush Garg <[email protected]> wrote: >> >> >>> Hi Rita, >>> >>> I have just started to learn hadoop as well, I know there is a long way >>> to go. >>> I found some useful links which I am sharing with you. >>> >>> Hadoop Tutorial - YDN >>> <http://developer.yahoo.com/hadoop/tutorial/index.html> excellent >>> beginners tutorial and well organized. >>> Running Hadoop On Ubuntu Linux (Single-Node Cluster) - Michael G. Noll >>> < >>> http://www.michael-noll.com/wiki/Running_Hadoop_On_Ubuntu_Linux_%28Single-Node_Cluster%29 >>> >>>> >>> Running_Hadoop_On_Ubuntu_Linux_(Multi-Node_Cluster) >>> < >>> http://www.michael-noll.com/wiki/Running_Hadoop_On_Ubuntu_Linux_%28Multi-Node_Cluster%29 >>> >>>> >>> The tutorial on the hadoop wiki >>> <http://hadoop.apache.org/common/docs/r0.20.0/mapred_tutorial.html> is >>> too much for a beginner. >>> >>> Debugger: >>> I do not think you can easily do debugging using remote debugger. This >>> is natural since hadoop is not sequential programming, it would be very >>> difficult to debug its apps. >>> The only way to debug is to use traces. >>> >>> I think you can learn how to setup multi-node cluster, but for practice >>> session you can use single node setup. >>> >>> Lets see what the experts say. >>> >>> Thanks and Regards >>> Piyush Garg >>> >>> >>> On Sunday 15 August 2010 09:07 AM, Rita Liu wrote: >>> >>>> Hi! >>>> >>>> I am a total beginner, but I am very interested in hadoop. I've already >>>> downloaded hadoop 0.19.2 and run on Ubuntu in single-node mode. Now I >>>> >>> want >>> >>>> to do two things: >>>> >>>> 1. Explore how hadoop works internally with one of the example >>>> >>> applications >>> >>>> hadoop provides >>>> 2. Write an application on my own >>>> >>>> Those two things bring me following questions: >>>> >>>> a. debugger? >>>> I am stuck since I don't know how to "explore" hadoop. I used to trace >>>> through the code using a debugger, but in this case, I don't know if >>>> >>> there >>> >>>> is a good debugger to use; or -- maybe a debugger is not necessary for >>>> hadoop? If not, then how do you trace through the code to either debug or >>>> just gain an understanding about the system? May I know what you, >>>> experienced experts, do? :) >>>> >>>> b. Where to run hadoop? >>>> Also -- may I know where you run your hadoop? Do you run on linux, or on >>>> >>> VM >>> >>>> -- in particular, Cloudera? I heard that Cloudera is good for writing >>>> mapreduce applications with hadoop itself as a blackbox; is it true? If >>>> >>> my >>> >>>> ultimate goal is to understand how hadoop works internally, would it be >>>> better if I directly run it on linux? >>>> >>>> c. Single-node or multi-node? >>>> In the beginning (just like my case :p) would it be better to use >>>> single-node or multi-node? If the latter is true, should I obtain more >>>> machines, or should I use more virtual machines to create more nodes? >>>> >>>> As a newbie, I am sorry for all those basic (and silly, I know :$) >>>> questions. If possible, please help me out? Any suggestion or advice will >>>> >>> be >>> >>>> greatly appreciated. Thank you very much! >>>> >>>> Best, >>>> Rita :) >>>> >>>> P.S. If my questions are not suitable for this mailing-list, please let >>>> >>> me >>> >>>> apologize, and then, could you please direct me to other mailing-lists? >>>> Sorry, and thanks a lot! :) >>>> >>>> >>>> >>> >> >
