Wait! I thought there was only one RecommenderJob? On Thu, Mar 15, 2012 at 3:44 AM, Sean Owen <sro...@gmail.com> wrote: > You would still need to use the 'job' file generated by the build to > get an artifact with all the dependencies. > You don't need to add Guava as a dependency; it already is one. It's > the job file that you're missing. > > There are two RecommenderJobs. One is what I call pseudo-distributed, > yes. The other is a fully distributed item-based recommender. > > Sean > > On Thu, Mar 15, 2012 at 10:01 AM, Janina <mail4jan...@googlemail.com> wrote: >> Thanks for your fast answer. >> >> I haven't added the jar manually, but by adding the dependency to the >> pom.xml. I tried it with and without the dependendy and with different >> versions of the dependency, but it remained the same error message. >> >> But the RecommenderJob is meant to be to run a pseudo distributed >> recommender on a Hadoop cluster? Am I guessing something wrong? Or do I >> have another possibility to run recommendations on a Hadoop Cluster? I have >> read that only the clustering and classification parts of mahout are really >> able to be distributed on a hadoop cluster. >> >> 2012/3/15 Sean Owen <sro...@gmail.com> >> >>> You shouldn't have to add anything to your jar, if you use the >>> supplied 'job' file which contains all transitive dependencies. >>> If you do add your own jars, I think you need to unpack and repack >>> them, not put them into the overall jar as a jar file, even with a >>> MANIFEST.MF entry. I am not sure that works on Hadoop. >>> >>> On Thu, Mar 15, 2012 at 9:42 AM, Janina <mail4jan...@googlemail.com> >>> wrote: >>> > Hi all, >>> > >>> > I am trying to run a RecommenderJob from a Java program. I have added the >>> > files users.txt and input.txt to a Hadoop VM and use the run-method of >>> > RecommenderJob to start the calculation. But the the following error >>> > message occurs while running the MapReducer: >>> > >>> > Error: java.lang.ClassNotFoundException: >>> com.google.common.primitives.Longs >>> > at java.net.URLClassLoader$1.run(URLClassLoader.java:202) >>> > at java.security.AccessController.doPrivileged(Native Method) >>> > at java.net.URLClassLoader.findClass(URLClassLoader.java:190) >>> > at java.lang.ClassLoader.loadClass(ClassLoader.java:307) >>> > at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:301) >>> > at java.lang.ClassLoader.loadClass(ClassLoader.java:248) >>> > at >>> > >>> org.apache.mahout.cf.taste.hadoop.TasteHadoopUtils.idToIndex(TasteHadoopUtils.java:61) >>> > at >>> > >>> org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexMapper.map(ItemIDIndexMapper.java:48) >>> > at >>> > >>> org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexMapper.map(ItemIDIndexMapper.java:31) >>> > at org.apache.hadoop.mapreduce.Mapper.run(Mapper.java:144) >>> > at org.apache.hadoop.mapred.MapTask.runNewMapper(MapTask.java:621) >>> > at org.apache.hadoop.mapred.MapTask.run(MapTask.java:305) >>> > at org.apache.hadoop.mapred.Child.main(Child.java:170) >>> > >>> > I have added the required guava-r09.jar explicitly to my jar which also >>> > lays on the hadoop cluster. >>> > This may be a stupid question, but does anyone know where this error >>> comes >>> > from? This would help me a lot. >>> > >>> > Thanks and greetings, >>> > Janina >>>
-- Lance Norskog goks...@gmail.com
