Dear all, I know it is best to use small amount of mem in mapper and reduce. However, sometimes it is hard to do so. For example, in machine learning algorithms, it is common to load the model into mem in the mapper step. When the model is big, I have to allocate a lot of mem for the mapper.
Here is my question: how can I config hadoop so that it does not fork too many mappers and run out of physical memory? My machines have 24G, and I have 100 of them. Each time, hadoop will fork 6 mappers on each machine, no matter what config I used. I really want to reduce it to what ever number I want, for example, just 1 mapper per machine. Here are the config I tried. (I use streaming, and I pass the config in the command line) -Dmapred.child.java.opts=-Xmx8000m <-- did not bring down the number of mappers -Dmapred.cluster.map.memory.mb=32000 <-- did not bring down the number of mappers Am I missing something here? I use Hadoop 0.20.205 Thanks a lot in advance! -Shaojun
