Hi
There is a way but it's not an easy one. You should overwrite the container
request code in MR_AM. As each container in MapReduce gets the same amount
of memory, the OOM shouldn't be problem as inner task "buffers" can be
spilled to disk. I am no MapReduce (code) specialist but I would start by
Hi,
Thank you for your answer. Now I understand the connection between the two
ways.
I asked this question because I want to take benefit from the YARN
architecture.
If I understood correctly, I can let my ApplicationMaster request
containers more flexibly. For example, I can request two containe
Hi
If I understood you correctly, you would like to run your AM with YARN
Client from shell as oppose to run the Driver like in MRv1. But it's the
same thing (more or less). In the example you provided
(org.apache.hadoop.yarn.applications.DistributedShell) the Client.class is
the "driver". However
Hi,
I took a look at the codes and found some examples on the web.
One example is: http://wiki.opf-labs.org/display/SP/Resource+management
It seems that users can run simple shell commands using Client of YARN.
But when it comes to a practical MapReduce example like WordCount, people
still run co
Hi
Follow the example provided in
Yarn_dist/hadoop-yarn-project/hadoop-yarn/hadoop-yarn-applications/hadoop-yarn-applications-distributedshell.
regards
tmp
2013/12/1 Yue Wang
> Hi,
>
> I found the page (
> http://hadoop.apache.org/docs/stable/hadoop-yarn/hadoop-yarn-site/WritingYarnApplicatio
