Mapreduce error when running Analytics Pipeline in single node Hadoop cluster in Openstack

I’ve been trying to run the analytics pipeline in single node Hadoop cluster created in an OpenStack Instance but I always get the same error:

INFO mapreduce.Job: Job job_1612970692718_0016 failed with state KILLED due to: REDUCE capability required is more than the supported max container capability in the cluster. Killing the Job. reduceResourceRequest: <memory:5120, vCores:1> maxContainerCapability:<memory:2048, vCores:32>

After doing some research in the internet I found that it might be related with the adjustment of the settings described here: configuration/main.yml at open-release/juniper.master · edx/configuration · GitHub

I set those variables and was able to see the changes in the Hadoop configuration files (/edx/app/hadoop/hadoop/etc/hadoop/yarn-site.xml and /edx/app/hadoop/hadoop/etc/hadoop/mapred-site.xml). Additionally I connected to the Haddoop Web UI exposed in the port 8088 and under the conf tab I was able to see the right values (I rebooted the server to restart all the hadoop services). However after trying several different combinations of settings I was always getting the same error. The reduceResourceRequest and maxContainerCapability were always the same. It made me think that the hadoop settings was being overridden or just ignored but I could not figure it out. I even tried with a bigger instance size (more RAM and VCPU) but the error always remained the same.

Some other important details are:

Analytics Pipeline Version: open-release/juniper.master
Hadoop single node cluster instance size: t1.xlarge (16 GB RAM, 4 VCPU) or t1.2xlarge (32 GB RAM, 8 VCPU), Any of those worked for me.
Configuration files: edx-analytics-pipeline-hadoop-issue · GitHub

I am not a Hadoop expert and I don’t understand why I keep getting the same error which seems to be related to Hadoop mapred client hadoop/RMContainerAllocator.java at 1e3a6efcef2924a7966c44ca63476c853956691d · apache/hadoop · GitHub. I hope someone here has experienced similar issues and can help me to fix them. Thanks in advance.