I can't see the relationship between yarn.scheduler.minimum-allocation-mb and the error is reported. According to hive documentation, yarn.scheduler.minimum-allocation-mb is the "container memory minimum". But in this case, the container is running of memory, so it makes sense to increase the "maximum-allocation" instead. Anyway, as it was answered, increasing "mapreduce.map.memory.mb" and "mapreduce.reduce.memory.mb" must work, as those parameters controls how much memory is used by the map-reduce task is run by Hive.
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