tang shanjiang created MAPREDUCE-5643:
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Summary: DynamicMR: A Dynamic Slot Utilization Optimization Framework for Hadoop
MRv1
Key: MAPREDUCE-5643
URL: https://issues.apache.org/jira/browse/MAPREDUCE-5643
Project: Hadoop Map/Reduce
Issue Type: Improvement
Components: contrib/fair-share
Affects Versions: 1.2.1
Reporter: tang shanjiang
Hadoop MRv1 uses the slot-based resource model with the static configuration of map/reduce
slots in advance. Due to the rigid execution order between map and reduce tasks in a MapReduce
environment and the strict execution constrain that map tasks can only run map slots and reduce
tasks can only reduce slots, slots can be severely under-utilized, which significantly degrades
the performance.
In contrast to YARN that gives up the slot-based resource model to maximize resource utilization,
we keep the slot-based model and propose a dynamic slot utilization optimization system called
DynamicMR to improve the performance of Hadoop by maximizing the slots utilization and improving
utilization efficiency while guaranteeing the fairness across pools. It consists of three
levels of scheduling components, namely, Dynamic Hadoop Fair Scheduler (DHFS), Dynamic Speculative
Task Scheduler (DSTS), and Data Locality Maximization Scheduler (DLMS).
Our tests show that DynamicMR outperforms YARN for MapReduce workloads with multiple jobs,
especially when the number of jobs is large.
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