When a new data node joins hdfs cluster, it does not hold much data. So any map task assigned to the machine most likely does not read local data, thus increasing the use of network bandwidth. On the other hand, when some data nodes become full, new data blocks are placed on only non-full data nodes, thus reducing their read parallelism. This jira aims to find an approach to redistribute data bloc
With this JIRA we are introducing distributed scheduling in YARN. In particular, we make the following contributions: - Introduce the notion of container types. GUARANTEED containers follow the semantics of the existing YARN containers. OPPORTUNISTIC ones can be seen as lower priority containers, and can be preempted in order to make space for GUARANTEED containers to run. - Queuing of tasks at th
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