Database Reference
In-Depth Information
Further Reading
This chapter has given a short overview of YARN. For more detail, see Apache Hadoop
YARN by Arun C. Murthy et al. (Addison-Wesley, 2014).
[ 35 ] It's also possible for the client to start the application master, possibly outside the cluster, or in the same
JVM as the client. This is called an unmanaged application master .
[ 36 ] For more on this topic see Scaling Out and Network Topology and Hadoop .
[ 37 ] The low-latency application master code lives in the Llama project .
[ 38 ] All of these projects are Apache Software Foundation projects.
[ 39 ] As of Hadoop 2.5.1, the YARN timeline server does not yet store MapReduce job history, so a MapRe-
duce job history server daemon is still needed (see Cluster Setup and Installation ) .
[ 40 ] Arun C. Murthy, “The Next Generation of Apache Hadoop MapReduce,” February 14, 2011.
[ 41 ] If the property yarn.scheduler.capacity. <queue-path> .user-limit-factor is set to
a value larger than 1 (the default), then a single job is allowed to use more than its queue's capacity.
[ 42 ] However, the Capacity Scheduler can perform work-preserving preemption, where the resource manager
asks applications to return containers to balance capacity.
[ 43 ] DRF was introduced in Ghodsi et al.'s “Dominant Resource Fairness: Fair Allocation of Multiple Re-
source Types,” March 2011.
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