Apache Hadoop YARN (Yet Another Resource Negotiator) is a cluster management technology. It decouples MapReduce’s resource management and scheduling capabilities from the data processing component, enabling Hadoop to support more varied processing approaches and a broader array of applications. YARN, (or sometimes called as MR2), is an extended and an improved version of MR1. It was… Continue reading Term of the Week : YARN
Fair Scheduler is a pluggable scheduler for Hadoop that allows YARN applications to share resources in large clusters fairly. As the name suggests, it allocates resources such that all applications get an equal share. By default, this is done on the basis of the memory. But, i t can be configured to schedule with both memory… Continue reading What is a Fair Scheduler in Hadoop?
Apache Hadoop YARN (Yet Another Resource Negotiator) is a cluster management technology. It decouples MapReduce’s resource management and scheduling capabilities from the data processing component, enabling Hadoop to support more varied processing approaches and a broader array of applications. YARN, (or sometimes called as MR2), is an extended and an improved version of MR1. It was… Continue reading Understanding YARN and it’s components
The Apache Tez project is an extensible framework built on top of Apache Hadoop YARN. It is used to process data, that earlier took multiple MR jobs, now in a single Tez job which uses Directed Acyclic Graph (DAG) for data processing. It is used for building high performance batch and interactive data processing applications.… Continue reading Term of the Week : Apache Tez
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