You can use YARN schedulers, YARN queues, and node labels to optimize performance when you run a mapping in the Hadoop environment.
A YARN scheduler assigns resources to YARN applications on the Hadoop cluster while honoring organizational policies on sharing resources. You can configure YARN to use a fair scheduler or a capacity scheduler. A fair scheduler shares resources evenly among all jobs running on the cluster over time. A capacity scheduler allows multiple organizations to share a large cluster and distributes resources based on capacity allocations. The capacity scheduler guarantees each organization a certain capacity and distributes any excess capacity that is underutilized.
YARN queues are organizing structures for YARN schedulers and allow multiple tenants to share a cluster. The capacity of each queue specifies the percentage of cluster resources that are available for applications submitted to the queue. You can redirect Blaze, Spark, Hive, and Sqoop jobs to specific YARN queues.
Node labels allow YARN queues to run on specific nodes in a cluster. You can use node labels to partition a cluster into sub-clusters such that jobs run on nodes with specific characteristics. For example, you might label nodes that process data faster compared to other nodes. Nodes that are not labeled belong to the default partition. You can associate the node labels with capacity scheduler queues.
You can also use the node labels to configure the Blaze engine. When you use node labels to configure the Blaze engine, you can specify the nodes on the Hadoop cluster where you want the Blaze engine to run.
You must install and configure Big Data Management for every node on the cluster, even if the cluster is not part of the queue you are using.