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Resource management is one of the most indispensable components ofcluster-level infrastructure layers. Users of such systems should be able tospecify their job requirements as a configuration parameter (CPU, RAM, diskI/O, network I/O) and have the scheduler translate those into an appropriatereservation and allocation of resources. YARN is an emerging resourcemanagement in the Hadoop ecosystem, which supports only RAM and CPU reservationat present.  In this paper, we propose a solution that takes into account the operation ofthe Hadoop Distributed File System to control the data rate of applications inthe framework of a Hadoop compute platform. We utilize the property that a datapipe between a container and a DataNode consists of a disk I/O subpipe and aTCP/IP subpipe. We have implemented building block software components tocontrol the data rate of data pipes between containers and DataNodes andprovide a proof-of-concept with measurement results.

Building Block Components to Control a Data Rate in the Apache Hadoop Compute Platform