The initial design of Apache Hadoop [1] was tightly focused on running massive, MapReduce jobs to process a web crawl. For increasingly diverse companies, Hadoop has become the data and computational agorá---the de facto place where data and computational resources are shared and accessed. This broad adoption and ubiquitous usage has stretched the initial design well beyond its intended target, exposing two key shortcomings: 1) tight coupling of a specific programming model with the resource management infrastructure, forcing developers to abuse the MapReduce programming model, and 2) centralized handling of jobs' control flow, which resulted in endless scalability concerns for the scheduler.

We explore Chord-like ring structures for Distributed Hash Tables (DHTs) and show that the Postage Stamp Problem (PSP) is equivalent to finding optimal structures for such ring topologies. We then describe a variant of the PSP that corresponds to ring-like DHTs that use greedy routing and develop an algorithm that smoothly trades off between the number of finger pointers and network diameter. We provide a dynamic programming solution to the number of nodes that can be supported as a function of the number of finger pointers and the network diameter and also note an interesting link to the Fibonacci sequence.