Abstract
Scalable, Distributed Data Structures (SDDSs) can provide fast access to large volumes of data. They allow the data structure to grow or shrink without suffering from a penalty with respect to the space utilization or the average access time. In this paper, we present a performance study of one particular SDDS, called LH*LH, which has been implemented for a cluster of workstations. Our experimental results demonstrate that our LH*LH implementation is truly scalable and yields access-times that are of an order of magnitude smaller than a typical disk access. Furthermore, we also show that parallel access to the LH*LH data structure can speed up client applications quite significantly .
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