A Data Generator for Cloud-Scale Benchmarking

Abstract. In many fields of research and business data sizes are breaking the petabyte barrier. This imposes new problems and research possibilities for the database community. Usually, data of this size is stored in large clusters or clouds. Although clouds have become very popular in recent years, there is only little work on benchmarking cloud applications. In this paper we present a data generator for cloud sized applications. Its architecture makes the data generator easy to extend and to configure. A key feature is the high degree of parallelism that allows linear scaling for arbitrary numbers of nodes. We show how distributions, relationships and dependencies in data can be computed in parallel with linear speed up.

Grazing lands in Sub-Saharan Africa and their potential role in climate change mitigation: What we do and don't know

In 2014, the USAID project ‘Grazing lands, livestock and climate resilient mitigation in Sub-Saharan Africa’ held two workshops, hosted by the Colorado State University, which brought together experts from around the world. Two reports resulted from these workshops, one an assessment of the state of the science, and the other an inventory of related activities in the region to date.. In this short communication we summarize the main points of the first report – The state of the science (Milne and Williams, 2015). A second report is in preparation