BDGS: A Scalable Big Data Generator Suite in Big Data Benchmarking

Data generation is a key issue in big data benchmarking that aims to generate application-specific data sets to meet the 4V requirements of big data. Specifically, big data generators need to generate scalable data (Volume) of different types (Variety) under controllable generation rates (Velocity) while keeping the important characteristics of raw data (Veracity). This gives rise to various new challenges about how we design generators efficiently and successfully. To date, most existing techniques can only generate limited types of data and support specific big data systems such as Hadoop. Hence we develop a tool, called Big Data Generator Suite (BDGS), to efficiently generate scalable big data while employing data models derived from real data to preserve data veracity. The effectiveness of BDGS is demonstrated by developing six data generators covering three representative data types (structured, semi-structured and unstructured) and three data sources (text, graph, and table data)

The impact of China's WTO accession on East Asia

China's World Trade Organization (WTO) accession will have major implications for China and present both opportunities and challenges for East Asia. Ianchovichina and Walmsley assess the possible channels through which China's accession to the WTO could affect East Asia and quantify these effects using a dynamic computable general equilibrium model. China will be the biggest beneficiary of accession, followed by the industrial and newly industrializing economies (NIEs) in East Asia. But their benefits are small relative to the size of their economies and to the vigorous growth projected to occur in the region over the next 10 years. By contrast, developing countries in East Asia are expected to incur small declines in real GDP and welfare as a result of China's accession, mainly because with the elimination of quotas on Chinese textile and apparel exports to industrial countries China will become a formidable competitor in areas in which these countries have comparative advantage. With WTO accession China will increase its demand for petrochemicals, electronics, machinery, and equipment from Japan and the NIEs, and farm, timber, energy products, and other manufactures from the developing countries in East Asia. New foreign investment is likely to flow into these expanding sectors. The overall impact on foreign investment is likely to be positive in the NIEs, but negative for the less developed East Asian countries as a result of the contraction of these economies'textile and apparel sector. As China becomes a more efficient supplier of services or a more efficient producer of high-end manufactures, its comparative advantage will shift into higher-end products. This is good news for the poor developing economies in East Asia, but it implies that the impact of China's WTO accession on the NIEs may change to include heightened competition in global markets.Environmental Economics&Policies,Economic Theory&Research,International Terrorism&Counterterrorism,Payment Systems&Infrastructure,Labor Policies,Economic Theory&Research,Environmental Economics&Policies,World Trade Organization,TF054105-DONOR FUNDED OPERATION ADMINISTRATION FEE INCOME AND EXPENSE ACCOUNT,Trade and Regional Integration

ShenZhen transportation system (SZTS): a novel big data benchmark suite

Data analytics is at the core of the supply chain for both products and services in modern economies and societies. Big data workloads, however, are placing unprecedented demands on computing technologies, calling for a deep understanding and characterization of these emerging workloads. In this paper, we propose ShenZhen Transportation System (SZTS), a novel big data Hadoop benchmark suite comprised of real-life transportation analysis applications with real-life input data sets from Shenzhen in China. SZTS uniquely focuses on a specific and real-life application domain whereas other existing Hadoop benchmark suites, such as HiBench and CloudRank-D, consist of generic algorithms with synthetic inputs. We perform a cross-layer workload characterization at the microarchitecture level, the operating system (OS) level, and the job level, revealing unique characteristics of SZTS compared to existing Hadoop benchmarks as well as general-purpose multi-core PARSEC benchmarks. We also study the sensitivity of workload behavior with respect to input data size, and we propose a methodology for identifying representative input data sets