Big Data Benchmarking: 5th International Workshop, WBDB by Tilmann Rabl, Kai Sachs, Meikel Poess, Chaitanya Baru,

By Tilmann Rabl, Kai Sachs, Meikel Poess, Chaitanya Baru, Hans-Arno Jacobson

This ebook constitutes the completely refereed post-workshop court cases of the fifth overseas Workshop on significant information Benchmarking, WBDB 2014, held in Potsdam, Germany, in August 2014.

The thirteen papers provided during this publication have been conscientiously reviewed and chosen from various submissions and canopy themes resembling benchmarks requisites and suggestions, Hadoop and MapReduce - within the various context equivalent to virtualization and cloud - in addition to in-memory, facts new release, and graphs.

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Additional info for Big Data Benchmarking: 5th International Workshop, WBDB 2014, Potsdam, Germany, August 5-6- 2014, Revised Selected Papers

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197–208. Springer, Heidelberg (2013) 5. com/datacenter/tpcbd/ 6. org/tpcx-hs 7. : TPC express – a new path for TPC benchmarks. , Poess, M. ) TPCTC 2013. LNCS, vol. 8391, pp. 48–60. Springer, Heidelberg (2014) 8. : Keeping the TPC relevant! com Abstract. The Internet of Things (IoT) is the network of physical objects accessed through the Internet, as defined by technology analysts and visionaries. These objects contain embedded technology allowing them to interact with the external environment. In other words, when objects can sense and communicate, it changes how and where decisions are made, and who makes them.

The performance evaluation proves its scalability and elasticity using the Star Schema Benchmark [17], but does not allow direct comparisons with other systems. Additionally, the properties scalability and elasticity are neither clearly separated nor is there a single metric to quantify the elasticity. 3 Benchmark Design The Elastic Query Processing Benchmark (EQP Benchmark) strives to assess the ability of analytical platforms to quickly and efficiently adapt to changing cluster sizes. To do so, it simulates an exploratory analysis of operational business data.

The measurement part is followed by the reference part in which we execute the same amount of work and measure the elapsed time as the reference time. In the Sect. 3 we describe how the benchmark metrics are calculated from these measurements. Updates. We simulate the database changes and maintenance by running a parallel update stream during each phase. TPC-H refresh functions one and two and are amended with updates to simulate data cleansing, as the benchmark represents operation on raw, transactional data dumps (Extract-Load-Transform approach).

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