Chapter

Performance Characterization and Benchmarking

Volume 8391 of the series Lecture Notes in Computer Science pp 109-124

PRIMEBALL: A Parallel Processing Framework Benchmark for Big Data Applications in the Cloud

  • Jaume FerraronsAffiliated withUniversité de Lyon (Laboratoire ERIC) Université Lumière Lyon 2
  • , Mulu AdhanaAffiliated withUniversité de Lyon (Laboratoire ERIC) Université Lumière Lyon 2
  • , Carlos ColmenaresAffiliated withUniversité de Lyon (Laboratoire ERIC) Université Lumière Lyon 2
  • , Sandra PietrowskaAffiliated withUniversité de Lyon (Laboratoire ERIC) Université Lumière Lyon 2
  • , Fadila BentayebAffiliated withUniversité de Lyon (Laboratoire ERIC) Université Lumière Lyon 2
  • , Jérôme DarmontAffiliated withUniversité de Lyon (Laboratoire ERIC) Université Lumière Lyon 2

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Abstract

In this position paper, we draw the specifications for a novel benchmark for comparing parallel processing frameworks in the context of big data applications hosted in the cloud. We aim at filling several gaps in already existing cloud data processing benchmarks, which lack a real-life context for their processes, thus losing relevance when trying to assess performance for real applications. Hence, we propose a fictitious news site hosted in the cloud that is to be managed by the framework under analysis, together with several objective use case scenarios and measures for evaluating system performance. The main strengths of our benchmark definition are parallelization capabilities supporting cloud features and big data properties.

Keywords

Benchmark Cloud Computing Parallel Processing Framework Big Data Real Data