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Performance Evaluation of Big Data Analysis

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Encyclopedia of Big Data Technologies

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Synonyms

Big Data performance characterization

Definitions

Evaluating the performance of Big Data systems is the usual way of getting information about the expected execution time of analytics applications. These applications are generally used to extract meaningful information from very large input datasets. There exist many high-level frameworks for Big Data analysis, each one oriented to different fields like machine learning and data mining, like Mahout (Apache Mahout 2009), or graph analytics like Giraph (Avery 2011). These high-level frameworks allow to define complex data processing pipelines that are later decomposed into more fine-grained operations in order to be executed by Big Data processing frameworks like Hadoop (Dean and Ghemawat 2008), Spark (Zaharia et al. 2016), and Flink (Apache Flink 2014). Therefore, the performance evaluation of these frameworks is key to determine their suitability for scalable Big Data analysis.

Big Data processing frameworks can be broken down...

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Authors and Affiliations

  1. Computer Architecture Group, Universidade da Coruña, A Coruña, Spain

    Jorge Veiga, Roberto R. Expósito & Juan Touriño

Authors
  1. Jorge Veiga
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  2. Roberto R. Expósito
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  3. Juan Touriño
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Corresponding author

Correspondence to Jorge Veiga .

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Editors and Affiliations

  1. Institute of Computer Science, University of Tartu, Tartu, Estonia

    Sherif Sakr

  2. School of Information Technologies, Sydney University, Sydney, Australia

    Albert Y. Zomaya

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Veiga, J., Expósito, R.R., Touriño, J. (2019). Performance Evaluation of Big Data Analysis. In: Sakr, S., Zomaya, A.Y. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-77525-8_143

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