Encyclopedia of Big Data Technologies

Living Edition
| Editors: Sherif Sakr, Albert Zomaya

Performance Evaluation of Big Data Analysis

  • Jorge Veiga
  • Roberto R. Expósito
  • Juan Touriño
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-63962-8_143-1

Synonyms

Definition

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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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Jorge Veiga
    • 1
  • Roberto R. Expósito
    • 1
  • Juan Touriño
    • 1
  1. 1.Computer Architecture GroupUniversidade da CoruñaA CoruñaSpain

Section editors and affiliations

  • Domenico Talia
    • 1
  • Paolo Trunfio
    • 1
  1. 1.DIMESUniversity of CalabriaRendeItaly