JBD Generator: Towards Semi-Structured JSON Big Data

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 637)

Abstract

This paper describes a tool for generation of synthetic semi-structured JSON Big Data, called JBD generator. Its main focus is on parallel execution of the generation process while preserving the ability to control the contents of the generated documents. It can also accept samples of real-world data characterizing the target synthetic data and is also capable of automatic creation of references between JSON documents. The results of experiments with the data generator exploited for the purpose of testing database MongoDB describe its added value.

Keywords

Big Data Data generator MongoDB JSON documents 

References

  1. 1.
    ECMA-404 The JSON Data Interchange Standard (2015). http://json.org/
  2. 2.
    Extensible Markup Language (XML) 1.0 (5th edn. ). W3C (2013)Google Scholar
  3. 3.
    Production Cluster Architecture. MongoDB Inc (2015). http://docs.mongodb.org/manual/core/sharded-cluster-architectures-production/
  4. 4.
    Betik, R.: Automatic Generation of Synthetic XML Documents, Master Thesis, Charles University in Prague (2015). http://www.ksi.mff.cuni.cz/~holubova/dp/Betik.pdf

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of Software EngineeringCharles UniversityPragueCzech Republic

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