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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 15

Proceedings of the 2018 Federated Conference on Computer Science and Information Systems

Model-driven Query Generation for Elasticsearch

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DOI: http://dx.doi.org/10.15439/2018F218

Citation: Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 15, pages 853–862 ()

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Abstract. Elasticsearch is a distributed RESTful search engine, capable of solving growing number of use cases and can handle petabytes of data in seconds. However, Elasticsearch comes with a complex query language which causes a steep learning curve for the developers and, therefore, creation of queries can be difficult and time-consuming in many cases. Hence, in this paper, we introduce a Domain-specific Modeling Language (DSML), called Dimension Query Language (DQL), to support the model-driven development of Elasticsearch queries. Elasticsearch queries can be automatically generated from DQL models and DQL's IDE is capable of executing these auto-generated Elasticsearch queries on remote repositories. An evaluation of using DQL has been performed at the industrial level with the participation of a group of developers. The conducted evaluation showed that the use of the language significantly decreases the development time required for creating Elasticsearch queries. Finally, qualitative assessment, based on the developers' feedback, exposed how DQL facilitates the development of Elasticsearch queries.

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