Stress-Testing Remote Model Querying APIs for Relational and Graph-Based Stores

TY - JOUR

T1 - Stress-Testing Remote Model Querying APIs for Relational and Graph-Based Stores

AU - Paige, Richard Freeman

AU - Kolovos, Dimitrios

AU - Barmpis, Konstantinos

AU - Wei, Ran

AU - Garcia-Dominguez, Antonio

N1 - © The Author(s) 2017. Funding Information: This research was part supported by the EPSRC, through the Large-Scale Complex IT Systems project (EP/F001096/1), and by the EU through the MONDO FP7 STREP project (#611125). We would also like to thank Gwendal Daniel for his support on the use of Mogwa? and NeoEMF. The research data supporting this publication are available on http://dx.doi.org/10.17036/44783FFA-DA36-424D-9B78-5C3BBAE4AAA1. Publisher Copyright: © 2017, The Author(s).

PY - 2019/4/4

Y1 - 2019/4/4

N2 - Recent research in scalable model-driven engineering now allows very large models to be stored and queried. Due to their size, rather than transferring such models over the network in their entirety, it is typically more efficient to access them remotely using networked services (e.g. model repositories, model indexes). Little attention has been paid so far to the nature of these services, and whether they remain responsive with an increasing number of concurrent clients. This paper extends a previous empirical study on the impact of certain key decisions on the scalability of concurrent model queries on two domains, using an Eclipse Connected Data Objects model repository, four configurations of the Hawk model index and a Neo4j-based configuration of the NeoEMF model store. The study evaluates the impact of the network protocol, the API design, the caching layer, the query language and the type of database, and analyses the reasons for their varying levels of performance. The design of the API was shown to make a bigger difference compared to the network protocol (HTTP/TCP) used. Where available, the query-specific indexed and derived attributes in Hawk outperformed the comprehensive generic caching in CDO. Finally, the results illustrate the still ongoing evolution of graph databases: two tools using different versions of the same backend had very different performance, with one slower than CDO and the other faster than it.

AB - Recent research in scalable model-driven engineering now allows very large models to be stored and queried. Due to their size, rather than transferring such models over the network in their entirety, it is typically more efficient to access them remotely using networked services (e.g. model repositories, model indexes). Little attention has been paid so far to the nature of these services, and whether they remain responsive with an increasing number of concurrent clients. This paper extends a previous empirical study on the impact of certain key decisions on the scalability of concurrent model queries on two domains, using an Eclipse Connected Data Objects model repository, four configurations of the Hawk model index and a Neo4j-based configuration of the NeoEMF model store. The study evaluates the impact of the network protocol, the API design, the caching layer, the query language and the type of database, and analyses the reasons for their varying levels of performance. The design of the API was shown to make a bigger difference compared to the network protocol (HTTP/TCP) used. Where available, the query-specific indexed and derived attributes in Hawk outperformed the comprehensive generic caching in CDO. Finally, the results illustrate the still ongoing evolution of graph databases: two tools using different versions of the same backend had very different performance, with one slower than CDO and the other faster than it.

KW - API design

KW - Collaborative modelling

KW - Model persistence

KW - NoSQL storage

KW - Relational databases

KW - Remote model querying

KW - Stress testing

UR - http://www.scopus.com/inward/record.url?scp=85021753284&partnerID=8YFLogxK

U2 - 10.1007/s10270-017-0606-9

DO - 10.1007/s10270-017-0606-9

M3 - Article

SN - 1619-1366

VL - 18

SP - 1047

EP - 1075

JO - Software and Systems Modeling

JF - Software and Systems Modeling

IS - 2

ER -