TY - CHAP AU - Szárnyas, Gábor AU - Marton, József AU - Maginecz, J. AU - Varró, Dániel ED - Meinel, Christoph ED - Polze, Andreas ED - Bein, Karstens ED - Strotmann, Rolf ED - Seibold, Ulrich ED - Rödszus, Kurt ED - Müller, Jürgen TI - High-Performance Property Graph Queries T2 - HPI Future SOC Lab – Proceedings 2018 VL - 151 PB - Universitätsverlag Potsdam CY - Potsdam SN - 9783869565477 T3 - Technische Berichte des Hasso-Plattner-Instituts für Softwaresystemtechnik an der Universität Potsdam, ISSN 1613-5652 ; 151. PY - 2023 SP - 243 EP - 254 PG - 12 UR - https://m2.mtmt.hu/api/publication/35459360 ID - 35459360 LA - English DB - MTMT ER - TY - JOUR AU - Wolde, Daniel ten AU - Szárnyas, Gábor AU - Boncz, Peter TI - DuckPGQ: Bringing SQL/PGQ to DuckDB JF - Proceedings of the VLDB Endowment J2 - PROC VLDB ENDOW VL - 16 PY - 2023 IS - 12 SP - 4034 EP - 4037 PG - 4 SN - 2150-8097 DO - 10.14778/3611540.3611614 UR - https://m2.mtmt.hu/api/publication/35135691 ID - 35135691 AB - We demonstrate the most important new feature of SQL:2023, namely SQL/PGQ, which eases querying graphs using SQL by introducing new syntax for pattern matching and (shortest) path-finding. We show how support for SQL/PGQ can be integrated into an RDBMS, specifically in the DuckDB system, using an extension module called DuckPGQ. As such, we also demonstrate the use of the DuckDB extensibility mechanism, which allows us to add new functions, data types, operators, optimizer rules, storage systems, and even parsers to DuckDB. We also describe the new data structures and algorithms that the DuckPGQ module is based on, and how they are injected into SQL plans. LA - English DB - MTMT ER - TY - JOUR AU - Hinkel, Georg AU - Garcia-Dominguez, Antonio AU - Schöne, René AU - Boronat, Artur AU - Tisi, Massimo AU - Le Calvar, Théo AU - Jouault, Frederic AU - Marton, József AU - Nyíri, Tamás AU - Antal, János Benjamin AU - Elekes, Márton AU - Szárnyas, Gábor TI - A cross-technology benchmark for incremental graph queries JF - SOFTWARE AND SYSTEMS MODELING J2 - SOFTW SYST MODEL VL - 21 PY - 2022 IS - 2 SP - 755 EP - 804 PG - 50 SN - 1619-1366 DO - 10.1007/s10270-021-00927-5 UR - https://m2.mtmt.hu/api/publication/32538562 ID - 32538562 N1 - Wiesbaden, Germany Aston University, Birmingham, United Kingdom Technische Universität Dresden, Software Technology Group, Dresden, Germany School of Informatics, University of Leicester, Leicester, United Kingdom IMT Atlantique, LS2N (UMR CNRS 6004), Nantes, France DIRO, Université de Montréal, Montreal, Canada ERIS, ESEO-TECH, Angers, France Department of Telecommunications and Media Informatics, Budapest University of Technology and Economics, Budapest, Hungary Department of Measurement and Information Systems, Budapest University of Technology and Economics, Budapest, Hungary CWI, Amsterdam, Netherlands Export Date: 29 April 2022 Correspondence Address: Elekes, M.; Department of Measurement and Information Systems, Hungary; email: elekes@mit.bme.hu AB - To cope with the increased complexity of systems, models are used to capture what is considered the essence of a system. Such models are typically represented as a graph, which is queried to gain insight into the modelled system. Often, the results of these queries need to be adjusted according to updated requirements and are therefore a subject of maintenance activities. It is thus necessary to support writing model queries with adequate languages. However, in order to stay meaningful, the analysis results need to be refreshed as soon as the underlying models change. Therefore, a good execution speed is mandatory in order to cope with frequent model changes. In this paper, we propose a benchmark to assess model query technologies in the presence of model change sequences in the domain of social media. We present solutions to this benchmark in a variety of 11 different tools and compare them with respect to explicitness of incrementalization, asymptotic complexity and performance. LA - English DB - MTMT ER - TY - JOUR AU - Szárnyas, Gábor AU - Waudby, Jack AU - Steer, Benjamin A. AU - Szakállas, Dávid AU - Birler, Altan AU - Wu, Mingxi AU - Zhang, Yuchen AU - Boncz, Peter TI - The LDBC Social Network Benchmark: Business Intelligence Workload JF - Proceedings of the VLDB Endowment J2 - PROC VLDB ENDOW VL - 16 PY - 2022 IS - 4 SP - 877 EP - 890 PG - 14 SN - 2150-8097 DO - 10.14778/3574245.3574270 UR - https://m2.mtmt.hu/api/publication/33559241 ID - 33559241 N1 - CWI, Netherlands Technische Universität München, Germany Newcastle University, United Kingdom TigerGraph, United States Pometry, United Kingdom Cited By :6 Export Date: 7 February 2024 Funding details: Engineering and Physical Sciences Research Council, EPSRC, EP/L015358/1 Funding text 1: Gábor Szárnyas and Peter Boncz were partially supported by the SQIREL-GRAPHS NWO project. Jack Waudby was supported by the Engineering and Physical Sciences Research Council, Centre for Doctoral Training in Cloud Computing for Big Data [grant number EP/L015358/1]. We thank the following people for their participation: Renzo Angles, János Benjamin Antal, Alex Averbuch, Chaker Benhamad, Márton Búr, Thomas Cook, Hassan Chafi, Már-ton Elekes, Orri Erling, Michael Freitag, Gurbinder Gill, Andrey Gubichev, Vlad Haprian, Bálint Hegyi, Moritz Kaufmann, Josep Lluís Larriba-Pey, Norbert Martínez, József Marton, Amine Mhed-hbi, Hannes Mühleisen, Thomas Neumann, Marcus Paradies, Arnau Prat-Pérez, Minh-Duc Pham, David Püroja, Mark Raasveldt, Oskar van Rest, Mirko Spasić, Vasileios Trigonakis, Danïel ten Wolde. LA - English DB - MTMT ER - TY - JOUR AU - Semeráth, Oszkár AU - Aren, A. Babikian AU - Boqi, Chen AU - Chuning, Li AU - Marussy, Kristóf AU - Szárnyas, Gábor AU - Varró, Dániel TI - Automated Generation of Consistent, Diverse and Structurally Realistic Graph Models JF - SOFTWARE AND SYSTEMS MODELING J2 - SOFTW SYST MODEL VL - 20 PY - 2021 IS - 5 SP - 1713 EP - 1734 PG - 22 SN - 1619-1366 DO - 10.1007/s10270-021-00884-z UR - https://m2.mtmt.hu/api/publication/32028274 ID - 32028274 N1 - EFOP 4.2.1-16-2017-00021 AB - In this paper, we present a novel technique to automatically synthesize consistent, diverse and structurally realistic domain-specific graph models. A graph model is (1) consistent if it is metamodel-compliant and it satisfies the well-formedness constraints of the domain; (2) it is diverse if local neighborhoods of nodes are highly different; and (1) it is structurally realistic if a synthetic graph is at a close distance to a representative real model according to various graph metrics used in network science, databases or software engineering. Our approach grows models by model extension operators using a hill-climbing strategy in a way that (A) ensures that there are no constraint violation in the models (for consistency reasons), while (B) more realistic candidates are selected to minimize a target metric value (wrt. the representative real model). We evaluate the effectiveness of the approach for generating realistic models using multiple metrics for guidance heuristics and compared to other model generators in the context of three case studies with a large set of real human models. We also highlight that our technique is able to generate a diverse set of models, which is a requirement in many testing scenarios. LA - English DB - MTMT ER - TY - JOUR AU - Sakr, Sherif AU - Bonifati, Angela AU - Voigt, Hannes AU - Iosup, Alexandru AU - Ammar, Khaled AU - Angles, Renzo AU - Aref, Walid AU - Arenas, Marcelo AU - Besta, Maciej AU - Boncz, Peter A. AU - Daudjee, Khuzaima AU - Valle, Emanuele Della AU - Dumbrava, Stefania AU - Hartig, Olaf AU - Haslhofer, Bernhard AU - Hegeman, Tim AU - Hidders, Jan AU - Hose, Katja AU - Iamnitchi, Adriana AU - Kalavri, Vasiliki AU - Kapp, Hugo AU - Martens, Wim AU - Özsu, M. Tamer AU - Peukert, Eric AU - Plantikow, Stefan AU - Ragab, Mohamed AU - Ripeanu, Matei R. AU - Salihoglu, Semih AU - Schulz, Christian AU - Selmer, Petra AU - Sequeda, Juan F. AU - Shinavier, Joshua AU - Szárnyas, Gábor AU - Tommasini, Riccardo AU - Tumeo, Antonino AU - Uta, Alexandru AU - Varbanescu, Ana Lucia AU - Wu, Hsiang-Yun AU - Yakovets, Nikolay AU - Yan, Da AU - Yoneki, Eiko TI - The future is big graphs: a community view on graph processing systems JF - COMMUNICATIONS OF THE ACM J2 - COMMUN ACM VL - 64 PY - 2021 IS - 9 SP - 62 EP - 71 PG - 10 SN - 0001-0782 DO - 10.1145/3434642 UR - https://m2.mtmt.hu/api/publication/32241157 ID - 32241157 N1 - Cited By :7 Export Date: 14 June 2022 CODEN: CACMA Correspondence Address: Bonifati, A.; Lyon 1 University and Liris Cnrs in VilleurbanneFrance; email: angela.bonifati@univ-lyon1.fr LA - English DB - MTMT ER - TY - CHAP AU - Waudby, Jack AU - Steer, Benjamin A. AU - Karimov, Karim AU - Marton, József AU - Boncz, Peter AU - Szárnyas, Gábor ED - Nambiar, R ED - Poess, M TI - Towards Testing ACID Compliance in the LDBC Social Network Benchmark T2 - Performance Evaluation and Benchmarking: 12th TPC Technology Conference, TPCTC 2020 PB - Springer International Publishing CY - Cham SN - 9783030849245 T3 - Lecture Notes in Computer Science, ISSN 0302-9743 ; 12752. PY - 2021 SP - 1 EP - 17 PG - 17 DO - 10.1007/978-3-030-84924-5_1 UR - https://m2.mtmt.hu/api/publication/32398430 ID - 32398430 N1 - Funding Agency and Grant Number: Engineering and Physical Sciences Research Council, Centre for Doctoral Training in Cloud Computing for Big Data [EP/L015358/1]; Engineering and Physical Sciences Research Council; Alan Turing Institute [EP/T001569/1]; SQIREL-GRAPHS NWO project; MTA-BME Lendulet Cyber-Physical Systems Research Group; NERC [1948749] Funding Source: UKRI Funding text: J. Waudby was supported by the Engineering and Physical Sciences Research Council, Centre for Doctoral Training in Cloud Computing for Big Data [grant number EP/L015358/1]. B. Steer was supported by the Engineering and Physical Sciences Research Council and Alan Turing Institute [grant number EP/T001569/1]. P. Boncz was partially supported by the SQIREL-GRAPHS NWO project. G. Szarnyas was partially supported by the MTA-BME Lendulet Cyber-Physical Systems Research Group. AB - Verifying ACID compliance is an essential part of database benchmarking, because the integrity of performance results can be undermined as the performance benefits of operating with weaker safety guarantees (at the potential cost of correctness) are well known. Traditionally, benchmarks have specified a number of tests to validate ACID compliance. However, these tests have been formulated in the context of relational database systems and SQL, whereas our scope of benchmarking are systems for graph data, many of which are non-relational. This paper presents a set of data model-agnostic ACID compliance tests for the LDBC (Linked Data Benchmark Council) Social Network Benchmark suite's Interactive (SNB-I) workload, a transaction processing benchmark for graph databases. We test all ACID properties with a particular emphasis on isolation, covering 10 transaction anomalies in total. We present results from implementing the test suite on 5 database systems. LA - English DB - MTMT ER - TY - CHAP AU - Azad, Ariful AU - Aznaveh, Mohsen Mahmoudi AU - Beamer, Scott AU - Blanco, Mark AU - Chen, Jinhao AU - D'Alessandro, Luke AU - Dathathri, Roshan AU - Davis, Tim AU - Deweese, Kevin AU - Firoz, Jesun AU - Gabb, Henry A AU - Gill, Gurbinder AU - Hegyi, Balint AU - Kolodziej, Scott AU - Low, Tze Meng AU - Lumsdaine, Andrew AU - Manlaibaatar, Tugsbayasgalan AU - Mattson, Timothy G AU - McMillan, Scott AU - Peri, Ramesh AU - Pingali, Keshav AU - Sridhar, Upasana AU - Szárnyas, Gábor AU - Zhang, Yunming AU - Zhang, Yongzhe TI - Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite T2 - 2020 IEEE International Symposium on Workload Characterization (IISWC) SN - 9781728176451 PY - 2020 SP - 216 EP - 227 PG - 12 DO - 10.1109/IISWC50251.2020.00029 UR - https://m2.mtmt.hu/api/publication/32868652 ID - 32868652 N1 - Indiana University, United States Texas Am University, United States University of California, Santa Cruz, United States Carnegie Mellon University, United States University of Texas at Austin, United States University of Washington, United States Pacific Northwest National Laboratory Intel Corporation Budapest University of Technology and Economics, Hungary Massachusetts Institute of Technology, United States Graduate University for Advanced Studies, Sokendai, Japan Cited By :6 Export Date: 9 June 2022 LA - English DB - MTMT ER - TY - CHAP AU - Aznaveh, Mohsen AU - Chen, Jinhao AU - Davis, Timothy A. AU - Hegyi, Bálint AU - Kolodziej, Scott P. AU - Mattson, Timothy G. AU - Szárnyas, Gábor ED - Li, Xiaoye Sherri ED - Bücker, H. Martin TI - Parallel GraphBLAS with OpenMP T2 - 2020 Proceedings of the SIAM Workshop on Combinatorial Scientific Computing PB - Society for Industrial and Applied Mathematics (SIAM) SN - 9781611976229 PY - 2020 SP - 138 EP - 148 PG - 11 DO - 10.1137/1.9781611976229.14 UR - https://m2.mtmt.hu/api/publication/31329295 ID - 31329295 LA - English DB - MTMT ER - TY - CHAP AU - Elekes, Márton AU - Nagy, Attila AU - Sándor, Dávid AU - Antal, János Benjamin AU - Davis, Timothy A. AU - Szárnyas, Gábor ED - IEEE, null TI - A GraphBLAS solution to the SIGMOD 2014 Programming Contest using multi-source BFS T2 - 2020 IEEE High Performance Extreme Computing Conference (HPEC) PB - Institute of Electrical and Electronics Engineers (IEEE) CY - Piscataway (NJ) SN - 9781728192192 PY - 2020 SP - 1 EP - 7 PG - 7 DO - 10.1109/HPEC43674.2020.9286186 UR - https://m2.mtmt.hu/api/publication/31861479 ID - 31861479 LA - English DB - MTMT ER -