Top

Datenbank-Spektrum

Published in:

14-02-2019 | Schwerpunktbeitrag

BIGGR: Bringing Gradoop to Applications

Authors: M. Ali Rostami, Matthias Kricke, Eric Peukert, Stefan Kühne, Moritz Wilke, Steffen Dienst, Erhard Rahm

Published in: Datenbank-Spektrum | Issue 1/2019

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

Analyzing large amounts of graph data, e.g., from social networks or bioinformatics, has recently gained much attention. Unfortunately, tool support for handling and analyzing such graph data is still weak and scalability to large data volumes is often limited. We introduce the BIGGR approach providing a novel tool for the user-friendly and efficient analysis and visualization of Big Graph Data on top of the open-source software KNIME and gradoop. Users can visually program graph analytics workflows, execute them on top of the distributed processing framework Apache Flink and visualize large graphs within KNIME. For visualization, we apply visualization-driven data reduction techniques by pushing down sampling and layouting to gradoop and Apache Flink. We also discuss an initial application of the tool for the analysis of patent citation graphs.

previous article A Big Data Case Study in Digital Humanities

next article Die Arbeitsgruppe Datenbanken und Informationssysteme an der TU Dortmund

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Datenbank-Spektrum

Datenbank-Spektrum ist das offizielle Organ der Fachgruppe Datenbanken und Information Retrieval der Gesellschaft für Informatik (GI) e.V. Die Zeitschrift widmet sich den Themen Datenbanken, Datenbankanwendungen und Information Retrieval.

inform now

Competence Center for Scalable Data Services and Solutions (ScaDS Dresden/Leipzig) [4].

The technology transfer into KNIME is funded within a joint BMBF project between ScaDS / University of Leipzig and Knime. It is planned to make the described extensions freely available within an upcoming release of KNIME.

http://hadoop.apache.org.

https://hive.apache.org.

https://impala.apache.org.

https://spark.apache.org.

https://neo4j.com.

https://www.oracle.com/technetwork/oracle-labs/parallel-graph-analytix.

http://js.cytoscape.org.

https://github.com/anvaka/VivaGraphJS.

http://www.patentsview.org/.

Junghanns M, Petermann A, Neumann M, Rahm E (2017) Management and analysis of big graph data: current systems and open challenges. In: Handbook of big data technologies. Springer, Berlin, Heidelberg, pp 457–505 https://doi.org/10.1007/978-3-319-49340-4-14 CrossRef

Junghanns M, Petermann A, Gómez K, Rahm E (2015) Gradoop: scalable graph data management and analytics with Hadoop. arXiv preprint 150600548

Junghanns M, Kiessling M, Teichmann N, Gómez K, Petermann A, Rahm E (2018) Declarative and distributed graph analytics with GRADOOP. PVLDB 11:2006–2009. https://doi.org/10.14778/3229863.3236246

Rahm E, Nagel WE, Peukert E, Jäkel R, Gärtner F, Stadler PF, Wiegreffe D, Zeckzer D, Lehner W (2019) Big Data competence center ScaDS Dresden/Leipzig: Overview and selected research activities. Datenbank Spektrum 19(1). https://doi.org/10.1007/s13222-018-00303-6

Junghanns M, Petermann A, Teichmann N, Gómez K, Rahm E (2016) Analyzing extended property graphs with Apache Flink. In: Proc. ACM SIGMOD Workshop on Network Data Analytics (NDA). https://doi.org/10.1145/2980523.2980527

Junghanns M, Kiessling M, Averbuch A, Petermann A, Rahm E (2017) Cypher-based graph pattern matching in GRADOOP. In: Proc. 7th Int. Workshop on Graph Data Management Experiences & Systems (GRADES). https://doi.org/10.1145/3078447.3078450

Junghanns M, Petermann A, Rahm E (2017) Distributed grouping of property graphs with GRADOOP. In: Proc. Database systems for Business, Technology and Web (BTW), pp 103–122

Petermann A, Junghanns M, Rahm E (2017) DIMSpan: Transactional frequent subgraph mining with distributed in-memory dataflow systems. In: Proc. 4th IEEE/ACM Int. Conf. on Big Data Computing, Applications and Technologies (BDCAT), pp 237–246 https://doi.org/10.1145/3148055.3148064

Berthold MR, Cebron N, Dill F, Gabriel TR, Kötter T, Meinl T, Ohl P, Thiel K, Wiswedel B (2009) KNIME-the Konstanz information miner: version 2.0 and beyond. ACM SIGKDD Explor Newsl 11(1):26–31. https://doi.org/10.1145/1656274.1656280 CrossRef

10.

Ludäscher B, Altintas I, Berkley C, Higgins D, Jaeger E, Jones M, Lee EA, Tao J, Zhao Y (2006) Scientific workflow management and the Kepler system: Research articles. Concurr Comput Pract Exper 18(10):1039–1065. https://doi.org/10.1002/cpe.994 CrossRef

11.

Hofmann M, Klinkenberg R (2013) Rapidminer: data mining use cases and business analytics applications. Chapman & Hall/CRC, Boca Raton, FL

12.

Afgan E, Baker D, van den Beek M, Blankenberg D, Bouvier D, Cech M, Chilton J, Clements D, Coraor N, Eberhard C, Grüning BA, Guerler A, Hillman-Jackson J, Kuster GV, Rasche E, Soranzo N, Turaga N, Taylor J, Nekrutenko A, Goecks J (2016) The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res. https://doi.org/10.1093/nar/gkw343

13.

da Silva RF, Filgueira R, Pietri I, Jiang M, Sakellariou R, Deelman E (2017) A characterization of workflow management systems for extreme-scale applications. Future Gener Comput Syst. https://doi.org/10.1016/j.future.2017.02.026

14.

Wolstencroft K, Haines R, Fellows D, Williams A, Withers D, Owen S, Soiland-Reyes S, Dunlop I, Nenadic A, Fisher P, Bhagat J, Belhajjame K, Bacall F, Hardisty A, Nieva de la Hidalga A, Balcazar Vargas M, Sufi S, Goble C (2013) The Taverna workflow suite: designing and executing workflows of web services on the desktop, web or in the cloud. Nucleic Acids Res 41:W557–561. https://doi.org/10.1093/nar/gkt328 CrossRef

15.

Grunzke R, Jug F, Schuller B, Jäkel R, Myers G, Nagel WE (2016) Seamless HPC integration of data-intensive KNIME workflows via UNICORE. In: Euro-Par Workshops. Lecture Notes in Computer Science, vol 10104. Springer, Berlin, Heidelberg, pp 480–491 https://doi.org/10.1007/978-3-319-58943-5-39

16.

Riazi S, Norris B (2016) Graphflow: Workflow-based big graph processing. In: 2016 IEEE Int. Conf. on Big Data, pp 3336–3343 https://doi.org/10.1109/BigData.2016.7840993 CrossRef

17.

Riazi S (2016) SparkGalaxy: Workflow-based Big Data processing. http://www.cs.uoregon.edu/Reports/DRP-201603-Riazi.pdf. Accessed 1 Mar 2019 (directed Research Proposal)

18.

Herman I, Melançon G, Marshall MS (2000) Graph visualization and navigation in information visualization: a survey. IEEE Trans Vis Comput Graph 6(1):24–43. https://doi.org/10.1109/2945.841119 CrossRef

19.

Bikakis N, Sellis TK (2016) Exploration and visualization in the web of big linked data: a survey of the state of the art. CoRR abs/1601.08059

20.

Caldarola EG, Picariello A, Rinaldi A, Sacco M (2016) Exploration and visualization of big graphs – the DBpedia case study. In: Proc. 8th Int. Conf. on Knowledge Discovery, Knowledge Engineering and Knowledge Management (KDIR) https://doi.org/10.5220/0006046802570264

21.

Jugel U, Jerzak Z, Hackenbroich G, Markl V (2016) VDDA: automatic visualization-driven data aggregation in relational databases. VLDB J 25(1):53–77. https://doi.org/10.1007/s00778-015-0396-z CrossRef

22.

Rodriguez M, Neubauer P (2010) Constructions from dots and lines. Bull Am Soc Inf Sci Technol 36(6):35–41CrossRef

23.

Rodriguez M, Neubauer P (2012) The graph traversal pattern. In: Graph Data Management: Techniques and Applications IGI Global, pp 29–46CrossRef

24.

Kricke M, Peukert E, Rahm E (2019) Graph data transformations in gradoop. Proc BTW conf.

25.

Hudak P (1989) Conception, evolution, and application of functional programming languages. ACM Comput Surv 21(3):359–411. https://doi.org/10.1145/72551.72554 CrossRef

26.

Seidman SB (1983) Network structure and minimum degree. Soc Networks 5(3):269–287MathSciNetCrossRef

27.

Giatsidis C, Malliaros FD, Tziortziotis N, Dhanjal C, Kiagias E, Thilikos DM, Vazirgiannis M (2016) A k-core decomposition framework for graph clustering. CoRR abs/1607.02096

28.

Hu P, Lau WC (2013) A survey and taxonomy of graph sampling. CoRR abs/1308.5865

29.

Rostami MA, Saeedi A, Peukert E, Rahm E (2018) Interactive visualization of large similarity graphs and entity resolution clusters. In: Proc. Extending Database Technology (EDBT) https://doi.org/10.5441/002/edbt.2018.86

30.

Kobourov SG (2012) Spring embedders and force directed graph drawing algorithms. Computing Research Repository (CoRR) abs/1201.3011

Title: BIGGR: Bringing Gradoop to Applications
Authors: M. Ali Rostami
Matthias Kricke
Eric Peukert
Stefan Kühne
Moritz Wilke
Steffen Dienst
Erhard Rahm
Publication date: 14-02-2019
Publisher: Springer Berlin Heidelberg
Published in: Datenbank-Spektrum / Issue 1/2019
Print ISSN: 1618-2162
Electronic ISSN: 1610-1995
DOI: https://doi.org/10.1007/s13222-019-00306-x

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Datenbank-Spektrum

Other articles of this Issue 1/2019

Big Data Competence Center ScaDS Dresden/Leipzig: Overview and selected research activities

Die Arbeitsgruppe Datenbanken und Informationssysteme an der TU Dortmund

ScaDS Research on Scalable Privacy-preserving Record Linkage

Wie funktioniert die Blockchain?

Dissertationen

Editorial

Premium Partner