Implementing Graph Transformations in the Bulk Synchronous Parallel Model
Paper i proceeding, 2015

Big data becomes a challenge in more and more domains. In many areas, such as in social networks, the entities of interest have relational references to each other and thereby form large-scale graphs (in the order of billions of vertices). At the same time, querying and updating these data structures is a key requirement. Complex queries and updates demand expressive high-level languages which can still be efficiently executed on these large-scale graphs.We use graph transformation rules and units as a high-level modeling language with declarative and operational features for transforming graph structures. To apply them to large-scale graphs, we introduce a method to distribute and parallelize graph transformations by mapping them to the Bulk Synchronous Parallel model. Our tool support builds on Henshin as modeling tool and consists of a code generator for Apache Giraph. We evaluated our approach with the IMDb movie database on a cluster with 24 servers with 8 cores each.

Författare

Christian Krause

SAP SE

Matthias Tichy

Chalmers, Data- och informationsteknik, Software Engineering

Göteborgs universitet

Holger Giese

Hasso-Plattner-Institut fur Softwaresystemtechnik GmbH

Lecture Notes in Informatics

1617-5468 (ISSN)

Vol. P-239 99-100
9783885796336 (ISBN)

Software Engineering and Management 2015: Multikonferenz der GI-Fachbereiche Softwaretechnik (SWT) und Wirtschaftsinformatik (WI), FA WI-MAW - Software Engineering and Management 2015: Multiconference of the GI Special Interest Groups Software Engineering (SWT) and Information Systems (WI), FA WI-MAW
Dresden, Germany,

Ämneskategorier

Annan data- och informationsvetenskap

Datavetenskap (datalogi)

Datorsystem

ISBN

9783885796336

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2022-08-04