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DatalogRA
2016
Proceedings of the Fourth International Workshop on Graph Data Management Experiences and Systems - GRADES '16
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Distributed computations on graphs are becoming increasingly important with the emergence of large graphs such as social networks and the Web that contain huge amounts of useful information. ...
This approach makes it possible to express graph algorithms in a declarative query language, accessible to a broader group of users than typical programming languages, and execute them on an existing infrastructure ...
Figure 3 : 3 Results of experiments.
Table 1 : 1 Number of lines of code in programs, excluding data loading and comments. ...
doi:10.1145/2960414.2960417
dblp:conf/grades/RogalaHS16
fatcat:qxapxoz2znfihawt3l3ujtwudy
Evaluation of parallel graph loading techniques
2016
Proceedings of the Fourth International Workshop on Graph Data Management Experiences and Systems - GRADES '16
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For many exploratory graph workloads, the initial loading and construction of the graph data structures makes up a significant part of the total runtime. ...
Still, this topic is hardly analyzed in literature and often neglected in systems and their evaluations. ...
Experiment Setup We implemented the presented graph loading techniques in C++14 and compiled them using GCC 5.2.1. ...
doi:10.1145/2960414.2960418
dblp:conf/grades/ThenKK016
fatcat:zrshwdodf5h5nkkzwwvsbygq3y
ASGraph
2016
Proceedings of the Fourth International Workshop on Graph Data Management Experiences and Systems - GRADES '16
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In the last years researchers and industry have become interested in the analysis of graphs to gain insights into social networks, road networks, and other data that is naturally organized as a set of ...
Meanwhile it outperforms CSR both in runtime and memory consumption in scenarios where a graph is repeatedly updated between analysis. ...
In the past the general trend when handling large amounts of data has been to use separate systems that are either optimized for updates or analytics. ...
doi:10.1145/2960414.2960422
dblp:conf/grades/HaubenschildTHC16
fatcat:qvlhuw7jszgg3nwcl7inawquh4
Entropy-based Selection of Graph Cuboids
2017
Proceedings of the Fifth International Workshop on Graph Data-management Experiences & Systems - GRADES'17
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Emerging applications face the need to store and analyze interconnected data that are naturally depicted as graphs. ...
Recent proposals take the idea of data cubes that have been successfully applied to multidimensional data and extend them to work for interconnected datasets. ...
In the following experiments we compute the Iceberg graph cube, for di erent values of minimum support and then, we adjust the internal entropy rate threshold so as to retain the same number of graph cube ...
doi:10.1145/3078447.3078449
dblp:conf/grades/BlecoK17
fatcat:ny7piwnn6fh3znfikrv5frvdzq
Time-evolving graph processing at scale
2016
Proceedings of the Fourth International Workshop on Graph Data Management Experiences and Systems - GRADES '16
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However, existing graph processing systems lack support for efficient computations on dynamic graphs. ...
Introduction Graph-structured data is on the rise, in size, complexity and the dynamism they exhibit. ...
Building a time-evolving graph processing system with all desired properties is challenging and requires managing many tasks. ...
doi:10.1145/2960414.2960419
dblp:conf/grades/IyerLDS16
fatcat:tks4gkhimzhtzocriqu3vxwrle
PGQL
2016
Proceedings of the Fourth International Workshop on Graph Data Management Experiences and Systems - GRADES '16
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Such a graph query language needs not only SQL-like functionality for querying structured data, but also intrinsic support for typical graph-style applications: reachability analysis, path finding and ...
Graph-based approaches to data analysis have become more widespread, which has given need for a query language for graphs. ...
ACKNOWLEDGMENTS We thank our team members from Oracle Labs Parallel Graph Analytics (PGX) as well as the teams behind Oracle Big Data Spatial and Graph, Oracle Labs Frappé, Sparsity Technologies and LDBC's ...
doi:10.1145/2960414.2960421
dblp:conf/grades/RestHKMC16
fatcat:opjvu2ae3rdqtixjirwootg3ge
SPARQL Graph Pattern Processing with Apache Spark
2017
Proceedings of the Fifth International Workshop on Graph Data-management Experiences & Systems - GRADES'17
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Processing basic graph pattern (BGP) expressions generating large join plans over distributed data partitions is a major challenge in these frameworks. ...
We compare five possible implementation and illustrate the importance of cautiously choosing the physical data storage layer and of the possibility to use both join algorithms to efficiently take account ...
All DF based methods (SPARQL DF, SQL and Hybrid DF) use data compression and allow for managing ten times larger data sets than RDD, at equal memory capacity. ...
doi:10.1145/3078447.3078448
dblp:conf/grades/NaackeAC17
fatcat:yi4z2tmprzdvlkgwpebrujgkgy
GraphFrames
2016
Proceedings of the Fourth International Workshop on Graph Data Management Experiences and Systems - GRADES '16
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GraphFrames generalize the ideas in previous graph-on-RDBMS systems, such as GraphX and Vertexica, by letting the system materialize multiple views of the graph (not just the specific triplet views in ...
We present GraphFrames, an integrated system that lets users combine graph algorithms, pattern matching and relational queries, and optimizes work across them. ...
Graph-Parallel Programming Standalone systems including Pregel and GraphLab [12, 11] have been designed to run graph algorithms, but they require separate data export and import and thus make end-to-end ...
doi:10.1145/2960414.2960416
dblp:conf/grades/DaveJLXGZ16
fatcat:i3jegtzpn5hwvc4iofmndfwvku
Do We Need Specialized Graph Databases?
2017
Proceedings of the Fifth International Workshop on Graph Data-management Experiences & Systems - GRADES'17
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Social networking applications pose new challenges to data management systems due to demand for real-time querying and manipulation of the graph structure. ...
Recently, several systems specialized systems for graph-structured data have been introduced. ...
ACKNOWLEDGMENTS This research was supported by multiple Discovery Grants from the Natural Sciences and Engineering Research Council (NSERC) of Canada. ...
doi:10.1145/3078447.3078459
dblp:conf/grades/PacaciZLO17
fatcat:d3v735oe5rfwhlcg6jei4rq3ti
DynaGraph
2022
Proceedings of the 5th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)
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In this paper, we present DynaGraph, a system that supports dynamic Graph Neural Networks (GNNs) efficiently. ...
It further proposes a simple distributed data-parallel dynamic graph processing strategy that enables scalable dynamic GNN computation. ...
and PyG Temporal for this experiment. ...
doi:10.1145/3534540.3534691
fatcat:otsx5wfjxvbmja4g2btvshh2dm
Granula
2017
Proceedings of the Fifth International Workshop on Graph Data-management Experiences & Systems - GRADES'17
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In this work, we propose Granula, a performance analysis system for Big Data platforms that focuses on graph processing. ...
To cope with the data deluge, existing Big Data platforms require significant conceptual and engineering advances. ...
, occupation of computing and data infrastructure during experiments, and generation of large volumes of empirical data than must later be processed and further understood. ...
doi:10.1145/3078447.3078455
dblp:conf/grades/NgaiHHI17
fatcat:y6lxqnhbsrgzjdronauexqtroy
Experiences with Implementing Landmark Embedding in Neo4j
2019
Proceedings of the 2nd Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA) - GRADES-NDA'19
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Reachability, distance, and shortest path queries are fundamental operations in the field of graph data management with various applications in research and industry. ...
However, while various preprocessing-based methods have been proposed to optimize the computation of such queries, the integration of existing methods into graph database management systems and processing ...
of graph data. ...
doi:10.1145/3327964.3328496
dblp:conf/grades/HotzCWG19
fatcat:lkj5qqkbp5fpdf2b7tjnfgnrjy
Cypher-based Graph Pattern Matching in Gradoop
2017
Proceedings of the Fifth International Workshop on Graph Data-management Experiences & Systems - GRADES'17
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Graph pa ern matching is an important and challenging operation on graph data. Typical use cases are related to graph analytics. ...
Using LDBC graph data, we show that our query engine is scalable for operational as well as analytical workloads. e implementation is open-source and easy to extend for further research. ...
An established solution to manage and query graph data is using a graph database system such as Neo4j [18] . ese systems provide exible data models to t di erent application domains and o er declarative ...
doi:10.1145/3078447.3078450
dblp:conf/grades/JunghannsKAPR17
fatcat:gpmpjqjgprdfvnnldiq6loc64i
Can Modern Graph Processing Engines Run Concurrent Queries Efficiently?
2017
Proceedings of the Fifth International Workshop on Graph Data-management Experiences & Systems - GRADES'17
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We perform an extensive evaluation of Galois for various graph algorithms and data sets to gain a fundamental understanding of the performance bo lenecks of existing graph engines. ...
CCS CONCEPTS •Information systems →Online analytical processing engines; •General and reference →Performance; • eory of computation →Graph algorithms analysis; KEYWORDS Concurrent query processing, Graph ...
INTRODUCTION Analytic graph processing has witnessed a widespread adoption across multiple application domains, including social media, health care, transportation management, and telecommunication. ...
doi:10.1145/3078447.3078452
dblp:conf/grades/HauckPF17
fatcat:lwn5xdqstrghdke6upvkb5mmxi
Leveraging flexible data management with graph databases
2013
First International Workshop on Graph Data Management Experiences and Systems - GRADES '13
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In this paper, we will provide our vision of such a system and describe an extension of the well-studied property graph model that allows to "integrate and analyze as you go" external data exposed in the ...
What we need is a system which 1) provides a flexible storage of heterogeneous information of different degrees of structure in an ad-hoc manner, and 2) supports mass data operations suited for data analytics ...
In comparison, our system works with two different models (RDF and AIS graph data model). ...
doi:10.1145/2484425.2484437
dblp:conf/sigmod/VasilyevaTBL13
fatcat:ganlepwvz5dkfam74xzfjttnm4
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