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ZipG
2017
Proceedings of the 2017 ACM International Conference on Management of Data - SIGMOD '17
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We present ZipG, a distributed memory-efficient graph store for serving interactive graph queries. ZipG achieves memory efficiency by storing the input graph data using a compressed representation. ...
ZipG can thus execute a larger fraction of queries in main memory, achieving query interactivity. ...
We present ZipG -a memory-efficient, distributed graph store for efficiently serving interactive graph queries. ...
doi:10.1145/3035918.3064012
dblp:conf/sigmod/KhandelwalYY0S17
fatcat:d7ouljqbgza2lehoshuf37npua
Practice of Streaming Processing of Dynamic Graphs: Concepts, Models, and Systems
[article]
2021
arXiv
pre-print
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However, they differ in their general architectures (with key details such as the support for the concurrent execution of graph updates and queries, or the incorporated graph data organization), the types ...
Moreover, we provide a bridge with the very rich landscape of graph streaming theory by giving a broad overview of recent theoretical related advances, and by discussing which graph streaming models and ...
We thank PRODYNA AG (Darko Križić, Jens Nixdorf, and Christoph K örner) for generous support, and anonymous reviewers for comments that helped to significantly enhance the paper quality. ...
arXiv:1912.12740v4
fatcat:no647uyvbzgnvpdpmmmoxao2xm
Columnar Storage and List-based Processing for Graph Database Management Systems
[article]
2021
arXiv
pre-print
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We first derive a set of desiderata for optimizing storage and query processors of GDBMS based on their access patterns. ...
We revisit column-oriented storage and query processing techniques in the context of contemporary graph database management systems (GDBMSs). ...
We thank the anonymous reviewers for their valuable comments. ...
arXiv:2103.02284v2
fatcat:57nkckqv5zceni4yz5d47xfvtu
Survey and Taxonomy of Lossless Graph Compression and Space-Efficient Graph Representations
[article]
2019
arXiv
pre-print
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Compressing such datasets can accelerate graph processing by reducing the amount of I/O accesses and the pressure on the memory subsystem. ...
., compressing web graphs), techniques (e.g., gap encoding), and features (e.g., whether or not a given scheme targets dynamic graphs). ...
ACKNOWLEDGEMENTS We thank Olivier Devillers, Hsueh-I Lu, Miguel A. Martínez Prieto, Luca Castelli Aleardi, Gonzalo Navarro, and Sebastiano Vigna for their insightful comments. ...
arXiv:1806.01799v2
fatcat:r7lvpwok4neyrinmpomx4g6cca