Decentralized Indexing over a Network of RDF Peers

Aebeloe, Christian; Montoya, Gabriela; Hose, Katja

doi:10.1007/978-3-030-30793-6_1

Cited by 9 publications

(37 citation statements)

References 20 publications

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“…However, even if P2P systems increase the availability of datasets, they are vulnerable to churn (when nodes frequently leave and join the network) [6,12] or can cause very high network traffic [3] (when queries have large numbers of intermediate results). In any case, Star Pattern Fragments (SPF) are orthogonal to P2P systems.…”

Section: Related Workmentioning

confidence: 99%

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Star Pattern Fragments: Accessing Knowledge Graphs through Star Patterns

Aebeloe¹,

Keleş²,

Montoya³

et al. 2020

Preprint

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The Semantic Web offers access to a vast Web of interlinked information accessible via SPARQL endpoints. Such endpoints offer a well-defined interface to retrieve results for complex SPARQL queries. The computational load for processing such queries, however, lies entirely with the server hosting the SPARQL endpoint, which can easily become overloaded and in the worst case not only become slow in responding but even crash so that the data becomes temporarily unavailable. Recently proposed interfaces, such as Triple Pattern Fragments, have therefore shifted the query processing load from the server to the client. For queries involving triple patterns with low selectivity, this can easily result in high network traffic and slow execution times. In this paper, we therefore present a novel interface, Star Pattern Fragments (SPF), which decomposes SPARQL queries into star-shaped subqueries and can combine a lower network load with a higher query throughput and a comparatively low server load. Our experimental results show that our approach does not only significantly reduce network traffic but is also at least an order of magnitude faster in comparison to the state-of-the-art interfaces under high query processing load.

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Section: Related Workmentioning

confidence: 99%

“…In any case, Star Pattern Fragments (SPF) are orthogonal to P2P systems. For example, [3] could be extended with SPF to achieve a similar reduction of intermediate results as described in Section 6.…”

Section: Related Workmentioning

confidence: 99%

Star Pattern Fragments: Accessing Knowledge Graphs through Star Patterns

Aebeloe¹,

Keleş²,

Montoya³

et al. 2020

Preprint

Self Cite

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“…With this detailed study and the derived guidelines, we aim at paving the way towards an ultimate solution for this problem. In this sense, we envision archiving solutions to not only serve as standalone single server systems but also as components of the RDF ecosystem on the Web in all its flavors covering federated [1,52,65,70] and clientserver architectures [2,10,11,38,50,51,80] as well as peer-to-peer [3,4] solutions.…”

Section: Discussionmentioning

confidence: 99%

“…In the light of the evolution of real-world RDF data, we then survey the strengths and weaknesses of the different stateof-the-art solutions in Section 5 (contribution 3). Section 6 addresses contribution (4). The insights from the previous sections are then used to drive the sketch of an optimal RDF archiving system in Section 7, which addresses contribution (5).…”

Section: Introductionmentioning

confidence: 99%

Towards fully-fledged archiving for RDF datasets

Pelgrin

Galárraga

Hose

2021

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The dynamicity of RDF data has motivated the development of solutions for archiving, i.e., the task of storing and querying previous versions of an RDF dataset. Querying the history of a dataset finds applications in data maintenance and analytics. Notwithstanding the value of RDF archiving, the state of the art in this field is under-developed: (i) most existing systems are neither scalable nor easy to use, (ii) there is no standard way to query RDF archives, and (iii) solutions do not exploit the evolution patterns of real RDF data. On these grounds, this paper surveys the existing works in RDF archiving in order to characterize the gap between the state of the art and a fully-fledged solution. It also provides RDFev, a framework to study the dynamicity of RDF data. We use RDFev to study the evolution of YAGO, DBpedia, and Wikidata, three dynamic and prominent datasets on the Semantic Web. These insights set the ground for the sketch of a fully-fledged archiving solution for RDF data.

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“…For instance, due to the lack of global knowledge over the network, basic P2P systems have to flood the network with requests for a given horizon to increase the likelyhood of receiving complete query results. To counteract this, distributed indexes [5,20,66] like Prefix-Partitioned Bloom Filter (PPBF) indexes [5] determine which nodes may include relevant data for a given query and thus allow the system to prune nodes from consideration during query optimization. Yet, the aforementioned systems still experience a significant overhead partly caused by inaccurate cardinality estimations, query optimization that does not consider the locality of data, as well as data fragmentation that splits up closely related data.…”

Section: Peer-to-peer Systemsmentioning

confidence: 99%

Optimizing SPARQL queries over decentralized knowledge graphs

Aebeloe

Montoya

Hose

2023

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While the Web of Data in principle offers access to a wide range of interlinked data, the architecture of the Semantic Web today relies mostly on the data providers to maintain access to their data through SPARQL endpoints. Several studies, however, have shown that such endpoints often experience downtime, meaning that the data they maintain becomes inaccessible. While decentralized systems based on Peer-to-Peer (P2P) technology have previously shown to increase the availability of knowledge graphs, even when a large proportion of the nodes fail, processing queries in such a setup can be an expensive task since data necessary to answer a single query might be distributed over multiple nodes. In this paper, we therefore propose an approach to optimizing SPARQL queries over decentralized knowledge graphs, called Lothbrok. While there are potentially many aspects to consider when optimizing such queries, we focus on three aspects: cardinality estimation, locality awareness, and data fragmentation. We empirically show that Lothbrok is able to achieve significantly faster query processing performance compared to the state of the art when processing challenging queries as well as when the network is under high load.

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Decentralized Indexing over a Network of RDF Peers

Cited by 9 publications

References 20 publications

Star Pattern Fragments: Accessing Knowledge Graphs through Star Patterns

Star Pattern Fragments: Accessing Knowledge Graphs through Star Patterns

Towards fully-fledged archiving for RDF datasets

Optimizing SPARQL queries over decentralized knowledge graphs

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