Using Global Information for Load Balancing in DHTs

Högqvist, Mikael; Haridi, Seif; Kruber, Nico; Reinefeld, Alexander; Schütt, Thorsten

doi:10.1109/sasow.2008.50

Cited by 3 publications

(1 citation statement)

References 16 publications

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“…In more detail, the stronger physical server will split into more virtual nodes. However, some systems (e.g., Apache Cassandra) put a limit on the number of virtual nodes as they have several side-eects [63] such as increased agitation due to the failure of a physical node and increasing state maintenance. Some NoSQL stores, such as Apache Cassandra, Amazon Dynamo [58], Riak KV 15 and Microsoft Trinity [64], use this strategy.…”

Section: Key-oriented Static Partitioningmentioning

confidence: 99%

A Workload-Driven Framework for NoSQL Data Modeling and Partitioning

Davoudian¹

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Due to the scalability problems in traditional relational database systems, a variety of NoSQL stores have emerged over the last decade to deal with big data. The lack of standard processes for designing and partitioning NoSQL datasets, as two non-orthogonal principles of distributed database systems, has led to the proposal of several recent methods. On the one hand, the existing design methods provide various conceptual modeling notations and mainly target a particular NoSQL data model that cause extra eort for designers when switching from one data model to another. Also, by providing just a set of guidelines and heuristics for the design process, many methods have to be applied manually which is an error-prone and time-consuming process. To deal with these limitations, we present a novel method for designing key-value, wide-column, and document NoSQL database schemas from the same conceptual model. It rst generates a generic NoSQL logical schema from the conceptual model and query workload of the system. Then it converts the generic schema to the schemas of targeted NoSQL data models regarding their important features and design trade-os between the read query performance and storage overhead or consistency maintenance.On the other hand, the existing graph partitioning strategies are mostly workloadagnostic, as they presume the same probability of traversing edges or visiting vertices, which does not always hold with dierent query workloads. In addition, they are mostly graph topology-agnostic, as they do not dierentiate between high-degree ii and low-degree vertices. Furthermore, many existing workload-aware strategies are unable to adapt to dynamic workloads. To address these limitations, we present a novel workload-adaptive and topology-driven approach named Helios, that aims to achieve low-latency and high-throughput online graph queries. In order to assess the impact of Helios on a graph store and to show how easily the approach can be plugged on top of the system, we exploit it in a distributed graph-based RDF store.

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Section: Key-oriented Static Partitioningmentioning

confidence: 99%

A Workload-Driven Framework for NoSQL Data Modeling and Partitioning

Davoudian¹

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A Fully Decentralized File System Cache for the CernVM-FS

Blomer

Fuhrmann

2010

2010 Proceedings of 19th International Conference on Computer Communications and Networks

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A Survey on NoSQL Stores

2018

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Recent demands for storing and querying big data have revealed various shortcomings of traditional relational database systems. This, in turn, has led to the emergence of a new kind of complementary nonrelational data store, named as NoSQL. This survey mainly aims at elucidating the design decisions of NoSQL stores with regard to the four nonorthogonal design principles of distributed database systems: data model, consistency model, data partitioning, and the CAP theorem. For each principle, its available strategies and corresponding features, strengths, and drawbacks are explained. Furthermore, various implementations of each strategy are exemplified and crystallized through a collection of representative academic and industrial NoSQL technologies. Finally, we disclose some existing challenges in developing effective NoSQL stores, which need attention of the research community, application designers, and architects.

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Using Global Information for Load Balancing in DHTs

Cited by 3 publications

References 16 publications

A Workload-Driven Framework for NoSQL Data Modeling and Partitioning

A Workload-Driven Framework for NoSQL Data Modeling and Partitioning

A Fully Decentralized File System Cache for the CernVM-FS

A Survey on NoSQL Stores

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