Open AccessBook Chapter10.1007/978-3-540-85451-7_67

Efficient Processing of Continuous Join Queries Using Distributed Hash Tables

- 26 Aug 2008

- pp 632-641

TL;DR: This paper presents a new method, called DHTJoin, which combines hash-based placement of tuples in a Distributed Hash Table (DHT) and dissemination of queries using a gossip style protocol and shows that DHT join can achieve significant performance gains in terms of network traffic.

Abstract: This paper addresses the problem of computing approximate answers to continuous join queries. We present a new method, called DHTJoin, which combines hash-based placement of tuples in a Distributed Hash Table (DHT) and dissemination of queries using a gossip style protocol. We provide a performance evaluation of DHTJoin which shows that DHTJoin can achieve significant performance gains in terms of network traffic.

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1. What are the contributions mentioned in the paper "Efficient processing of continuous join queries using distributed hash tables" ?

This paper addresses the problem of computing approximate answers to continuous join queries.. The authors present a new method, called DHTJoin, which combines hash-based placement of tuples in a Distributed Hash Table ( DHT ) and dissemination of queries using a gossip style protocol.. The authors provide a performance evaluation of DHTJoin which shows that DHTJoin can achieve significant performance gains in terms of network traffic.

2. What have the authors stated for future works in "Efficient processing of continuous join queries using distributed hash tables" ?

As future work, the authors plan to address the problem of efficient execution of top-k join queries over data streams using DHTs taking advantage of the best position algorithms [ 2 ] which can be used in many distributed and P2P systems for efficient processing of top-k queries.

Figure 5 Speed of dissemination Figure 6 Message Overhead

Figure 3 Effect of Number of Joins Figure 4 Dissemination progress

Figure 1 Effect of Tuples Arrival Rate Figure 2 Effect of Query Arrival Rate

Citations

Journal Article•10.1016/J.JPDC.2017.06.016

Improving the robustness and performance of parallel joins over distributed systems

Long Cheng, +4 more

- 01 Nov 2017

- Journal of Parallel and Distributed Comp...

TL;DR: A new method called PRPQ (partial redistribution & partial query), with targets for efficient and robust joins with large datasets over high performance clusters, is proposed, which is scalable and robust and can outperform the state-of-the-art approach with less network communication.

...read moreread less

Proceedings Article•10.1145/1698790.1698798

Distributed processing of continuous join queries using DHT networks

Wenceslao Palma, +3 more

- 22 Mar 2009

TL;DR: A new method, called DHTJoin, is presented, which combines hash-based placement of tuples in a Distributed Hash Table (DHT) and dissemination of queries exploiting the trees formed by the underlying DHT links.

...read moreread less

•Dissertation

Parallel Techniques for Big Data Analytics

Reza Akbarinia

- 24 May 2019

TL;DR: The experimental results show that by using the parallel technique, the indexing and mining of very large volumes of time series can now be done in very small execution times, which are impossible to achieve using traditional centralized approaches.

...read moreread less

P2P Join Query Processing over Data Streams

Wenceslao Palma, +3 more

- 20 Oct 2009

TL;DR: A new method is presented that exploits the power of a Distributed Hash Table (DHT) combining hash-based placement of tuples and dissemination of queries by exploiting the embedded trees in the underlying DHT, thereby incuring little overhead.

...read moreread less

•Journal Article•10.1007/S10619-009-7054-7

DHTJoin: processing continuous join queries using DHT networks

Wenceslao Palma, +3 more

- 01 Dec 2009

- Distributed and Parallel Databases

TL;DR: A new method is presented, called DHTJoin, which combines hash-based placement of tuples in a Distributed Hash Table (DHT) and dissemination of queries by exploiting the embedded trees in the underlying DHT, thereby incurring little overhead.

...read moreread less

References

Proceedings Article•10.1145/383059.383071

Chord: A scalable peer-to-peer lookup service for internet applications

Ion Stoica, +4 more

- 27 Aug 2001

TL;DR: Results from theoretical analysis, simulations, and experiments show that Chord is scalable, with communication cost and the state maintained by each node scaling logarithmically with the number of Chord nodes.

...read moreread less

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•Proceedings Article•10.1145/383059.383072

A scalable content-addressable network

Sylvia Ratnasamy, +4 more

- 27 Aug 2001

TL;DR: The concept of a Content-Addressable Network (CAN) as a distributed infrastructure that provides hash table-like functionality on Internet-like scales is introduced and its scalability, robustness and low-latency properties are demonstrated through simulation.

...read moreread less

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•Proceedings Article•10.1145/543613.543615

Models and issues in data stream systems

Brian Babcock, +4 more

- 03 Jun 2002

TL;DR: The need for and research issues arising from a new model of data processing, where data does not take the form of persistent relations, but rather arrives in multiple, continuous, rapid, time-varying data streams are motivated.

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Proceedings Article•10.1145/41840.41841

Epidemic algorithms for replicated database maintenance

Alan J. Demers, +8 more

- 01 Dec 1987

TL;DR: This paper descrikrs several randomized algorit, hms for dist,rihut.ing updates and driving t,he replicas toward consist,c>nc,y.

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2.1K

•Proceedings Article

TelegraphCQ: Continuous Dataflow Processing for an Uncertain World.

Sirish Chandrasekaran, +10 more

- 01 Jan 2003

TL;DR: The next generation Telegraph system, called TelegraphCQ, is focused on meeting the challenges that arise in handling large streams of continuous queries over high-volume, highly-variable data streams and leverages the PostgreSQL open source code base.

...read moreread less

1.2K

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Efficient Processing of Continuous Join Queries Using Distributed Hash Tables

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1. What are the contributions mentioned in the paper "Efficient processing of continuous join queries using distributed hash tables" ?

2. What have the authors stated for future works in "Efficient processing of continuous join queries using distributed hash tables" ?

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Citations

Improving the robustness and performance of parallel joins over distributed systems

Distributed processing of continuous join queries using DHT networks

Parallel Techniques for Big Data Analytics

P2P Join Query Processing over Data Streams

DHTJoin: processing continuous join queries using DHT networks

References

Chord: A scalable peer-to-peer lookup service for internet applications

A scalable content-addressable network

Models and issues in data stream systems

Epidemic algorithms for replicated database maintenance

TelegraphCQ: Continuous Dataflow Processing for an Uncertain World.

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