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Relevant Query Answering over Streaming and Distributed Data pp 41–54Cite as

Handling Queries with a FILTER Clause

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Part of the book series: SpringerBriefs in Applied Sciences and Technology ((BRIEFSPOLIMI))

Abstract

This chapter extends the ACQUA proposal presented in Chap. 3. It presents ACQUA.F, a new maintenance policy for an extended class of queries: the one that joins streaming data with the distributed data, and contains a filter constrain on distributed data. In addition, it explains how to combine this policy with the one proposed in the previous chapter. Finally, a set of experimental evaluations shows how the proposed policies guarantee reactiveness while keeping the replica fresh.

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Notes

  1. 1.

    100 ms is the average response time of the REST APIs of Twitter that returns the information of a user given his/her ID. For more information see https://dev.twitter.com/rest/reference/get/users/lookup.

  2. 2.

    http://www.w3.org/TR/sparql11-federated-query/.

  3. 3.

    The wording smoothly changes over time means if \(?x=98\) in the previous evaluation and \(?x=101\) in the current evaluation, in next evaluation it is more likely that \(?x=99\) than jumping to \(?x=1000\).

  4. 4.

    The value of the Filtering Threshold is chosen to guarantee that no one of the original time-series crosses it.

  5. 5.

    Later, in the next chapter, it is found that determining the band a priori is not straightforward.

References

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Authors and Affiliations

  1. DEIB, Politecnico di Milano, Milano, Italy

    Shima Zahmatkesh & Emanuele Della Valle

Authors
  1. Shima Zahmatkesh
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  2. Emanuele Della Valle
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Correspondence to Shima Zahmatkesh .

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Zahmatkesh, S., Della Valle, E. (2020). Handling Queries with a FILTER Clause. In: Relevant Query Answering over Streaming and Distributed Data. SpringerBriefs in Applied Sciences and Technology(). Springer, Cham. https://doi.org/10.1007/978-3-030-38339-8_4

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  • DOI: https://doi.org/10.1007/978-3-030-38339-8_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-38338-1

  • Online ISBN: 978-3-030-38339-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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