scholarly journals Distributed Query Evaluation over Encrypted Data

2021 ◽  
pp. 96-114
Author(s):  
Sabrina De Capitani di Vimercati ◽  
Sara Foresti ◽  
Sushil Jajodia ◽  
Giovanni Livraga ◽  
Stefano Paraboschi ◽  
...  
Keyword(s):  
Query Evaluation ◽  
Encrypted Data ◽  
Distributed Query

Database Principles and Challenges in Text Analysis

2021 ◽  
Vol 50 (2) ◽  
pp. 6-17
Author(s):  
Johannes Doleschal ◽  
Benny Kimelfeld ◽  
Wim Martens
Keyword(s):  
Text Analysis ◽  
Relational Databases ◽  
Query Evaluation ◽  
Text Documents ◽  
Step Process ◽  
Distributed Query ◽  
Recent Advances ◽  
Aggregate Queries ◽  
Technical Challenges ◽  
Query Planning

A common conceptual view of text analysis is that of a two-step process, where we first extract relations from text documents and then apply a relational query over the result. Hence, text analysis shares technical challenges with, and can draw ideas from, relational databases. A framework that formally instantiates this connection is that of the document spanners. In this article, we review recent advances in various research efforts that adapt fundamental database concepts to text analysis through the lens of document spanners. Among others, we discuss aspects of query evaluation, aggregate queries, provenance, and distributed query planning.

Authorization enforcement in distributed query evaluation*

2011 ◽  
Vol 19 (4) ◽  
pp. 751-794 ◽  
Author(s):  
Sabrina De Capitani di Vimercati ◽  
Sara Foresti ◽  
Sushil Jajodia ◽  
Stefano Paraboschi ◽  
Pierangela Samarati
Keyword(s):  
Query Evaluation ◽  
Distributed Query

Reasoning on the Efficiency of Distributed Complex Event Processing

2021 ◽  
Vol 179 (2) ◽  
pp. 113-134
Author(s):  
Samira Akili ◽  
Matthias Weidlich
Keyword(s):  
High Frequency ◽  
Complex Event Processing ◽  
Data Sources ◽  
Event Processing ◽  
Query Evaluation ◽  
Query Execution ◽  
Event Data ◽  
Distributed Query ◽  
Geographically Distributed ◽  
Network Costs

Complex event processing (CEP) evaluates queries over streams of event data to detect situations of interest. If the event data are produced by geographically distributed sources, CEP may exploit in-network processing that distributes the evaluation of a query among the nodes of a network. To this end, a query is modularized and individual query operators are assigned to nodes, especially those that act as data sources. Existing solutions for such operator placement, however, are limited in that they assume all query results to be gathered at one designated node, commonly referred to as a sink. Hence, existing techniques postulate a hierarchical structure of the network that generates and processes the event data. This largely neglects the optimisation potential that stems from truly decentralised query evaluation with potentially many sinks. To address this gap, in this paper, we propose Multi-Sink Evaluation (MuSE) graphs as a formal computational model to evaluate common CEP queries in a decentralised manner. We further prove the completeness of query evaluation under this model. Striving for distributed CEP that can scale to large volumes of high-frequency event streams, we show how to reason on the network costs induced by distributed query evaluation and prune inefficient query execution plans. As such, our work lays the foundation for distributed CEP that is both, sound and efficient.

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