Materialized view selection for XQuery workloads

Katsifodimos, Asterios; Manolescu, Ioana; Vassalos, Vasilis

doi:10.1145/2213836.2213900

Cited by 17 publications

(14 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many more experiments are described in our technical report [4]. We currently investigate a distributed version of our automatic view selection algorithm [5]. We also consider multiple-level subscriptions, where some views could be filled with data based on lower-level views.…”

Section: Discussionmentioning

confidence: 99%

ViP2P: Efficient XML Management in DHT Networks

Karanasos

Katsifodimos

Manolescu

et al. 2012

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

Abstract. We consider the problem of efficiently sharing large volumes of XML data based on distributed hash table overlay networks. Over the last three years, we have built ViP2P (standing for Views in Peerto-Peer), a platform for the distributed, parallel dissemination of XML data among peers. At the core of ViP2P stand distributed materialized XML views, defined as XML queries, filled in with data published anywhere in the network, and exploited to efficiently answer queries issued by any network peer. ViP2P is one of the very few fully implemented P2P platforms for XML sharing, deployed on hundreds of peers in a WAN. This paper describes the system architecture and modules, and the engineering lessons learned. We show experimental results, showing that our choices, outperf related systems by orders of magnitude in terms of data volumes, network size and data dissemination throughput.

show abstract

Section: Discussionmentioning

confidence: 99%

ViP2P: Efficient XML Management in DHT Networks

Karanasos

Katsifodimos

Manolescu

et al. 2012

Lecture Notes in Computer Science

Self Cite

View full text Add to dashboard Cite

show abstract

“…It has been studied in the context of query optimization, warehouse design, distributed databases, semantic web databases, etc. [17,[21][22][23]. According to [20], view selection is concerned with the selection of views, for a given query workload, from a database that is capable of being stored within the available storage space.…”

Section: View Selectionmentioning

confidence: 99%

A novel quantum-inspired evolutionary view selection algorithm

Kumar¹,

Kumar

2018

Sādhanā

View full text Add to dashboard Cite

A data warehouse (DW) is designed primarily to meet the informational needs of an organization's decision support system. Most queries posed on such systems are analytical in nature. These queries are long and complex, and are posed in an exploratory and ad-hoc manner. The response time of these queries is high when processed directly against a continuously growing DW. In order to reduce this time, materialized views are used as an alternative. It is infeasible to materialize all views due to storage space constraints. Further, optimal view selection is an NP-Complete problem. Alternately, a subset of views, from amongst all possible views, needs to be selected that improves the response time for analytical queries. In this paper, a quantum-inspired evolutionary view selection algorithm (QIEVSA) that selects Top-K views from a multidimensional lattice has been proposed. Experimental comparison of QIEVSA with other evolutionary view selection algorithms shows that QIEVSA is able to select Top-K views that are comparatively better in reducing the response times for analytical queries. This in turn aids in efficient decision making.

show abstract

“…For instance, Rhonda could embed Sam's query as an "inner" query in a nested query as shown in Figure 4. Alternatively, Rhonda could use Sam's for $t in doc("book.xml")//book/title let $a := $t/../author return <title>{$t/text()} {$a} </title> [1,9,14,21,22,24].…”

Section: Transforming Data Breaks Pbnmentioning

confidence: 99%

“…The most relevant front-end research is to combine an XML query with a view [1,9,14,21,22,24]. Views that transform data are cumbersome to write, and element types constructed in the return clause of a view are distinct from seemingly similar element types referred to in path expressions in a query; they potentially have different values which must be first constructed before being queried.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Querying virtual hierarchies using virtual prefix-based numbers

Dyreson

Bhowmick

Grapp

2014

Proceedings of the 2014 ACM SIGMOD International Conference on Management of Data

View full text Add to dashboard Cite

Prefix-based numbering (PBN) is a popular method for numbering nodes in a hierarchy. But PBN breaks down when a node's location within a hierarchy changes, such as when XML data is queried after being transformed by an XSLT program or when data is reformatted in the return clause of an inner FLWR expression in a nested XQuery program. A query on transformed data cannot be evaluated as efficiently since the extant PBN numbers cannot be used (unless the data is materialized and then renumbered, which can be expensive). In this paper we present a novel strategy to virtually transform the data without instantiating and renumbering. Our method, which we call virtual prefix-based numbering, couples each PBN number with a level array that locates the node in the numbering space of the virtual hierarchy. The virtual numbering space preserves the property that location-based relationships between nodes can be determined by comparing (virtual) numbers.

show abstract

Materialized view selection for XQuery workloads

Cited by 17 publications

References 25 publications

ViP2P: Efficient XML Management in DHT Networks

ViP2P: Efficient XML Management in DHT Networks

A novel quantum-inspired evolutionary view selection algorithm

Querying virtual hierarchies using virtual prefix-based numbers

Contact Info

Product

Resources

About