Comparison of access methods for time-evolving data

Salzberg, Betty; Tsotras, Vassilis J.

doi:10.1145/319806.319816

Cited by 253 publications

(146 citation statements)

References 57 publications

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“…Some of them are based on the methods proposed by Bozkaya et al [3] and Salzberg et al [47], where a B+ tree indexes the FROM value in the intervals being indexed, and each internal node is augmented with the information of the maximum TO value in an interval of the corresponding subtree. These proposals are "indexing" schemes rather than summaries.…”

Section: Example 15mentioning

confidence: 99%

Temporal XML: modeling, indexing, and query processing

Rizzolo

Vaisman

2007

The VLDB Journal

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In this paper we address the problem of modeling and implementing temporal data in XML. We propose a data model for tracking historical information in an XML document and for recovering the state of the document as of any given time. We study the temporal constraints imposed by the data model, and present algorithms for validating a temporal XML document against these constraints, along with methods for fixing inconsistent documents. In addition, we discuss different ways of mapping the abstract representation into a temporal XML document, and introduce TXPath, a temporal XML query language that extends XPath 2.0.In the second part of the paper, we present our approach for summarizing and indexing temporal XML documents. In particular we show that by indexing continuous paths, i.e., paths that are valid continuously during a certain interval in a temporal XML graph, we can dramatically increase query performance. To achieve this, we introduce a new class of summaries, denoted TSummary, that adds the time dimension to the wellknown path summarization schemes. Within this framework, we present two new summaries: LCP and Interval summaries. The indexing scheme, denoted TempIndex, integrates these summaries with additional data structures. We give a query processing strategy based on TempIndex and a type of ancestor-descendant encoding, denoted temporal interval encoding. We present a persistent implementation of TempIndex, and a comparison against a system based on a non-temporal path index, and one based on DOM. Finally, we sketch a language for updates, and show that the cost of updating the index is compatible with real-world requirements.

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Section: Example 15mentioning

confidence: 99%

Temporal XML: modeling, indexing, and query processing

Rizzolo

Vaisman

2007

The VLDB Journal

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“…There are many proposals in the literature for indexing temporal intervals. Some of them are based on the methods proposed by Bozkaya et al [2] and Salzberg et al [21], where a B+ tree indexes the FROM value in the intervals being indexed, and each internal node is augmented with the information of the maximum TO value in an interval of the corresponding subtree. We propose a different scheme, embodied in For each temporal depth k, we define the nodes that are valid at that depth during an interval I as follows.…”

Section: Indexing Intervalsmentioning

confidence: 99%

Indexing Temporal XML documents

Mendelzon

Rizzolo

Vaisman

2004

Proceedings 2004 VLDB Conference

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Different models have been proposed recently for representing temporal data, tracking historical information, and recovering the state of the document as of any given time, in XML documents. We address the problem of indexing temporal XML documents. In particular we show that by indexing continuous paths, i.e. paths that are valid continuously during a certain interval in a temporal XML graph, we can dramatically increase query performance. We describe in detail the indexing scheme, denoted TempIndex, and compare its performance against both a system based on a nontemporal path index, and one based on DOM.

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“…Depending on which concept(s) of time is (are) considered, a TDB is characterized as transaction time, valid-time or bi-temporal. A survey on access methods used in TDBs can be found in [16]. The most cited temporal access methods that support efficient indexing on transaction time are the following.…”

Section: Indexing Transaction-time Datamentioning

confidence: 99%

Benchmarking access methods for time-evolving regional data

Tzouramanis¹

2003

Data & Knowledge Engineering

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In this paper we present a performance comparison of access methods for time-evolving regional data. Initially, we briefly review four temporal extensions of the Linear Region Quadtree: the Time-Split Linear Quadtree, the Multiversion Linear Quadtree, the Multiversion Access Structure for Evolving Raster Images and Overlapping Linear Quadtrees. These methods comprise a family of specialized access methods that can efficiently store and manipulate consecutive raster images. A new simpler implementation solution that provides efficient support for spatio-temporal queries referring to the past through these methods, is suggested. An extensive experimental space and time performance comparison of all the above access methods follows. The comparison is made under a common and flexible benchmarking environment in order to choose the best technique depending on the application and on the image characteristics. These experimental results show that in most cases the Overlapping Linear Quadtrees method is the best choice.

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Comparison of access methods for time-evolving data

Cited by 253 publications

References 57 publications

Temporal XML: modeling, indexing, and query processing

Temporal XML: modeling, indexing, and query processing

Indexing Temporal XML documents

Benchmarking access methods for time-evolving regional data

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