Making data structures persistent

Driscoll, James R.; Sarnak, Neil; Sleator, Daniel D.; Tarjan, Robert E.

doi:10.1145/12130.12142

Cited by 331 publications

(238 citation statements)

References 32 publications

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“…A data structure is called multi-version (or Bpersistent,^ [4], [12], [24]) if it maintains all its past versions. Typical data structures are single-version (or Bephemeral^) in the sense that an update (insertion or deletion) creates a new version of the data structure while its previous version is discarded.…”

Section: Mvr-treementioning

confidence: 99%

SaIL: A Spatial Index Library for Efficient Application Integration

2005

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With the proliferation of spatial and spatio-temporal data that are produced everyday by a wide range of applications, Geographic Information Systems (GIS) have to cope with millions of objects with diverse spatial characteristics. Clearly, under these circumstances, substantial performance speed up can be achieved with the use of spatial, spatiotemporal and other multi-dimensional indexing techniques. Due to the increasing research effort on developing new indexing methods, the number of available alternatives is becoming overwhelming, making the task of selecting the most appropriate method for indexing the data according to application needs rather challenging. Therefore, developing a library that can combine a variety of indexing techniques under a common application programming interface can prove to be a valuable tool. In this paper we present SaIL (SpAtial Index Library), an extensible framework that enables easy integration of spatial and spatio-temporal index structures into existing applications. We focus on design issues and elaborate on techniques for making the framework generic enough, so that it can support user defined data types, customizable spatial queries, and a broad range of spatial (and spatio-temporal) index structures, in a way that does not compromise functionality, extensibility and, primarily, ease of use. SaIL is publicly available and has already been successfully utilized for research and commercial applications.

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Section: Mvr-treementioning

confidence: 99%

SaIL: A Spatial Index Library for Efficient Application Integration

2005

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“…Reference [14] describes algorithms for 'fully persistent' [15] B-trees for versions where both vdprevand vtprev-style versioning relationships are supported. Their technique efficiently maintains multiple versions of a B+-tree in such a way that any version of it can be accessed and updated.…”

Section: Related Workmentioning

confidence: 99%

Versions in Ode: implementation and experiences

Lieuwen¹,

Gehani²

1999

Softw: Pract. Exper.

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The Ode object-oriented database system supports the creation and manipulation of objects with versions. Versioning is orthogonal to type -any object in the database can be versioned at any time, and the same code works on both versioned and non-versioned instances. Object versioning is supported by many objectoriented databases (e.g. Gemstone, ObjectStore, Versant). However, the facilities are often complex and may not quite match application requirements. Furthermore, the implementation techniques are not welldocumented. Ode took the approach of designing a minimal set of versioning primitives with which users can specify the exact policy they require. To illustrate the flexibility and power of these versioning facilities, we use them to implement a set of previously suggested versioning capabilities. We describe how these versioning facilities are implemented, and discuss our experience in using them. The semantics of vlatest were modified for increased expressivity between the old [5] and the eventual Ode model. The effects of the original vlatest can be produced by composing the vlatest and vroot functions.More precisely, vlatest returns a pointer to the most recent version -in the vtprev order -that can reach parent using vdprev links. If parent has no descendents, vlatest returns parent. (f ) Function vlatestdirectchild -version's latest direct child -returns the most recent directly-derived version of its parameter. It has the specification template persistent T *vlatestdirectchild(persistent T *parent)

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“…The other edges in the path remain contracted, but this replacement changes their type from (2) to (1).…”

Section: Performing Updatesmentioning

confidence: 99%

“…We make most of the parts above persistent using the techniques of Driscoll et al [1]. Using these techniques, we can add persistence with no increase in the time bounds, to any pointer-based data structure for which the in-degree as well as the out-degree of any object is constant.…”

Section: A Priority Queue Of Swapsmentioning

confidence: 99%

Separator Based Sparsification

Eppstein

Galil

Italiano

et al. 1996

Journal of Computer and System Sciences

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We describe algorithms and data structures for maintaining a dynamic planar graph subject to edge insertions and edge deletions that preserve planarity but that can change the embedding. We give a fully dynamic planarity testing algorithm that maintains a graph subject to edge insertions and deletions and that allows queries that test whether the graph is currently planar, or whether a potential new edge would violate planarity, in O(n 1Â2 ) amortized time per update or query. We give fully dynamic algorithms for maintaining the connected components, the best swap and the minimum spanning forest of a planar graph in O(log n) worst-case time per insertion and O(log 2 n) per deletion. Finally, we give fully dynamic algorithms for maintaining the 2-edge-connected components of a planar graph in O(log n) amortized time per insertion and O(log 2 n) per deletion. All of the data structures, except for the one that answers planarity queries, handle only insertions that keep the graph planar. All our algorithms improve previous bounds. The improvements are based upon a new type of sparsification combined with several properties of separators in planar graphs. ]

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Making data structures persistent

Cited by 331 publications

References 32 publications

SaIL: A Spatial Index Library for Efficient Application Integration

SaIL: A Spatial Index Library for Efficient Application Integration

Versions in Ode: implementation and experiences

Separator Based Sparsification

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