基于基库的多实化视图增量维护算法

基于基库的多实化视图维护将基库集作为多个实化视图的辅助视图集保存在集成端。当信息源发生变化时,基库随着更新,同时触发多实化视图的更新与维护。在保存基库的情况下,多实化视图的维护无需访问信息源就可完成,是多实化视图的自维护方式。     

Recommending XML physical designs for XML databases

Database systems employ physical structures such as indexes and materialized views to improve query performance, potentially by orders of magnitude. It is therefore important for a database administrator to choose the appropriate configuration of these physical structures for a given database. XML database systems are increasingly being used to manage semi-structured data, and XML support has been added to commercial database systems. In this paper, we address the problem of automatic physical design for XML databases, which is the process of automatically selecting the best set of physical structures for a database and a query workload. We focus on recommending two types of physical structures: XML indexes and relational materialized views of XML data. We present a design advisor for recommending XML indexes, one for recommending materialized views, and an integrated design advisor that recommends both indexes and materialized views. A key characteristic of our advisors is that they are tightly coupled with the query optimizer of the database system, and they rely on the optimizer for enumerating and evaluating physical designs. We have implemented our advisors in a prototype version of IBM DB2 V9, and we experimentally demonstrate the effectiveness of their recommendations using this implementation.     

Incremental recomputation of active relational expressions

Database updates are small and incremental compared to database contents. It is therefore desirable that recomputations of active relational expressions-such as views, derived data, integrity constraints, active queries, and monitors-can also be performed incrementally. An efficient algorithm for the incremental recomputation of active relational expressions based on finite differencing techniques is presented. Database updates are modeled as incremental changes to database relations, and the algorithm derives, by update propagation, the minimal incremental relational expressions that need recomputation. The algorithm has applications in the maintenance of materialized views and derived data, the checking of integrity constraints, and the evaluation of active queries and monitors     

Incremental View Maintenance for Mobile Databases

In a mobile environment, querying a database at a stationary server from a mobile client is expensive due to the limited bandwidth of a wireless channel and the instability of the wireless network. We address this problem by maintaining a materialized view in a mobile client's local storage. Such a materialized view can be considered as a data warehouse. The materialized view contains results of common queries in which the mobile client is interested. In this paper, we address the view update problem for maintaining the consistency between a materialized view at a mobile client and the database server. The content of a materialized view could become incoherent with that at the database server when the content of the database server and/or when the location of the client is changed. Existing view update mechanisms are ‘push-based’. The server is responsible for notifying all clients whose views might be affected by the changes in database or the mobility of the client. This is not appropriate in a mobile environment due to the frequent wireless channel disconnection. Furthermore, it is not easy for a server to keep track of client movements to update individual client location-dependent views. We propose a ‘pull-based’ approach that allows a materialized view to be updated at a client in an incremental manner, requiring a client to request changes to its view from the server. We demonstrate the feasibility of our approach with experimental results. Received 27 January 1999 / Revised 26 November 1999 / Accepted 17 April 2000     

Updating distributed materialized views

The problem of updating materialized views in distributed database systems is discussed. An architecture and detailed procedures for updating a collection of remote views with arbitrary refresh times by using a single differential file are described. The efficiency of the update procedure is enhanced by adopting s multiquery optimization approach and by introducing a powerful prescreening procedure to eliminate differential tuples. It is shown that even for a single remote view, there are many instances where the update procedure performs better (with respect to total I/O and communication costs) than a base table approach     

数据库视图增量保持的并行主动触发机制

当前数据库并行处理已经引起了很大的关注,而利用主动触发规则导出数据库数据(如视图)的研究也很多见,但在物化视图增量保持领域这方面的研究还不多见,尤其是利用并行处理能力来解决物化视图增量保持的多触发问题的研究。文章提出了并行环境下物化视图增量保持的主动多触发规则处理机制。     

Maintaining Views in Object-Relational Databases

View materialization is an important way of improving the performance of query processing. When an update occurs to the source data from which a materialized view is derived, the materialized view has to be updated so that it is consistent with the source data. This update process is called view maintenance. The incremental method of view maintenance, which computes the new view using the old view and the update to the source data, is widely preferred to full view recomputation when the update is small in size. In this paper we investigate how to incrementally maintain views in object-relational (OR) databases. The investigation focuses on maintaining views defined in OR-SQL, a language containing the features of object referencing, inheritance, collection, and aggregate functions including user-defined set aggregate functions. We propose an architecture and algorithms for incremental OR viewmaintenance. We implement all algorithms and analyze the performance of them in comparison with full view recomputation. The analysis shows that the algorithms significantly reduce the cost of updating a vieww hen the size of an update to the source data is relatively small. Received 23 May 2000 / Revised 27 March 2001 / Accepted in revised form 30 April 2001 Correspondence and offprint requests to: Jixue Liu, School of Computer and Information Science, University of South Australia, Mawson Lakes, Adelaide SA5084, Australia. Email: jixue.liu@unisa.edu.auau     

Incremental computation and maintenance of temporal aggregates

We consider the problems of computing aggregation queries in temporal databases and of maintaining materialized temporal aggregate views efficiently. The latter problem is particularly challenging since a single data update can cause aggregate results to change over the entire time line. We introduce a new index structure called the SB-tree, which incorporates features from both segment-trees and B-trees. SB-trees support fast lookup of aggregate results based on time and can be maintained efficiently when the data change. We extend the basic SB-tree index to handle cumulative (also called moving-window) aggregates, considering separatelycases when the window size is or is not fixed in advance. For materialized aggregate views in a temporal database or warehouse, we propose building and maintaining SB-tree indices instead of the views themselves.Received: 20 March 2001, Accepted: 21 March 2001, Published online: 17 September 2003This work was supported by the National Science Foundation under grant IIS-9811947 and by NASA Ames under grant NCC2-5278.Edited by R. Snodgrass     

ViewDF: Declarative incremental view maintenance for streaming data

We present ViewDF: a flexible and declarative framework for incremental maintenance of materialized views (i.e., results of continuous queries) over streaming data. The main component of the proposed framework is the View Delta Function (ViewDF), which declaratively specifies how to update a materialized view when a new batch of data arrives. We describe and experimentally evaluate a prototype system based on this idea, which allows users to write ViewDFs directly and automatically translates common classes of streaming queries into ViewDFs. Our approach generalizes existing work on incremental view maintenance and enables new optimizations for views that are common in stream analytics, including those with pattern matching and sliding windows.     

Maintaining materialized views without accessing base data

Access to a database through a user view can be serviced quickly when the view is materialized, i.e. the transformed data is explicitly stored. In the presence of database updates, however, the materialized view can become costly to maintain; often it must be completely rederived from the base data using the view definition. Under some conditions the view can be updated directly given only the view definition, the current contents of the materialized view, and the update operation (still expressed against the base data), without accessing the base data itself. In this paper, we consider relational views defined by projection, selection, and join. We present necessary and sufficient conditions on the view definition, contents, and update operations for insertions and deletions to be reflected in the view without reference to base data. Because the possibility of such view-based updating is dependent on the current contents of view, we call the update conditionally autonomously computable.     

数据仓库中基于实体化辅助视图的视图增量维护

为了加快对大量数据的查询处理速度，通常在数据仓库以实视图方式存储数据，当基础数据发生变化时，这些实视图也必须随着更新，因而视图自维护和一致性维护成为数据仓库的重要问题。本文提出利用视图计算的中间结果创建辅助视图，在数据仓库中进行实体化，采用有效的增量维护算法计算实视图的精确变化，实现数据仓库视图自维护。     

OODB中连接类视图的物化和增量保持技术

目前,对数据库视图的物化和增量保持技术已有很多讨论,但对ＯＯＤＢ视图的物化和增量保持基本上局限于ＩＳＡ关系由单个类导出视图的范围内,而对于由两个或多个类通过连接操作导出的视图这一范围尚无涉及,该文提出了基于这一范畴的视图物化和增量保持的一种数据模式和基于该模式的增量保持技术。     

数据仓库性能优化之索引和物化视图耦合方法

为了进一步提高数据仓库的性能, 通过分析数据仓库中性能优化技术的特点, 提出了索引和物化视图耦合的性能优化技术。通过数据挖掘自动选择候选索引和物化视图, 减少查询的扫描范围; 然后研究在物化视图上建立索引的空间高效存储方法, 以提高查询速率; 最后利用成本模型对耦合情况进行分析, 验证了耦合方法可以极大提高单一索引查询或者物化视图的性能。     

Using partial information to update materialized views

This paper lays the theoretical foundations for identifying classes of views and data partitioning strategies that allow efficient incremental view maintenance using “partial information” about the underlying base relations. We present necessary and sufficient conditions for determining how a materialized select-project-join view can be updated using only the view definition, the current view materialization, and the update (i.e., no base relations); and also how to update views using only the view definition, the update, and the updated base relation (i.e., not the other base relations). We generalize the above results to use an arbitrary subset of the base relations and the current view materialization. Our results are especially useful in distributed databases, in disconnected and mobile computing environments where the underlying database is not always accessible, and in data warehousing applications. Our techniques can be used to minimize remote data access and often to completely avoid remote access. This paper gives the intuition and theory necessary for identifying and designing views that are efficiently maintainable using partial information.     

An efficient query evaluation in a mediator based on implementation plan

Recent research which purports to integrate distributed information has been concentrated on developing efficient mediator systems that not only provide a high degree of autonomy for local users, but also support the flexible integration of required functions for global users. However, there has been little attention paid to the implementation of the global views defined in a mediator. It is possible to speed up the execution of a global query if the previous result of a view is materialized in a mediator. Since the integration schema of a mediator can be incrementally modified and its usage can also be continuously varied, view usage should be carefully monitored to determine the optimized set of materialized views. Furthermore, as the number of views increases, the optimization process itself may take too long, so that the optimized set identified by a long optimization process becomes obsolete due to the recent change of view usage. This paper proposes the adaptive selection of a practical implementation method for each global view, such that available storage in a mediator can be highly utilized at any time. In order to differentiate the recent usage of a view from the past, the accumulated usage frequency of a view decays as time goes by. As a result, it is possible to change the implementation of each view adaptively with respect to the recent variation of view usage.     

数据仓库中多数据源物化视图的一种有效更新算法

数据仓库中存储着大量的汇总数据以支持查询和相关决策的制定，这些汇总数据常常是定义在若干数据源上的物化视图．当数据源发生变化时，物化视图也需要相应的更新，这必然给数据仓库带来庞大的开销，因而如何有效地对物化视图进行更新成为一个非常重要的问题．利用BinPartition算法可以使计算费用达到最低，随后证明了该算法的正确性并分析了其时间复杂性．     

Answering queries using views: A survey

The problem of answering queries using views is to find efficient methods of answering a query using a set of previously defined materialized views over the database, rather than accessing the database relations. The problem has recently received significant attention because of its relevance to a wide variety of data management problems. In query optimization, finding a rewriting of a query using a set of materialized views can yield a more efficient query execution plan. To support the separation of the logical and physical views of data, a storage schema can be described using views over the logical schema. As a result, finding a query execution plan that accesses the storage amounts to solving the problem of answering queries using views. Finally, the problem arises in data integration systems, where data sources can be described as precomputed views over a mediated schema. This article surveys the state of the art on the problem of answering queries using views, and synthesizes the disparate works into a coherent framework. We describe the different applications of the problem, the algorithms proposed to solve it and the relevant theoretical results. Received: 1 August 1999 / Accepted: 23 March 2001 Published online: 6 September 2001     

Incremental Design of a Data Warehouse

A data warehouse (DW) can be seen as a set of materialized views defined over remote base relations. When a query is posed, it is evaluated locally, using the materialized views, without accessing the original information sources. The DWs are dynamic entities that evolve continuously over time. As time passes, new queries need to be answered by them. Some of these queries can be answered using exclusively the materialized views. In general though new views need to be added to the DW.In this paper we investigate the problem of incrementally designing a DW when new queries need to be answered and possibly extra space is allocated for view materialization. Based on an AND/OR dag representation of multiple queries, we model the problem as a state space search problem. We design incremental algorithms for selecting a set of new views to additionally materialize in the DW that: (a) fits in the extra space, (b) allows a complete rewriting of the new queries over the materialized views, and (c) minimizes the combined new query evaluation and new view maintenance cost. Finally, we discuss methods for pruning the search space so that efficiency is improved.     

PKTS view:一种多媒体数据库视图

在多媒体数据库管理系统中采用视图技术是一个新的课题。文章分析了逻辑视图和实视图在应用于MMDBMS时的不足,给出了一个多媒体数据库视图的时间成本和空间成本模型,并基于这些分析,提出了一种新的视图模式,较好地解决了该类应用中时间成本与空间成本的矛盾。     

PKTS view：一种多媒体数据库视图

在多媒体数据库管理系统中采用视图技术是一个新的课题。文章分析了逻辑视图和实视图在应用于MMDBMS时的不足，给出了一个多媒体数据库视图的时间成本和空间成本模型，并基于这些分析，提出了一种新的视图模式．较好地解决了该类应用中时间成本与空间成本的矛盾。