Query Caching Research Articles

Monitoring nearest neighbor queries with cache strategies

The problem of continuously monitoring multiple K-nearest neighbor (K-NN) queries with dynamic object and query dataset is valuable for many location-based applications. A practical method is to partition the data space into grid cells, with both object and query table being indexed by this grid structure, while solving the problem by periodically joining cells of objects with queries having their influence regions intersecting the cells. In the worst case, all cells of objects will be accessed once. Object and query cache strategies are proposed to further reduce the I/O cost. With object cache strategy, queries remaining static in current processing cycle seldom need I/O cost, they can be returned quickly. The main I/O cost comes from moving queries, the query cache strategy is used to restrict their search-regions, which uses current results of queries in the main memory buffer. The queries can share not only the accessing of object pages, but also their influence regions. Theoretical analysis of the expected I/O cost is presented, with the I/O cost being about 40% that of the SEA-CNN method in the experiment results.

Semantic query Cache using Dynamic Facts (SCDF): a novel approach to efficient information retrieval

XML query engines can be exploited by caching technology to reduce the latency caused by data transmission. This paper reports on a caching system designed to facilitate XML query processing in the Web. It provides an alternative approach to other architectures, in which the unit of transfer is a page or a tuple. Semantic caching gives enhanced performance based on the result sets of previously answered queries when compared with other systems. A mechanism capable of caching previously computed results for answering future queries with a knowledge-based analysis would be beneficial for improving performance. We have proposed a framework Semantic Cache using Dynamic Facts, which improves the query response reducing network traffic.

Form-based proxy caching for database-backed web sites: keywords and functions

Web caching proxy servers are essential for improving web performance and scalability, and recent research has focused on making proxy caching work for database-backed web sites. In this paper, we explore a new proxy caching framework that exploits the query semantics of HTML forms. We identify two common classes of form-based queries from real-world database-backed web sites, namely, keyword-based queries and function-embedded queries. Using typical examples of these queries, we study two representative caching schemes within our framework: (i) traditional passive query caching, and (ii) active query caching, in which the proxy cache can service a request by evaluating a query over the contents of the cache. Results from our experimental implementation show that our form-based proxy is a general and flexible approach that efficiently enables active caching schemes for database-backed web sites. Furthermore, handling query containment at the proxy yields significant performance advantages over passive query caching, but extending the power of the active cache to do full semantic caching appears to be less generally effective.

ORDBMS를 사용한 XML 질의 캐쉬의 효율적인 지연 갱신

XML 문서의 생성 및 활용도가 증가함으로 인해 XML 문서를 데이터베이스에 저장하여 관리하는 기법이 활발히 연구되고 있다. 관계형 또는 객체 관계형 데이터베이스 관리 시스템(RDBMS/ORDBMS)을 XML 문서의 저장소로 사용하는 것은 현재 가장 실용적인 방법으로 받아들여지고 있다. 데이터베이스에 저장된 XML 문서에 대한 빠른 질의 처리를 위하여 XML 질의 캐쉬를 사용할 수 있다. 그러나 XML 질의 캐쉬의 사용은 하부 자료의 변경에 대한 일관성 유지비용이 든다. 본 논문에서는, ORDBMS를 XML 질의 캐쉬와 하부 XML 자료의 저장소로 사용하고 변경로그를 사용하여 XML 질의 캐쉬를 지연 갱신할 때, XML 질의 캐쉬에 대한 비효율적인 갱신의 원인인 변경로그에 저장된 동일한 XML 문서에 대한 중복 변경을 제거 또는 여과하는 알고리즘을 제시한다. 또한 이를 바탕으로 XML 질의 캐쉬의 갱신에 사용할 최적화된 SQL 문을 생성한다. 실험을 통해 본 논문에서 제안한 XML 질의 캐쉬의 지연 갱신 방법의 효율성을 보인다. As we are to deal with more and more XML documents, research on storing and managing XML documents in databases are actively conducted. Employing RDBMS or ORDBMS as a repository of XML documents is currently regarded as most practical. The query results out of XML documents stored in databases could be cached for query performance though the cost of cache consistency against the update of the underlying data is incurred. In this paper, we assume that an ORDBMS is used as a repository for the XML query cache as well as its underlying XML documents, and that XML query cache is refreshed in a deferred way with the update log. When the same XML document was updated multiple times, the deferred refresh of the XML query cache may Bet inefficient. We propose an algorithm that removes or filters such duplicate updates. Based on that, the optimal SQL statements that are to be executed for XML query cache consistency are generated. Through experiments, we show the efficiency of our proposed deferred refresh of XML query cache.

Client-side caching for nearest neighbor queries

The Voronoi diagram (VD) is the most suitable mechanism to find the nearest neighbor (NN) for mobile clients. In NN query processing, it is important to reduce the query response time, since a late query response may contain out-of-date information. In this paper, we study the issue of location dependent information services (LDISs) using a VD. To begin our study, we first introduce a broadcast-based spatial query processing methods designed to support NN query processing. In further sections, we introduce a generic method for location-dependent sequential prefetching and caching. The performance of this scheme is studied in different simulated environments. The core contribution of this research, resides in our analytical proof and experimental results.

Finding hot query patterns over an XQuery stream

Caching query results is one efficient approach to improving the performance of XML management systems. This entails the discovery of frequent XML queries issued by users. In this paper, we model user queries as a stream of XML query pattern trees and mine the frequent query patterns over the query stream. To facilitate the one-pass mining process, we devise a novel data structure called DTS to summarize the pattern trees seen so far. By grouping the incoming pattern trees into batches, we can dynamically mark the active portion of the current batch in DTS and limit the enumeration of candidate trees to only the currently active pattern trees. We also design another summary data structure called ECTree that provides for the incremental computation of the frequent tree patterns over the query stream. Based on the above two constructs, we present two mining algorithms called XQSMinerI and XQSMinerII. XQSMinerI is fast, but it tends to overestimate, while XQSMinerII adopts a filter-and-refine approach to minimize the amount of overestimation. Experimental results show that the proposed methods are both efficient and scalable and require only small memory footprints.

Multitiered Cache Management and Acceleration for Database-Driven Websites

Response time is a key differentiation point among electronic commerce (e-commerce) applications. For many e-commerce applications, web pages are created dynamically based on the current state of a business stored in database systems. To improve the response time, many e-commerce websites deploy caching solutions for acceleration of content delivery. There are multiple tiers in the content delivery infrastructure where cache servers can be deployed, including (1) data caching (in data centers), (2) content page caching (in edge or front end caches), and (3) database query result set caching (between application servers and DBMS). The architecture of database-driven e-commerce websites is more complex than that of typical websites. It requires the integration of web servers, application servers, and back end database systems as well as dynamic content caching solutions. In this paper, the issues associated with the management of content page caching and database query result set caching tiers are studied. It is observed that caching management for these two tiers have their unique characteristics. It is because cached object types and information available for the caching management in the two tiers are different. Solutions are proposed for effective caching management for each tier and extensive evaluations are conducted. The experimental results show the usefulness of the technology in improving overall system performance.

Competitive caching of query results in search engines

We study the problem of caching query result pages in Web search engines. Popular search engines receive millions of queries per day, and for each query, return a result page to the user who submitted the query. The user may request additional result pages for the same query, submit a new query, or quit searching altogether. An efficient scheme for caching query result pages may enable search engines to lower their response time and reduce their hardware requirements. This work studies query result caching within the framework of the competitive analysis of algorithms. We define a discrete time stochastic model for the manner in which queries are submitted to search engines by multiple user sessions. We then present an adaptation of a known online paging scheme to this model. The expected number of cache misses of the resulting algorithm is no greater than 4 times the expected number of misses that any online caching algorithm will experience under our specific model of query generation.

Efficient WISH in an indoor environment

With the diffusion of wireless connections to Internet, the number of complex operations carried out from mobile users is increasing. To cope with bandwidth limitations and with disconnections, data caching is the most used technique. However for complex operation like dynamic searching a better solution is to take advantage of the multichannel property offered by CDMA protocol. In this case, cached documents can be allocated on distinguished channels in a dynamic way to obtain a better utilization of the radio communication links. We study a particular caching strategy suitable to be integrated with a radio-channel policy. We consider a semantic caching for intranet queries (or intranet searching) that takes advantage of data semantics by caching query answers instead of pages in order to exploit similarities between different queries. In fact, in a WLAN scenario, Internet activity is frequently composed by intranet searching operations characterized by local queries that aim to explore documents stored in a neighbor of the home site. We study benefits from a channel allocation strategy applied to intranet searching with semantic caching. Simulation experiments are carried out by considering an indoor scenario model where mobile clients perform keyword-based queries answered by local Web servers running application we refer to as WISH (Wireless Intranet SearcHing), an intranet searching tool based on semantic caching. The results show a 12% improvement in radio channel usage for 20% of users that share cached documents.

Usability-based caching of query results in OLAP systems

In this paper we propose a new cache management scheme for online analytical processing (OLAP) systems based on the usability of query results in rewriting and processing other queries. For effective admission and replacement of OLAP query results, we consider the benefit of query results not only for recently issued queries but for the expected future queries of a current query. We exploit semantic relationships between successive queries in an OLAP session, which are derived from the interactive and navigational nature of OLAP query workloads, in order to classify and predict subsequent future queries. We present a method for estimating the usability of query results for the representative future queries using a probability model for them. Experimental evaluation shows that our caching scheme using the past and future usability of query results can reduce the cost of processing OLAP query workloads effectively only with a small cache size and outperforms the previous caching strategies for OLAP systems.

메타데이터 레지스트리 기반의 분산 정보 통합 시스템 설계 및 구현

The mediator-based system integrates heterogeneous information systems with the flexible manner. But it does not give much attention on the query optimization issues, especially for the query reusing. The other thing is that it does not use standardized metadata for schema matching. To improve this two issues, we propose mediator-based Distributed Information Integration System (DIIS) which uses query caching regarding performance and uses ISO/IEC 11179 metadata registry in terms of standardization. The DIIS is designed to provide decision-making support, which logically integrates the distributed heterogeneous business information systems based on the Web environment. We designed the system in the aspect of three-layer expression formula architecture using the layered pattern to improve the system reusability and to facilitate the system maintenance. The functionality and flow of core components of three-layer architecture are expressed in terms of process line diagrams and assembly line diagrams of Eriksson Penker Extension Model (EPEM), a methodology of an extension of UML. For the implementation, Supply Chain Management (SCM) domain is used. And we used the Web-based environment for user interface. The DIIS supports functions of query caching and query reusability through Query Function Manager (QFM) and Query Function Repository (QFR) such that it enhances the query processing speed and query reusability by caching the frequently used queries and optimizing the query cost. The DIIS solves the diverse heterogeneity problems by mapping MetaData Registry (MDR) based on ISO/IEC 11179 and Schema Repository (SCR).

Web search engine: Characteristics of user behaviors and their implication

In this paper, first studied are the distribution characteristics of user behaviors based on log data from a massive web search engine. Analysis shows that stochastic distribution of user queries accords with the characteristics of power-law function and exhibits strong similarity, and the user’s queries and clicked URLs present dramatic locality, which implies that query cache and ‘hot click’ cache can be employed to improve system performance. Then three typical cache replacement policies are compared, including LRU, FIFO, and LFU with attenuation. In addition, the distribution characteristics of web information are also analyzed, which demonstrates that the link popularity and replica popularity of a URL have positive influence on its importance. Finally, variance between the link popularity and user popularity, and variance between replica popularity and user popularity are analyzed, which give us some important insight that helps us improve the ranking algorithms in a search engine.

Enhancing data warehouse performance through query caching

The main function of a data warehouse is the separation of the decision layer from the operation layer so that users can invoke analysis, planning, and decision support applications without having to worry about constantly evolving operational databases. Such applications allow ad hoc queries for which no predefined reports exist. It is possible that an ad hoc query is submitted by different users or even by the same user at different times, requiring its repeated evaluations even though the contents of the warehouse have not changed in between. In this work, we propose an enhancement to a data warehouse structure, by building additional intelligence in the form of an adaptive and efficient query cache. The cache contains a list of recently executed ad hoc queries and their answers. Whenever possible, a new query is satisfied by answers already stored in the cache, thereby avoiding potentially large data scans. We discuss issues related to organizing and searching the query cache. In particular, we outline subsumption detection algorithms for a number of different situations that allow for quick decision on whether the cache can be used to evaluate an arriving query.

Enhancing data warehouse performance through query caching

Enhancing data warehouse performance through query caching

Enhancing data warehouse performance through query caching

The main function of a data warehouse is the separation of the decision layer from the operation layer so that users can invoke analysis, planning, and decision support applications without having to worry about constantly evolving operational databases. Such applications allow ad hoc queries for which no predefined reports exist. It is possible that an ad hoc query is submitted by different users or even by the same user at different times, requiring its repeated evaluations even though the contents of the warehouse have not changed in between. In this work, we propose an enhancement to a data warehouse structure, by building additional intelligence in the form of an adaptive and efficient query cache. The cache contains a list of recently executed ad hoc queries and their answers. Whenever possible, a new query is satisfied by answers already stored in the cache, thereby avoiding potentially large data scans. We discuss issues related to organizing and searching the query cache. In particular, we outline subsumption detection algorithms for a number of different situations that allow for quick decision on whether the cache can be used to evaluate an arriving query.

Semantic caching of Web queries

In meta-searchers accessing distributed Web-based information repositories, performance is a major issue. Efficient query processing requires an appropriate caching mechanism. Unfortunately, standard page-based as well as tuple-based caching mechanisms designed for conventional databases are not efficient on the Web, where keyword-based querying is often the only way to retrieve data. In this work, we study the problem of semantic caching of Web queries and develop a caching mechanism for conjunctive Web queries based on signature files. Our algorithms cope with both relations of semantic containment and intersection between a query and the corresponding cache items. We also develop the cache replacement strategy to treat situations when cached items differ in size and contribution when providing partial query answers. We report results of experiments and show how the caching mechanism is realized in the Knowledge Broker system.

Semantic cache mechanism for heterogeneous Web querying

In Web-based searching systems that access distributed information providers, efficient query processing requires an advanced caching mechanism to reduce the query response time. The keyword-based querying is often the only way to retrieve data from Web providers, and therefore standard page-based and tuple-based caching mechanisms turn out to be improper for such a task. In this work, we develop a mechanism for efficient caching of Web queries and the answers received from heterogeneous Web providers. We also report results of experiments and show how the caching mechanism is implemented in the Knowledge Broker system.

Semantic query caching in a mobile environment

Caching of remote data in a mobile client's local storage can improve data access performance and data availability. Traditional approaches are page-based, without taking advantage of the semantics of cached data. It is difficult for a client to determine if a query could be answered entirely based on locally cached data, forcing it to contact the database server for additional data. We propose a semantic caching mechanism which allows data to be cached as a collection of possibly related blocks, each of which is the result of a previously evaluated query. We investigate mechanisms for transforming projection-selection queries to reuse cached data blocks. This avoids transmitting unwanted data items over low bandwidth wireless channels. Cache replacement techniques based on the semantics of cached data are also proposed. We describe the design of our prototype and study its performance.

Data sufficiency for queries on cache

In distributed environments, replication of data provides improved availability, isolation between workloads with different characteristics, and improved performance through local access to data. The “real data” is server resident and by “local data” we refer to cached client data. We examine which data should be cached on behalf of a cached query. The minimum requirement for cached data for a query Q is that it enables answering Q locally. We consider the following: 1. (i) Definitions of what data is cached for a cached query. 2. (ii) Deciding whether cached data can be used to solve a “new” query. 3. (iii) A simple class of caching rules.

Query caching and optimization in distributed mediator systems

Query processing and optimization in mediator systems that access distributed non-proprietary sources pose many novel problems. Cost-based query optimization is hard because the mediator does not have access to source statistics information and furthermore it may not be easy to model the source's performance. At the same time, querying remote sources may be very expensive because of high connection overhead, long computation time, financial charges, and temporary unavailability. We propose a cost-based optimization technique that caches statistics of actual calls to the sources and consequently estimates the cost of the possible execution plans based on the statistics cache. We investigate issues pertaining to the design of the statistics cache and experimentally analyze various tradeoffs. We also present a query result caching mechanism that allows us to effectively use results of prior queries when the source is not readily available. We employ the novel invariants mechanism, which shows how semantic information about data sources may be used to discover cached query results of interest.