Oliver Po

Incremental maintenance of path-expression views

Caching data by maintaining materialized views typically requires updating the cache appropriately to reflect dynamic source updates. Extensive research has addressed the problem of incremental view maintenance for relational data but only few works have addressed it for semi-structured data. In this paper we address the problem of incremental maintenance of views defined over XML documents using path-expressions. The approach described in this paper has the following main features that distinguish it from the previous works: (1) The view specification language is powerful and standardized enough to be used in realistic applications. (2) The size of the auxiliary data maintained with the views depends on the expression size and the answer size regardless of the source data size.(3) No source schema is assumed to exist; the source data can be any general well-formed XML document. Experimental evaluation is conducted to assess the performance benefits of the proposed approach.

View invalidation for dynamic content caching in multitiered architectures

In todays multitiered application architectures, clients do not access data stored in the databases directly. Instead, they use applications which in turn invoke the DBMS to generate the relevant content. Since executing application programs may require significant time and other resources, it is more advantageous to cache application results in a result cache. Various view materialization and update management techniques have been proposed to deal with updates to the underlying data. These techniques guarantee that the cached results are always consistent with the underlying data. Several applications, including e-commerce sites, on the other hand, do not require the caches be consistent all the time. Instead, they require that all outdated pages in the caches are invalidated in a timely fashion. In this paper, we show that invalidation is inherently different from view maintenance. We develop algorithms that benefit from this difference in reducing the cost of update management in certain applications and we present an invalidation framework that benefits from these algorithms.

Mashup Feeds: continuous queries over web services

Mashup Feeds is a system that supports integrated web service feeds as continuous queries. We introduce collection-based stream processing semantics to enable information extraction by monitoring source evolution over time.

Issues and evaluations of caching solutions for web application acceleration

Response time is a key differentiation 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. Recently, the topic of Web acceleration for database-driven Web applications has drawn a lot of attention in both the research community and commercial arena. In this paper, we analyze the factors that have impacts on the performance and scalability of Web applications. We discuss system architecture issues and describe approaches to deploying caching solutions for accelerating Web applications. We give the performance matrix measurement for network latency and various system architectures. The paper is summarized with a road map for creating high performance Web applications.

CloudDB: One Size Fits All Revived

We present a data management platform in the cloud, CloudDB. The guiding principle of CloudDB’s design is establishing data independence for the applications that need to use diverse underlying data stores that are optimized for varying workload needs and characteristics. The applications should not have to be aware of the physical organization of the data and how the data is accessed. Ideally, an application only needs a logical specification of the data access layer and the data access requests are handled in a declarative way. CloudDB hosts variety of specialized databases that deliver high performance, scalability, and cost efficiency for varying application needs. CloudDB’s API layer is designed in such a way to give data independence to the higher level applications. The goal is to let the clients use just a simple, standard, and uniform language API to access data management functions as a service.

Engineering and hosting adaptive freshness-sensitive web applications on data centers

Wide-area database replication technologies and the availability of content delivery networks allow Web applications to be hosted and served from powerful data centers. This form of application support requires a complete Web application suite to be distributed along with the database replicas. A major advantage of this approach is that dynamic content is served from locations closer to users, leading into reduced network latency and fast response times. However, this is achieved at the expense of overheads due to (a) invalidation of cached dynamic content in the edge caches and (b) synchronization of database replicas in the data center. These have adverse effects on the freshness of delivered content. In this paper, we propose a freshness-driven adaptive dynamic content caching, which monitors the system status and adjusts caching policies to provide content freshness guarantees. The proposed technique has been intensively evaluated to validate its effectiveness. The experimental results show that the freshness-driven adaptive dynamic content caching technique consistently provides good content freshness. Furthermore, even a Web site that enables dynamic content caching can further benefit from our solution, which improves content freshness up to 7 times, especially under heavy user request traffic and long network latency conditions. Our approach also provides better scalability and significantly reduced response times up to 70% in the experiments.

Performance Evaluation of Range Queries in Key Value Stores

Recently there has been a considerable increase in the number of different Key-Value stores, for supporting data storage and applications on the cloud environment. While all these solutions try to offer highly available and scalable services on the cloud, they are significantly different with each other in terms of the architecture and types of the applications, they try to support. Considering three widely-used such systems: Cassandra, HBase and Voldemort; in this paper we compare them in terms of their support for different types of query workloads. We are mainly focused on the range queries. Unlike HBase and Cassandra that have built-in support for range queries, Voldemort does not support this type of queries via its available API. For this matter, practical techniques are presented on top of Voldemort to support range queries. Our performance evaluation is based on mixed query workloads, in the sense that they contain a combination of short and long range queries, beside other types of typical queries on key-value stores such as lookup and update. We show that there are trade-offs in the performance of the selected system and scheme, and the types of the query workloads that can be processed efficiently.

UQBE: uncertain query by example for web service mashup

The UQBE is a mashup tool for non-programmers that supports query-by-example (QBE) over a schema made up by the user without knowing the schema of the original sources. Based on automated schema matching with uncertainty, the UQBE system returns the best confident results. The system lets the user refine them interactively. A tuple in the query result is associated with lineage that is a boolean formula over schema matching decisions representing underlying conditions on which the corresponding tuple is included in the result. Given binary feedbacks on tuples by the user, which are possibly imprecise, the system solves it as an optimization problem to refine confidence values of matching decisions. The demo features graphical user interaction on the UQBE system, including querying and refinement.

Freshness-driven adaptive caching for dynamic content web sites

Both response time and content freshness are essential to e-commerce applications on the Web. One option to achieve good response time is to build a high performance Web site by deploying the state of art IT infrastructures with large network and server capacities. With such a system architecture, freshness of the content delivered is limited by the network latency since when users receive the contents, the contents may have changed at the server. With the wide availability of content delivery networks, many e-commerce Web applications utilize edge cache servers to cache and deliver dynamic contents at locations much closer to users, avoiding network latency. By caching a large number of dynamic content pages in the edge cache servers, response time can be reduced, benefiting from higher cache hit rates. However, this is achieved at the expense of higher invalidation cost. On the other hand, a higher invalidation cost leads to a longer invalidation cycle (time to perform invalidation check on the pages in caches) at the expense of freshness of cached dynamic content. In this paper, we propose a freshness-driven adaptive dynamic content caching technique, which monitors response time and invalidation cycle length and dynamically adjusts caching policies. We have implemented the proposed technique within NECs Cache Portal Web acceleration solution. We have conducted experiments to evaluate effectiveness of the proposed freshness-driven adaptive dynamic content caching technique. The experimental results show that the proposed technique consistently maintains the best content freshness to users. The experimental results also show that even a Web site with dynamic content caching enabled can further benefit from deployment of our solution with improvement of its content freshness up to 10 times especially during heavy user request traffic and long network latency delay.

CachePortal II: acceleration of very large scale data center-hosted database-driven web applications

Wide-area database replication technologies and the avail-ability of data centers allow database copies to be dis-tributed across the network. This requires a complete e-commercewebsite suite (i.e. edgecaches, Web servers, ap-plication servers, and DBMS) to be distributed along withthe database replicas. A major advantage of this approachis, like the caches, the possibility of serving dynamic con-tent from a location close to the users, reducing networklatency. However, this is achieved at the expense of ad-ditional overhead, caused by the need of invalidating dy-namic content cached in the edge caches and synchroniza-tion of the database replicas in the data center.A typical data center architecture for hosting Web ap-plications requires a complete e-commerce Web site suite(i.e. Web server, application server, and DBMS) to be dis-tributed along with the database replicas. Typically, theWS/AS/DBMS suite is installed in the network to servenon-transaction requests which require accesses to read-only database replicas of the master database at the ori-gin site. In order to distinguish between the asymmetricfunctionalityof master and slave DBMSs, we refer the mir-ror database in the data center as data cache or DB Cache.DBCache can be a lightweight DBMS without the trans-action management system and it may cache only a sub-set of the tables in the master database. Updates to thedatabase are handled using a master/slave database cong-uration: all updates and transactions are processed at themaster database at the origin site.This architecture has two drawbacks: (1) all requests