Method-based caching in multi-tiered server applications

Abstract In recent years, application server technology has become very popular for building complex but mission-critical systems such as Web-based E-Commerce applications. However, the resulting solutions tend to suffer from serious performance and scalability bottlenecks, because of their distributed nature and their various software layers. This paper deals with the problem by presenting an approach about transparently caching results of a service interface\u27s read-only methods on the client side. Cache consistency is provided by a descriptive cache invalidation model which may be specified by an application programmer. As the cache layer is transparent to the server as well as to the client code, it can be integrated with relatively low effort even in systems that have already been implemented. Experimental results show that the approach is very effective in improving a server\u27s response times and its transactional throughput. Roughly speaking, the overhead for cache maintenance is small when compared to the cost for method invocations on the server side. The cache\u27s performance improvements are dominated by the fraction of read method invocations and the cache hit rate. Our experiments are based on a realistic E-commerce Web site scenario and site user behaviour is emulated in an authentic way. By inserting our cache, the maximum user request throughput of the web application could be more than doubled while its response time (such as perceived by a web client) was kept at a very low level. Moreover, the cache can be smoothly integrated with traditional caching strategies acting on other system tiers (e.g. caching of dynamic Web pages on a Web server). The presented approach as well as the related implementation are not restricted to application server scenarios but may be applied to any kind of interface-based software layers

A comparison of two physical data designs for interactive social networking actions

This paper compares the performance of an SQL solution that implements a relational data model with a document store named MongoDB. We report on the performance of a single node configuration of each data store and assume the database is small enough to fit in main memory. We analyze utilization of the CPU cores and the network bandwidth to compare the two data stores. Our key findings are as follows. First, for those social networking actions that read and write a small amount of data, the join operator of the SQL solution is not slower than the JSON representation of MongoDB. Second, with a mix of actions, the SQL solution provides either the same performance as MongoDB or outperforms it by 20%. Third, a middle-tier cache enhances the performance of both data stores as query result look up is significantly faster than query processing with either system.

A Middleware System Which Intelligently Caches Query Results

. This paper 1 describes how caching was used to improve performance in the Accessible Business Rules framework #ABR# for IBM's Websphere. ABR is a middleware system which enables application writers to build applications where the time and situation-variable parts of their business logic are externally applied entities known as business rules. The cache signi#cantly reduced the number of queries to remote databases by storing query results. A key problem we faced was howto keep the cache current after database updates. This was solved using data update propagation #DUP#. Two enhancements we made to DUP were to employ an update strategy which considers the values of database updates in order to perform intelligent cache invalidations and to automatically compute dependencies using compile and run-time analysis. Our techniques can be applied to other caching environments besides ABR. We showhow our cache invalidation strategies perform for applications with database updates having queries similar to those in the Set Query benchmark.

Application-level caching with transactional consistency

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from PDF version of thesis.Includes bibliographical references (p. 147-159).Distributed in-memory application data caches like memcached are a popular solution for scaling database-driven web sites. These systems increase performance significantly by reducing load on both the database and application servers. Unfortunately, such caches present two challenges for application developers. First, they cannot ensure that the application sees a consistent view of the data within a transaction, violating the isolation properties of the underlying database. Second, they leave the application responsible for locating data in the cache and keeping it up to date, a frequent source of application complexity and programming errors. This thesis addresses both of these problems in a new cache called TxCache. TxCache is a transactional cache: it ensures that any data seen within a transaction, whether from the cache or the database, reflects a slightly stale but consistent snapshot of the database. TxCache also offers a simple programming model. Application developers simply designate certain functions as cacheable, and the system automatically caches their results and invalidates the cached data as the underlying database changes. Our experiments found that TxCache can substantially increase the performance of a web application: on the RUBiS benchmark, it increases throughput by up to 5.2x relative to a system without caching. More importantly, on this application, TxCache achieves performance comparable (within 5%) to that of a non-transactional cache, showing that consistency does not have to come at the price of performance.by Dan R. K. Ports.Ph.D