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This approach has a further benefit in that the JMS software should be able to use MDBs to load-balance requests across a farm of EJB servers--delivering requests using a round-robin or least-loaded receiver algorithm--so the workload is spread across multiple resources.

Caching to Reduce the Load

However, the most effective way to reduce unnecessary workload is to use a cache. Deep down, all programmers know this. Sometimes they think they are using one (perhaps the database cache), but it is often too far away from the application to be effective. JCACHE, or Java Temporary Caching API--a specification that has recently come out of the Java Community Process--can help Java developers create data caches. The JCACHE specification provides a way to standardize in-process caching of Java objects and enable faster implementation.

By introducing caching at the Web server and ensuring that the EJB application server publishes updates to the cache, you further enhance the generic architecture. Frequently accessed data is cached; as the cache "warms up," the frequency of access (directly or via EJBs) to the data servers declines. Remember that at least 90 percent of activity on Web-based applications is read-only, so most requests for data are satisfied immediately (without I/O), and latency is hugely reduced.

By severely reducing the traffic to the application server and database, the net effect is to substantially diminish the size and cost of the installation--the cash savings involved can be considerable when you take into account CPU-based pricing of database and application server--or, conversely, to increase the amount of traffic that a given installation can support while ensuring that user satisfaction is protected.

Figure 3--taken from a real application--shows how caching reduces the number of database accesses.

Figure 3: Cache Response Tests

Without a cache, the number of database reads increases linearly with the number of users. With a cache, two things happen:

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