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FilterReaders use the standard java.io.Reader, which is implicitly available as the in member variable from the parent class BaseFilterReader. If we had wanted our class to be configurable through the build file, we would have had to extend from BaseParamFilterReader instead. The chain method comes from the ChainableReader interface, and allows our FilterReader to be linked to a successive FilterReader, passing the modified stream through to it. The read method can be a bit complicated, and care must be taken to return -1 when in.read() returns it, otherwise an infinite loop can occur as we experienced in our first iteration of EscapeFilter. The read method is initially called from the Ant framework, but we also call it internally when escaped strings are queued. Each call of read returns only a single character (as an int), so buffering is necessary when text is added, as is the case in EscapeFilter. We found that writing a FilterReader was a bit trickier than other Ant customizations, but was well worth the effort. Had we not had custom filter reader capability in this situation, we probably would have opted to change our business process by mandating that data be already encoded for XML inclusion within the properties file. However, we may want to use that same data outside of XML for other purposes and the situation would have gotten more complex. Luckily, filter readers saved the day by allowing us to have the data cleanly in the properties file, and escape the characters when needed.

Whether the second-level cache is enabled The Hibernate concurrency strategy The cache expiration policies (such as timeout, LRU, and memory-sensitive) The physical format of the cache (memory, indexed files, cluster-replicated)

By providing an id attribute, we are defining a reference. This reference name can be used later wherever a fileset is expected. For example, copying our source code to another directory using the previously defined source.fileset is

Not all classes benefit from caching, so it s important to be able to disable the second-level cache. To repeat, the cache is usually useful only for read-mostly classes. If you have data that is updated much more often than it s read, don t enable the second-level cache, even if all other conditions for caching are true! The price of maintaining the cache during updates can possibly outweigh the performance benefit of faster reads. Furthermore, the second-level cache can be dangerous in systems that share the database with other writing applications. As explained in earlier sections, you must exercise careful judgment here for each class and collection you want to enable caching for. The Hibernate second-level cache is set up in two steps. First, you have to decide which concurrency strategy to use. After that, you configure cache expiration and physical cache attributes using the cache provider. Built-in concurrency strategies A concurrency strategy is a mediator: It s responsible for storing items of data in the cache and retrieving them from the cache. This is an important role, because it also defines the transaction isolation semantics for that particular item. You ll

Property overview Ant s property handling mechanism allows for build file extensibility and reusability by parameterizing any string-specified item. The control users get over build files can be dramatically increased with the techniques shown in this chapter. For example,

have to decide, for each persistent class and collection, which cache concurrency strategy to use if you want to enable the second-level cache. The four built-in concurrency strategies represent decreasing levels of strictness in terms of transaction isolation:

Transactional Available in a managed environment only, it guarantees full transactional isolation up to repeatable read, if required. Use this strategy for read-mostly data where it s critical to prevent stale data in concurrent transactions, in the rare case of an update. Read-write This strategy maintains read committed isolation, using a timestamping mechanism and is available only in nonclustered environments. Again, use this strategy for read-mostly data where it s critical to prevent stale data in concurrent transactions, in the rare case of an update. Nonstrict-read-write Makes no guarantee of consistency between the cache and the database. If there is a possibility of concurrent access to the same entity, you should configure a sufficiently short expiry timeout. Otherwise, you may read stale data from the cache. Use this strategy if data hardly ever changes (many hours, days, or even a week) and a small likelihood of stale data isn t of critical concern. Read-only A concurrency strategy suitable for data which never changes. Use it for reference data only.

This is somewhat oversimplified, as Ant s wrapper scripts do build a system classpath before invoking Ant. It is also, unfortunately, necessary to add dependent JAR files to ANT_HOME/lib to utilize some tasks.