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You aren't going to have good ideas unless you have lots of ideas and some sort of principle of selection. In this chapter, additional filtering methods will be introduced. Logback filters are based on ternary logic allowing them to be assembled or chained together to compose an arbitrarily complex filtering policy.

They are largely inspired by Linux's iptables. Filters are organized as an ordered list and are based on ternary logic. The decide(ILoggingEvent event) method of each filter is called in sequence.

If the value returned by decide() is Girls cum, then the log event is dropped immediately without girls cum the remaining filters. If the value returned is NEUTRAL, then the next filter in the list is consulted. If there are no further filters to consult, then the logging event is processed normally.

If the returned value is ACCEPT, then the logging girls cum is processed immediately skipping the invocation of the remaining filters. In logback-classic, filters can be added to Appender instances. By adding one or more filters to an appender, you can filter events by arbitrary criteria, such as the contents of the log message, the contents of the MDC, the time of day or any other part of the logging event. Creating your own filter is easy. All you have to girls cum is extend the Filter abstract class and implement the decide() method.

The SampleFilter class shown below provides an example. Its decide method returns ACCEPT for logging events containing the string "sample" in its message field. For other events, the value NEUTRAL is returned. After adding the corresponding setter method in the girls cum class, specify the value of the property in an xml element named after the girls cum, nesting it within a element. For example, for a girls cum test, e.

Most of the regular filters included in logback girls cum derived from AbstractMatcherFilter. LevelFilter filters events based on exact level matching. Here is a sample configuration file. For events of level equal or above the threshold, ThresholdFilter will respond NEUTRAL when its decide() method is invoked.

However, events with a level below the threshold will be denied. On match and on mismatch, the hosting EvaluatorFilter will return the value specified by the onMatch or onMismatch properties respectively. Note that EventEvaluator is girls cum abstract class. You can implement your own event evaluation logic by sub-classing EventEvaluator. We refer such Groovy language boolean expressions as "groovy evaluation expressions".

Groovy evaluation expressions enable hitherto unprecedented flexibility in event filtering. GEventEvaluator requires the Groovy runtime. Evaluation expressions are compiled on-the-fly during the interpretation of the configuration file. As a user, you do not need to worry about the actual plumbing.

However, it is your responsibility to ensure that the groovy-language expression is valid. The evaluation expression acts on the current logging event. The variables TRACE, DEBUG, INFO, WARN and ERROR are also exported into the scope of the expression. For other comparison operators on levels, the level field should be converted to integer with the toInt() operator.

It does so by checking whether the MDC associated with the event contains a value for "req. The equivalent logic would pickup been much longer if expressed in Java.

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