Tracing in a multithreaded, multiplatform environment
In \"Use a consistent trace system for easier debugging,\" Scott Clee showed you how to trace and log from a custom class to provide a consistent tracing approach across your applications. This approa
Tutorial Details:
Log4j is easy to set up: all you need to do is supply the log4j JAR files to each piece of your application and get on with logging (see Downloading and installing log4j). The use of log4j is explained in its documentation, and there are a few articles looking at its basic usage (see Resources for a link). In this article, I will talk about the things that you need to consider for logging in a complex environment, and show you how to use the facilities provided in log4j to best effect in the context of a working example. I will also show you how to mine the log information once it has been gathered. Even with the best planning in the world, it can still be time consuming and tricky to find the information you\'re looking for in a large log file.
Why is multithreading a big deal?
If your program runs on several threads simultaneously, the logging information from each can become tangled up. Anyone who has tried reading output from 15 interleaved threads knows what I mean! In addition, your code might often be running in a distributed system on multiple machines. If you\'re using the same trace system for all your components, you\'ll be left to tie together multiple outputs from systems with potentially unsynchronized internal clocks. (This last issue is a real gotcha. Imagine reading through trace information, not realizing that the timestamps on your client machine are all 20 seconds earlier than the equivalent timestamps on the server!)
Listing 1 is an example of trace information coming from a single program being run using a simple output using timestamps and messages. It\'s much like the output you might see if you rolled your own logging infrastructure.
Listing 1. Trace information for a simple application
(12:01:02) Starting
(12:01:02) initializing variables
(12:01:03) making call to db
(12:01:04) got value \'A\'
(12:01:05) setting new value to db
(12:01:05) done
That all seems straightforward enough. But now look at Listing 2, which shows what happens when you scale up and run five threads at the same time.
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Tracing in a multithreaded, multiplatform environment
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In \"Use a consistent trace system for easier debugging,\" Scott Clee showed you how to trace and log from a custom class to provide a consistent tracing approach across your applications. This approa
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