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Tuning JRockit JVM

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Analyzing and Improving Application Performance

This section describes how you can improve application performance by uncovering "hotpaths," or bottlenecks in processing, and either working around those hotpaths or eliminating them completely.

Analyzing and improving your application is a four-step process:

Alternate Methods of Analysis

The method presented here differs somewhat from the normal use of Java profilers you might have encountered. The reason for the difference is to provide a more accurate picture of what the application is doing. All kinds of profiling are intrusive, and thus change the behaviour of the application you are observing. This causes you to look at data that is not really representative of the application's behaviour.

One way to minimize the impact of profiling is to collect less data (use sampling instead of callgraph analysis), but then this data may not tell you enough to find problems. Therefore, you should can then combine the exact data with information taken during a more instrusive run. This will give you a better picture of what the application is doing. To do this, follow these steps:

Note: While this method provides a good way to find out accurate profiles of your application, a more thorough analysis might still be needed.

 


Step 1: Find the Hotpaths

Finding Hotpaths is a two-step process:

Find the Bottleneck Methods

As their name implies, bottleneck methods are those methods that require excessive time and processing resources to execute. These bottlenecks can greatly affect system performance and need to be identified. To find bottleneck methods, do the following:

Cluster the Bottleneck Methods Together into Hotpaths

To cluster the bottleneck methods together into hotpaths, do the following:

  1. Run your favorite profiler, such as OptimizeIt or JProbe.
  2. Review the call-traces produced by it.
  3. Combine these call-traces with the bottleneck methods discovered in Find the Bottleneck Methods, above. This combination of bottleneck methods and call-traces will identify your hotpaths.

 


Step 2: Prioritize the Hotpaths

To prioritize the hotpaths, do the following:

  1. Sum all of the time spent in each hotpath to compute a total hotpath time.
  2. Remove all individual hotpaths that represent less than a prescribed percentage of the total hotpath time; for example, a good initial percentage might be 5%. This is the hotpath threshold.
  3. Ignore any hotpath that falls below the hotpath threshold. Any hotpath time above the threshold should be optimized.

 


Step 3: Fix the Hotpath

You need to rely on your own judgement and knowledge of the application to fix hotpaths. Once you've identified and prioritized the hotpaths, look at each one and decide if the code is really needed or if you can make some simple changes, perhaps to the coding or to an algorithm, to avoid it or eliminate it as a hotpath. If you determine that you cannot remove the hotpath, what can you do to make it faster? Rewrite the code so it's more efficient?

Also, are you sure that anything you do will actually improve performance. Any optimization you attempt should at least double performance of the hotpath or your efforts might be wasted. For example, a performance increase of 5% or a hotpath that takes only 5% of the time is only going to improve performance .25%.

 


Step 4: Repeat Steps 1-3

Continue repeating the optimization process until you attain the desired system performance.

 

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