Reducing Garbage-Collection Pause Time

Chapter: Memory Management

There are two general ways to reduce garbage-collection pause time and the impact it has on application performance:

These two logical solutions have led to the development of serial, parallel, and concurrent garbage-collection strategies , which represent the foundation of all existing Java garbage-collection implementations (see Figure 2.6).

The difference between the different garbage collection algorithms becomes most clear when looking at the garbage collection suspensions.

Figure 2.6: The differences between garbage-collection algorithms becomes clearest when comparing garbage-collection suspensions.

The serial collector suspends the application and executes the mark-and-sweep algorithm in a single thread. It is the simplest and oldest form of garbage collection in Java and is still the default in the Oracle HotSpot JVM.

The parallel collector uses multiple threads to do its work. It can therefore decrease the GC pause time by leveraging multiple CPUs. It is often the best choice for throughput applications.

The concurrent collector does the majority of its work concurrent with the application execution. It has to suspend the application for only very short amounts of time. This has a big benefit for response-time—sensitive applications, but is not without drawbacks.

(Mostly) Concurrent Marking and Sweeping

CConcurrent garbage-collection strategies complicate the relatively simple mark-and-sweep algorithm a bit. The mark phase is usually sub-divided into some variant of the following:

The concurrent mark works mostly, but not completely, without pausing the application. The tradeoff is a more complex algorithm and an additional phase that is not necessary in a normal stop-the-world GC: the final marking.

The Oracle JRockit JVM improves this algorithm with the help of a keep area, which, if you’re interested, is described in detail in the JRockit documentation . New objects are kept separately and not considered garbage during the first GC. This eliminates the need for a final marking or re-mark.

In the sweep phase of the CMS, all memory areas not occupied by marked objects are found and added to the free list. In other words, the objects are swept by the GC. This phase can run at least partially concurrent to the application. For instance, JRockit divides the heap into two areas of equal size and sweeps one then the other. During this phase, no threads are stopped, but allocations take place only in the area that is not actively being swept.

The downsides of the CMS algorithm can be quickly identified:

These disadvantages aside, the CMS will nearly always lead to greater predictability and better application response time.

Reducing the Impact of Compacting

Modern garbage collectors execute their compacting processes in parallel, leveraging multiple CPUs. Nevertheless, nearly all of them have to suspend the application during this process. JVMs with several gigabytes of memory can be suspended for several seconds or more. To work around this, the various JVMs each implements a set of parameters that can be used to compact memory in smaller, incremental steps instead of as a single big block. The parameters are as follows:

This works, but the optimization process is tedious, involves a lot of testing, and needs to be done again and again for every application to achieve optimum results.

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Chapter: Application Performance Concepts

Differentiating Performance from Scalability

Calculating Performance Data

Collecting Performance Data

Collecting and Analyzing Execution Time Data

Visualizing Performance Data

Controlling Measurement Overhead

Theory Behind Performance

How Humans Perceive Performance

Chapter: Memory Management

How Garbage Collection Works

The Impact of Garbage Collection on application performance

Reducing Garbage Collection Pause time

Making Garbage Collection faster

Not all JVMS are created equal

Analyzing the Performance impact of Memory Utilization and Garbage Collection


GC Configuration Problems

The different kinds of Java memory leaks and how to analyse them

High Memory utilization and their root causes

Classloader releated memory issues

Out-Of-Memory, Churn Rate and more

Chapter: Performance Engineering

Approaching Performance Engineering Afresh

Agile Principles for Performance Evaluation

Employing Dynamic Architecture Validation

Performance in Continuous Integration

Enforcing Development Best Practices

Load Testing—Essential and Not Difficult!

Load Testing in the Era of Web 2.0

Chapter: Virtualization and Cloud Performance

Introduction to Performance Monitoring in virtualized and Cloud Environments

IaaS, PaaS and Saas – All Cloud, All different

Virtualization’s Impact on Performance Management

Monitoring Applications in Virtualized Environments

Monitoring and Understanding Application Performance in The Cloud

Performance Analysis and Resolution of Cloud Applications

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