Jvm performance tuning

By using our site, you acknowledge that you have read and understand our Cookie PolicyPrivacy Policyand our Terms of Service. The dark mode beta is finally here. Change your preferences any time. Stack Overflow for Teams is a private, secure spot for you and your coworkers to find and share information.

The default JVM parameters are not optimal for running large applications. Any insights from people who have tuned it on a real application would be helpful. We are running the application on a bit windows machine, where the client JVM is used by default. We have added -server and changed the NewRatio to A larger young generation. Also assume that the application is profiled already.

jvm performance tuning

I'm looking for general guidelines in terms of JVM performance only. Second, read the JVM documentation carefully; there are a lot of sort of "urban legends" around. There are several good books and websites around.

Been at a Java shop. Spent entire months dedicated to running performance tests on distributed systems, the main apps being in Java. Some of which implying products developed and sold by Sun themselves then Oracle.

I will go over the lessons I learned, some history about the JVM, some talks about the internals, a couple of parameters explained and finally some tuning. Trying to keep it to the point so you can apply it in practice.

Things are changing fast in the Java world so part of it might be already outdated since the last year I've done all that. Is Java 10 out already? When you really need to know about performances, you need to perform real benchmarks, specific to your workload.

JVM performance tuning

There is no alternatives. Also, you should monitor the JVM. Enable monitoring. Be aware that there is usually no performance to gain by tuning the JVM. It's more a "to crash or not to crash, finding the transition point".

It's about knowing that when you give that amount of resources to your application, you can consistently expect that amount of performances in return.The Java platform's garbage collection mechanism greatly increases developer productivity, but a poorly implemented garbage collector can over-consume application resources.

In this third article in the JVM performance optimization series, Eva Andreasson offers Java beginners an overview of the Java platform's memory model and GC mechanism.

She then explains why fragmentation and not GC is the major "gotcha! Garbage collection GC is the process that aims to free up occupied memory that is no longer referenced by any reachable Java object, and is an essential part of the Java virtual machine's JVM's dynamic memory management system.

In a typical garbage collection cycle all objects that are still referenced, and thus reachable, are kept. The space occupied by previously referenced objects is freed and reclaimed to enable new object allocation. In order to understand garbage collection and the various GC approaches and algorithms, you must first know a few things about the Java platform's memory model. When you specify the startup option -Xmx on the command line of your Java application for instance: java -Xmx:2g MyApp memory is assigned to a Java process.

This memory is referred to as the Java heap or just heap. This is the dedicated memory address space where all objects created by your Java program or sometimes the JVM will be allocated. As your Java program keeps running and allocating new objects, the Java heap meaning that address space will fill up. Eventually, the Java heap will be full, which means that an allocating thread is unable to find a large-enough consecutive section of free memory for the object it wants to allocate. At that point, the JVM determines that a garbage collection needs to happen and it notifies the garbage collector.

A garbage collection can also be triggered when a Java program calls System. Using System. Before any garbage collection can start, a GC mechanism will first determine whether it is safe to start it. It is safe to start a garbage collection when all of the application's active threads are at a safe point to allow for it, e.

A garbage collector should never reclaim an actively referenced object; to do so would break the Java virtual machine specification. A garbage collector is also not required to immediately collect dead objects.

Dead objects are eventually collected during subsequent garbage collection cycles. While there are many ways to implement garbage collection, these two assumptions are true for all varieties. The real challenge of garbage collection is to identify everything that is live still referenced and reclaim any unreferenced memory, but do so without impacting running applications any more than necessary.

A garbage collector thus has two mandates:. In the first article in this series I touched on the two main approaches to garbage collection, which are reference counting and tracing collectors.

This time I'll drill down further into each approach then introduce some of the algorithms used to implement tracing collectors in production environments. Reference counting collectors keep track of how many references are pointing to each Java object. Once the count for an object becomes zero, the memory can be immediately reclaimed.

This immediate access to reclaimed memory is the major advantage of the reference-counting approach to garbage collection. There is very little overhead when it comes to holding on to un-referenced memory. Keeping all reference counts up to date can be quite costly, however.

The main difficulty with reference counting collectors is keeping the reference counts accurate. Another well-known challenge is the complexity associated with handling circular structures. If two objects reference each other and no live object refers to them, their memory will never be released.

Both objects will forever remain with a non-zero count. Reclaiming memory associated with circular structures requires major analysis, which brings costly overhead to the algorithm, and hence to the application. Tracing collectors are based on the assumption that all live objects can be found by iteratively tracing all references and subsequent references from an initial set of known to be live objects.

The initial set of live objects called root objects or just roots for short are located by analyzing the registers, global fields, and stack frames at the moment when a garbage collection is triggered. After an initial live set has been identified, the tracing collector follows references from these objects and queues them up to be marked as live and subsequently have their references traced. Marking all found referenced objects live means that the known live set increases over time.Apache Tomcat, developed by the Apache Software Foundation, is an open source Java servlet container that also functions as a web server.

Production environments must be high performing. This requires that Apache Tomcat be configured to handle the maximum load possible and yet provide the best response time to users.

The performance that an application server delivers is often dependent on how well it is configured. Often the default settings provided are non-optimal. Over the years, we have discovered several tips and tricks for configuring Tomcat to achieve the highest level of scalability possible. This blog post documents our learnings on best practices that you should employ when deploying Tomcat in production. A first step to achieving high performance is to recognize that tuning the Tomcat application server alone is not sufficient.

So, a poorly configured JVM will compromise performance. Likewise, the JVM runs on an operating system and it is important to have the best possible operating system configuration to achieve the highest performance possible. All in all, a holistic approach must be taken for Tomcat performance tuning. Performance tuning must be done at every layer: the operating system, JVM, Tomcat container, and at the application code level.

In the following sections, we will present best practices to configure the operating system, JVM, Tomcat container, and application code for best possible performance. In the past, garbage collection was done in a stop-the-world manner. That is, when garbage collection happened, the application was paused in order to reclaim memory. Today, there are many garbage collection implementations where the garbage collection happens in parallel with the application execution.

jvm performance tuning

Memory availability in the JVM can also adversely impact Tomcat performance. Make sure that the memory available to each of the memory pools of the JVM is sufficient. Memory shortage will adversely affect Tomcat server performance. If memory grows unbounded in the JVM, you will need to determine if there is a memory leak in the application.Comment Java application performance is an abstract word until you face its real implications.

It may vary depending on your interpretation of the word 'performance'. This article is meant to give the developer a perspective of the various aspects of the JVM internals, the controls, and switches that can be altered to optimal effects that suit your application.

There is no single size that can fit all. You need to customize to suit your application. Before we take the plunge into solving the issues, we first need to understand some of the theory behind the issues. An object is created in the heap and is garbage-collected after there are no more references to it. Objects cannot be reclaimed or freed by explicit language directives.

Objects inside the blue square are reachable from the thread root set, while objects outside the square in red are not. Hence there is a need to figure out this rough infant mortality number so that you can tune the JVM accordingly. The diagram below shows how objects get created in New generation and then move to survivor Spaces at every GC run, and if they survive for long to be considered old, they get moved to the Tenured generation.

The number of times an object need to survive GC cycles to be considered old enough can be configured. If the major GC too fails to free required memory, the JVM increases the current memory to help create new object.

JVM process memory. If F is the fraction of a calculation that is sequential i. So we assume that there is a scope of leveraging benefits of multiple CPUs or multithreading. All right, enough of theory OutOfMemoryError can occur due to 3 possible reasons: 1. JavaHeap space low to create new objects.

OutOfMemoryError: Java heap space. Permanent Generation low. Out of swap space If you use java NIO packages, watch out for this issue. DirectBuffer allocation uses the native heap.

There are some starting points to diagnose the problem. You may start with the '-verbose:gc' flag on the java command and see the memory footprint as the application progresses, till you find a spike. You may analyze the logs or use a light profiler like JConsole part of JDK to check the memory graph. This is a memory intensive procedure and not meant for production systems. Depending upon your application, these heavy profilers can slow down the app upto 10 times.

Java memory leaks or what we like to call unintentionally retained objectsare often caused by saving an object reference in a class level collection and forgetting to remove it at the proper time. The collection might be storing objects, out of which 95 might never be used.Maven and Eclipse have always had a rocky relationship, and a common pain point between the two is how to force Maven JDK 1. Without jumping through a few The latest version of the Java Platform, Standard Edition, delivers new features to make developers more productive with the Java programming language.

What is a 'lambda function' and more importantly, where did the term 'lambda expression' come from? Here we look at the basics of lambda functions in Java and computer science. As things get better, they often get slower, making better things worse. Continue Reading.

JVM Tuning: How to Prepare Your Environment for Performance Tuning

Understandably, Java SE 9 was a popular topic of discussion inbut so were DevOps and cloud native, according to this list of the 10 most popular podcasts of With content distribution networks loaded with edge JavaScript, Cloudfare promises to improve application performance and reducing resource consumption.

At JavaOne, the vice president of Java development at Oracle opened up about Java 8 trends and expectations. A slow landing page makes a bad first impression for any potential website visitor.

Here are five tips to improve the page and increase page load speeds. Java platform architects reminisce about the design of Java and how the platform is being pushed forward. Discussion at JavaOne turned to leveraging capabilities from Lambda expressions.

Java Performance Puzzlers by Douglas Hawkins

Soon, any code that uses Java internal APIs will not compile, and shortly after that, code that uses classes in sun. Developers and architects at JavaOne discussed how to improve Java application performance. Surges in app user activity caused by the COVID pandemic have forced architects to make immediate decisions around service As enterprises move in on RPA, they need developers who can juggle both the business and technical sides of automation.

Here are Plenty of vendors have jumped on the API gateway trend, which can make it difficult to choose the right one for you. We examineDiscussion of open source software and enterprise architecture, including middleware, software development, and all manner of hardware. You said you have achieved over 3x improvement after tuning. Could you provide a little more info about how about original setting before tuning.

What tuning tools you are using. Thanks in advance. They were mostly adjustments to the pool sizes for the EJB 3 objects. The starting point was using -server -msm -mxm. This is simply putting the HotSpot JVM into server mode, and using a minimum and maximum heap size of 3. Of course, in order for this to work, you have to go through the OS setup instructions in the blog.

That was all I did. I believe in keeping things as simply as possible as your starting point, and adding one thing to see what it does for you. The simpler you keep the options, the better off you are going to be, IMHO.

Thanks for the tips Andrig. Additional info for those who still stuck with 2. RHEL 3use vm. So to configure 6GB page size, the sysctl parameter is vm.

Thanks for the additional RHEL 3 information. That will probably help quite a few folks, considering the cycle time to upgrade the OS that most organizations have. Thanks again! Do u know what could be wrong? If you want to show me specifically what you setup on the Linux side of things, and what you are passing on the JVM command-line I can probably tell you what's wrong.

jvm performance tuning

Hi Andrig, Hopefully you still read your blog and this post! I have a RH Linux machine that is configured for large pages. If I run my application with 24gb using Jrockit, I can access the large pages. Any idea what to look at? Are you sure you are really accessing the large pages with JRockit? How do you know that the JVM is not using the large pages? Very helpful. It is important to update the kernel, glibc and maybe other packages in order this to work. Even if I did all settings correctly before this.

Thanks for the tip. Yes, keeping your RHEL installation up to date is definitely key to making sure this works. I'm not surprised there were issues, and that you had to upgrade to update 6 for it to work.

jvm performance tuning

I setup my env. Can you help me? In looking at this rather long set of options, here is what is wrong.Manage your account and access personalized content. Sign up for an Oracle Account. Access your cloud dashboard, manage orders, and more. Sign up for a free trial. Home Skip to Content Skip to Search. Sign In Account. Oracle Account Manage your account and access personalized content. Sign up for an Oracle Account Sign in to my Account. Sign in to Cloud Access your cloud dashboard, manage orders, and more.

Sign up for a free trial Sign in to Cloud. Oracle Technology Network Java.

Java Tuning White Paper

Java SE. Java Tuning White Paper. The initial target for this tuning document is tuning server applications on large, multi-processor servers. Future versions of this document will explore similar recommendations for desktop Java performance.

Therefore this document will evolve on a frequent basis to reflect the latest performance features and new best practices.

Start with Best Practices to insure you are getting the best Java performance possible even before you do any tuning. Before you dive into performance tuning it's essential to understand the right ways of Making Decisions from Data. Only with that basis in directed analysis can you safely proceed to explore Tuning Ideas for your application.

Why are there "Tuning Ideas" and not just blanket recommendations? Because every application is different and no one set of recommendations is right for every deployment environment. The Tuning Ideas section is intended to give you not just Java command line options but also background on what they mean and when they may lead to increased performance. Even during the tuning process, but certainly as you want to take performance to the next level it will be necessary to explore Monitoring and Profiling your application.

By gathering detailed data on actual application performance you can fine tune command line options and have an idea where to focus coding improvement efforts. Many other documents and sites will be collected in the Pointers section.

We encourage you to help continue making Java faster through Feedback and the Java Performance Community.

Replies to “Jvm performance tuning”

Leave a Reply

Your email address will not be published. Required fields are marked *