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You can explore the code for this example in the GitHub repo: -samples/aws-lambda-java-tiered-compilation-example. The project includes the Lambda function source code, infrastructure as code template, and instructions to deploy it to your own AWS account.
Before optimizing, you should carefully consider whether you need to optimize at all. Optimization in Java can be an elusive target since the execution environments vary. Using a better algorithm probably will yield a bigger performance increase than any amount of low-level optimizations and is more likely to deliver an improvement under all execution conditions. As a rule, high-level optimizations should be considered before doing low-level optimizations.
As a rule, 90 percent of a program's excution time is spent executing 10 percent of the code. (Some people use the 80 percent/20 percent rule, but my experience writing and optimizing commercial games in several languages for the last 15 years has shown that the 90 percent/10 percent formula is typical for performance-hungry programs since few tasks tend to be performed with great frequency.) Optimizing the other 90 percent of the program (where 10 percent of the execution time was spent) has no noticeable effect on performance. If you were able to make that 90 percent of the code execute twice as fast, the program would only be 5 percent faster. So the first task in optimizing code is to identify the 10 percent (frequently it is less than this) of the program that consumes most of the execution time. This isn't always where you expect it to be.
The level of optimization javac provides should improve, probably dramatically, as the language matures and compiler vendors begin to compete in earnest on the basis of code generation. Java just now is getting second-generation compilers.
Unfortunately, the 1.0 versions of the javac compiler have a bug that will generate code that can't pass the bytecode verifier when the -O option is used. This has been fixed in JDK 1.1. (The bytecode verifier checks code before it is allowed to run to make sure that it doesn't violate any Java rules.) It will inline methods that reference class members inaccessible to the calling class. For example, if the following classes are compiled together using the -O option
This bug doesn't make the -O option useless, but you do have to be careful about how you use it. If invoked on a single class, it can inline certain method calls within the class without risk. Several classes can be inlined together as long as there aren't any potential access restrictions. And some code (such as applications) isn't subjected to the bytecode verifier. You can ignore the bug if you know your code will only execute without being subjected to the verifier. For additional information, see my javac-O FAQ.
Fortunately, the JDK comes with a built-in profiler to help identify where time is spent in a program. It will keep track of the time spent in each routine and write the information to the file java.prof. To run the profiler, use the -prof option when invoking the Java interpreter:
Evans: One of the things that the book tries to teach is an understanding of what features are potentially performance-affecting. Things like Java's generics or the new var reserved type name are purely compile-time language features - they only really exist while javac is crunching your code. As a result, they have no runtime impact at all!
As a Java developer, you know how vital the Java runtime environment (JRE) is. The JRE is what enables your Java applications to run. In this blog post, we will discuss tips for optimizing your JRE and ensuring that your applications run as smoothly as possible.
A JRE is a software package that contains all the necessary files and libraries for running a Java application. This includes the Java Virtual Machine (JVM), responsible for executing Java code, and other standard libraries such as the java.util package.
When you download a JRE, it will usually be bundled with a Java Development Kit (JDK), which contains additional tools for developers, such as the javac compiler. If you are not a Java developer, you do not need the JDK and can use the JRE.
If you require an alpine based image with Java support, Anapsix created a set of Alpine-based images with varioustypes of java support - with JRE, with JDK, with unlimited encryption support etc - all based on the Oracle Javadistribution. In most cases the JRE version are sufficient to run your systems.
Like other NGS data analysts, as a new user i am also utilizing java applications designed for NGS data analysis.However, i saw various Java jar's optimizing parameters in command lines while processing large data sets. For example, recently i have come across two example commands, i.e.:
Note: This is the fourth of a five-part series covering Kubernetes resource management and optimization. In this article, we walk through the process of optimizing Java applications using machine learning. Previous articles in the series explained Kubernetes resource types, requests and limits and using machine learning to automate optimization.
Integrating Java and Python code is incredibly easy with Jython. The performance of Java will often be sufficient, even for CPU intensive tasks. This makes optimizing Python by means of Java extensions easy, natural and an option worth considering for your next Python project.
Optimizing finds defects that make code difficult to improve and maintain. The JDeveloper optimizing tools help you find and fix defects so that Java programs run faster, are smaller in size, and easier to maintain.
where class name is fully qualified Java class name (example: java.net.URL) or array class name. char (or [C) is char array name, java.io.File (or [Ljava.io.File;) is name of java.io.File and so on. Note that fully qualified class name does not always uniquely identify a Java class at runtime. There may be more than one Java class with the same name but loaded by different loaders. So, class name is permitted to be id string of the class object. If instanceof keyword is used, subtype objects are selected. If this keyword is not specified, only the instances of exact class specified are selected. Both from and where clauses are optional.
clazz is the class whose instances are selected. If not specified, defaults to java.lang.Object. includeSubtypes is a boolean flag that specifies whether to include subtype instances or not. Default value of this flag is true.
clazz is the class whose instances are selected. If not specified, defaults to java.lang.Object. includeSubtypes is a boolean flag that specifies whether to include subtype instances or not. Default value of this flag is true. This method accepts an optional filter expression to filter the result set of objects.
Returns an array of Java objects to which the given Java object directly refers to. This method accepts optional second parameter that is a boolean flag. This flag tells whether to include weak reference(s) or not. By default, weak reference(s) are not included. For example, to print all static reference fields of java.io.File class:
The JUnit BC4J Test Suite wizard will generate tests for each view object in the application module. If the application module does not have exported methods, the wizard will also generate a test for the application module itself. A generated view object class has the format view_objectVOTest.java and is placed into a package with the format package.view.viewobjectVO, where package is the application module package. A generated application module test has the format application_moduleAMTest.java and is placed into a package with the format package.applicationModule. A generated test fixture class has the format applicationmoduleAMFixture.java and is placed in the same package as the application module test.
You can also improve Java performance by setting the initial Java heap size, avoiding recursion, acquiring resources late and releasing them early (i.e., database connections), fixing inefficient code, optimizing garbage collection routines, using faster database queries and stored procedures, choosing the right GC algorithm (Serial GC, Parallel GC, etc.), choosing the right GC, refactoring your code, or analyzing your code with an application performance monitoring tool.
Theoretically, javac could do something similar when translating Java to bytecode, but the JIT compiler has better knowledge of the actual CPU that the code will be running on and knows how to fine-tune the code in a much more efficient way.
The first & foremost thing to do while optimizing is to collect data. Put loggers at each method (or each step of the service which is taking time). We can also use profilers or application monitoring tools on our application to identify bottleneck in our code.
So, try to use loggers extensively when you are trying to identify which part of application is taking more time. I used to log all SQL queries, file system interactions, complex loops (with queries inside it) etc while optimizing.
This doc describes how Java code is optimized in Chrome on Android and how to deal with issues caused by the optimizer. For tips on how to write optimized code, see //docs/speed/binary_size/optimization_advice.md#optimizing-java-code.
When is_java_debug = false and a target has enabled ProGuard, the proguard step generates the .dex files for the application. The proguard step takes as input a list of .jar files, runs R8/ProGuard on those .jar files, and produces the final .dex file(s) that will be packaged into your .apk
For instance, don't replace a standard library or build some complex workaround just because you believe it will improve Java performance. Prematurely optimizing things usually just makes code harder to read and harder to maintain while wasting precious development resources. 59ce067264