Comparing Java Implementations for Linux
Given the amount of hype that Linux and Java are currently receiving, the combination of the two rates a solid 12 on a hype scale ranging from 1 to 10. However, being an engineer—and thus a skeptic—at heart, I prefer hard facts over marketing slogans. So, I set out to create a simple benchmark program to compare different Java implementations for Linux.
No matter what the hype says, I believe the most important contribution of Java is that it is simply a very well-designed programming language that most professionals enjoy using. Some of the features of Java that make it attractive for software engineers are:
Java is a “pure” object-oriented programming language (unlike C++, which is a hybrid), with a simple and elegant object model. Depending on your point of view, this may be an advantage or disadvantage. My personal experience is that programmers who are new to objects get up to speed a lot faster if they use “pure” OO languages such as Smalltalk, Eiffel or Java as opposed to hybrids such as C++.
Java avoids many of the complexities of C++, thus making programs less error-prone and programmers more productive. For example, in Java there is only one way to make a new object: you call the new operator and get a reference (or pointer, if you like) to the object. Compare this to the many ways to create objects in C++.
Java needs no preprocessor and therefore is immune to “macroitis” and endlessly nested include files.
Java has a garbage collector to free memory consumed by objects which are no longer used. In C and C++, a fair amount of design and programming work must be spent on memory allocation and deallocation schemes. Freeing objects in Java is automatic (as it is in Smalltalk and Eiffel).
The sizes of basic data types such as int and float are defined by the Java language specification, so an int is always 32 bits, regardless of the platform your program runs on. How often have you implicitly assumed that a pointer has the same size as an integer in a C program, and suffered the consequences when you ported your program to an architecture where this is not true?
Finally, Java has built-in support for multithreading and synchronization of multiple threads, and comes with a huge class library out of the box (although some people, including myself, feel that the library has gotten too huge lately).
Java is still not a standardized language, and it is doubtful if it will ever be. Sun has the final say over what's in the language and the libraries and what isn't, period. The “Java 2 Platform” or simply the Java Developer Kit (JDK) V1.2 has about 1200 classes in its libraries. Sun ships its JDK on Solaris/SPARC, Solaris/Intel, Windows-32 and recently on Linux, too. IBM has recently released a JDK 1.3 implementation for Linux. I ran the benchmark with this JDK on the same hardware and OS as all other benchmarks and got the following numbers:
Elapsed time: 1384 millisecondsObjects / millisecond: 361Output of java-version: Classic VM (J2RE 1.3.0 IBM buildcxdev-20000502 (JIT enabled: jitc))
Sun's JDK achieves platform independence of Java programs by relying on an architecture-neutral intermediate code called “bytecode”, which is interpreted on each target machine. The interpreter is called a “Java Virtual Machine” or JVM for short.
Since interpretation is slow, most JVMs come with a Just in Time Compiler (JIT). A JIT translates bytecodes into machine code on the fly, i.e., while the interpreter is running. The resulting machine code is stored in memory and lost when the interpreter terminates. Generally speaking, pure interpreters show faster program startup times, while a JVM with a JIT takes longer to start (because it compiles bytecodes); but once a program is up and running, it is faster than an interpreted program. There are many optimizations that can be made to interpreters and JIT compilers. Sun's “Hotspot” JVM, which is not yet available under Linux, but should be eventually, is one attempt to get the best from both worlds.
Finally, there is nothing in the Java language specification which prevents the application of standard compiler technology, i.e., compiling Java source code directly into machine code. The Java front end to the GNU compiler system does just that.
At the time of this writing, there were quite a few Java implementations available for Linux. These are the ones I am aware of and was able to get to work:
The Blackdown port of the Sun JDK, version 1.2.2. I tested release candidate 4 of this port, which includes both an interpreter and a JIT. The JIT is a port of the JIT shipped by Sun with the JDK for Solaris. By default, the JIT is enabled, but it can be turned off with a command-line switch. The documentation that comes with this port warns that the JIT is not yet entirely reliable. I downloaded this port from one of the numerous Blackdown FTP mirrors, which are accessible from Blackdown's homepage at http://www.blackdown.org/.
Sun's own version of the Blackdown port of Sun's JDK, version 1.2.2. Recently Sun began to publish a JDK for Linux on their own web site. This port is, as far as I can tell, the same as published by the Blackdown folks. There is at least one noticeable difference though: Sun's version comes without a JIT; it is an interpreter only. However, Sun recommends using the JIT developed by Borland. I downloaded this port from Sun's Javasoft web site at http://www.javasoft.com/.
Borland's JIT for the Sun and Blackdown ports of the JDK 1.1.2. This is not a complete Java developer kit; it is only a JIT. It works with the Blackdown port of Sun's JDK 1.2.2, and hence with the Linux JDK 1.2.2 published by Sun. I downloaded this JIT, which is a simple shared library of about 170KB, from Borland's web site at http://www.borland.com/.
The Blackdown port of the Sun JDK 1.1.8. I tested version 1 of this port, which only includes an interpreter (unlike the Windows version which comes with a JIT).
IBM's JDK version 1.1.8 for Linux. This JDK has a reputation of being “very fast” and also very stable. It comes with a JIT, which is enabled by default, but can be turned off with a command-line switch. I downloaded this JDK from IBM's web site at http://www.ibm.com/.
Kaffe version 1.0b4 from Transvirtual Technologies. Kaffe was developed by Tim Wilkonson and others from scratch, without any code from Sun. The version of Kaffe I used is compatible with Sun's JDK 1.1. I used the Kaffe package which is on the Red Hat 6.1 CD-ROM; however, there is a web site devoted to the open-source version of Kaffe at http://www.kaffe.org/. Kaffe is available for a wide range of UNIX versions and processor architectures, not just for Linux on x86 processors. The version of Kaffe I used includes a JIT, which is always on, or at least, I couldn't figure out how to turn it off.
The native Java compiler from Cygnus Support shipped with their Codefusion-1.0 development environment. This compiler is an enhanced version of EGCS, the Experimental GNU Compiler System, although you can hardly call this high-quality compiler “experimental” any more. Unlike all other Java implementations I looked at, this compiler generates native code which is link-compatible with object files created from C and C++ source files. The compiler comes with a library with the necessary runtime support for Java programs, which includes, among other things, a garbage collector. The version of EGCS I used (“2.9-codefusion-990706”) is not free; you have to buy it from Cygnus. Their web site is at www.cygnus.com/ or www.redhat.com.
|Speed Up Your Web Site with Varnish||Jun 19, 2013|
|Non-Linux FOSS: libnotify, OS X Style||Jun 18, 2013|
|Containers—Not Virtual Machines—Are the Future Cloud||Jun 17, 2013|
|Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer||Jun 12, 2013|
|Weechat, Irssi's Little Brother||Jun 11, 2013|
|One Tail Just Isn't Enough||Jun 07, 2013|
- Speed Up Your Web Site with Varnish
- Containers—Not Virtual Machines—Are the Future Cloud
- Linux Systems Administrator
- Non-Linux FOSS: libnotify, OS X Style
- Lock-Free Multi-Producer Multi-Consumer Queue on Ring Buffer
- Senior Perl Developer
- Technical Support Rep
- UX Designer
- RSS Feeds
- Reply to comment | Linux Journal
3 hours 59 min ago
- Yeah, user namespaces are
5 hours 15 min ago
- Cari Uang
8 hours 46 min ago
- user namespaces
11 hours 40 min ago
12 hours 6 min ago
- One advantage with VMs
14 hours 34 min ago
- about info
15 hours 7 min ago
15 hours 8 min ago
15 hours 9 min ago
15 hours 11 min ago
Free Webinar: Hadoop
How to Build an Optimal Hadoop Cluster to Store and Maintain Unlimited Amounts of Data Using Microservers
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
Some of key questions to be discussed are:
- What is the “typical” Hadoop cluster and what should be installed on the different machine types?
- Why should you consider the typical workload patterns when making your hardware decisions?
- Are all microservers created equal for Hadoop deployments?
- How do I plan for expansion if I require more compute, memory, storage or networking?