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Java Performance Tuning, 2nd Edition

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Review of ORA’s 2nd Edition Java Performance Tuning


Performance has been the albatross around Java’s neck for a long time. It’s a popular subject when developers get together “Don’t use Vector, use ArrayList, it’s more efficient.” “Don’t concatenate Strings, use a StringBuffer, it’s more efficient.” It’s a chance for the experienced developers to sit around the design campfire and tell ghost stories of previous projects where they implemented their own basic data structures {String, Linked List…} that was anywhere from 10-50% faster than the JDK implementation (and in the grand oral tradition of tall tales, it gets a little more efficient every time they tell it). Every developer has written a microbenchmark (a bit of code that does something 100-1000 times in a tight loop and measure the time it takes for the supposed “expensive operation”) to try and prove an argument about which way is “more efficient” based on the execution time. The problem is when running in a dynamic, managed environment like the 1.4.x JVM, there more factors that you don’t control than you do, and it can be dificult to say whether one piece of code will be “more efficient” than another without testing with actual usage patterns. This book provides substantial benchmarks (not just simple microbenchmaks) with thorough coverage of the JDK including loops, exceptions, strings, threading, and even underlying JVM improvements in the 1.4 VM. This book is one of a kind in its scope and completeness.

The Gory Details

The best part of this book is that it not only tells you how fast various standard Java operations are (sorting strings, dealing with exceptions, etc.), but he has kept all of the timing information from the previous edition of the book. This shows you how the VMs performance has changed from version 1.1.8 up to 1.4.0, and it’s very clear that things are getting better. The author also breaks out the timing information for 3 different flavors of the 1.4.0 JVM: mixed interpreted/compiled mode (standard), server (with Hotspot), and interpreted mode only (no run time optimization applied).


The book starts off with three chapters of sage advice about the tools and process of profiling/tuning. Before you spend any time profiling, you have to have a process and a goal. Without setting goals, the tuning process will never end and it will likely never be successful. The author outlines a general strategy that will give you a great starting point for your tuning task forces. Chapter 2 presents the profiling facilities that are available in the Java VM and how to interpret the results, while chapter 3 covers VM optimizations (different garbage collectors, memory allocation options) and compiler optimizations.


Chapters 4-9 cover the nuts and bolts, code-level optimizations that you can implement. Chapter 4 discusses various object allocation tweaks including: lazy initialization, canonicalizing objects, and how to use the diferent types of references (Phantom, Soft, and Weak) to implement priority object pooling. Chapter 5 tells you more about handling Strings in Java that you ever wanted to know. Converting numbers (floats, decimals, etc) to Strings efficiently, string matching, it’s all here in gory detail with timings and sample code. This chapter also shows the author’s depth and maturity; when presenting his algorithm to convert integers to Strings, he notes that while his implementation previously beat the pants off of Sun’s implementation, in 1.3.1/1.4.0 Sun implemented a change that now beats his code. He analyzes the new implementation, discusses why it’s faster without losing face. That is just one of many gems in this updated edition of the book. Chapter 6 covers the cost of throwing and catching exceptions, passing parameters to methods and accessing variables of differnt scopes (instance vs. local) and different types (scalar vs. array). Chapter 7 covers loop optimization with a java bent. The author offers proof that an exception terminated loop, while bad programming style, can offer better performance than more accepted practices. Chapter 8 covers IO, focusing in on using the proper flavor of java.io class (stream vs. reader, buffered vs. unbuffered) to acheive the best performance for a gven situation. The author also covers performance isses with object serialization (used under the hood in most Java distributed computing mechanisms) in detail and wraps up the chapter with a 12 page discussion of how best to use the “new IO” package (java.nio) that was introduced with Java 1.4. Sadly, the author doesn’t offer a detailed timing comparison of the 1.4 NIO API to the existing IO API. Chapter 9 covers Java’s native sorting implementations and how to extend their framework for your specific application.

PART 3 : Threads, Distributed Computing and Other Topics

Chapters 10-14 covers a grab bag of topics including: threading, proper Collections use, distributed computing paradigms, an optimization primer that covers full life cycle approaches to optimization. Chapter 10 does a great job of presenting threading, common threading pitfalls (deadlocks, race conditions), and how to solve them for optimal perforamce (e.g. proper scope of locks, etc). Chapter 11 provides a wonderful discussion about one of the most powerful parts of the JDK, the Collections API. It includes detailed timings of using ArrayList vs. LinkedList when traversing and building collections. To close the chapter, the author discusses different object caching implementations and their individual performance results. Chapter 12 gives some general optmization principles (with code samples) for speeding up distributed computing including techniques to minimize the amount of data transferred along with some more practical advice for designing web serivces and using JDBC. Chapter 13 deals specifically with designing/architecting applications for performance. It discusses how performance should be addressed in each phase of the development cycle (analysis, design, development, deployment), and offers tips a checklist for your performance initiatives. The puzzling thing about this chapter is why it is presented at the end of the book instead of towards the front with all of the other process-related material. It makes much more sense to put this material together up front. Chapter 14 covers various hardware and network aspects that can impact applicaiton performance including: network topology, DNS lookups, and machine specs (CPU speed, RAM, disk).

PART 4 : J2EE Performance

Chapters 15-18 deal with performance specifically with the J2EE APIs: EJBs, JDBC, Servlets and JSPs. These chapters are essentially tips or suggested patterns (use coarse grained EJBs, apply the Value Object pattern, etc) instead of very low-level performance tips and metrics provided in earlier chapters. You could say that the author is getting lazy, but the truth is that due to huge number of combinations of appserver/database vendor combinations, it would be very dificult to establish a meaningful performance baseline without a large testbed. Chapter 15 is a reiteration of Chapter 1, Tuning Strategy, re-tooled with a J2EE focus. The author reiterates that a good testing strategy determines what to measure, how to measure it, and what the expectations are. From here, the author presents possible solutions including load balancing. This chapter also contains about 1.5 pages about tuning JMS, which seems to have been added to be J2EE 1.3 acronym compliant. Chapter 16 provides excellent information about JDBC performance strategies. The author presents a proxy implementation to capture accurate profiling data and minimize changes to your code once the profiling effort is over. The author also covers data caching, batch processing and how the different transaction levels can affect JDBC performance. Chapter 17 covers JSPs and servlets, with very little earth shattering information. The author presents tips such as consider GZipping the content before returning it to the client, and minimize custom tags. This chapter is easily the weakest section of the books. Admittedly, it’s difficult to optimize JSPs since much of the actual running code is produced by the interpreter/compiler, but this chapter either needs to be beefed up or dropped from future editions. Finally, chapter 18 provides a design/architecture-time approach towards EJB performance. The author presents standard EJB patterns that lend themselves towards squeezing greater performance out of the often maligned EJB. The patterns include: data access object, page iterator, service locator, message facade, and others. Again, there’s nothing earth shattering in this chapter. Chapter 19 is list of resources with links to articles, books and profiling/optimizing projects and products.

What’s Bad?

Since the book has been published, the 1.4.1 VM has been released with the much anticipated concurrent garbage collector. The author mentions that he received an early version of 1.4.1 from Sun to test with. However, the text doesn’t state that he used the concurrent garbage collector, so the performance of this new feature hasn’t been determined by this text.

The J2EE performance chapters aren’t as strong as the J2SE chapters. After seeing the statistics and extensive code samples of the J2SE sections, I expected a similar treatment for J2EE. Many of the J2SE performance practices still apply for J2EE (serialization most notably, since that his how EJB, JMS, and RMI ship method parameters/results across the wire), but it would be useful to fortify these chapters with actual performance metrics.

So What’s In It For Me?

This book is indispensible for the archtiect drafting the performance requirements/testing process, and contains sage advice for the programmer as well. It’s the most up to date publication dealing specifically with performance of Java applications, and is a one of a kind resource.

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