JDK 5.0 is a huge step forward in developing concurrent Java classes and applications, providing a rich set of high-level concurrency building blocks.

Prior to the release of JDK 5.0, the Java platform provided basic primitives for writing concurrent programs, but they were just that -- primitive -- and difficult to use properly. Building multithreaded applications on the Java platform's low-level concurrency primitives posed many traps for the unwary, and many developers were forced to reinvent the wheel by writing their own classes for thread pools, semaphores, and task schedulers.

To help users create robust, scalable, and (most importantly) correct multithreaded applications, JDK 5.0 includes a rich set of high-level concurrency constructs, such as thread pools, semaphores, mutexes, barriers, and high-performance concurrent collection classes. Using these concurrency utilities will, in most cases, make your programs clearer, shorter, faster, easier to write, and more reliable. This session provides you with an overview of the new high-level concurrency utilities in the new java.util.concurrent package in JDK 5.0.

The Java programming language has turned a generation of applications programmers into concurrent programmers through its direct support of multithreading. However, the Java concurrency primitives are just that: primitive. From them you can build many concurrency utilities, but doing so takes great care as concurrent programming poses many traps for the unwary.

Based on the principles in the best-selling Java Concurrency in Practice, this talk focuses on design techniques that help you create correct and maintainable concurrent code.

Presented in the style of Effective Java, this talk offers bite-sized items for effectively writing concurrent code, divided into three categories: writing thread-safe code, structuring concurrent applications, and improving scalability.

Writing thread-safe code: - Encapsulate your data - Encapsulate any needed synchronization - Document thread-safety intent and implementation - Prefer immutable objects - Exploit effective immutability

Rules for structuring concurrent applications - Think tasks, not threads - Build resource-management into your architecture - Decouple identification of work from execution

Rules for improving scalability - Find and eliminate serialization

Transactions are the software building blocks of enterprise applications, but not all transactional systems are created equally. This talk covers the basics of what transactions are, why they are essential to building reliable enterprise software, the fundamental properties of transactions, and how transactions are supported and implemented in popular frameworks such as Java EE and Spring.

Murphy's Law states that anything that can go wrong, will go wrong. And in enterprise applications, there are lots of things that can go wrong -- disks fill up or fail, systems crash, network connections go down, clumsy people trip over power cords. While you can't prevent failures from happening, you can prevent failures from corrupting your application data, and transactions are the standard way to structure application logic to enable reliable error recovery in the face of inevitable failures.

This talk covers what transactions are, the various participants in local and distributed transactions, the role of transactions in enterprise technologies such as Java EE, Spring, and Web Services, how user code communicates its transactional requirements, and the behind-the-scenes magic how enterprise frameworks hide most of the implementation of transactions from applications.

What's the worst thing that can happen when you fail to synchronize in a concurrent Java program? Its probably worse than you think -- modern shared-memory processors can do some pretty weird things when left to their own devices.

Java was the first mainstream programming language to incorporate a formal, cross-platform memory model, which is what enabled the development of write-once, run-anywhere concurrent classes. It is the Java Memory model that defines the semantics of synchronized, volatile, and final.

However, because the most commonly used processors (Intel and Sparc) offer stronger memory models than is required by the JMM, many developers frequently use synchronization and volatile incorrectly, but have been insulated from failure by the stronger memory guarantees offered by the processor architecture they happen to be deploying on. (The infamous "double checked locking" idiom is an example of this sort of error.)

Understanding the Java Memory model is key to using the core concurrency primitives (synchronized and volatile) to develop thread-safe, efficient concurrent classes. We?ll cover what a memory model is (and why we should care), what synchronization really means, and what can really go wrong when we fail to synchronized correctly.

Performance myths about the Java platform abound, from the general "Java is slow", to the more specific "reflection is slow", "allocation is slow", "synchronization is slow", "garbage collection is slow", etc. Many of these myths have their root in fact (in JDK 1.0, everything was slow); today, not only are many of these statements not true, but Java performance has surpassed that of C in many areas, such as memory management.

In this class, we'll look at some common Java performance myths, identify where they came from, and explore the platform changes that have rendered them no longer true. Many common performance hacks don't actually help, and some can seriously hurt performance. The result is that clean code that follows common usage patterns generally shows far better behavior on modern JVMs than code laden with tweaks designed to "help" the JIT or garbage collector. More often than not, this well-intentioned assistance has the unfortunate effect of undermining many common JIT optimizations, resulting in slower -- not faster -- code.