Nuances of Java development
This blog is about Java development and describes in detail the most interesting topics.
The singleton design pattern is one of the most inappropriately used patterns. In this article we review several implementations of a singleton that work correctly in multithreaded environment, with serialization and cloning tasks and even with reflection attacks.
Contents What for you can use singleton Distinction from static class Lazy or eager loading singleton? Eager loading singleton Rough synchronization Double-checked locking singleton Initialization-on-demand holder idiom The enum based singleton Problems with serialization and deserialization Problems with clone Problems with reflection So, why you can think about singleton as anti-pattern? Conclusion What for you can use singleton The singleton pattern is used when there must be exactly one instance of a class, and it must be accessible to clients from a well-known access point or when the single instance should be extensible by sub-classes, and clients should be able to use an extended instance without modifying their code. Distinction from static class JDK has examples of both singleton and static, on the one hand java.lang.Math is a final class with static methods, on the other hand java.lang.Runtime is a singleton class. Advantages of singleton If your need to maintain state than singleton pattern is better choice than static class, because maintaining state in static class leads to bugs, especially in concurrent environment, that could lead to race conditions without adeq... Read more
One addition in Java 7 is an interface TransferQueue in addition already exists from Java 5 SynchronousQueue. What is the reason of new interface?
Contents Firstly about TransferQueue Couple words about SynchronousQueue SynchronousQueue vs TransferQueue Firstly about TransferQueue Java 7 included new interface TransferQueue and corresponded implementation LinkedTransferQueue. TransferQueue extends BlockingQueue which extends Queue interface, added in Java 5. BlockingQueue is a queue, which can block Producer threads during adding items into a full queue and Consumer threads, during removing from an empty queue. Main idea of blocking queues is to cope with flood of data, which can not be processed by system for appropriate time. TransferQueue goes further, and blocks Producer threads until the items consumed by Consumer threads. New method — transfer — blocking occurs until item moves from one thread to another. There are additional methods — two forms of tryTransfer — one is blocking with time-out, other is non-blocking but transfer only if Consumer thread is waiting. Also there are a couple helper methods hasWaitingConsumer and getWaitingConsumerCount. Couple words about SynchronousQueue We remember about SynchronousQueue from Java 5, which provides queue with size 0 and quite good for transfer items between threads. Thi... Read more
Before Java 1.5, if you need Map implementation, which can be safely used in multithreading Java-application, you have only Hashtable or synchronized Map, because HashMap is NOT safe.
Contents Introduction How ConcurrentHashMap is implemented Some important features of ConcurrentHashMap When you should use ConcurrentHashMap in Java Introduction ConcurrentHashMap was presented as alternative to Hashtable in Java 1.5 as part of concurrency package. With ConcurrentHashMap, you have a better choice not only if it can be safely used in the concurrent multi-threaded environment but also provides better performance than Hashtable and synchronizedMap. ConcurrentHashMap performs better because it locks a part of Map. It allows concurred read operations and the same time maintains integrity by synchronizing write operations. How ConcurrentHashMap is implemented ConcurrentHashMap was developed as alternative of Hashtable and support all functionality of Hashtable with additional ability, so called concurrency level. ConcurrentHashMap allows multiple readers to read simultaneously without using blocks. It becomes possible by separating Map to different parts and blocking only part of Map in updates. By default, concurrency level is 16, so Map is spitted to 16 parts and each part is managed by separated block. It means, that 16 threads can work with Map simultaneously, i... Read more