Accesso contemporaneo da + thread ad una stessa hashmap statica

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ConcurrentHashMap

The ConcurrentHashMap class from util.concurrent (which will also appear in the java.util.concurrent package in JDK 1.5) is a thread-safe implementation of Map that offers far better concurrency than synchronizedMap. Multiple reads can almost always execute concurrently, simultaneous reads and writes can usually execute concurrently, and multiple simultaneous writes can often execute concurrently. (The related ConcurrentReaderHashMap class offers similar multiple-reader concurrency, but allows only a single active writer.) ConcurrentHashMap is designed to optimize retrieval operations; in fact, successful get() operations usually succeed with no locking at all. Achieving thread-safety without locking is tricky and requires a deep understanding of the details of the Java Memory Model. The ConcurrentHashMap implementation, along with the rest of util.concurrent, has been extensively peer-reviewed by concurrency experts for correctness and thread safety. We will look at the implementation details of ConcurrentHashMap in next month's article.

ConcurrentHashMap achieves higher concurrency by slightly relaxing the promises it makes to callers. A retrieval operation will return the value inserted by the most recent completed insert operation, and may also return a value added by an insertion operation that is concurrently in progress (but in no case will it return a nonsense result). Iterators returned by ConcurrentHashMap.iterator() will return each element once at most and will not ever throw ConcurrentModificationException, but may or may not reflect insertions or removals that occurred since the iterator was constructed. No table-wide locking is needed (or even possible) to provide thread-safety when iterating the collection. ConcurrentHashMap may be used as a replacement for synchronizedMap or Hashtable in any application that does not rely on the ability to lock the entire table to prevent updates.

These compromises enable ConcurrentHashMap to provide far superior scalability over Hashtable, without compromising its effectiveness in a wide variety of common-use cases, such as shared caches.