Retrieval operations (including {@code get}) generally do not block, so may overlap with update operations (including {@code put}and {@code remove}). Retrievals reflect the results of the most recently completed update operations holding upon their onset. (More formally, an update operation for a given key bears a happens-before relation with any (non-null) retrieval for that key reporting the updated value.) For aggregate operations such as {@code putAll} and {@code clear}, concurrent retrievals may reflect insertion or removal of only some entries. Similarly, Iterators and Enumerations return elements reflecting the state of the hash table at some point at or since the creation of the iterator/enumeration. They do not throw {@link ConcurrentModificationException}. However, iterators are designed to be used by only one thread at a time. Bear in mind that the results of aggregate status methods including {@code size}, {@code isEmpty}, and {@code containsValue} are typically useful only whena map is not undergoing concurrent updates in other threads. Otherwise the results of these methods reflect transient states that may be adequate for monitoring or estimation purposes, but not for program control.
The table is dynamically expanded when there are too many collisions (i.e., keys that have distinct hash codes but fall into the same slot modulo the table size), with the expected average effect of maintaining roughly two bins per mapping (corresponding to a 0.75 load factor threshold for resizing). There may be much variance around this average as mappings are added and removed, but overall, this maintains a commonly accepted time/space tradeoff for hash tables. However, resizing this or any other kind of hash table may be a relatively slow operation. When possible, it is a good idea to provide a size estimate as an optional {@code initialCapacity} constructor argument. An additional optional{@code loadFactor} constructor argument provides a further means ofcustomizing initial table capacity by specifying the table density to be used in calculating the amount of space to allocate for the given number of elements. Also, for compatibility with previous versions of this class, constructors may optionally specify an expected {@code concurrencyLevel} as an additional hint forinternal sizing. Note that using many keys with exactly the same {@code hashCode()} is a sure way to slow down performance of anyhash table.
A {@link Set} projection of a ConcurrentHashMapV8 may be created(using {@link #newKeySet()} or {@link #newKeySet(int)}), or viewed (using {@link #keySet(Object)} when only keys are of interest, and themapped values are (perhaps transiently) not used or all take the same mapping value.
A ConcurrentHashMapV8 can be used as scalable frequency map (a form of histogram or multiset) by using {@link LongAdder} valuesand initializing via {@link #computeIfAbsent}. For example, to add a count to a {@code ConcurrentHashMapV8 This class and its views and iterators implement all of the optional methods of the {@link Map} and {@link Iterator}interfaces. Like {@link Hashtable} but unlike {@link HashMap}, this class does not allow {@code null} to be used as a key or value. The concurrency properties of bulk operations follow from those of ConcurrentHashMapV8: Any non-null result returned from {@code get(key)} and related access methods bears ahappens-before relation with the associated insertion or update. The result of any bulk operation reflects the composition of these per-element relations (but is not necessarily atomic with respect to the map as a whole unless it is somehow known to be quiescent). Conversely, because keys and values in the map are never null, null serves as a reliable atomic indicator of the current lack of any result. To maintain this property, null serves as an implicit basis for all non-scalar reduction operations. For the double, long, and int versions, the basis should be one that, when combined with any other value, returns that other value (more formally, it should be the identity element for the reduction). Most common reductions have these properties; for example, computing a sum with basis 0 or a minimum with basis MAX_VALUE. Search and transformation functions provided as arguments should similarly return null to indicate the lack of any result (in which case it is not used). In the case of mapped reductions, this also enables transformations to serve as filters, returning null (or, in the case of primitive specializations, the identity basis) if the element should not be combined. You can create compound transformations and filterings by composing them yourself under this "null means there is nothing there now" rule before using them in search or reduce operations. Methods accepting and/or returning Entry arguments maintain key-value associations. They may be useful for example when finding the key for the greatest value. Note that "plain" Entry arguments can be supplied using {@code newAbstractMap.SimpleEntry(k,v)}. Bulk operations may complete abruptly, throwing an exception encountered in the application of a supplied function. Bear in mind when handling such exceptions that other concurrently executing functions could also have thrown exceptions, or would have done so if the first exception had not occurred. Parallel speedups for bulk operations compared to sequential processing are common but not guaranteed. Operations involving brief functions on small maps may execute more slowly than sequential loops if the underlying work to parallelize the computation is more expensive than the computation itself. Similarly, parallelization may not lead to much actual parallelism if all processors are busy performing unrelated tasks. All arguments to all task methods must be non-null. jsr166e note: During transition, this class uses nested functional interfaces with different names but the same forms as those expected for JDK8.
@since 1.5
@author Doug Lea
@param < K> the type of keys maintained by this map
@param < V> the type of mapped values
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