JDK8之ConcurrentHashMap源码解读
2024-04-17 01:11:08
本文默认读者阅读过JDK8的HashMap源码，不再对源码中的红黑树操作进行分析。
本文主要对put()、transfer()、addCount()进行分析（replaceNode()源码近似于put就不再多言)
如果大家对其有异议，请留言。
共同进步(2018-03-02)
package java.util.concurrent;
import java.io.ObjectStreamField;
import java.io.Serializable;
import java.lang.reflect.ParameterizedType;
import java.lang.reflect.Type;
import java.util.AbstractMap;
import java.util.Arrays;
import java.util.Collection;
import java.util.Comparator;
import java.util.Enumeration;
import java.util.HashMap;
import java.util.Hashtable;
import java.util.Iterator;
import java.util.Map;
import java.util.NoSuchElementException;
import java.util.Set;
import java.util.Spliterator;
import java.util.concurrent.ConcurrentMap;
import java.util.concurrent.ForkJoinPool;
import java.util.concurrent.atomic.AtomicReference;
import java.util.concurrent.locks.LockSupport;
import java.util.concurrent.locks.ReentrantLock;
import java.util.function.BiConsumer;
import java.util.function.BiFunction;
import java.util.function.BinaryOperator;
import java.util.function.Consumer;
import java.util.function.DoubleBinaryOperator;
import java.util.function.Function;
import java.util.function.IntBinaryOperator;
import java.util.function.LongBinaryOperator;
import java.util.function.ToDoubleBiFunction;
import java.util.function.ToDoubleFunction;
import java.util.function.ToIntBiFunction;
import java.util.function.ToIntFunction;
import java.util.function.ToLongBiFunction;
import java.util.function.ToLongFunction;
import java.util.stream.Stream;
/**
* A hash table supporting full concurrency of retrievals and
* high expected concurrency for updates. This class obeys the
* same functional specification as {@link java.util.Hashtable}, and
* includes versions of methods corresponding to each method of
* {@code Hashtable}. However, even though all operations are
* thread-safe, retrieval operations do <em>not</em> entail locking,
* and there is <em>not</em> any support for locking the entire table
* in a way that prevents all access. This class is fully
* interoperable with {@code Hashtable} in programs that rely on its
* thread safety but not on its synchronization details.
*
* <p>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 <em>completed</em> update operations holding upon their
* onset. (More formally, an update operation for a given key bears a
* <em>happens-before</em> 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, Spliterators 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 <em>not</em> throw {@link
* java.util.ConcurrentModificationException 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 when a 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.
*
* <p>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 of
* customizing 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 for
* internal sizing. Note that using many keys with exactly the same
* {@code hashCode()} is a sure way to slow down performance of any
* hash table. To ameliorate impact, when keys are {@link Comparable},
* this class may use comparison order among keys to help break ties.
*
* <p>A {@link Set} projection of a ConcurrentHashMap may be created
* (using {@link #newKeySet()} or {@link #newKeySet(int)}), or viewed
* (using {@link #keySet(Object)} when only keys are of interest, and the
* mapped values are (perhaps transiently) not used or all take the
* same mapping value.
*
* <p>A ConcurrentHashMap can be used as scalable frequency map (a
* form of histogram or multiset) by using {@link
* java.util.concurrent.atomic.LongAdder} values and initializing via
* {@link #computeIfAbsent computeIfAbsent}. For example, to add a count
* to a {@code ConcurrentHashMap<String,LongAdder> freqs}, you can use
* {@code freqs.computeIfAbsent(k -> new LongAdder()).increment();}
*
* <p>This class and its views and iterators implement all of the
* <em>optional</em> methods of the {@link Map} and {@link Iterator}
* interfaces.
*
* <p>Like {@link Hashtable} but unlike {@link HashMap}, this class
* does <em>not</em> allow {@code null} to be used as a key or value.
*
* <p>ConcurrentHashMaps support a set of sequential and parallel bulk
* operations that, unlike most {@link Stream} methods, are designed
* to be safely, and often sensibly, applied even with maps that are
* being concurrently updated by other threads; for example, when
* computing a snapshot summary of the values in a shared registry.
* There are three kinds of operation, each with four forms, accepting
* functions with Keys, Values, Entries, and (Key, Value) arguments
* and/or return values. Because the elements of a ConcurrentHashMap
* are not ordered in any particular way, and may be processed in
* different orders in different parallel executions, the correctness
* of supplied functions should not depend on any ordering, or on any
* other objects or values that may transiently change while
* computation is in progress; and except for forEach actions, should
* ideally be side-effect-free. Bulk operations on {@link java.util.Map.Entry}
* objects do not support method {@code setValue}.
*
* <ul>
* <li> forEach: Perform a given action on each element.
* A variant form applies a given transformation on each element
* before performing the action.</li>
*
* <li> search: Return the first available non-null result of
* applying a given function on each element; skipping further
* search when a result is found.</li>
*
* <li> reduce: Accumulate each element. The supplied reduction
* function cannot rely on ordering (more formally, it should be
* both associative and commutative). There are five variants:
*
* <ul>
*
* <li> Plain reductions. (There is not a form of this method for
* (key, value) function arguments since there is no corresponding
* return type.)</li>
*
* <li> Mapped reductions that accumulate the results of a given
* function applied to each element.</li>
*
* <li> Reductions to scalar doubles, longs, and ints, using a
* given basis value.</li>
*
* </ul>
* </li>
* </ul>
*
* <p>These bulk operations accept a {@code parallelismThreshold}
* argument. Methods proceed sequentially if the current map size is
* estimated to be less than the given threshold. Using a value of
* {@code Long.MAX_VALUE} suppresses all parallelism. Using a value
* of {@code 1} results in maximal parallelism by partitioning into
* enough subtasks to fully utilize the {@link
* ForkJoinPool#commonPool()} that is used for all parallel
* computations. Normally, you would initially choose one of these
* extreme values, and then measure performance of using in-between
* values that trade off overhead versus throughput.
*
* <p>The concurrency properties of bulk operations follow
* from those of ConcurrentHashMap: Any non-null result returned
* from {@code get(key)} and related access methods bears a
* happens-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.
*
* <p>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.
*
* <p>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 new
* AbstractMap.SimpleEntry(k,v)}.
*
* <p>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.
*
* <p>Speedups for parallel compared to sequential forms are common
* but not guaranteed. Parallel operations involving brief functions
* on small maps may execute more slowly than sequential forms 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.
*
* <p>All arguments to all task methods must be non-null.
*
* <p>This class is a member of the
* <a href="{@docRoot}/../technotes/guides/collections/index.html">
* Java Collections Framework</a>.
*
* @since 1.5
* @author Doug Lea
* @param <K> the type of keys maintained by this map
* @param <V> the type of mapped values
*/
public class ConcurrentHashMap<K,V> extends AbstractMap<K,V>implements ConcurrentMap<K,V>, Serializable {private static final long serialVersionUID = 7249069246763182397L;
/*
* Overview:
*
* The primary design goal of this hash table is to maintain
* concurrent readability (typically method get(), but also
* iterators and related methods) while minimizing update
* contention. Secondary goals are to keep space consumption about
* the same or better than java.util.HashMap, and to support high
* initial insertion rates on an empty table by many threads.
*
* This map usually acts as a binned (bucketed) hash table. Each
* key-value mapping is held in a Node. Most nodes are instances
* of the basic Node class with hash, key, value, and next
* fields. However, various subclasses exist: TreeNodes are
* arranged in balanced trees, not lists. TreeBins hold the roots
* of sets of TreeNodes. ForwardingNodes are placed at the heads
* of bins during resizing. ReservationNodes are used as
* placeholders while establishing values in computeIfAbsent and
* related methods. The types TreeBin, ForwardingNode, and
* ReservationNode do not hold normal user keys, values, or
* hashes, and are readily distinguishable during search etc
* because they have negative hash fields and null key and value
* fields. (These special nodes are either uncommon or transient,
* so the impact of carrying around some unused fields is
* insignificant.)
*
* The table is lazily initialized to a power-of-two size upon the
* first insertion. Each bin in the table normally contains a
* list of Nodes (most often, the list has only zero or one Node).
* Table accesses require volatile/atomic reads, writes, and
* CASes. Because there is no other way to arrange this without
* adding further indirections, we use intrinsics
* (sun.misc.Unsafe) operations.
*
* We use the top (sign) bit of Node hash fields for control
* purposes -- it is available anyway because of addressing
* constraints. Nodes with negative hash fields are specially
* handled or ignored in map methods.
*
* Insertion (via put or its variants) of the first node in an
* empty bin is performed by just CASing it to the bin. This is
* by far the most common case for put operations under most
* key/hash distributions. Other update operations (insert,
* delete, and replace) require locks. We do not want to waste
* the space required to associate a distinct lock object with
* each bin, so instead use the first node of a bin list itself as
* a lock. Locking support for these locks relies on builtin
* "synchronized" monitors.
*
* Using the first node of a list as a lock does not by itself
* suffice though: When a node is locked, any update must first
* validate that it is still the first node after locking it, and
* retry if not. Because new nodes are always appended to lists,
* once a node is first in a bin, it remains first until deleted
* or the bin becomes invalidated (upon resizing).
*
* The main disadvantage of per-bin locks is that other update
* operations on other nodes in a bin list protected by the same
* lock can stall, for example when user equals() or mapping
* functions take a long time. However, statistically, under
* random hash codes, this is not a common problem. Ideally, the
* frequency of nodes in bins follows a Poisson distribution
* (http://en.wikipedia.org/wiki/Poisson_distribution) with a
* parameter of about 0.5 on average, given the resizing threshold
* of 0.75, although with a large variance because of resizing
* granularity. Ignoring variance, the expected occurrences of
* list size k are (exp(-0.5) * pow(0.5, k) / factorial(k)). The
* first values are:
*
* 0: 0.60653066
* 1: 0.30326533
* 2: 0.07581633
* 3: 0.01263606
* 4: 0.00157952
* 5: 0.00015795
* 6: 0.00001316
* 7: 0.00000094
* 8: 0.00000006
* more: less than 1 in ten million
*
* Lock contention probability for two threads accessing distinct
* elements is roughly 1 / (8 * #elements) under random hashes.
*
* Actual hash code distributions encountered in practice
* sometimes deviate significantly from uniform randomness. This
* includes the case when N > (1<<30), so some keys MUST collide.
* Similarly for dumb or hostile usages in which multiple keys are
* designed to have identical hash codes or ones that differs only
* in masked-out high bits. So we use a secondary strategy that
* applies when the number of nodes in a bin exceeds a
* threshold. These TreeBins use a balanced tree to hold nodes (a
* specialized form of red-black trees), bounding search time to
* O(log N). Each search step in a TreeBin is at least twice as
* slow as in a regular list, but given that N cannot exceed
* (1<<64) (before running out of addresses) this bounds search
* steps, lock hold times, etc, to reasonable constants (roughly
* 100 nodes inspected per operation worst case) so long as keys
* are Comparable (which is very common -- String, Long, etc).
* TreeBin nodes (TreeNodes) also maintain the same "next"
* traversal pointers as regular nodes, so can be traversed in
* iterators in the same way.
*
* The table is resized when occupancy exceeds a percentage
* threshold (nominally, 0.75, but see below). Any thread
* noticing an overfull bin may assist in resizing after the
* initiating thread allocates and sets up the replacement array.
* However, rather than stalling, these other threads may proceed
* with insertions etc. The use of TreeBins shields us from the
* worst case effects of overfilling while resizes are in
* progress. Resizing proceeds by transferring bins, one by one,
* from the table to the next table. However, threads claim small
* blocks of indices to transfer (via field transferIndex) before
* doing so, reducing contention. A generation stamp in field
* sizeCtl ensures that resizings do not overlap. Because we are
* using power-of-two expansion, the elements from each bin must
* either stay at same index, or move with a power of two
* offset. We eliminate unnecessary node creation by catching
* cases where old nodes can be reused because their next fields
* won't change. On average, only about one-sixth of them need
* cloning when a table doubles. The nodes they replace will be
* garbage collectable as soon as they are no longer referenced by
* any reader thread that may be in the midst of concurrently
* traversing table. Upon transfer, the old table bin contains
* only a special forwarding node (with hash field "MOVED") that
* contains the next table as its key. On encountering a
* forwarding node, access and update operations restart, using
* the new table.
*
* Each bin transfer requires its bin lock, which can stall
* waiting for locks while resizing. However, because other
* threads can join in and help resize rather than contend for
* locks, average aggregate waits become shorter as resizing
* progresses. The transfer operation must also ensure that all
* accessible bins in both the old and new table are usable by any
* traversal. This is arranged in part by proceeding from the
* last bin (table.length - 1) up towards the first. Upon seeing
* a forwarding node, traversals (see class Traverser) arrange to
* move to the new table without revisiting nodes. To ensure that
* no intervening nodes are skipped even when moved out of order,
* a stack (see class TableStack) is created on first encounter of
* a forwarding node during a traversal, to maintain its place if
* later processing the current table. The need for these
* save/restore mechanics is relatively rare, but when one
* forwarding node is encountered, typically many more will be.
* So Traversers use a simple caching scheme to avoid creating so
* many new TableStack nodes. (Thanks to Peter Levart for
* suggesting use of a stack here.)
*
* The traversal scheme also applies to partial traversals of
* ranges of bins (via an alternate Traverser constructor)
* to support partitioned aggregate operations. Also, read-only
* operations give up if ever forwarded to a null table, which
* provides support for shutdown-style clearing, which is also not
* currently implemented.
*
* Lazy table initialization minimizes footprint until first use,
* and also avoids resizings when the first operation is from a
* putAll, constructor with map argument, or deserialization.
* These cases attempt to override the initial capacity settings,
* but harmlessly fail to take effect in cases of races.
*
* The element count is maintained using a specialization of
* LongAdder. We need to incorporate a specialization rather than
* just use a LongAdder in order to access implicit
* contention-sensing that leads to creation of multiple
* CounterCells. The counter mechanics avoid contention on
* updates but can encounter cache thrashing if read too
* frequently during concurrent access. To avoid reading so often,
* resizing under contention is attempted only upon adding to a
* bin already holding two or more nodes. Under uniform hash
* distributions, the probability of this occurring at threshold
* is around 13%, meaning that only about 1 in 8 puts check
* threshold (and after resizing, many fewer do so).
*
* TreeBins use a special form of comparison for search and
* related operations (which is the main reason we cannot use
* existing collections such as TreeMaps). TreeBins contain
* Comparable elements, but may contain others, as well as
* elements that are Comparable but not necessarily Comparable for
* the same T, so we cannot invoke compareTo among them. To handle
* this, the tree is ordered primarily by hash value, then by
* Comparable.compareTo order if applicable. On lookup at a node,
* if elements are not comparable or compare as 0 then both left
* and right children may need to be searched in the case of tied
* hash values. (This corresponds to the full list search that
* would be necessary if all elements were non-Comparable and had
* tied hashes.) On insertion, to keep a total ordering (or as
* close as is required here) across rebalancings, we compare
* classes and identityHashCodes as tie-breakers. The red-black
* balancing code is updated from pre-jdk-collections
* (http://gee.cs.oswego.edu/dl/classes/collections/RBCell.java)
* based in turn on Cormen, Leiserson, and Rivest "Introduction to
* Algorithms" (CLR).
*
* TreeBins also require an additional locking mechanism. While
* list traversal is always possible by readers even during
* updates, tree traversal is not, mainly because of tree-rotations
* that may change the root node and/or its linkages. TreeBins
* include a simple read-write lock mechanism parasitic on the
* main bin-synchronization strategy: Structural adjustments
* associated with an insertion or removal are already bin-locked
* (and so cannot conflict with other writers) but must wait for
* ongoing readers to finish. Since there can be only one such
* waiter, we use a simple scheme using a single "waiter" field to
* block writers. However, readers need never block. If the root
* lock is held, they proceed along the slow traversal path (via
* next-pointers) until the lock becomes available or the list is
* exhausted, whichever comes first. These cases are not fast, but
* maximize aggregate expected throughput.
*
* Maintaining API and serialization compatibility with previous
* versions of this class introduces several oddities. Mainly: We
* leave untouched but unused constructor arguments refering to
* concurrencyLevel. We accept a loadFactor constructor argument,
* but apply it only to initial table capacity (which is the only
* time that we can guarantee to honor it.) We also declare an
* unused "Segment" class that is instantiated in minimal form
* only when serializing.
*
* Also, solely for compatibility with previous versions of this
* class, it extends AbstractMap, even though all of its methods
* are overridden, so it is just useless baggage.
*
* This file is organized to make things a little easier to follow
* while reading than they might otherwise: First the main static
* declarations and utilities, then fields, then main public
* methods (with a few factorings of multiple public methods into
* internal ones), then sizing methods, trees, traversers, and
* bulk operations.
*/
/* ---------------- Constants -------------- */
/**
* The largest possible table capacity. This value must be
* exactly 1<<30 to stay within Java array allocation and indexing
* bounds for power of two table sizes, and is further required
* because the top two bits of 32bit hash fields are used for
* control purposes.
*/
private static final int MAXIMUM_CAPACITY = 1 << 30;
/**
* The default initial table capacity. Must be a power of 2
* (i.e., at least 1) and at most MAXIMUM_CAPACITY.
*/
/**
* 默认数组容量
*/
private static final int DEFAULT_CAPACITY = 16;
/**
* The largest possible (non-power of two) array size.
* Needed by toArray and related methods.
*/
static final int MAX_ARRAY_SIZE = Integer.MAX_VALUE - 8;
/**
* The default concurrency level for this table. Unused but
* defined for compatibility with previous versions of this class.
*/
/**
* Concurrency_level在之前的版本上是用于并发度的，但是1.8直接对
* 每一个桶都上锁了，所以这里还留着Concurrecy_level是为了兼容之前的版本
*/
private static final int DEFAULT_CONCURRENCY_LEVEL = 16;
/**
* The load factor for this table. Overrides of this value in
* constructors affect only the initial table capacity. The
* actual floating point value isn't normally used -- it is
* simpler to use expressions such as {@code n - (n >>> 2)} for
* the associated resizing threshold.
*/
private static final float LOAD_FACTOR = 0.75f;
/**
* The bin count threshold for using a tree rather than list for a
* bin. Bins are converted to trees when adding an element to a
* bin with at least this many nodes. The value must be greater
* than 2, and should be at least 8 to mesh with assumptions in
* tree removal about conversion back to plain bins upon
* shrinkage.
*/
static final int TREEIFY_THRESHOLD = 8;
/**
* The bin count threshold for untreeifying a (split) bin during a
* resize operation. Should be less than TREEIFY_THRESHOLD, and at
* most 6 to mesh with shrinkage detection under removal.
*/
static final int UNTREEIFY_THRESHOLD = 6;
/**
* The smallest table capacity for which bins may be treeified.
* (Otherwise the table is resized if too many nodes in a bin.)
* The value should be at least 4 * TREEIFY_THRESHOLD to avoid
* conflicts between resizing and treeification thresholds.
*/
static final int MIN_TREEIFY_CAPACITY = 64;
/**
* Minimum number of rebinnings per transfer step. Ranges are
* subdivided to allow multiple resizer threads. This value
* serves as a lower bound to avoid resizers encountering
* excessive memory contention. The value should be at least
* DEFAULT_CAPACITY.
*/
/**
* 一次(扩容)迁移的最少的slot数目（即CPU处理的量），避免桶的数目太小，
* 导致出现过多的内存争用
*/
private static final int MIN_TRANSFER_STRIDE = 16;
/**
* The number of bits used for generation stamp in sizeCtl.
* Must be at least 6 for 32bit arrays.
*/
private static int RESIZE_STAMP_BITS = 16;
/**
* The maximum number of threads that can help resize.
* Must fit in 32 - RESIZE_STAMP_BITS bits.
*/
private static final int MAX_RESIZERS = (1 << (32 - RESIZE_STAMP_BITS)) - 1;
/**
* The bit shift for recording size stamp in sizeCtl.
*/
private static final int RESIZE_STAMP_SHIFT = 32 - RESIZE_STAMP_BITS;
/*
* Encodings for Node hash fields. See above for explanation.
*/
/**
* hash值为-1的时候表示是ForwardingNode，ForwardingNode在构造函数的时候传入了MOVED
* 下面都类似，TREEBIN在TreeBin构造函数中使用,RESERVED在ReservationNode构造函数中使用
*/
static final int MOVED = -1; // hash for forwarding nodes
static final int TREEBIN = -2; // hash for roots of trees
static final int RESERVED = -3; // hash for transient reservations
static final int HASH_BITS = 0x7fffffff; // usable bits of normal node hash
/** Number of CPUS, to place bounds on some sizings */
static final int NCPU = Runtime.getRuntime().availableProcessors();
/** For serialization compatibility. */
private static final ObjectStreamField[] serialPersistentFields = {new ObjectStreamField("segments", Segment[].class),
new ObjectStreamField("segmentMask", Integer.TYPE),
new ObjectStreamField("segmentShift", Integer.TYPE)};
/* ---------------- Nodes -------------- */
/**
* Key-value entry. This class is never exported out as a
* user-mutable Map.Entry (i.e., one supporting setValue; see
* MapEntry below), but can be used for read-only traversals used
* in bulk tasks. Subclasses of Node with a negative hash field
* are special, and contain null keys and values (but are never
* exported). Otherwise, keys and vals are never null.
*/
static class Node<K,V> implements Map.Entry<K,V> {final int hash;
final K key;
volatile V val;
volatile Node<K,V> next;
Node(int hash, K key, V val, Node<K,V> next) {this.hash = hash;
this.key = key;
this.val = val;
this.next = next;
}public final K getKey() { return key; }public final V getValue() { return val; }public final int hashCode() { return key.hashCode() ^ val.hashCode(); }public final String toString(){ return key + "=" + val; }public final V setValue(V value) {throw new UnsupportedOperationException();
}public final boolean equals(Object o) {Object k, v, u; Map.Entry<?,?> e;
return ((o instanceof Map.Entry) &&(k = (e = (Map.Entry<?,?>)o).getKey()) != null &&(v = e.getValue()) != null &&(k == key || k.equals(key)) &&(v == (u = val) || v.equals(u)));
}/**
* Virtualized support for map.get(); overridden in subclasses.
*/
Node<K,V> find(int h, Object k) {Node<K,V> e = this;
if (k != null) {do {K ek;
if (e.hash == h &&((ek = e.key) == k || (ek != null && k.equals(ek))))return e;
} while ((e = e.next) != null);
}return null;
}}/* ---------------- Static utilities -------------- */
/**
* Spreads (XORs) higher bits of hash to lower and also forces top
* bit to 0. Because the table uses power-of-two masking, sets of
* hashes that vary only in bits above the current mask will
* always collide. (Among known examples are sets of Float keys
* holding consecutive whole numbers in small tables.) So we
* apply a transform that spreads the impact of higher bits
* downward. There is a tradeoff between speed, utility, and
* quality of bit-spreading. Because many common sets of hashes
* are already reasonably distributed (so don't benefit from
* spreading), and because we use trees to handle large sets of
* collisions in bins, we just XOR some shifted bits in the
* cheapest possible way to reduce systematic lossage, as well as
* to incorporate impact of the highest bits that would otherwise
* never be used in index calculations because of table bounds.
*/
/**
* 再次散列hashcode，把hashcode的高16位信息藏于hashcode中
*/
static final int spread(int h) {return (h ^ (h >>> 16)) & HASH_BITS;
}/**
* Returns a power of two table size for the given desired capacity.
* See Hackers Delight, sec 3.2
*/
private static final int tableSizeFor(int c) {int n = c - 1;
n |= n >>> 1;
n |= n >>> 2;
n |= n >>> 4;
n |= n >>> 8;
n |= n >>> 16;
return (n < 0) ? 1 : (n >= MAXIMUM_CAPACITY) ? MAXIMUM_CAPACITY : n + 1;
}/**
* Returns x's Class if it is of the form "class C implements
* Comparable<C>", else null.
*/
static Class<?> comparableClassFor(Object x) {if (x instanceof Comparable) {Class<?> c; Type[] ts, as; Type t; ParameterizedType p;
if ((c = x.getClass()) == String.class) // bypass checks
return c;
if ((ts = c.getGenericInterfaces()) != null) {for (int i = 0; i < ts.length; ++i) {if (((t = ts[i]) instanceof ParameterizedType) &&((p = (ParameterizedType)t).getRawType() ==Comparable.class) &&(as = p.getActualTypeArguments()) != null &&as.length == 1 && as[0] == c) // type arg is c
return c;
}}}return null;
}/**
* Returns k.compareTo(x) if x matches kc (k's screened comparable
* class), else 0.
*/
@SuppressWarnings({"rawtypes","unchecked"}) // for cast to Comparable
static int compareComparables(Class<?> kc, Object k, Object x) {return (x == null || x.getClass() != kc ? 0 :((Comparable)k).compareTo(x));
}/* ---------------- Table element access -------------- */
/*
* Volatile access methods are used for table elements as well as
* elements of in-progress next table while resizing. All uses of
* the tab arguments must be null checked by callers. All callers
* also paranoically precheck that tab's length is not zero (or an
* equivalent check), thus ensuring that any index argument taking
* the form of a hash value anded with (length - 1) is a valid
* index. Note that, to be correct wrt arbitrary concurrency
* errors by users, these checks must operate on local variables,
* which accounts for some odd-looking inline assignments below.
* Note that calls to setTabAt always occur within locked regions,
* and so in principle require only release ordering, not
* full volatile semantics, but are currently coded as volatile
* writes to be conservative.
*/
@SuppressWarnings("unchecked")static final <K,V> Node<K,V> tabAt(Node<K,V>[] tab, int i) {return (Node<K,V>)U.getObjectVolatile(tab, ((long)i << ASHIFT) + ABASE);
}static final <K,V> boolean casTabAt(Node<K,V>[] tab, int i,
Node<K,V> c, Node<K,V> v) {return U.compareAndSwapObject(tab, ((long)i << ASHIFT) + ABASE, c, v);
}static final <K,V> void setTabAt(Node<K,V>[] tab, int i, Node<K,V> v) {U.putObjectVolatile(tab, ((long)i << ASHIFT) + ABASE, v);
}/* ---------------- Fields -------------- */
/**
* The array of bins. Lazily initialized upon first insertion.
* Size is always a power of two. Accessed directly by iterators.
*/
transient volatile Node<K,V>[] table;
/**
* The next table to use; non-null only while resizing.
*/
private transient volatile Node<K,V>[] nextTable;
/**
* Base counter value, used mainly when there is no contention,
* but also as a fallback during table initialization
* races. Updated via CAS.
*/
/**
* 没有竞争时的元素计数，实际使用map.size()返回元素个数的时候
* 还需要获取到counterCells里面的值，合计才为真正的元素个数.
* 需要使用CAS来更新
*/
private transient volatile long baseCount;
/**
* Table initialization and resizing control. When negative, the
* table is being initialized or resized: -1 for initialization,
* else -(1 + the number of active resizing threads). Otherwise,
* when table is null, holds the initial table size to use upon
* creation, or 0 for default. After initialization, holds the
* next element count value upon which to resize the table.
*/
/**
* 1、-1表示正在进行初始化操作
* 2、-N表示有N-1个线程可以同时进行扩容操作
* 3、0或正数表示table是null。
* 4、在初始化后，正数表示下一次会进行扩容时的大小
* （即扩容阈值，它的值始终是当前ConcurrentHashMap容量的0.75倍，这与loadfactor是对应的）
*/
private transient volatile int sizeCtl;
/**
* The next table index (plus one) to split while resizing.
* 扩容时用到，初始时为table.length，表示从索引 0 到transferIndex的节点还未转移
*/
private transient volatile int transferIndex;
/**
* Spinlock (locked via CAS) used when resizing and/or creating CounterCells.
*/
/**
* 相当于自旋锁，当扩容 或者 counterCells正在被创建的时候
* cellsBusy是0表示还没有线程在创建cells数组 或 扩容
*/
private transient volatile int cellsBusy;
/**
* Table of counter cells. When non-null, size is a power of 2.
* 初始化时容量为2
*/
/**
* 底竞争下直接更新base，类似AtomicLong
* 高并发下，会将每个线程的操作hash到不同的
* cells数组中，从而将AtomicLong中更新
* 一个value的行为优化之后，分散到多个value中
* 从而降低更新热点，而需要得到当前值的时候，直接
* 将所有cell中的value与base相加即可。
*/
private transient volatile CounterCell[] counterCells;
// views
private transient KeySetView<K,V> keySet;
private transient ValuesView<K,V> values;
private transient EntrySetView<K,V> entrySet;
/* ---------------- Public operations -------------- */
/**
* Creates a new, empty map with the default initial table size (16).
*/
public ConcurrentHashMap() {}/**
* Creates a new, empty map with an initial table size
* accommodating the specified number of elements without the need
* to dynamically resize.
*
* @param initialCapacity The implementation performs internal
* sizing to accommodate this many elements.
* @throws IllegalArgumentException if the initial capacity of
* elements is negative
*/
public ConcurrentHashMap(int initialCapacity) {if (initialCapacity < 0)throw new IllegalArgumentException();
int cap = ((initialCapacity >= (MAXIMUM_CAPACITY >>> 1)) ?MAXIMUM_CAPACITY :tableSizeFor(initialCapacity + (initialCapacity >>> 1) + 1));
this.sizeCtl = cap;
}/**
* Creates a new map with the same mappings as the given map.
*
* @param m the map
*/
public ConcurrentHashMap(Map<? extends K, ? extends V> m) {this.sizeCtl = DEFAULT_CAPACITY;
putAll(m);
}/**
* Creates a new, empty map with an initial table size based on
* the given number of elements ({@code initialCapacity}) and
* initial table density ({@code loadFactor}).
*
* @param initialCapacity the initial capacity. The implementation
* performs internal sizing to accommodate this many elements,
* given the specified load factor.
* @param loadFactor the load factor (table density) for
* establishing the initial table size
* @throws IllegalArgumentException if the initial capacity of
* elements is negative or the load factor is nonpositive
*
* @since 1.6
*/
public ConcurrentHashMap(int initialCapacity, float loadFactor) {this(initialCapacity, loadFactor, 1);
}/**
* Creates a new, empty map with an initial table size based on
* the given number of elements ({@code initialCapacity}), table
* density ({@code loadFactor}), and number of concurrently
* updating threads ({@code concurrencyLevel}).
*
* @param initialCapacity the initial capacity. The implementation
* performs internal sizing to accommodate this many elements,
* given the specified load factor.
* @param loadFactor the load factor (table density) for
* establishing the initial table size
* @param concurrencyLevel the estimated number of concurrently
* updating threads. The implementation may use this value as
* a sizing hint.
* @throws IllegalArgumentException if the initial capacity is
* negative or the load factor or concurrencyLevel are
* nonpositive
*/
public ConcurrentHashMap(int initialCapacity,
float loadFactor, int concurrencyLevel) {if (!(loadFactor > 0.0f) || initialCapacity < 0 || concurrencyLevel <= 0)throw new IllegalArgumentException();
if (initialCapacity < concurrencyLevel) // Use at least as many bins
initialCapacity = concurrencyLevel; // as estimated threads
long size = (long)(1.0 + (long)initialCapacity / loadFactor);
int cap = (size >= (long)MAXIMUM_CAPACITY) ?MAXIMUM_CAPACITY : tableSizeFor((int)size);
this.sizeCtl = cap;
}// Original (since JDK1.2) Map methods
/**
* {@inheritDoc}
*/
public int size() {long n = sumCount();
return ((n < 0L) ? 0 :(n > (long)Integer.MAX_VALUE) ? Integer.MAX_VALUE :(int)n);
}/**
* {@inheritDoc}
*/
public boolean isEmpty() {return sumCount() <= 0L; // ignore transient negative values
}/**
* Returns the value to which the specified key is mapped,
* or {@code null} if this map contains no mapping for the key.
*
* <p>More formally, if this map contains a mapping from a key
* {@code k} to a value {@code v} such that {@code key.equals(k)},
* then this method returns {@code v}; otherwise it returns
* {@code null}. (There can be at most one such mapping.)
*
* @throws NullPointerException if the specified key is null
*/
public V get(Object key) {Node<K,V>[] tab; Node<K,V> e, p; int n, eh; K ek;
int h = spread(key.hashCode());
if ((tab = table) != null && (n = tab.length) > 0 &&(e = tabAt(tab, (n - 1) & h)) != null) {if ((eh = e.hash) == h) {if ((ek = e.key) == key || (ek != null && key.equals(ek)))return e.val;
}else if (eh < 0)return (p = e.find(h, key)) != null ? p.val : null;
while ((e = e.next) != null) {if (e.hash == h &&((ek = e.key) == key || (ek != null && key.equals(ek))))return e.val;
}}return null;
}/**
* Tests if the specified object is a key in this table.
*
* @param key possible key
* @return {@code true} if and only if the specified object
* is a key in this table, as determined by the
* {@code equals} method; {@code false} otherwise
* @throws NullPointerException if the specified key is null
*/
public boolean containsKey(Object key) {return get(key) != null;
}/**
* Returns {@code true} if this map maps one or more keys to the
* specified value. Note: This method may require a full traversal
* of the map, and is much slower than method {@code containsKey}.
*
* @param value value whose presence in this map is to be tested
* @return {@code true} if this map maps one or more keys to the
* specified value
* @throws NullPointerException if the specified value is null
*/
public boolean containsValue(Object value) {if (value == null)throw new NullPointerException();
Node<K,V>[] t;
if ((t = table) != null) {Traverser<K,V> it = new Traverser<K,V>(t, t.length, 0, t.length);
for (Node<K,V> p; (p = it.advance()) != null; ) {V v;
if ((v = p.val) == value || (v != null && value.equals(v)))return true;
}}return false;
}/**
* Maps the specified key to the specified value in this table.
* Neither the key nor the value can be null.
*
* <p>The value can be retrieved by calling the {@code get} method
* with a key that is equal to the original key.
*
* @param key key with which the specified value is to be associated
* @param value value to be associated with the specified key
* @return the previous value associated with {@code key}, or
* {@code null} if there was no mapping for {@code key}
* @throws NullPointerException if the specified key or value is null
*/
public V put(K key, V value) {return putVal(key, value, false);
}/** Implementation for put and putIfAbsent */
final V putVal(K key, V value, boolean onlyIfAbsent) {if (key == null || value == null) throw new NullPointerException();
int hash = spread(key.hashCode());
int binCount = 0;
/**
* 注意：这里循环是因为在CAS操作中可能失败（即其他线程占用）
* 所以这里循环即失败重试（自旋）
*/
for (Node<K,V>[] tab = table;;) {Node<K,V> f; int n, i, fh;
/**
* 第一次put操作，执行初始化
*/
if (tab == null || (n = tab.length) == 0)tab = initTable();
/**
* 如果桶中位置是Null,那么CAS存入
*/
else if ((f = tabAt(tab, i = (n - 1) & hash)) == null) {if (casTabAt(tab, i, null,
new Node<K,V>(hash, key, value, null)))break; // no lock when adding to empty bin
}/**
* 如果这个桶是ForwardingNode节点，说明这个桶
* 正在被扩容、转移，此时该线程进入帮忙扩容
*/
else if ((fh = f.hash) == MOVED)tab = helpTransfer(tab, f);
else {//开始添加节点
V oldVal = null;
synchronized (f) {if (tabAt(tab, i) == f) {if (fh >= 0) {//如果是链表，先查相同的，有就替换，没有就放链尾
binCount = 1;
for (Node<K,V> e = f;; ++binCount) {K ek;
if (e.hash == hash &&((ek = e.key) == key ||(ek != null && key.equals(ek)))) {oldVal = e.val;
if (!onlyIfAbsent)e.val = value;
break;
}Node<K,V> pred = e;
if ((e = e.next) == null) {pred.next = new Node<K,V>(hash, key,
value, null);
break;
}}}else if (f instanceof TreeBin) {//红黑树插入，详见hashMap(1.8)
Node<K,V> p;
binCount = 2;
if ((p = ((TreeBin<K,V>)f).putTreeVal(hash, key,
value)) != null) {oldVal = p.val;
if (!onlyIfAbsent)p.val = value;
}}}}/**
* binCount != 0 即说明节点插入了，那么线程就不必自旋了，跳出自旋循环。
* 注意：binCount在链表中循环的时候，有个++binCount操作，所以如果从
* 链表逻辑出来的话，binCount就是链表的节点数（如果是替换操作，那就不必判断了，
* 只要维持原状就好）
*/
if (binCount != 0) {if (binCount >= TREEIFY_THRESHOLD)treeifyBin(tab, i);
//如果是替换，就维持原状
if (oldVal != null)return oldVal;
break;
}}}addCount(1L, binCount);
return null;
}/**
* Copies all of the mappings from the specified map to this one.
* These mappings replace any mappings that this map had for any of the
* keys currently in the specified map.
*
* @param m mappings to be stored in this map
*/
public void putAll(Map<? extends K, ? extends V> m) {tryPresize(m.size());
for (Map.Entry<? extends K, ? extends V> e : m.entrySet())putVal(e.getKey(), e.getValue(), false);
}/**
* Removes the key (and its corresponding value) from this map.
* This method does nothing if the key is not in the map.
*
* @param key the key that needs to be removed
* @return the previous value associated with {@code key}, or
* {@code null} if there was no mapping for {@code key}
* @throws NullPointerException if the specified key is null
*/
public V remove(Object key) {return replaceNode(key, null, null);
}/**
* Implementation for the four public remove/replace methods:
* Replaces node value with v, conditional upon match of cv if
* non-null. If resulting value is null, delete.
*/
/**
* 这里其实逻辑都和putVal()大部分相同的，相信看完putVal的话，
* 这里也没难度
*/
final V replaceNode(Object key, V value, Object cv) {int hash = spread(key.hashCode());
for (Node<K,V>[] tab = table;;) {Node<K,V> f; int n, i, fh;
if (tab == null || (n = tab.length) == 0 ||(f = tabAt(tab, i = (n - 1) & hash)) == null)break;
else if ((fh = f.hash) == MOVED)tab = helpTransfer(tab, f);
else {V oldVal = null;
boolean validated = false;
synchronized (f) {if (tabAt(tab, i) == f) {if (fh >= 0) {validated = true;
for (Node<K,V> e = f, pred = null;;) {K ek;
if (e.hash == hash &&((ek = e.key) == key ||(ek != null && key.equals(ek)))) {V ev = e.val;
if (cv == null || cv == ev ||(ev != null && cv.equals(ev))) {oldVal = ev;
if (value != null)e.val = value;
else if (pred != null)pred.next = e.next;
else
setTabAt(tab, i, e.next);
}break;
}pred = e;
if ((e = e.next) == null)break;
}}else if (f instanceof TreeBin) {validated = true;
TreeBin<K,V> t = (TreeBin<K,V>)f;
TreeNode<K,V> r, p;
if ((r = t.root) != null &&(p = r.findTreeNode(hash, key, null)) != null) {V pv = p.val;
if (cv == null || cv == pv ||(pv != null && cv.equals(pv))) {oldVal = pv;
if (value != null)p.val = value;
else if (t.removeTreeNode(p))setTabAt(tab, i, untreeify(t.first));
}}}}}if (validated) {if (oldVal != null) {if (value == null)addCount(-1L, -1);
return oldVal;
}break;
}}}return null;
}/**
* Removes all of the mappings from this map.
*/
public void clear() {long delta = 0L; // negative number of deletions
int i = 0;
Node<K,V>[] tab = table;
while (tab != null && i < tab.length) {int fh;
Node<K,V> f = tabAt(tab, i);
if (f == null)++i;
else if ((fh = f.hash) == MOVED) {tab = helpTransfer(tab, f);
i = 0; // restart
}else {synchronized (f) {if (tabAt(tab, i) == f) {Node<K,V> p = (fh >= 0 ? f :(f instanceof TreeBin) ?((TreeBin<K,V>)f).first : null);
while (p != null) {--delta;
p = p.next;
}setTabAt(tab, i++, null);
}}}}if (delta != 0L)addCount(delta, -1);
}/**
* Returns a {@link Set} view of the keys contained in this map.
* The set is backed by the map, so changes to the map are
* reflected in the set, and vice-versa. The set supports element
* removal, which removes the corresponding mapping from this map,
* via the {@code Iterator.remove}, {@code Set.remove},
* {@code removeAll}, {@code retainAll}, and {@code clear}
* operations. It does not support the {@code add} or
* {@code addAll} operations.
*
* <p>The view's iterators and spliterators are
* <a href="package-summary.html#Weakly"><i>weakly consistent</i></a>.
*
* <p>The view's {@code spliterator} reports {@link Spliterator#CONCURRENT},
* {@link Spliterator#DISTINCT}, and {@link Spliterator#NONNULL}.
*
* @return the set view
*/
public KeySetView<K,V> keySet() {KeySetView<K,V> ks;
return (ks = keySet) != null ? ks : (keySet = new KeySetView<K,V>(this, null));
}/**
* Returns a {@link Collection} view of the values contained in this map.
* The collection is backed by the map, so changes to the map are
* reflected in the collection, and vice-versa. The collection
* supports element removal, which removes the corresponding
* mapping from this map, via the {@code Iterator.remove},
* {@code Collection.remove}, {@code removeAll},
* {@code retainAll}, and {@code clear} operations. It does not
* support the {@code add} or {@code addAll} operations.
*
* <p>The view's iterators and spliterators are
* <a href="package-summary.html#Weakly"><i>weakly consistent</i></a>.
*
* <p>The view's {@code spliterator} reports {@link Spliterator#CONCURRENT}
* and {@link Spliterator#NONNULL}.
*
* @return the collection view
*/
public Collection<V> values() {ValuesView<K,V> vs;
return (vs = values) != null ? vs : (values = new ValuesView<K,V>(this));
}/**
* Returns a {@link Set} view of the mappings contained in this map.
* The set is backed by the map, so changes to the map are
* reflected in the set, and vice-versa. The set supports element
* removal, which removes the corresponding mapping from the map,
* via the {@code Iterator.remove}, {@code Set.remove},
* {@code removeAll}, {@code retainAll}, and {@code clear}
* operations.
*
* <p>The view's iterators and spliterators are
* <a href="package-summary.html#Weakly"><i>weakly consistent</i></a>.
*
* <p>The view's {@code spliterator} reports {@link Spliterator#CONCURRENT},
* {@link Spliterator#DISTINCT}, and {@link Spliterator#NONNULL}.
*
* @return the set view
*/
public Set<Map.Entry<K,V>> entrySet() {EntrySetView<K,V> es;
return (es = entrySet) != null ? es : (entrySet = new EntrySetView<K,V>(this));
}/**
* Returns the hash code value for this {@link Map}, i.e.,
* the sum of, for each key-value pair in the map,
* {@code key.hashCode() ^ value.hashCode()}.
*
* @return the hash code value for this map
*/
public int hashCode() {int h = 0;
Node<K,V>[] t;
if ((t = table) != null) {Traverser<K,V> it = new Traverser<K,V>(t, t.length, 0, t.length);
for (Node<K,V> p; (p = it.advance()) != null; )h += p.key.hashCode() ^ p.val.hashCode();
}return h;
}/**
* Returns a string representation of this map. The string
* representation consists of a list of key-value mappings (in no
* particular order) enclosed in braces ("{@code {}}"). Adjacent
* mappings are separated by the characters {@code ", "} (comma
* and space). Each key-value mapping is rendered as the key
* followed by an equals sign ("{@code =}") followed by the
* associated value.
*
* @return a string representation of this map
*/
public String toString() {Node<K,V>[] t;
int f = (t = table) == null ? 0 : t.length;
Traverser<K,V> it = new Traverser<K,V>(t, f, 0, f);
StringBuilder sb = new StringBuilder();
sb.append('{');
Node<K,V> p;
if ((p = it.advance()) != null) {for (;;) {K k = p.key;
V v = p.val;
sb.append(k == this ? "(this Map)" : k);
sb.append('=');
sb.append(v == this ? "(this Map)" : v);
if ((p = it.advance()) == null)break;
sb.append(',').append(' ');
}}return sb.append('}').toString();
}/**
* Compares the specified object with this map for equality.
* Returns {@code true} if the given object is a map with the same
* mappings as this map. This operation may return misleading
* results if either map is concurrently modified during execution
* of this method.
*
* @param o object to be compared for equality with this map
* @return {@code true} if the specified object is equal to this map
*/
public boolean equals(Object o) {if (o != this) {if (!(o instanceof Map))return false;
Map<?,?> m = (Map<?,?>) o;
Node<K,V>[] t;
int f = (t = table) == null ? 0 : t.length;
Traverser<K,V> it = new Traverser<K,V>(t, f, 0, f);
for (Node<K,V> p; (p = it.advance()) != null; ) {V val = p.val;
Object v = m.get(p.key);
if (v == null || (v != val && !v.equals(val)))return false;
}for (Map.Entry<?,?> e : m.entrySet()) {Object mk, mv, v;
if ((mk = e.getKey()) == null ||(mv = e.getValue()) == null ||(v = get(mk)) == null ||(mv != v && !mv.equals(v)))return false;
}}return true;
}/**
* Stripped-down version of helper class used in previous version,
* declared for the sake of serialization compatibility
*/
static class Segment<K,V> extends ReentrantLock implements Serializable {private static final long serialVersionUID = 2249069246763182397L;
final float loadFactor;
Segment(float lf) { this.loadFactor = lf; }}/**
* Saves the state of the {@code ConcurrentHashMap} instance to a
* stream (i.e., serializes it).
* @param s the stream
* @throws java.io.IOException if an I/O error occurs
* @serialData
* the key (Object) and value (Object)
* for each key-value mapping, followed by a null pair.
* The key-value mappings are emitted in no particular order.
*/
private void writeObject(java.io.ObjectOutputStream s)throws java.io.IOException {// For serialization compatibility
// Emulate segment calculation from previous version of this class
int sshift = 0;
int ssize = 1;
while (ssize < DEFAULT_CONCURRENCY_LEVEL) {++sshift;
ssize <<= 1;
}int segmentShift = 32 - sshift;
int segmentMask = ssize - 1;
@SuppressWarnings("unchecked")Segment<K,V>[] segments = (Segment<K,V>[])new Segment<?,?>[DEFAULT_CONCURRENCY_LEVEL];
for (int i = 0; i < segments.length; ++i)segments[i] = new Segment<K,V>(LOAD_FACTOR);
s.putFields().put("segments", segments);
s.putFields().put("segmentShift", segmentShift);
s.putFields().put("segmentMask", segmentMask);
s.writeFields();
Node<K,V>[] t;
if ((t = table) != null) {Traverser<K,V> it = new Traverser<K,V>(t, t.length, 0, t.length);
for (Node<K,V> p; (p = it.advance()) != null; ) {s.writeObject(p.key);
s.writeObject(p.val);
}}s.writeObject(null);
s.writeObject(null);
segments = null; // throw away
}/**
* Reconstitutes the instance from a stream (that is, deserializes it).
* @param s the stream
* @throws ClassNotFoundException if the class of a serialized object
* could not be found
* @throws java.io.IOException if an I/O error occurs
*/
private void readObject(java.io.ObjectInputStream s)throws java.io.IOException, ClassNotFoundException {/*
* To improve performance in typical cases, we create nodes
* while reading, then place in table once size is known.
* However, we must also validate uniqueness and deal with
* overpopulated bins while doing so, which requires
* specialized versions of putVal mechanics.
*/
sizeCtl = -1; // force exclusion for table construction
s.defaultReadObject();
long size = 0L;
Node<K,V> p = null;
for (;;) {@SuppressWarnings("unchecked")K k = (K) s.readObject();
@SuppressWarnings("unchecked")V v = (V) s.readObject();
if (k != null && v != null) {p = new Node<K,V>(spread(k.hashCode()), k, v, p);
++size;
}else
break;
}if (size == 0L)sizeCtl = 0;
else {int n;
if (size >= (long)(MAXIMUM_CAPACITY >>> 1))n = MAXIMUM_CAPACITY;
else {int sz = (int)size;
n = tableSizeFor(sz + (sz >>> 1) + 1);
}@SuppressWarnings("unchecked")Node<K,V>[] tab = (Node<K,V>[])new Node<?,?>[n];
int mask = n - 1;
long added = 0L;
while (p != null) {boolean insertAtFront;
Node<K,V> next = p.next, first;
int h = p.hash, j = h & mask;
if ((first = tabAt(tab, j)) == null)insertAtFront = true;
else {K k = p.key;
if (first.hash < 0) {TreeBin<K,V> t = (TreeBin<K,V>)first;
if (t.putTreeVal(h, k, p.val) == null)++added;
insertAtFront = false;
}else {int binCount = 0;
insertAtFront = true;
Node<K,V> q; K qk;
for (q = first; q != null; q = q.next) {if (q.hash == h &&((qk = q.key) == k ||(qk != null && k.equals(qk)))) {insertAtFront = false;
break;
}++binCount;
}if (insertAtFront && binCount >= TREEIFY_THRESHOLD) {insertAtFront = false;
++added;
p.next = first;
TreeNode<K,V> hd = null, tl = null;
for (q = p; q != null; q = q.next) {TreeNode<K,V> t = new TreeNode<K,V>(q.hash, q.key, q.val, null, null);
if ((t.prev = tl) == null)hd = t;
else
tl.next = t;
tl = t;
}setTabAt(tab, j, new TreeBin<K,V>(hd));
}}}if (insertAtFront) {++added;
p.next = first;
setTabAt(tab, j, p);
}p = next;
}table = tab;
sizeCtl = n - (n >>> 2);
baseCount = added;
}}// ConcurrentMap methods
/**
* {@inheritDoc}
*
* @return the previous value associated with the specified key,
* or {@code null} if there was no mapping for the key
* @throws NullPointerException if the specified key or value is null
*/
public V putIfAbsent(K key, V value) {return putVal(key, value, true);
}/**
* {@inheritDoc}
*
* @throws NullPointerException if the specified key is null
*/
public boolean remove(Object key, Object value) {if (key == null)throw new NullPointerException();
return value != null && replaceNode(key, null, value) != null;
}/**
* {@inheritDoc}
*
* @throws NullPointerException if any of the arguments are null
*/
public boolean replace(K key, V oldValue, V newValue) {if (key == null || oldValue == null || newValue == null)throw new NullPointerException();
return replaceNode(key, newValue, oldValue) != null;
}/**
* {@inheritDoc}
*
* @return the previous value associated with the specified key,
* or {@code null} if there was no mapping for the key
* @throws NullPointerException if the specified key or value is null
*/
public V replace(K key, V value) {if (key == null || value == null)throw new NullPointerException();
return replaceNode(key, value, null);
}// Overrides of JDK8+ Map extension method defaults
/**
* Returns the value to which the specified key is mapped, or the
* given default value if this map contains no mapping for the
* key.
*
* @param key the key whose associated value is to be returned
* @param defaultValue the value to return if this map contains
* no mapping for the given key
* @return the mapping for the key, if present; else the default value
* @throws NullPointerException if the specified key is null
*/
public V getOrDefault(Object key, V defaultValue) {V v;
return (v = get(key)) == null ? defaultValue : v;
}public void forEach(BiConsumer<? super K, ? super V> action) {if (action == null) throw new NullPointerException();
Node<K,V>[] t;
if ((t = table) != null) {Traverser<K,V> it = new Traverser<K,V>(t, t.length, 0, t.length);
for (Node<K,V> p; (p = it.advance()) != null; ) {action.accept(p.key, p.val);
}}}public void replaceAll(BiFunction<? super K, ? super V, ? extends V> function) {if (function == null) throw new NullPointerException();
Node<K,V>[] t;
if ((t = table) != null) {Traverser<K,V> it = new Traverser<K,V>(t, t.length, 0, t.length);
for (Node<K,V> p; (p = it.advance()) != null; ) {V oldValue = p.val;
for (K key = p.key;;) {V newValue = function.apply(key, oldValue);
if (newValue == null)throw new NullPointerException();
if (replaceNode(key, newValue, oldValue) != null ||(oldValue = get(key)) == null)break;
}}}}/**
* If the specified key is not already associated with a value,
* attempts to compute its value using the given mapping function
* and enters it into this map unless {@code null}. The entire
* method invocation is performed atomically, so the function is
* applied at most once per key. Some attempted update operations
* on this map by other threads may be blocked while computation
* is in progress, so the computation should be short and simple,
* and must not attempt to update any other mappings of this map.
*
* @param key key with which the specified value is to be associated
* @param mappingFunction the function to compute a value
* @return the current (existing or computed) value associated with
* the specified key, or null if the computed value is null
* @throws NullPointerException if the specified key or mappingFunction
* is null
* @throws IllegalStateException if the computation detectably
* attempts a recursive update to this map that would
* otherwise never complete
* @throws RuntimeException or Error if the mappingFunction does so,
* in which case the mapping is left unestablished
*/
public V computeIfAbsent(K key, Function<? super K, ? extends V> mappingFunction) {if (key == null || mappingFunction == null)throw new NullPointerException();
int h = spread(key.hashCode());
V val = null;
int binCount = 0;
for (Node<K,V>[] tab = table;;) {Node<K,V> f; int n, i, fh;
if (tab == null || (n = tab.length) == 0)tab = initTable();
else if ((f = tabAt(tab, i = (n - 1) & h)) == null) {Node<K,V> r = new ReservationNode<K,V>();
synchronized (r) {if (casTabAt(tab, i, null, r)) {binCount = 1;
Node<K,V> node = null;
try {if ((val = mappingFunction.apply(key)) != null)node = new Node<K,V>(h, key, val, null);
} finally {setTabAt(tab, i, node);
}}}if (binCount != 0)break;
}else if ((fh = f.hash) == MOVED)tab = helpTransfer(tab, f);
else {boolean added = false;
synchronized (f) {if (tabAt(tab, i) == f) {if (fh >= 0) {binCount = 1;
for (Node<K,V> e = f;; ++binCount) {K ek; V ev;
if (e.hash == h &&((ek = e.key) == key ||(ek != null && key.equals(ek)))) {val = e.val;
break;
}Node<K,V> pred = e;
if ((e = e.next) == null) {if ((val = mappingFunction.apply(key)) != null) {added = true;
pred.next = new Node<K,V>(h, key, val, null);
}break;
}}}else if (f instanceof TreeBin) {binCount = 2;
TreeBin<K,V> t = (TreeBin<K,V>)f;
TreeNode<K,V> r, p;
if ((r = t.root) != null &&(p = r.findTreeNode(h, key, null)) != null)val = p.val;
else if ((val = mappingFunction.apply(key)) != null) {added = true;
t.putTreeVal(h, key, val);
}}}}if (binCount != 0) {if (binCount >= TREEIFY_THRESHOLD)treeifyBin(tab, i);
if (!added)return val;
break;
}}}if (val != null)addCount(1L, binCount);
return val;
}/**
* If the value for the specified key is present, attempts to
* compute a new mapping given the key and its current mapped
* value. The entire method invocation is performed atomically.
* Some attempted update operations on this map by other threads
* may be blocked while computation is in progress, so the
* computation should be short and simple, and must not attempt to
* update any other mappings of this map.
*
* @param key key with which a value may be associated
* @param remappingFunction the function to compute a value
* @return the new value associated with the specified key, or null if none
* @throws NullPointerException if the specified key or remappingFunction
* is null
* @throws IllegalStateException if the computation detectably
* attempts a recursive update to this map that would
* otherwise never complete
* @throws RuntimeException or Error if the remappingFunction does so,
* in which case the mapping is unchanged
*/
public V computeIfPresent(K key, BiFunction<? super K, ? super V, ? extends V> remappingFunction) {if (key == null || remappingFunction == null)throw new NullPointerException();
int h = spread(key.hashCode());
V val = null;
int delta = 0;
int binCount = 0;
for (Node<K,V>[] tab = table;;) {Node<K,V> f; int n, i, fh;
if (tab == null || (n = tab.length) == 0)tab = initTable();
else if ((f = tabAt(tab, i = (n - 1) & h)) == null)break;
else if ((fh = f.hash) == MOVED)tab = helpTransfer(tab, f);
else {synchronized (f) {if (tabAt(tab, i) == f) {if (fh >= 0) {binCount = 1;
for (Node<K,V> e = f, pred = null;; ++binCount) {K ek;
if (e.hash == h &&((ek = e.key) == key ||(ek != null && key.equals(ek)))) {val = remappingFunction.apply(key, e.val);
if (val != null)e.val = val;
else {delta = -1;
Node<K,V> en = e.next;
if (pred != null)pred.next = en;
else
setTabAt(tab, i, en);
}break;
}pred = e;
if ((e = e.next) == null)break;
}}else if (f instanceof TreeBin) {binCount = 2;
TreeBin<K,V> t = (TreeBin<K,V>)f;
TreeNode<K,V> r, p;
if ((r = t.root) != null &&(p = r.findTreeNode(h, key, null)) != null) {val = remappingFunction.apply(key, p.val);
if (val != null)p.val = val;
else {delta = -1;
if (t.removeTreeNode(p))setTabAt(tab, i, untreeify(t.first));
}}}}}if (binCount != 0)break;
}}if (delta != 0)addCount((long)delta, binCount);
return val;
}/**
* Attempts to compute a mapping for the specified key and its
* current mapped value (or {@code null} if there is no current
* mapping). The entire method invocation is performed atomically.
* Some attempted update operations on this map by other threads
* may be blocked while computation is in progress, so the
* computation should be short and simple, and must not attempt to
* update any other mappings of this Map.
*
* @param key key with which the specified value is to be associated
* @param remappingFunction the function to compute a value
* @return the new value associated with the specified key, or null if none
* @throws NullPointerException if the specified key or remappingFunction
* is null
* @throws IllegalStateException if the computation detectably
* attempts a recursive update to this map that would
* otherwise never complete
* @throws RuntimeException or Error if the remappingFunction does so,
* in which case the mapping is unchanged
*/
public V compute(K key,
BiFunction<? super K, ? super V, ? extends V> remappingFunction) {if (key == null || remappingFunction == null)throw new NullPointerException();
int h = spread(key.hashCode());
V val = null;
int delta = 0;
int binCount = 0;
for (Node<K,V>[] tab = table;;) {Node<K,V> f; int n, i, fh;
if (tab == null || (n = tab.length) == 0)tab = initTable();
else if ((f = tabAt(tab, i = (n - 1) & h)) == null) {Node<K,V> r = new ReservationNode<K,V>();
synchronized (r) {if (casTabAt(tab, i, null, r)) {binCount = 1;
Node<K,V> node = null;
try {if ((val = remappingFunction.apply(key, null)) != null) {delta = 1;
node = new Node<K,V>(h, key, val, null);
}} finally {setTabAt(tab, i, node);
}}}if (binCount != 0)break;
}else if ((fh = f.hash) == MOVED)tab = helpTransfer(tab, f);
else {synchronized (f) {if (tabAt(tab, i) == f) {if (fh >= 0) {binCount = 1;
for (Node<K,V> e = f, pred = null;; ++binCount) {K ek;
if (e.hash == h &&((ek = e.key) == key ||(ek != null && key.equals(ek)))) {val = remappingFunction.apply(key, e.val);
if (val != null)e.val = val;
else {delta = -1;
Node<K,V> en = e.next;
if (pred != null)pred.next = en;
else
setTabAt(tab, i, en);
}break;
}pred = e;
if ((e = e.next) == null) {val = remappingFunction.apply(key, null);
if (val != null) {delta = 1;
pred.next =new Node<K,V>(h, key, val, null);
}break;
}}}else if (f instanceof TreeBin) {binCount = 1;
TreeBin<K,V> t = (TreeBin<K,V>)f;
TreeNode<K,V> r, p;
if ((r = t.root) != null)p = r.findTreeNode(h, key, null);
else
p = null;
V pv = (p == null) ? null : p.val;
val = remappingFunction.apply(key, pv);
if (val != null) {if (p != null)p.val = val;
else {delta = 1;
t.putTreeVal(h, key, val);
}}else if (p != null) {delta = -1;
if (t.removeTreeNode(p))setTabAt(tab, i, untreeify(t.first));
}}}}if (binCount != 0) {if (binCount >= TREEIFY_THRESHOLD)treeifyBin(tab, i);
break;
}}}if (delta != 0)addCount((long)delta, binCount);
return val;
}/**
* If the specified key is not already associated with a
* (non-null) value, associates it with the given value.
* Otherwise, replaces the value with the results of the given
* remapping function, or removes if {@code null}. The entire
* method invocation is performed atomically. Some attempted
* update operations on this map by other threads may be blocked
* while computation is in progress, so the computation should be
* short and simple, and must not attempt to update any other
* mappings of this Map.
*
* @param key key with which the specified value is to be associated
* @param value the value to use if absent
* @param remappingFunction the function to recompute a value if present
* @return the new value associated with the specified key, or null if none
* @throws NullPointerException if the specified key or the
* remappingFunction is null
* @throws RuntimeException or Error if the remappingFunction does so,
* in which case the mapping is unchanged
*/
public V merge(K key, V value, BiFunction<? super V, ? super V, ? extends V> remappingFunction) {if (key == null || value == null || remappingFunction == null)throw new NullPointerException();
int h = spread(key.hashCode());
V val = null;
int delta = 0;
int binCount = 0;
for (Node<K,V>[] tab = table;;) {Node<K,V> f; int n, i, fh;
if (tab == null || (n = tab.length) == 0)tab = initTable();
else if ((f = tabAt(tab, i = (n - 1) & h)) == null) {if (casTabAt(tab, i, null, new Node<K,V>(h, key, value, null))) {delta = 1;
val = value;
break;
}}else if ((fh = f.hash) == MOVED)tab = helpTransfer(tab, f);
else {synchronized (f) {if (tabAt(tab, i) == f) {if (fh >= 0) {binCount = 1;
for (Node<K,V> e = f, pred = null;; ++binCount) {K ek;
if (e.hash == h &&((ek = e.key) == key ||(ek != null && key.equals(ek)))) {val = remappingFunction.apply(e.val, value);
if (val != null)e.val = val;
else {delta = -1;
Node<K,V> en = e.next;
if (pred != null)pred.next = en;
else
setTabAt(tab, i, en);
}break;
}pred = e;
if ((e = e.next) == null) {delta = 1;
val = value;
pred.next =new Node<K,V>(h, key, val, null);
break;
}}}else if (f instanceof TreeBin) {binCount = 2;
TreeBin<K,V> t = (TreeBin<K,V>)f;
TreeNode<K,V> r = t.root;
TreeNode<K,V> p = (r == null) ? null :r.findTreeNode(h, key, null);
val = (p == null) ? value :remappingFunction.apply(p.val, value);
if (val != null) {if (p != null)p.val = val;
else {delta = 1;
t.putTreeVal(h, key, val);
}}else if (p != null) {delta = -1;
if (t.removeTreeNode(p))setTabAt(tab, i, untreeify(t.first));
}}}}if (binCount != 0) {if (binCount >= TREEIFY_THRESHOLD)treeifyBin(tab, i);
break;
}}}if (delta != 0)addCount((long)delta, binCount);
return val;
}// Hashtable legacy methods
/**
* Legacy method testing if some key maps into the specified value
* in this table. This method is identical in functionality to
* {@link #containsValue(Object)}, and exists solely to ensure
* full compatibility with class {@link java.util.Hashtable},
* which supported this method prior to introduction of the
* Java Collections framework.
*
* @param value a value to search for
* @return {@code true} if and only if some key maps to the
* {@code value} argument in this table as
* determined by the {@code equals} method;
* {@code false} otherwise
* @throws NullPointerException if the specified value is null
*/
public boolean contains(Object value) {return containsValue(value);
}/**
* Returns an enumeration of the keys in this table.
*
* @return an enumeration of the keys in this table
* @see #keySet()
*/
public Enumeration<K> keys() {Node<K,V>[] t;
int f = (t = table) == null ? 0 : t.length;
return new KeyIterator<K,V>(t, f, 0, f, this);
}/**
* Returns an enumeration of the values in this table.
*
* @return an enumeration of the values in this table
* @see #values()
*/
public Enumeration<V> elements() {Node<K,V>[] t;
int f = (t = table) == null ? 0 : t.length;
return new ValueIterator<K,V>(t, f, 0, f, this);
}// ConcurrentHashMap-only methods
/**
* Returns the number of mappings. This method should be used
* instead of {@link #size} because a ConcurrentHashMap may
* contain more mappings than can be represented as an int. The
* value returned is an estimate; the actual count may differ if
* there are concurrent insertions or removals.
*
* @return the number of mappings
* @since 1.8
*/
public long mappingCount() {long n = sumCount();
return (n < 0L) ? 0L : n; // ignore transient negative values
}/**
* Creates a new {@link Set} backed by a ConcurrentHashMap
* from the given type to {@code Boolean.TRUE}.
*
* @param <K> the element type of the returned set
* @return the new set
* @since 1.8
*/
public static <K> KeySetView<K,Boolean> newKeySet() {return new KeySetView<K,Boolean>(new ConcurrentHashMap<K,Boolean>(), Boolean.TRUE);
}/**
* Creates a new {@link Set} backed by a ConcurrentHashMap
* from the given type to {@code Boolean.TRUE}.
*
* @param initialCapacity The implementation performs internal
* sizing to accommodate this many elements.
* @param <K> the element type of the returned set
* @return the new set
* @throws IllegalArgumentException if the initial capacity of
* elements is negative
* @since 1.8
*/
public static <K> KeySetView<K,Boolean> newKeySet(int initialCapacity) {return new KeySetView<K,Boolean>(new ConcurrentHashMap<K,Boolean>(initialCapacity), Boolean.TRUE);
}/**
* Returns a {@link Set} view of the keys in this map, using the
* given common mapped value for any additions (i.e., {@link
* Collection#add} and {@link Collection#addAll(Collection)}).
* This is of course only appropriate if it is acceptable to use
* the same value for all additions from this view.
*
* @param mappedValue the mapped value to use for any additions
* @return the set view
* @throws NullPointerException if the mappedValue is null
*/
public KeySetView<K,V> keySet(V mappedValue) {if (mappedValue == null)throw new NullPointerException();
return new KeySetView<K,V>(this, mappedValue);
}/* ---------------- Special Nodes -------------- */
/**
* A node inserted at head of bins during transfer operations.
*/
static final class ForwardingNode<K,V> extends Node<K,V> {final Node<K,V>[] nextTable;
ForwardingNode(Node<K,V>[] tab) {super(MOVED, null, null, null);
this.nextTable = tab;
}Node<K,V> find(int h, Object k) {// loop to avoid arbitrarily deep recursion on forwarding nodes
outer: for (Node<K,V>[] tab = nextTable;;) {Node<K,V> e; int n;
if (k == null || tab == null || (n = tab.length) == 0 ||(e = tabAt(tab, (n - 1) & h)) == null)return null;
for (;;) {int eh; K ek;
if ((eh = e.hash) == h &&((ek = e.key) == k || (ek != null && k.equals(ek))))return e;
if (eh < 0) {if (e instanceof ForwardingNode) {tab = ((ForwardingNode<K,V>)e).nextTable;
continue outer;
}else
return e.find(h, k);
}if ((e = e.next) == null)return null;
}}}}/**
* A place-holder node used in computeIfAbsent and compute
*/
static final class ReservationNode<K,V> extends Node<K,V> {ReservationNode() {super(RESERVED, null, null, null);
}Node<K,V> find(int h, Object k) {return null;
}}/* ---------------- Table Initialization and Resizing -------------- */
/**
* Returns the stamp bits for resizing a table of size n.
* Must be negative when shifted left by RESIZE_STAMP_SHIFT.
*/
/**
* 从调用处得知n为tab的length,所以必然为2的幂次方（int rs = resizeStamp(n);）
* 方法简化后即 Integer.numberOfLeadingZeros(n) | 1<<15
* 由于做的是或运算，并且Integer.numberOfLeadingZeros(n)必然不会大于32
* 因此resizeStamp(n)得到的结果必然是(-32< resizeStamp(n) <-1 )
* （注：1<<15，随后rs在使用的时候rs << RESIZE_STAMP_SHIFT然后才被赋值给了sizeCtl(addCount方法中)，
* 这是可以看到1在最高位因此必然是负数）
* 从sizeCtl的含义可以得到，-n表示最多有n-1个线程可以同时进行扩容操作。
* 因此这里实际是计算可以参与操作的线程数
*/
static final int resizeStamp(int n) {return Integer.numberOfLeadingZeros(n) | (1 << (RESIZE_STAMP_BITS - 1));
}/**
* Initializes table, using the size recorded in sizeCtl.
*/
private final Node<K,V>[] initTable() {Node<K,V>[] tab; int sc;
//多线程操作时，如果线程发现sizeCtl小于0，那么线程等待一会
//（需要死循环，直到table被初始化完毕）
while ((tab = table) == null || tab.length == 0) {if ((sc = sizeCtl) < 0)Thread.yield(); // lost initialization race; just spin
/**
* compareAndSwapInt，
* 第一个参数表示需要改变的对象
* 第二个参数表示需要修改的字段在内存中的偏移量
* 第三个参数表示需要修改的字段的值如果和这个参数的值相等，那么可以进行修改
* 第四个参数表示修改后的值
*/
//一开始构造函数中sizeCtl被设置为容量，所以先走下面的逻辑，然后sizeCtl被设置为-1
else if (U.compareAndSwapInt(this, SIZECTL, sc, -1)) {try {if ((tab = table) == null || tab.length == 0) {int n = (sc > 0) ? sc : DEFAULT_CAPACITY;
@SuppressWarnings("unchecked")Node<K,V>[] nt = (Node<K,V>[])new Node<?,?>[n];
table = tab = nt;
//sc被设置为扩容的阈值
sc = n - (n >>> 2);
}} finally {/**
* sizeCtl被设置为阈值后，扩容完毕
* 原先阻塞的线程重新循环，发现tab不为null，就返回tab
*/
sizeCtl = sc;
}break;
}}return tab;
}/**
* Adds to count, and if table is too small and not already
* resizing, initiates transfer. If already resizing, helps
* perform transfer if work is available. Rechecks occupancy
* after a transfer to see if another resize is already needed
* because resizings are lagging additions.
*
* @param x the count to add
* @param check if <0, don't check resize, if <= 1 only check if uncontended
*/
/**
* x为需要增加的个数，即count+x
*/
private final void addCount(long x, int check) {CounterCell[] as; long b, s;
/**
* 如果counterCells不为空 或者 baseCount更新失败（说明多线程参与）
*/
if ((as = counterCells) != null ||!U.compareAndSwapLong(this, BASECOUNT, b = baseCount, s = b + x)) {CounterCell a; long v; int m;
boolean uncontended = true;
/**
* 注意，ThreadLocalRandom.getProbe()是package作用域下面的，所以api上找不到
* 进入getProbe()，可以看到其上有一段英文注释，说getProbe()其实是返回随机的hashCode
* 则as[ThreadLocalRandom.getProbe() & m])即在数组中随机找一个元素
*/
/**
* 如果此时counterCells为空了 或者 counterCells[i]是空 或者
* counterCells[i]更新失败
* （如果cells[i]直接更新成功就可以直接返回了）
*/
if (as == null || (m = as.length - 1) < 0 ||(a = as[ThreadLocalRandom.getProbe() & m]) == null ||!(uncontended =U.compareAndSwapLong(a, CELLVALUE, v = a.value, v + x))) {/**
* fullAddCount处理cells的初始化、cell对象的新增、cell[i]值的更新
*/
fullAddCount(x, uncontended);
return;
}/**
* replace或者clear的时候，check直接传的-1，那就不用检查扩容了
*/
if (check <= 1)return;
//获取到总数，然后去判断是否扩容
s = sumCount();
}/**
* 如果是添加节点的操作，那么还要检查一下增加的长度会不会导致扩容操作
*/
if (check >= 0) {Node<K,V>[] tab, nt; int n, sc;
/**
* 如果元素个数大于等于阈值，并且sc >= 0（说明没有其他线程进入扩容），
* 那么就可以扩容
*/
while (s >= (long)(sc = sizeCtl) && (tab = table) != null &&(n = tab.length) < MAXIMUM_CAPACITY) {int rs = resizeStamp(n);
//sc小于0说明已经有线程在扩容了
if (sc < 0) {/**
* 这里的逻辑和helpTransfer()中是一样的，都是其他线程参与扩容，
* 这里表示扩容完毕，那么线程直接退出
*/
if ((sc >>> RESIZE_STAMP_SHIFT) != rs || sc == rs + 1 ||sc == rs + MAX_RESIZERS || (nt = nextTable) == null ||transferIndex <= 0)break;
/**
* 线程进入扩容，sc+1 即 可以进入的线程数少1
*/
if (U.compareAndSwapInt(this, SIZECTL, sc, sc + 1))transfer(tab, nt);
//第一个线程进入扩容
}else if (U.compareAndSwapInt(this, SIZECTL, sc,
(rs << RESIZE_STAMP_SHIFT) + 2))transfer(tab, null);
s = sumCount();
}}}/**
* Helps transfer if a resize is in progress.
* 如果tab正在进行扩容，那么该线程一起帮助扩容
* 这是一个辅助操作
*/
final Node<K,V>[] helpTransfer(Node<K,V>[] tab, Node<K,V> f) {Node<K,V>[] nextTab; int sc;
if (tab != null && (f instanceof ForwardingNode) &&(nextTab = ((ForwardingNode<K,V>)f).nextTable) != null) {int rs = resizeStamp(tab.length);
while (nextTab == nextTable && table == tab &&(sc = sizeCtl) < 0) {/**
* 如果有一个线程退出了,或者要转移的箱子没有了，
* 那么说明扩容完成了，所有线程退出辅助操作
*/
if ((sc >>> RESIZE_STAMP_SHIFT) != rs || sc == rs + 1 ||sc == rs + MAX_RESIZERS || transferIndex <= 0)break;
/**
* 线程进入扩容，sc+1 即 可以进入的线程数少1
*/
if (U.compareAndSwapInt(this, SIZECTL, sc, sc + 1)) {transfer(tab, nextTab);
break;
}}return nextTab;
}return table;
}/**
* Tries to presize table to accommodate the given number of elements.
*
* @param size number of elements (doesn't need to be perfectly accurate)
*/
private final void tryPresize(int size) {int c = (size >= (MAXIMUM_CAPACITY >>> 1)) ? MAXIMUM_CAPACITY :tableSizeFor(size + (size >>> 1) + 1);
int sc;
while ((sc = sizeCtl) >= 0) {Node<K,V>[] tab = table; int n;
if (tab == null || (n = tab.length) == 0) {n = (sc > c) ? sc : c;
if (U.compareAndSwapInt(this, SIZECTL, sc, -1)) {try {if (table == tab) {@SuppressWarnings("unchecked")Node<K,V>[] nt = (Node<K,V>[])new Node<?,?>[n];
table = nt;
sc = n - (n >>> 2);
}} finally {sizeCtl = sc;
}}}else if (c <= sc || n >= MAXIMUM_CAPACITY)break;
else if (tab == table) {int rs = resizeStamp(n);
if (sc < 0) {Node<K,V>[] nt;
if ((sc >>> RESIZE_STAMP_SHIFT) != rs || sc == rs + 1 ||sc == rs + MAX_RESIZERS || (nt = nextTable) == null ||transferIndex <= 0)break;
if (U.compareAndSwapInt(this, SIZECTL, sc, sc + 1))transfer(tab, nt);
}else if (U.compareAndSwapInt(this, SIZECTL, sc,
(rs << RESIZE_STAMP_SHIFT) + 2))transfer(tab, null);
}}}/**
* Moves and/or copies the nodes in each bin to new table. See
* above for explanation.
* 扩容操作
*/
private final void transfer(Node<K,V>[] tab, Node<K,V>[] nextTab) {int n = tab.length, stride;
/**
* stride即每个线程处理桶的最小步幅（个数），
* 当NCPU > 1时，即n/(8*NCPU)，可见CPU个数越多，
* 每个线程处理的桶个数越少，但最少处理16个
*/
if ((stride = (NCPU > 1) ? (n >>> 3) / NCPU : n) < MIN_TRANSFER_STRIDE)stride = MIN_TRANSFER_STRIDE; // subdivide range
if (nextTab == null) { // initiating
try {/**
* 新数组扩容两倍
*/
@SuppressWarnings("unchecked")Node<K,V>[] nt = (Node<K,V>[])new Node<?,?>[n << 1];
nextTab = nt;
} catch (Throwable ex) { // try to cope with OOME
sizeCtl = Integer.MAX_VALUE;
return;
}nextTable = nextTab;
/**
* transferIndex表示还剩下待转移的桶数
*/
transferIndex = n;
}int nextn = nextTab.length;
ForwardingNode<K,V> fwd = new ForwardingNode<K,V>(nextTab);
/**
* 控制线程的任务领取，如果领取完成了，确定了自己移动桶的范围，就设置为false
*/
boolean advance = true;
/**
* 确保迁移完成的标志
*/
boolean finishing = false; // to ensure sweep before committing nextTab
for (int i = 0, bound = 0;;) {Node<K,V> f; int fh;
/**
* 当线程领取完任务以后，就不再进来了
*/
while (advance) {int nextIndex, nextBound;
/**
* 如果线程手上的迁移工作还没做好 或 桶都迁移完了
*/
if (--i >= bound || finishing)advance = false;
/**
* 如果所有桶都移完了，那么该线程可以设置i=-1,到时候return
* 如果该线程手上的迁移任务做完了，但是数组中还有桶没有移动，
* 那么继续分配桶给该线程移动
*/
else if ((nextIndex = transferIndex) <= 0) {i = -1;
advance = false;
}/**
* 每次线程领取扩容任务后，需要更新transferIndex的值(transferIndex-stride)。
* CAS将transferIndex更新为新的索引边界，防止不同线程之间领取重复的任务。
* 确定当前线程每次分配的待迁移桶的范围[bound, nextIndex]
*/
else if (U.compareAndSwapInt(this, TRANSFERINDEX, nextIndex,
nextBound = (nextIndex > stride ?nextIndex - stride : 0))) {/**
* 假设容量n为16，线程最小处理桶范围为16，
* 因此这里nextBound=0,i=15
*/
bound = nextBound;
i = nextIndex - 1;
advance = false;
}}/**
* 如果该线程迁移工作做完了，并且数组中没有剩余桶需要迁移，
* 那么此时i=-1，则进入
*/
if (i < 0 || i >= n || i + n >= nextn) {int sc;
/**
* (第一次进来这里的时候，finishing都是false，直接跳过)
* 注意：finishing为true的时候，只有是扩容时最后一个线程退出的时候
* 所以finishing用来控制整个扩容操作的完成
*/
if (finishing) {/**
* 注意：后面转移桶的时候，用的都是transfer的两个入参
* tab和nextTab，而这两个是nextTable和table的引用，
* 所以这里更改nextTable和table的引用没什么关系
*/
nextTable = null;
table = nextTab;
/**
* 将sizeCtl设置为下次需要扩容时的阈值，
* 大小即是扩容前容量的1.5n，扩容后的容量为2n
* 1.5n/2n = 0.75
*/
sizeCtl = (n << 1) - (n >>> 1);
return;
}/**
* 该线程完成任务以后，sc-1则负数越小，线程数越大
* （调用transfer()的时候有个sc+1的操作，说明该线程进入transfer以后，
* 可以进入的线程数小了，现在线程完成后再把可以进入的线程数加回来）
*/
if (U.compareAndSwapInt(this, SIZECTL, sc = sizeCtl, sc - 1)) {/**
* 在addCount中，sizeCtl被赋值为(rs << RESIZE_STAMP_SHIFT) + 2
* 所以这里如果sc != (rs << RESIZE_STAMP_SHIFT) + 2 那么就说明
* 还有线程没有退出，那么这些辅助扩容的线程如果已经完成了自己的迁移操作
* 可以直接return。
* 如果这个时候是最后一个线程了，那么finishing设置为完成，并重新检查
* 一遍所有的桶是否被迁移，如果全部完成了，那么走if(finishing)逻辑退出
*/
if ((sc - 2) != resizeStamp(n) << RESIZE_STAMP_SHIFT)return;
finishing = advance = true;
/**
* 返回之前重新检查一遍，所有的桶都被转移了(即Fwd节点)
*/
i = n; // recheck before commit
}}/**
* 注意：每次桶被移动以后，advance会被设置为true，然后
* 进入while循环，i将被减1
*/
//i位置节点为空，替换为ForwardingNode节点，用于通知其他线程该位置已经处理
else if ((f = tabAt(tab, i)) == null)advance = casTabAt(tab, i, null, fwd);
else if ((fh = f.hash) == MOVED)advance = true; // already processed
else {/**
* 如果该桶位置不为空，那么锁住这个桶
*/
synchronized (f) {/**
* 这里主要做双重检查，防止上锁的时候，tab[i]已经被移动了
*/
if (tabAt(tab, i) == f) {/**
* ln和hn在最后的使用上来看，就是
* 旧节点需要迁移到新数组上的位置，
* 其中ln的位置在[0,i]，
* 而hn的位置在(i,i+n]
*/
Node<K,V> ln, hn;
/**
* table[i]节点的hashcode大于0，说明是普通节点，
* 而不是ForwardNode或Treebin节点
*/
if (fh >= 0) {/**
* n为2的幂次方，所以必然是1开头,
* table[i]的hashcode & n 即只有两种结果 0 或 n
* 因此这里的意思其实是把链表中的节点分为两类来处理
*/
int runBit = fh & n;
Node<K,V> lastRun = f;
/**
* 这里主要是确定分成两类以后，最后连续一类的节点边界
* 比如一条链表被技术处为：0 0 n 0 0 0
* 这里运行过后，计算出来的runbit就是第四个节点的0
* lastRun就是第四个节点。
* 这样做的好处是：第四个节点后面的节点不用再迁移，因为
* 他们是一个链表(next关系)，所以只要移动第四个节点就
* 可以连着后面一起移动
*/
for (Node<K,V> p = f.next; p != null; p = p.next) {int b = p.hash & n;
if (b != runBit) {runBit = b;
lastRun = p;
}}/**
* 这里根据runBit将链表节点分成两类，
* runBit是0的迁移到新数组的[0,i]桶上，
* 其他的迁移到新数组的(i,i+n]桶上
*/
//假设用上面的 0 0 n 0 0 0逻辑走，那么这里
//ln就是第四个节点，hn = null
if (runBit == 0) {ln = lastRun;
hn = null;
}else {hn = lastRun;
ln = null;
}/**
* 从头一个节点处理至lastRun节点，新增的节点放在头部
*/
for (Node<K,V> p = f; p != lastRun; p = p.next) {int ph = p.hash; K pk = p.key; V pv = p.val;
if ((ph & n) == 0)ln = new Node<K,V>(ph, pk, pv, ln);
else
hn = new Node<K,V>(ph, pk, pv, hn);
}setTabAt(nextTab, i, ln);
setTabAt(nextTab, i + n, hn);
//迁移后放上fwd表示该桶已被处理
setTabAt(tab, i, fwd);
advance = true;
}else if (f instanceof TreeBin) {TreeBin<K,V> t = (TreeBin<K,V>)f;
TreeNode<K,V> lo = null, loTail = null;
TreeNode<K,V> hi = null, hiTail = null;
int lc = 0, hc = 0;
/**
* 和链表时的逻辑一样，分两类走
* 后面的树节点就往头结点后面加
*/
//TreeBin继承自Node，也有next属性
for (Node<K,V> e = t.first; e != null; e = e.next) {int h = e.hash;
TreeNode<K,V> p = new TreeNode<K,V>(h, e.key, e.val, null, null);
if ((h & n) == 0) {if ((p.prev = loTail) == null)lo = p;
else
loTail.next = p;
loTail = p;
++lc;
}else {if ((p.prev = hiTail) == null)hi = p;
else
hiTail.next = p;
hiTail = p;
++hc;
}}/**
* 如果最后发现子树的节点数小于等于UNTREEIFY_THRESHOLD,
* 那就将树转换为链
*/
ln = (lc <= UNTREEIFY_THRESHOLD) ? untreeify(lo) :(hc != 0) ? new TreeBin<K,V>(lo) : t;
hn = (hc <= UNTREEIFY_THRESHOLD) ? untreeify(hi) :(lc != 0) ? new TreeBin<K,V>(hi) : t;
setTabAt(nextTab, i, ln);
setTabAt(nextTab, i + n, hn);
setTabAt(tab, i, fwd);
advance = true;
}}}}}}/* ---------------- Counter support -------------- */
/**
* A padded cell for distributing counts. Adapted from LongAdder
* and Striped64. See their internal docs for explanation.
*/
/**
* @Contended 即解决数组连续内存中可能存在的缓存行伪共享问题
* （即两个变量共享一个缓存行）
*/
@sun.misc.Contended static final class CounterCell {volatile long value;
CounterCell(long x) { value = x; }}final long sumCount() {CounterCell[] as = counterCells; CounterCell a;
long sum = baseCount;
if (as != null) {for (int i = 0; i < as.length; ++i) {if ((a = as[i]) != null)sum += a.value;
}}return sum;
}// See LongAdder version for explanation
/**
* cells初始化、扩容、创建、新增cell节点
*/
private final void fullAddCount(long x, boolean wasUncontended) {int h;
/**
* ThreadLocalRandom.getProbe() == 0 说明需要
* 调用ThreadLocalRandom.current()初始化（其实底部也是调用localInit()）
*/
if ((h = ThreadLocalRandom.getProbe()) == 0) {ThreadLocalRandom.localInit(); // force initialization
h = ThreadLocalRandom.getProbe();
wasUncontended = true;
}//没用的变量
boolean collide = false; // True if last slot nonempty
for (;;) {CounterCell[] as; CounterCell a; int n; long v;
/**
* 如果cells已经初始化过了，新增cell
*/
if ((as = counterCells) != null && (n = as.length) > 0) {if ((a = as[(n - 1) & h]) == null) {if (cellsBusy == 0) { // Try to attach new Cell
CounterCell r = new CounterCell(x); // Optimistic create
/**
* 新增cell的时候要持有cellBusy，避免多线程新增
* 到同一个index上
*/
if (cellsBusy == 0 &&U.compareAndSwapInt(this, CELLSBUSY, 0, 1)) {boolean created = false;
try { // Recheck under lock
CounterCell[] rs; int m, j;
if ((rs = counterCells) != null &&(m = rs.length) > 0 &&rs[j = (m - 1) & h] == null) {rs[j] = r;
created = true;
}} finally {cellsBusy = 0;
}if (created)break;
continue; // Slot is now non-empty
}}collide = false;
}/**
* wasUncontended其实在ConcurrentHashMap中没有设置过false，
* 这里的意思是，如果wasUncontended是false，说明cells[i]处于
* 竞争状态，那么continue一次重新hash & (n-1)去找一个新的index
*/
else if (!wasUncontended) // CAS already known to fail
wasUncontended = true; // Continue after rehash
/**
* 如果cells[i]存在，那么去更新cells[i]的value
*/
else if (U.compareAndSwapLong(a, CELLVALUE, v = a.value, v + x))break;
/**
* 最大只能扩容到CPU数目,或者是已经扩容成功但本地引用as已经过期了
* （注：代码中collide在true的时候没有用到if条件中，所以collide
* 只有自己赋值玩。。。其实删掉也没事，另外，cells数组大小超过NCPU，
* 也没做啥限制的操作）
*/
else if (counterCells != as || n >= NCPU)collide = false; // At max size or stale
else if (!collide)collide = true;
/**
* 如果cells[i]存在，但是依旧被其他线程占据更新，那么就扩容2倍
*/
else if (cellsBusy == 0 &&U.compareAndSwapInt(this, CELLSBUSY, 0, 1)) {try {if (counterCells == as) {// Expand table unless stale
CounterCell[] rs = new CounterCell[n << 1];
for (int i = 0; i < n; ++i)rs[i] = as[i];
counterCells = rs;
}} finally {cellsBusy = 0;
}collide = false;
continue; // Retry with expanded table
}h = ThreadLocalRandom.advanceProbe(h);
/**
* cellsBusy是0表示还没有线程在创建cells数组。
* 如果还没有线程进入 且 cells是空
* 那么就开始初始化cells
*/
}else if (cellsBusy == 0 && counterCells == as &&U.compareAndSwapInt(this, CELLSBUSY, 0, 1)) {boolean init = false;
try { // Initialize table
if (counterCells == as) {CounterCell[] rs = new CounterCell[2];
//hash & (2-1) 将需要统计的个数x放到Cell中
rs[h & 1] = new CounterCell(x);
counterCells = rs;
init = true;
}//cellsBusy == 1的时候，确保了只有一个线程能修改，所以这里不用CAS更新
} finally {cellsBusy = 0;
}if (init)break;
/**
* 如果cells正在被其他线程初始化，那么这里直接尝试自旋（循环）更新baseCount
*/
}else if (U.compareAndSwapLong(this, BASECOUNT, v = baseCount, v + x))break; // Fall back on using base
}}/* ---------------- Conversion from/to TreeBins -------------- */
/**
* Replaces all linked nodes in bin at given index unless table is
* too small, in which case resizes instead.
*/
private final void treeifyBin(Node<K,V>[] tab, int index) {Node<K,V> b; int n, sc;
if (tab != null) {if ((n = tab.length) < MIN_TREEIFY_CAPACITY)tryPresize(n << 1);
else if ((b = tabAt(tab, index)) != null && b.hash >= 0) {synchronized (b) {if (tabAt(tab, index) == b) {TreeNode<K,V> hd = null, tl = null;
for (Node<K,V> e = b; e != null; e = e.next) {TreeNode<K,V> p =new TreeNode<K,V>(e.hash, e.key, e.val,
null, null);
if ((p.prev = tl) == null)hd = p;
else
tl.next = p;
tl = p;
}setTabAt(tab, index, new TreeBin<K,V>(hd));
}}}}}/**
* Returns a list on non-TreeNodes replacing those in given list.
*/
static <K,V> Node<K,V> untreeify(Node<K,V> b) {Node<K,V> hd = null, tl = null;
for (Node<K,V> q = b; q != null; q = q.next) {Node<K,V> p = new Node<K,V>(q.hash, q.key, q.val, null);
if (tl == null)hd = p;
else
tl.next = p;
tl = p;
}return hd;
}/* ---------------- TreeNodes -------------- */
/**
* Nodes for use in TreeBins
*/
static final class TreeNode<K,V> extends Node<K,V> {TreeNode<K,V> parent; // red-black tree links
TreeNode<K,V> left;
TreeNode<K,V> right;
TreeNode<K,V> prev; // needed to unlink next upon deletion
boolean red;
TreeNode(int hash, K key, V val, Node<K,V> next,
TreeNode<K,V> parent) {super(hash, key, val, next);
this.parent = parent;
}Node<K,V> find(int h, Object k) {return findTreeNode(h, k, null);
}/**
* Returns the TreeNode (or null if not found) for the given key
* starting at given root.
*/
final TreeNode<K,V> findTreeNode(int h, Object k, Class<?> kc) {if (k != null) {TreeNode<K,V> p = this;
do {int ph, dir; K pk; TreeNode<K,V> q;
TreeNode<K,V> pl = p.left, pr = p.right;
if ((ph = p.hash) > h)p = pl;
else if (ph < h)p = pr;
else if ((pk = p.key) == k || (pk != null && k.equals(pk)))return p;
else if (pl == null)p = pr;
else if (pr == null)p = pl;
else if ((kc != null ||(kc = comparableClassFor(k)) != null) &&(dir = compareComparables(kc, k, pk)) != 0)p = (dir < 0) ? pl : pr;
else if ((q = pr.findTreeNode(h, k, kc)) != null)return q;
else
p = pl;
} while (p != null);
}return null;
}}/* ---------------- TreeBins -------------- */
/**
* TreeNodes used at the heads of bins. TreeBins do not hold user
* keys or values, but instead point to list of TreeNodes and
* their root. They also maintain a parasitic read-write lock
* forcing writers (who hold bin lock) to wait for readers (who do
* not) to complete before tree restructuring operations.
*/
static final class TreeBin<K,V> extends Node<K,V> {TreeNode<K,V> root;
volatile TreeNode<K,V> first;
volatile Thread waiter;
volatile int lockState;
// values for lockState
static final int WRITER = 1; // set while holding write lock
static final int WAITER = 2; // set when waiting for write lock
static final int READER = 4; // increment value for setting read lock
/**
* Tie-breaking utility for ordering insertions when equal
* hashCodes and non-comparable. We don't require a total
* order, just a consistent insertion rule to maintain
* equivalence across rebalancings. Tie-breaking further than
* necessary simplifies testing a bit.
*/
static int tieBreakOrder(Object a, Object b) {int d;
if (a == null || b == null ||(d = a.getClass().getName().compareTo(b.getClass().getName())) == 0)d = (System.identityHashCode(a) <= System.identityHashCode(b) ?-1 : 1);
return d;
}/**
* Creates bin with initial set of nodes headed by b.
*/
TreeBin(TreeNode<K,V> b) {super(TREEBIN, null, null, null);
this.first = b;
TreeNode<K,V> r = null;
for (TreeNode<K,V> x = b, next; x != null; x = next) {next = (TreeNode<K,V>)x.next;
x.left = x.right = null;
if (r == null) {x.parent = null;
x.red = false;
r = x;
}else {K k = x.key;
int h = x.hash;
Class<?> kc = null;
for (TreeNode<K,V> p = r;;) {int dir, ph;
K pk = p.key;
if ((ph = p.hash) > h)dir = -1;
else if (ph < h)dir = 1;
else if ((kc == null &&(kc = comparableClassFor(k)) == null) ||(dir = compareComparables(kc, k, pk)) == 0)dir = tieBreakOrder(k, pk);
TreeNode<K,V> xp = p;
if ((p = (dir <= 0) ? p.left : p.right) == null) {x.parent = xp;
if (dir <= 0)xp.left = x;
else
xp.right = x;
r = balanceInsertion(r, x);
break;
}}}}this.root = r;
assert checkInvariants(root);
}/**
* Acquires write lock for tree restructuring.
*/
private final void lockRoot() {if (!U.compareAndSwapInt(this, LOCKSTATE, 0, WRITER))contendedLock(); // offload to separate method
}/**
* Releases write lock for tree restructuring.
*/
private final void unlockRoot() {lockState = 0;
}/**
* Possibly blocks awaiting root lock.
*/
private final void contendedLock() {boolean waiting = false;
for (int s;;) {if (((s = lockState) & ~WAITER) == 0) {if (U.compareAndSwapInt(this, LOCKSTATE, s, WRITER)) {if (waiting)waiter = null;
return;
}}else if ((s & WAITER) == 0) {if (U.compareAndSwapInt(this, LOCKSTATE, s, s | WAITER)) {waiting = true;
waiter = Thread.currentThread();
}}else if (waiting)LockSupport.park(this);
}}/**
* Returns matching node or null if none. Tries to search
* using tree comparisons from root, but continues linear
* search when lock not available.
*/
final Node<K,V> find(int h, Object k) {if (k != null) {for (Node<K,V> e = first; e != null; ) {int s; K ek;
if (((s = lockState) & (WAITER|WRITER)) != 0) {if (e.hash == h &&((ek = e.key) == k || (ek != null && k.equals(ek))))return e;
e = e.next;
}else if (U.compareAndSwapInt(this, LOCKSTATE, s,
s + READER)) {TreeNode<K,V> r, p;
try {p = ((r = root) == null ? null :r.findTreeNode(h, k, null));
} finally {Thread w;
if (U.getAndAddInt(this, LOCKSTATE, -READER) ==(READER|WAITER) && (w = waiter) != null)LockSupport.unpark(w);
}return p;
}}}return null;
}/**
* Finds or adds a node.
* @return null if added
*/
final TreeNode<K,V> putTreeVal(int h, K k, V v) {Class<?> kc = null;
boolean searched = false;
for (TreeNode<K,V> p = root;;) {int dir, ph; K pk;
if (p == null) {first = root = new TreeNode<K,V>(h, k, v, null, null);
break;
}else if ((ph = p.hash) > h)dir = -1;
else if (ph < h)dir = 1;
else if ((pk = p.key) == k || (pk != null && k.equals(pk)))return p;
else if ((kc == null &&(kc = comparableClassFor(k)) == null) ||(dir = compareComparables(kc, k, pk)) == 0) {if (!searched) {TreeNode<K,V> q, ch;
searched = true;
if (((ch = p.left) != null &&(q = ch.findTreeNode(h, k, kc)) != null) ||((ch = p.right) != null &&(q = ch.findTreeNode(h, k, kc)) != null))return q;
}dir = tieBreakOrder(k, pk);
}TreeNode<K,V> xp = p;
if ((p = (dir <= 0) ? p.left : p.right) == null) {TreeNode<K,V> x, f = first;
first = x = new TreeNode<K,V>(h, k, v, f, xp);
if (f != null)f.prev = x;
if (dir <= 0)xp.left = x;
else
xp.right = x;
if (!xp.red)x.red = true;
else {lockRoot();
try {root = balanceInsertion(root, x);
} finally {unlockRoot();
}}break;
}}assert checkInvariants(root);
return null;
}/**
* Removes the given node, that must be present before this
* call. This is messier than typical red-black deletion code
* because we cannot swap the contents of an interior node
* with a leaf successor that is pinned by "next" pointers
* that are accessible independently of lock. So instead we
* swap the tree linkages.
*
* @return true if now too small, so should be untreeified
*/
final boolean removeTreeNode(TreeNode<K,V> p) {TreeNode<K,V> next = (TreeNode<K,V>)p.next;
TreeNode<K,V> pred = p.prev; // unlink traversal pointers
TreeNode<K,V> r, rl;
if (pred == null)first = next;
else
pred.next = next;
if (next != null)next.prev = pred;
if (first == null) {root = null;
return true;
}if ((r = root) == null || r.right == null || // too small
(rl = r.left) == null || rl.left == null)return true;
lockRoot();
try {TreeNode<K,V> replacement;
TreeNode<K,V> pl = p.left;
TreeNode<K,V> pr = p.right;
if (pl != null && pr != null) {TreeNode<K,V> s = pr, sl;
while ((sl = s.left) != null) // find successor
s = sl;
boolean c = s.red; s.red = p.red; p.red = c; // swap colors
TreeNode<K,V> sr = s.right;
TreeNode<K,V> pp = p.parent;
if (s == pr) { // p was s's direct parent
p.parent = s;
s.right = p;
}else {TreeNode<K,V> sp = s.parent;
if ((p.parent = sp) != null) {if (s == sp.left)sp.left = p;
else
sp.right = p;
}if ((s.right = pr) != null)pr.parent = s;
}p.left = null;
if ((p.right = sr) != null)sr.parent = p;
if ((s.left = pl) != null)pl.parent = s;
if ((s.parent = pp) == null)r = s;
else if (p == pp.left)pp.left = s;
else
pp.right = s;
if (sr != null)replacement = sr;
else
replacement = p;
}else if (pl != null)replacement = pl;
else if (pr != null)replacement = pr;
else
replacement = p;
if (replacement != p) {TreeNode<K,V> pp = replacement.parent = p.parent;
if (pp == null)r = replacement;
else if (p == pp.left)pp.left = replacement;
else
pp.right = replacement;
p.left = p.right = p.parent = null;
}root = (p.red) ? r : balanceDeletion(r, replacement);
if (p == replacement) { // detach pointers
TreeNode<K,V> pp;
if ((pp = p.parent) != null) {if (p == pp.left)pp.left = null;
else if (p == pp.right)pp.right = null;
p.parent = null;
}}} finally {unlockRoot();
}assert checkInvariants(root);
return false;
}/* ------------------------------------------------------------ */
// Red-black tree methods, all adapted from CLR
static <K,V> TreeNode<K,V> rotateLeft(TreeNode<K,V> root,
TreeNode<K,V> p) {TreeNode<K,V> r, pp, rl;
if (p != null && (r = p.right) != null) {if ((rl = p.right = r.left) != null)rl.parent = p;
if ((pp = r.parent = p.parent) == null)(root = r).red = false;
else if (pp.left == p)pp.left = r;
else
pp.right = r;
r.left = p;
p.parent = r;
}return root;
}static <K,V> TreeNode<K,V> rotateRight(TreeNode<K,V> root,
TreeNode<K,V> p) {TreeNode<K,V> l, pp, lr;
if (p != null && (l = p.left) != null) {if ((lr = p.left = l.right) != null)lr.parent = p;
if ((pp = l.parent = p.parent) == null)(root = l).red = false;
else if (pp.right == p)pp.right = l;
else
pp.left = l;
l.right = p;
p.parent = l;
}return root;
}static <K,V> TreeNode<K,V> balanceInsertion(TreeNode<K,V> root,
TreeNode<K,V> x) {x.red = true;
for (TreeNode<K,V> xp, xpp, xppl, xppr;;) {if ((xp = x.parent) == null) {x.red = false;
return x;
}else if (!xp.red || (xpp = xp.parent) == null)return root;
if (xp == (xppl = xpp.left)) {if ((xppr = xpp.right) != null && xppr.red) {xppr.red = false;
xp.red = false;
xpp.red = true;
x = xpp;
}else {if (x == xp.right) {root = rotateLeft(root, x = xp);
xpp = (xp = x.parent) == null ? null : xp.parent;
}if (xp != null) {xp.red = false;
if (xpp != null) {xpp.red = true;
root = rotateRight(root, xpp);
}}}}else {if (xppl != null && xppl.red) {xppl.red = false;
xp.red = false;
xpp.red = true;
x = xpp;
}else {if (x == xp.left) {root = rotateRight(root, x = xp);
xpp = (xp = x.parent) == null ? null : xp.parent;
}if (xp != null) {xp.red = false;
if (xpp != null) {xpp.red = true;
root = rotateLeft(root, xpp);
}}}}}}static <K,V> TreeNode<K,V> balanceDeletion(TreeNode<K,V> root,
TreeNode<K,V> x) {for (TreeNode<K,V> xp, xpl, xpr;;) {if (x == null || x == root)return root;
else if ((xp = x.parent) == null) {x.red = false;
return x;
}else if (x.red) {x.red = false;
return root;
}else if ((xpl = xp.left) == x) {if ((xpr = xp.right) != null && xpr.red) {xpr.red = false;
xp.red = true;
root = rotateLeft(root, xp);
xpr = (xp = x.parent) == null ? null : xp.right;
}if (xpr == null)x = xp;
else {TreeNode<K,V> sl = xpr.left, sr = xpr.right;
if ((sr == null || !sr.red) &&(sl == null || !sl.red)) {xpr.red = true;
x = xp;
}else {if (sr == null || !sr.red) {if (sl != null)sl.red = false;
xpr.red = true;
root = rotateRight(root, xpr);
xpr = (xp = x.parent) == null ?null : xp.right;
}if (xpr != null) {xpr.red = (xp == null) ? false : xp.red;
if ((sr = xpr.right) != null)sr.red = false;
}if (xp != null) {xp.red = false;
root = rotateLeft(root, xp);
}x = root;
}}}else { // symmetric
if (xpl != null && xpl.red) {xpl.red = false;
xp.red = true;
root = rotateRight(root, xp);
xpl = (xp = x.parent) == null ? null : xp.left;
}if (xpl == null)x = xp;
else {TreeNode<K,V> sl = xpl.left, sr = xpl.right;
if ((sl == null || !sl.red) &&(sr == null || !sr.red)) {xpl.red = true;
x = xp;
}else {if (sl == null || !sl.red) {if (sr != null)sr.red = false;
xpl.red = true;
root = rotateLeft(root, xpl);
xpl = (xp = x.parent) == null ?null : xp.left;
}if (xpl != null) {xpl.red = (xp == null) ? false : xp.red;
if ((sl = xpl.left) != null)sl.red = false;
}if (xp != null) {xp.red = false;
root = rotateRight(root, xp);
}x = root;
}}}}}/**
* Recursive invariant check
*/
static <K,V> boolean checkInvariants(TreeNode<K,V> t) {TreeNode<K,V> tp = t.parent, tl = t.left, tr = t.right,
tb = t.prev, tn = (TreeNode<K,V>)t.next;
if (tb != null && tb.next != t)return false;
if (tn != null && tn.prev != t)return false;
if (tp != null && t != tp.left && t != tp.right)return false;
if (tl != null && (tl.parent != t || tl.hash > t.hash))return false;
if (tr != null && (tr.parent != t || tr.hash < t.hash))return false;
if (t.red && tl != null && tl.red && tr != null && tr.red)return false;
if (tl != null && !checkInvariants(tl))return false;
if (tr != null && !checkInvariants(tr))return false;
return true;
}private static final sun.misc.Unsafe U;
private static final long LOCKSTATE;
static {try {U = sun.misc.Unsafe.getUnsafe();
Class<?> k = TreeBin.class;
LOCKSTATE = U.objectFieldOffset(k.getDeclaredField("lockState"));
} catch (Exception e) {throw new Error(e);
}}}/* ----------------Table Traversal -------------- */
/**
* Records the table, its length, and current traversal index for a
* traverser that must process a region of a forwarded table before
* proceeding with current table.
*/
static final class TableStack<K,V> {int length;
int index;
Node<K,V>[] tab;
TableStack<K,V> next;
}/**
* Encapsulates traversal for methods such as containsValue; also
* serves as a base class for other iterators and spliterators.
*
* Method advance visits once each still-valid node that was
* reachable upon iterator construction. It might miss some that
* were added to a bin after the bin was visited, which is OK wrt
* consistency guarantees. Maintaining this property in the face
* of possible ongoing resizes requires a fair amount of
* bookkeeping state that is difficult to optimize away amidst
* volatile accesses. Even so, traversal maintains reasonable
* throughput.
*
* Normally, iteration proceeds bin-by-bin traversing lists.
* However, if the table has been resized, then all future steps
* must traverse both the bin at the current index as well as at
* (index + baseSize); and so on for further resizings. To
* paranoically cope with potential sharing by users of iterators
* across threads, iteration terminates if a bounds checks fails
* for a table read.
*/
static class Traverser<K,V> {Node<K,V>[] tab; // current table; updated if resized
Node<K,V> next; // the next entry to use
TableStack<K,V> stack, spare; // to save/restore on ForwardingNodes
int index; // index of bin to use next
int baseIndex; // current index of initial table
int baseLimit; // index bound for initial table
final int baseSize; // initial table size
Traverser(Node<K,V>[] tab, int size, int index, int limit) {this.tab = tab;
this.baseSize = size;
this.baseIndex = this.index = index;
this.baseLimit = limit;
this.next = null;
}/**
* Advances if possible, returning next valid node, or null if none.
*/
final Node<K,V> advance() {Node<K,V> e;
if ((e = next) != null)e = e.next;
for (;;) {Node<K,V>[] t; int i, n; // must use locals in checks
if (e != null)return next = e;
if (baseIndex >= baseLimit || (t = tab) == null ||(n = t.length) <= (i = index) || i < 0)return next = null;
if ((e = tabAt(t, i)) != null && e.hash < 0) {if (e instanceof ForwardingNode) {tab = ((ForwardingNode<K,V>)e).nextTable;
e = null;
pushState(t, i, n);
continue;
}else if (e instanceof TreeBin)e = ((TreeBin<K,V>)e).first;
else
e = null;
}if (stack != null)recoverState(n);
else if ((index = i + baseSize) >= n)index = ++baseIndex; // visit upper slots if present
}}/**
* Saves traversal state upon encountering a forwarding node.
*/
private void pushState(Node<K,V>[] t, int i, int n) {TableStack<K,V> s = spare; // reuse if possible
if (s != null)spare = s.next;
else
s = new TableStack<K,V>();
s.tab = t;
s.length = n;
s.index = i;
s.next = stack;
stack = s;
}/**
* Possibly pops traversal state.
*
* @param n length of current table
*/
private void recoverState(int n) {TableStack<K,V> s; int len;
while ((s = stack) != null && (index += (len = s.length)) >= n) {n = len;
index = s.index;
tab = s.tab;
s.tab = null;
TableStack<K,V> next = s.next;
s.next = spare; // save for reuse
stack = next;
spare = s;
}if (s == null && (index += baseSize) >= n)index = ++baseIndex;
}}/**
* Base of key, value, and entry Iterators. Adds fields to
* Traverser to support iterator.remove.
*/
static class BaseIterator<K,V> extends Traverser<K,V> {final ConcurrentHashMap<K,V> map;
Node<K,V> lastReturned;
BaseIterator(Node<K,V>[] tab, int size, int index, int limit,
ConcurrentHashMap<K,V> map) {super(tab, size, index, limit);
this.map = map;
advance();
}public final boolean hasNext() { return next != null; }public final boolean hasMoreElements() { return next != null; }public final void remove() {Node<K,V> p;
if ((p = lastReturned) == null)throw new IllegalStateException();
lastReturned = null;
map.replaceNode(p.key, null, null);
}}static final class KeyIterator<K,V> extends BaseIterator<K,V>implements Iterator<K>, Enumeration<K> {KeyIterator(Node<K,V>[] tab, int index, int size, int limit,
ConcurrentHashMap<K,V> map) {super(tab, index, size, limit, map);
}public final K next() {Node<K,V> p;
if ((p = next) == null)throw new NoSuchElementException();
K k = p.key;
lastReturned = p;
advance();
return k;
}public final K nextElement() { return next(); }}static final class ValueIterator<K,V> extends BaseIterator<K,V>implements Iterator<V>, Enumeration<V> {ValueIterator(Node<K,V>[] tab, int index, int size, int limit,
ConcurrentHashMap<K,V> map) {super(tab, index, size, limit, map);
}public final V next() {Node<K,V> p;
if ((p = next) == null)throw new NoSuchElementException();
V v = p.val;
lastReturned = p;
advance();
return v;
}public final V nextElement() { return next(); }}static final class EntryIterator<K,V> extends BaseIterator<K,V>implements Iterator<Map.Entry<K,V>> {EntryIterator(Node<K,V>[] tab, int index, int size, int limit,
ConcurrentHashMap<K,V> map) {super(tab, index, size, limit, map);
}public final Map.Entry<K,V> next() {Node<K,V> p;
if ((p = next) == null)throw new NoSuchElementException();
K k = p.key;
V v = p.val;
lastReturned = p;
advance();
return new MapEntry<K,V>(k, v, map);
}}/**
* Exported Entry for EntryIterator
*/
static final class MapEntry<K,V> implements Map.Entry<K,V> {final K key; // non-null
V val; // non-null
final ConcurrentHashMap<K,V> map;
MapEntry(K key, V val, ConcurrentHashMap<K,V> map) {this.key = key;
this.val = val;
this.map = map;
}public K getKey() { return key; }public V getValue() { return val; }public int hashCode() { return key.hashCode() ^ val.hashCode(); }public String toString() { return key + "=" + val; }public boolean equals(Object o) {Object k, v; Map.Entry<?,?> e;
return ((o instanceof Map.Entry) &&(k = (e = (Map.Entry<?,?>)o).getKey()) != null &&(v = e.getValue()) != null &&(k == key || k.equals(key)) &&(v == val || v.equals(val)));
}/**
* Sets our entry's value and writes through to the map. The
* value to return is somewhat arbitrary here. Since we do not
* necessarily track asynchronous changes, the most recent
* "previous" value could be different from what we return (or
* could even have been removed, in which case the put will
* re-establish). We do not and cannot guarantee more.
*/
public V setValue(V value) {if (value == null) throw new NullPointerException();
V v = val;
val = value;
map.put(key, value);
return v;
}}static final class KeySpliterator<K,V> extends Traverser<K,V>implements Spliterator<K> {long est; // size estimate
KeySpliterator(Node<K,V>[] tab, int size, int index, int limit,
long est) {super(tab, size, index, limit);
this.est = est;
}public Spliterator<K> trySplit() {int i, f, h;
return (h = ((i = baseIndex) + (f = baseLimit)) >>> 1) <= i ? null :new KeySpliterator<K,V>(tab, baseSize, baseLimit = h,
f, est >>>= 1);
}public void forEachRemaining(Consumer<? super K> action) {if (action == null) throw new NullPointerException();
for (Node<K,V> p; (p = advance()) != null;)action.accept(p.key);
}public boolean tryAdvance(Consumer<? super K> action) {if (action == null) throw new NullPointerException();
Node<K,V> p;
if ((p = advance()) == null)return false;
action.accept(p.key);
return true;
}public long estimateSize() { return est; }public int characteristics() {return Spliterator.DISTINCT | Spliterator.CONCURRENT |Spliterator.NONNULL;
}}static final class ValueSpliterator<K,V> extends Traverser<K,V>implements Spliterator<V> {long est; // size estimate
ValueSpliterator(Node<K,V>[] tab, int size, int index, int limit,
long est) {super(tab, size, index, limit);
this.est = est;
}public Spliterator<V> trySplit() {int i, f, h;
return (h = ((i = baseIndex) + (f = baseLimit)) >>> 1) <= i ? null :new ValueSpliterator<K,V>(tab, baseSize, baseLimit = h,
f, est >>>= 1);
}public void forEachRemaining(Consumer<? super V> action) {if (action == null) throw new NullPointerException();
for (Node<K,V> p; (p = advance()) != null;)action.accept(p.val);
}public boolean tryAdvance(Consumer<? super V> action) {if (action == null) throw new NullPointerException();
Node<K,V> p;
if ((p = advance()) == null)return false;
action.accept(p.val);
return true;
}public long estimateSize() { return est; }public int characteristics() {return Spliterator.CONCURRENT | Spliterator.NONNULL;
}}static final class EntrySpliterator<K,V> extends Traverser<K,V>implements Spliterator<Map.Entry<K,V>> {final ConcurrentHashMap<K,V> map; // To export MapEntry
long est; // size estimate
EntrySpliterator(Node<K,V>[] tab, int size, int index, int limit,
long est, ConcurrentHashMap<K,V> map) {super(tab, size, index, limit);
this.map = map;
this.est = est;
}public Spliterator<Map.Entry<K,V>> trySplit() {int i, f, h;
return (h = ((i = baseIndex) + (f = baseLimit)) >>> 1) <= i ? null :new EntrySpliterator<K,V>(tab, baseSize, baseLimit = h,
f, est >>>= 1, map);
}public void forEachRemaining(Consumer<? super Map.Entry<K,V>> action) {if (action == null) throw new NullPointerException();
for (Node<K,V> p; (p = advance()) != null; )action.accept(new MapEntry<K,V>(p.key, p.val, map));
}public boolean tryAdvance(Consumer<? super Map.Entry<K,V>> action) {if (action == null) throw new NullPointerException();
Node<K,V> p;
if ((p = advance()) == null)return false;
action.accept(new MapEntry<K,V>(p.key, p.val, map));
return true;
}public long estimateSize() { return est; }public int characteristics() {return Spliterator.DISTINCT | Spliterator.CONCURRENT |Spliterator.NONNULL;
}}// Parallel bulk operations
/**
* Computes initial batch value for bulk tasks. The returned value
* is approximately exp2 of the number of times (minus one) to
* split task by two before executing leaf action. This value is
* faster to compute and more convenient to use as a guide to
* splitting than is the depth, since it is used while dividing by
* two anyway.
*/
final int batchFor(long b) {long n;
if (b == Long.MAX_VALUE || (n = sumCount()) <= 1L || n < b)return 0;
int sp = ForkJoinPool.getCommonPoolParallelism() << 2; // slack of 4
return (b <= 0L || (n /= b) >= sp) ? sp : (int)n;
}/**
* Performs the given action for each (key, value).
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param action the action
* @since 1.8
*/
public void forEach(long parallelismThreshold,
BiConsumer<? super K,? super V> action) {if (action == null) throw new NullPointerException();
new ForEachMappingTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
action).invoke();
}/**
* Performs the given action for each non-null transformation
* of each (key, value).
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element, or null if there is no transformation (in
* which case the action is not applied)
* @param action the action
* @param <U> the return type of the transformer
* @since 1.8
*/
public <U> void forEach(long parallelismThreshold,
BiFunction<? super K, ? super V, ? extends U> transformer,
Consumer<? super U> action) {if (transformer == null || action == null)throw new NullPointerException();
new ForEachTransformedMappingTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
transformer, action).invoke();
}/**
* Returns a non-null result from applying the given search
* function on each (key, value), or null if none. Upon
* success, further element processing is suppressed and the
* results of any other parallel invocations of the search
* function are ignored.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param searchFunction a function returning a non-null
* result on success, else null
* @param <U> the return type of the search function
* @return a non-null result from applying the given search
* function on each (key, value), or null if none
* @since 1.8
*/
public <U> U search(long parallelismThreshold,
BiFunction<? super K, ? super V, ? extends U> searchFunction) {if (searchFunction == null) throw new NullPointerException();
return new SearchMappingsTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
searchFunction, new AtomicReference<U>()).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all (key, value) pairs using the given reducer to
* combine values, or null if none.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element, or null if there is no transformation (in
* which case it is not combined)
* @param reducer a commutative associative combining function
* @param <U> the return type of the transformer
* @return the result of accumulating the given transformation
* of all (key, value) pairs
* @since 1.8
*/
public <U> U reduce(long parallelismThreshold,
BiFunction<? super K, ? super V, ? extends U> transformer,
BiFunction<? super U, ? super U, ? extends U> reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceMappingsTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all (key, value) pairs using the given reducer to
* combine values, and the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all (key, value) pairs
* @since 1.8
*/
public double reduceToDouble(long parallelismThreshold,
ToDoubleBiFunction<? super K, ? super V> transformer,
double basis,
DoubleBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceMappingsToDoubleTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all (key, value) pairs using the given reducer to
* combine values, and the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all (key, value) pairs
* @since 1.8
*/
public long reduceToLong(long parallelismThreshold,
ToLongBiFunction<? super K, ? super V> transformer,
long basis,
LongBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceMappingsToLongTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all (key, value) pairs using the given reducer to
* combine values, and the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all (key, value) pairs
* @since 1.8
*/
public int reduceToInt(long parallelismThreshold,
ToIntBiFunction<? super K, ? super V> transformer,
int basis,
IntBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceMappingsToIntTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Performs the given action for each key.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param action the action
* @since 1.8
*/
public void forEachKey(long parallelismThreshold,
Consumer<? super K> action) {if (action == null) throw new NullPointerException();
new ForEachKeyTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
action).invoke();
}/**
* Performs the given action for each non-null transformation
* of each key.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element, or null if there is no transformation (in
* which case the action is not applied)
* @param action the action
* @param <U> the return type of the transformer
* @since 1.8
*/
public <U> void forEachKey(long parallelismThreshold,
Function<? super K, ? extends U> transformer,
Consumer<? super U> action) {if (transformer == null || action == null)throw new NullPointerException();
new ForEachTransformedKeyTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
transformer, action).invoke();
}/**
* Returns a non-null result from applying the given search
* function on each key, or null if none. Upon success,
* further element processing is suppressed and the results of
* any other parallel invocations of the search function are
* ignored.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param searchFunction a function returning a non-null
* result on success, else null
* @param <U> the return type of the search function
* @return a non-null result from applying the given search
* function on each key, or null if none
* @since 1.8
*/
public <U> U searchKeys(long parallelismThreshold,
Function<? super K, ? extends U> searchFunction) {if (searchFunction == null) throw new NullPointerException();
return new SearchKeysTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
searchFunction, new AtomicReference<U>()).invoke();
}/**
* Returns the result of accumulating all keys using the given
* reducer to combine values, or null if none.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param reducer a commutative associative combining function
* @return the result of accumulating all keys using the given
* reducer to combine values, or null if none
* @since 1.8
*/
public K reduceKeys(long parallelismThreshold,
BiFunction<? super K, ? super K, ? extends K> reducer) {if (reducer == null) throw new NullPointerException();
return new ReduceKeysTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all keys using the given reducer to combine values, or
* null if none.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element, or null if there is no transformation (in
* which case it is not combined)
* @param reducer a commutative associative combining function
* @param <U> the return type of the transformer
* @return the result of accumulating the given transformation
* of all keys
* @since 1.8
*/
public <U> U reduceKeys(long parallelismThreshold,
Function<? super K, ? extends U> transformer,
BiFunction<? super U, ? super U, ? extends U> reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceKeysTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all keys using the given reducer to combine values, and
* the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all keys
* @since 1.8
*/
public double reduceKeysToDouble(long parallelismThreshold,
ToDoubleFunction<? super K> transformer,
double basis,
DoubleBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceKeysToDoubleTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all keys using the given reducer to combine values, and
* the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all keys
* @since 1.8
*/
public long reduceKeysToLong(long parallelismThreshold,
ToLongFunction<? super K> transformer,
long basis,
LongBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceKeysToLongTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all keys using the given reducer to combine values, and
* the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all keys
* @since 1.8
*/
public int reduceKeysToInt(long parallelismThreshold,
ToIntFunction<? super K> transformer,
int basis,
IntBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceKeysToIntTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Performs the given action for each value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param action the action
* @since 1.8
*/
public void forEachValue(long parallelismThreshold,
Consumer<? super V> action) {if (action == null)throw new NullPointerException();
new ForEachValueTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
action).invoke();
}/**
* Performs the given action for each non-null transformation
* of each value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element, or null if there is no transformation (in
* which case the action is not applied)
* @param action the action
* @param <U> the return type of the transformer
* @since 1.8
*/
public <U> void forEachValue(long parallelismThreshold,
Function<? super V, ? extends U> transformer,
Consumer<? super U> action) {if (transformer == null || action == null)throw new NullPointerException();
new ForEachTransformedValueTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
transformer, action).invoke();
}/**
* Returns a non-null result from applying the given search
* function on each value, or null if none. Upon success,
* further element processing is suppressed and the results of
* any other parallel invocations of the search function are
* ignored.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param searchFunction a function returning a non-null
* result on success, else null
* @param <U> the return type of the search function
* @return a non-null result from applying the given search
* function on each value, or null if none
* @since 1.8
*/
public <U> U searchValues(long parallelismThreshold,
Function<? super V, ? extends U> searchFunction) {if (searchFunction == null) throw new NullPointerException();
return new SearchValuesTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
searchFunction, new AtomicReference<U>()).invoke();
}/**
* Returns the result of accumulating all values using the
* given reducer to combine values, or null if none.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param reducer a commutative associative combining function
* @return the result of accumulating all values
* @since 1.8
*/
public V reduceValues(long parallelismThreshold,
BiFunction<? super V, ? super V, ? extends V> reducer) {if (reducer == null) throw new NullPointerException();
return new ReduceValuesTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all values using the given reducer to combine values, or
* null if none.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element, or null if there is no transformation (in
* which case it is not combined)
* @param reducer a commutative associative combining function
* @param <U> the return type of the transformer
* @return the result of accumulating the given transformation
* of all values
* @since 1.8
*/
public <U> U reduceValues(long parallelismThreshold,
Function<? super V, ? extends U> transformer,
BiFunction<? super U, ? super U, ? extends U> reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceValuesTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all values using the given reducer to combine values,
* and the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all values
* @since 1.8
*/
public double reduceValuesToDouble(long parallelismThreshold,
ToDoubleFunction<? super V> transformer,
double basis,
DoubleBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceValuesToDoubleTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all values using the given reducer to combine values,
* and the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all values
* @since 1.8
*/
public long reduceValuesToLong(long parallelismThreshold,
ToLongFunction<? super V> transformer,
long basis,
LongBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceValuesToLongTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all values using the given reducer to combine values,
* and the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all values
* @since 1.8
*/
public int reduceValuesToInt(long parallelismThreshold,
ToIntFunction<? super V> transformer,
int basis,
IntBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceValuesToIntTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Performs the given action for each entry.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param action the action
* @since 1.8
*/
public void forEachEntry(long parallelismThreshold,
Consumer<? super Map.Entry<K,V>> action) {if (action == null) throw new NullPointerException();
new ForEachEntryTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
action).invoke();
}/**
* Performs the given action for each non-null transformation
* of each entry.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element, or null if there is no transformation (in
* which case the action is not applied)
* @param action the action
* @param <U> the return type of the transformer
* @since 1.8
*/
public <U> void forEachEntry(long parallelismThreshold,
Function<Map.Entry<K,V>, ? extends U> transformer,
Consumer<? super U> action) {if (transformer == null || action == null)throw new NullPointerException();
new ForEachTransformedEntryTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
transformer, action).invoke();
}/**
* Returns a non-null result from applying the given search
* function on each entry, or null if none. Upon success,
* further element processing is suppressed and the results of
* any other parallel invocations of the search function are
* ignored.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param searchFunction a function returning a non-null
* result on success, else null
* @param <U> the return type of the search function
* @return a non-null result from applying the given search
* function on each entry, or null if none
* @since 1.8
*/
public <U> U searchEntries(long parallelismThreshold,
Function<Map.Entry<K,V>, ? extends U> searchFunction) {if (searchFunction == null) throw new NullPointerException();
return new SearchEntriesTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
searchFunction, new AtomicReference<U>()).invoke();
}/**
* Returns the result of accumulating all entries using the
* given reducer to combine values, or null if none.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param reducer a commutative associative combining function
* @return the result of accumulating all entries
* @since 1.8
*/
public Map.Entry<K,V> reduceEntries(long parallelismThreshold,
BiFunction<Map.Entry<K,V>, Map.Entry<K,V>, ? extends Map.Entry<K,V>> reducer) {if (reducer == null) throw new NullPointerException();
return new ReduceEntriesTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all entries using the given reducer to combine values,
* or null if none.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element, or null if there is no transformation (in
* which case it is not combined)
* @param reducer a commutative associative combining function
* @param <U> the return type of the transformer
* @return the result of accumulating the given transformation
* of all entries
* @since 1.8
*/
public <U> U reduceEntries(long parallelismThreshold,
Function<Map.Entry<K,V>, ? extends U> transformer,
BiFunction<? super U, ? super U, ? extends U> reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceEntriesTask<K,V,U>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all entries using the given reducer to combine values,
* and the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all entries
* @since 1.8
*/
public double reduceEntriesToDouble(long parallelismThreshold,
ToDoubleFunction<Map.Entry<K,V>> transformer,
double basis,
DoubleBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceEntriesToDoubleTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all entries using the given reducer to combine values,
* and the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all entries
* @since 1.8
*/
public long reduceEntriesToLong(long parallelismThreshold,
ToLongFunction<Map.Entry<K,V>> transformer,
long basis,
LongBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceEntriesToLongTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/**
* Returns the result of accumulating the given transformation
* of all entries using the given reducer to combine values,
* and the given basis as an identity value.
*
* @param parallelismThreshold the (estimated) number of elements
* needed for this operation to be executed in parallel
* @param transformer a function returning the transformation
* for an element
* @param basis the identity (initial default value) for the reduction
* @param reducer a commutative associative combining function
* @return the result of accumulating the given transformation
* of all entries
* @since 1.8
*/
public int reduceEntriesToInt(long parallelismThreshold,
ToIntFunction<Map.Entry<K,V>> transformer,
int basis,
IntBinaryOperator reducer) {if (transformer == null || reducer == null)throw new NullPointerException();
return new MapReduceEntriesToIntTask<K,V>(null, batchFor(parallelismThreshold), 0, 0, table,
null, transformer, basis, reducer).invoke();
}/* ----------------Views -------------- */
/**
* Base class for views.
*/
abstract static class CollectionView<K,V,E>implements Collection<E>, java.io.Serializable {private static final long serialVersionUID = 7249069246763182397L;
final ConcurrentHashMap<K,V> map;
CollectionView(ConcurrentHashMap<K,V> map) { this.map = map; }/**
* Returns the map backing this view.
*
* @return the map backing this view
*/
public ConcurrentHashMap<K,V> getMap() { return map; }/**
* Removes all of the elements from this view, by removing all
* the mappings from the map backing this view.
*/
public final void clear() { map.clear(); }public final int size() { return map.size(); }public final boolean isEmpty() { return map.isEmpty(); }// implementations below rely on concrete classes supplying these
// abstract methods
/**
* Returns an iterator over the elements in this collection.
*
* <p>The returned iterator is
* <a href="package-summary.html#Weakly"><i>weakly consistent</i></a>.
*
* @return an iterator over the elements in this collection
*/
public abstract Iterator<E> iterator();
public abstract boolean contains(Object o);
public abstract boolean remove(Object o);
private static final String oomeMsg = "Required array size too large";
public final Object[] toArray() {long sz = map.mappingCount();
if (sz > MAX_ARRAY_SIZE)throw new OutOfMemoryError(oomeMsg);
int n = (int)sz;
Object[] r = new Object[n];
int i = 0;
for (E e : this) {if (i == n) {if (n >= MAX_ARRAY_SIZE)throw new OutOfMemoryError(oomeMsg);
if (n >= MAX_ARRAY_SIZE - (MAX_ARRAY_SIZE >>> 1) - 1)n = MAX_ARRAY_SIZE;
else
n += (n >>> 1) + 1;
r = Arrays.copyOf(r, n);
}r[i++] = e;
}return (i == n) ? r : Arrays.copyOf(r, i);
}@SuppressWarnings("unchecked")public final <T> T[] toArray(T[] a) {long sz = map.mappingCount();
if (sz > MAX_ARRAY_SIZE)throw new OutOfMemoryError(oomeMsg);
int m = (int)sz;
T[] r = (a.length >= m) ? a :(T[])java.lang.reflect.Array.newInstance(a.getClass().getComponentType(), m);
int n = r.length;
int i = 0;
for (E e : this) {if (i == n) {if (n >= MAX_ARRAY_SIZE)throw new OutOfMemoryError(oomeMsg);
if (n >= MAX_ARRAY_SIZE - (MAX_ARRAY_SIZE >>> 1) - 1)n = MAX_ARRAY_SIZE;
else
n += (n >>> 1) + 1;
r = Arrays.copyOf(r, n);
}r[i++] = (T)e;
}if (a == r && i < n) {r[i] = null; // null-terminate
return r;
}return (i == n) ? r : Arrays.copyOf(r, i);
}/**
* Returns a string representation of this collection.
* The string representation consists of the string representations
* of the collection's elements in the order they are returned by
* its iterator, enclosed in square brackets ({@code "[]"}).
* Adjacent elements are separated by the characters {@code ", "}
* (comma and space). Elements are converted to strings as by
* {@link String#valueOf(Object)}.
*
* @return a string representation of this collection
*/
public final String toString() {StringBuilder sb = new StringBuilder();
sb.append('[');
Iterator<E> it = iterator();
if (it.hasNext()) {for (;;) {Object e = it.next();
sb.append(e == this ? "(this Collection)" : e);
if (!it.hasNext())break;
sb.append(',').append(' ');
}}return sb.append(']').toString();
}public final boolean containsAll(Collection<?> c) {if (c != this) {for (Object e : c) {if (e == null || !contains(e))return false;
}}return true;
}public final boolean removeAll(Collection<?> c) {if (c == null) throw new NullPointerException();
boolean modified = false;
for (Iterator<E> it = iterator(); it.hasNext();) {if (c.contains(it.next())) {it.remove();
modified = true;
}}return modified;
}public final boolean retainAll(Collection<?> c) {if (c == null) throw new NullPointerException();
boolean modified = false;
for (Iterator<E> it = iterator(); it.hasNext();) {if (!c.contains(it.next())) {it.remove();
modified = true;
}}return modified;
}}/**
* A view of a ConcurrentHashMap as a {@link Set} of keys, in
* which additions may optionally be enabled by mapping to a
* common value. This class cannot be directly instantiated.
* See {@link #keySet() keySet()},
* {@link #keySet(Object) keySet(V)},
* {@link #newKeySet() newKeySet()},
* {@link #newKeySet(int) newKeySet(int)}.
*
* @since 1.8
*/
public static class KeySetView<K,V> extends CollectionView<K,V,K>implements Set<K>, java.io.Serializable {private static final long serialVersionUID = 7249069246763182397L;
private final V value;
KeySetView(ConcurrentHashMap<K,V> map, V value) { // non-public
super(map);
this.value = value;
}/**
* Returns the default mapped value for additions,
* or {@code null} if additions are not supported.
*
* @return the default mapped value for additions, or {@code null}
* if not supported
*/
public V getMappedValue() { return value; }/**
* {@inheritDoc}
* @throws NullPointerException if the specified key is null
*/
public boolean contains(Object o) { return map.containsKey(o); }/**
* Removes the key from this map view, by removing the key (and its
* corresponding value) from the backing map. This method does
* nothing if the key is not in the map.
*
* @param o the key to be removed from the backing map
* @return {@code true} if the backing map contained the specified key
* @throws NullPointerException if the specified key is null
*/
public boolean remove(Object o) { return map.remove(o) != null; }/**
* @return an iterator over the keys of the backing map
*/
public Iterator<K> iterator() {Node<K,V>[] t;
ConcurrentHashMap<K,V> m = map;
int f = (t = m.table) == null ? 0 : t.length;
return new KeyIterator<K,V>(t, f, 0, f, m);
}/**
* Adds the specified key to this set view by mapping the key to
* the default mapped value in the backing map, if defined.
*
* @param e key to be added
* @return {@code true} if this set changed as a result of the call
* @throws NullPointerException if the specified key is null
* @throws UnsupportedOperationException if no default mapped value
* for additions was provided
*/
public boolean add(K e) {V v;
if ((v = value) == null)throw new UnsupportedOperationException();
return map.putVal(e, v, true) == null;
}/**
* Adds all of the elements in the specified collection to this set,
* as if by calling {@link #add} on each one.
*
* @param c the elements to be inserted into this set
* @return {@code true} if this set changed as a result of the call
* @throws NullPointerException if the collection or any of its
* elements are {@code null}
* @throws UnsupportedOperationException if no default mapped value
* for additions was provided
*/
public boolean addAll(Collection<? extends K> c) {boolean added = false;
V v;
if ((v = value) == null)throw new UnsupportedOperationException();
for (K e : c) {if (map.putVal(e, v, true) == null)added = true;
}return added;
}public int hashCode() {int h = 0;
for (K e : this)h += e.hashCode();
return h;
}public boolean equals(Object o) {Set<?> c;
return ((o instanceof Set) &&((c = (Set<?>)o) == this ||(containsAll(c) && c.containsAll(this))));
}public Spliterator<K> spliterator() {Node<K,V>[] t;
ConcurrentHashMap<K,V> m = map;
long n = m.sumCount();
int f = (t = m.table) == null ? 0 : t.length;
return new KeySpliterator<K,V>(t, f, 0, f, n < 0L ? 0L : n);
}public void forEach(Consumer<? super K> action) {if (action == null) throw new NullPointerException();
Node<K,V>[] t;
if ((t = map.table) != null) {Traverser<K,V> it = new Traverser<K,V>(t, t.length, 0, t.length);
for (Node<K,V> p; (p = it.advance()) != null; )action.accept(p.key);
}}}/**
* A view of a ConcurrentHashMap as a {@link Collection} of
* values, in which additions are disabled. This class cannot be
* directly instantiated. See {@link #values()}.
*/
static final class ValuesView<K,V> extends CollectionView<K,V,V>implements Collection<V>, java.io.Serializable {private static final long serialVersionUID = 2249069246763182397L;
ValuesView(ConcurrentHashMap<K,V> map) { super(map); }public final boolean contains(Object o) {return map.containsValue(o);
}public final boolean remove(Object o) {if (o != null) {for (Iterator<V> it = iterator(); it.hasNext();) {if (o.equals(it.next())) {it.remove();
return true;
}}}return false;
}public final Iterator<V> iterator() {ConcurrentHashMap<K,V> m = map;
Node<K,V>[] t;
int f = (t = m.table) == null ? 0 : t.length;
return new ValueIterator<K,V>(t, f, 0, f, m);
}public final boolean add(V e) {throw new UnsupportedOperationException();
}public final boolean addAll(Collection<? extends V> c) {throw new UnsupportedOperationException();
}public Spliterator<V> spliterator() {Node<K,V>[] t;
ConcurrentHashMap<K,V> m = map;
long n = m.sumCount();
int f = (t = m.table) == null ? 0 : t.length;
return new ValueSpliterator<K,V>(t, f, 0, f, n < 0L ? 0L : n);
}public void forEach(Consumer<? super V> action) {if (action == null) throw new NullPointerException();
Node<K,V>[] t;
if ((t = map.table) != null) {Traverser<K,V> it = new Traverser<K,V>(t, t.length, 0, t.length);
for (Node<K,V> p; (p = it.advance()) != null; )action.accept(p.val);
}}}/**
* A view of a ConcurrentHashMap as a {@link Set} of (key, value)
* entries. This class cannot be directly instantiated. See
* {@link #entrySet()}.
*/
static final class EntrySetView<K,V> extends CollectionView<K,V,Map.Entry<K,V>>implements Set<Map.Entry<K,V>>, java.io.Serializable {private static final long serialVersionUID = 2249069246763182397L;
EntrySetView(ConcurrentHashMap<K,V> map) { super(map); }public boolean contains(Object o) {Object k, v, r; Map.Entry<?,?> e;
return ((o instanceof Map.Entry) &&(k = (e = (Map.Entry<?,?>)o).getKey()) != null &&(r = map.get(k)) != null &&(v = e.getValue()) != null &&(v == r || v.equals(r)));
}public boolean remove(Object o) {Object k, v; Map.Entry<?,?> e;
return ((o instanceof Map.Entry) &&(k = (e = (Map.Entry<?,?>)o).getKey()) != null &&(v = e.getValue()) != null &&map.remove(k, v));
}/**
* @return an iterator over the entries of the backing map
*/
public Iterator<Map.Entry<K,V>> iterator() {ConcurrentHashMap<K,V> m = map;
Node<K,V>[] t;
int f = (t = m.table) == null ? 0 : t.length;
return new EntryIterator<K,V>(t, f, 0, f, m);
}public boolean add(Entry<K,V> e) {return map.putVal(e.getKey(), e.getValue(), false) == null;
}public boolean addAll(Collection<? extends Entry<K,V>> c) {boolean added = false;
for (Entry<K,V> e : c) {if (add(e))added = true;
}return added;
}public final int hashCode() {int h = 0;
Node<K,V>[] t;
if ((t = map.table) != null) {Traverser<K,V> it = new Traverser<K,V>(t, t.length, 0, t.length);
for (Node<K,V> p; (p = it.advance()) != null; ) {h += p.hashCode();
}}return h;
}public final boolean equals(Object o) {Set<?> c;
return ((o instanceof Set) &&((c = (Set<?>)o) == this ||(containsAll(c) && c.containsAll(this))));
}public Spliterator<Map.Entry<K,V>> spliterator() {Node<K,V>[] t;
ConcurrentHashMap<K,V> m = map;
long n = m.sumCount();
int f = (t = m.table) == null ? 0 : t.length;
return new EntrySpliterator<K,V>(t, f, 0, f, n < 0L ? 0L : n, m);
}public void forEach(Consumer<? super Map.Entry<K,V>> action) {if (action == null) throw new NullPointerException();
Node<K,V>[] t;
if ((t = map.table) != null) {Traverser<K,V> it = new Traverser<K,V>(t, t.length, 0, t.length);
for (Node<K,V> p; (p = it.advance()) != null; )action.accept(new MapEntry<K,V>(p.key, p.val, map));
}}}// -------------------------------------------------------
/**
* Base class for bulk tasks. Repeats some fields and code from
* class Traverser, because we need to subclass CountedCompleter.
*/
@SuppressWarnings("serial")abstract static class BulkTask<K,V,R> extends CountedCompleter<R> {Node<K,V>[] tab; // same as Traverser
Node<K,V> next;
TableStack<K,V> stack, spare;
int index;
int baseIndex;
int baseLimit;
final int baseSize;
int batch; // split control
BulkTask(BulkTask<K,V,?> par, int b, int i, int f, Node<K,V>[] t) {super(par);
this.batch = b;
this.index = this.baseIndex = i;
if ((this.tab = t) == null)this.baseSize = this.baseLimit = 0;
else if (par == null)this.baseSize = this.baseLimit = t.length;
else {this.baseLimit = f;
this.baseSize = par.baseSize;
}}/**
* Same as Traverser version
*/
final Node<K,V> advance() {Node<K,V> e;
if ((e = next) != null)e = e.next;
for (;;) {Node<K,V>[] t; int i, n;
if (e != null)return next = e;
if (baseIndex >= baseLimit || (t = tab) == null ||(n = t.length) <= (i = index) || i < 0)return next = null;
if ((e = tabAt(t, i)) != null && e.hash < 0) {if (e instanceof ForwardingNode) {tab = ((ForwardingNode<K,V>)e).nextTable;
e = null;
pushState(t, i, n);
continue;
}else if (e instanceof TreeBin)e = ((TreeBin<K,V>)e).first;
else
e = null;
}if (stack != null)recoverState(n);
else if ((index = i + baseSize) >= n)index = ++baseIndex;
}}private void pushState(Node<K,V>[] t, int i, int n) {TableStack<K,V> s = spare;
if (s != null)spare = s.next;
else
s = new TableStack<K,V>();
s.tab = t;
s.length = n;
s.index = i;
s.next = stack;
stack = s;
}private void recoverState(int n) {TableStack<K,V> s; int len;
while ((s = stack) != null && (index += (len = s.length)) >= n) {n = len;
index = s.index;
tab = s.tab;
s.tab = null;
TableStack<K,V> next = s.next;
s.next = spare; // save for reuse
stack = next;
spare = s;
}if (s == null && (index += baseSize) >= n)index = ++baseIndex;
}}/*
* Task classes. Coded in a regular but ugly format/style to
* simplify checks that each variant differs in the right way from
* others. The null screenings exist because compilers cannot tell
* that we've already null-checked task arguments, so we force
* simplest hoisted bypass to help avoid convoluted traps.
*/
@SuppressWarnings("serial")static final class ForEachKeyTask<K,V>extends BulkTask<K,V,Void> {final Consumer<? super K> action;
ForEachKeyTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
Consumer<? super K> action) {super(p, b, i, f, t);
this.action = action;
}public final void compute() {final Consumer<? super K> action;
if ((action = this.action) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
new ForEachKeyTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
action).fork();
}for (Node<K,V> p; (p = advance()) != null;)action.accept(p.key);
propagateCompletion();
}}}@SuppressWarnings("serial")static final class ForEachValueTask<K,V>extends BulkTask<K,V,Void> {final Consumer<? super V> action;
ForEachValueTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
Consumer<? super V> action) {super(p, b, i, f, t);
this.action = action;
}public final void compute() {final Consumer<? super V> action;
if ((action = this.action) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
new ForEachValueTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
action).fork();
}for (Node<K,V> p; (p = advance()) != null;)action.accept(p.val);
propagateCompletion();
}}}@SuppressWarnings("serial")static final class ForEachEntryTask<K,V>extends BulkTask<K,V,Void> {final Consumer<? super Entry<K,V>> action;
ForEachEntryTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
Consumer<? super Entry<K,V>> action) {super(p, b, i, f, t);
this.action = action;
}public final void compute() {final Consumer<? super Entry<K,V>> action;
if ((action = this.action) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
new ForEachEntryTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
action).fork();
}for (Node<K,V> p; (p = advance()) != null; )action.accept(p);
propagateCompletion();
}}}@SuppressWarnings("serial")static final class ForEachMappingTask<K,V>extends BulkTask<K,V,Void> {final BiConsumer<? super K, ? super V> action;
ForEachMappingTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
BiConsumer<? super K,? super V> action) {super(p, b, i, f, t);
this.action = action;
}public final void compute() {final BiConsumer<? super K, ? super V> action;
if ((action = this.action) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
new ForEachMappingTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
action).fork();
}for (Node<K,V> p; (p = advance()) != null; )action.accept(p.key, p.val);
propagateCompletion();
}}}@SuppressWarnings("serial")static final class ForEachTransformedKeyTask<K,V,U>extends BulkTask<K,V,Void> {final Function<? super K, ? extends U> transformer;
final Consumer<? super U> action;
ForEachTransformedKeyTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
Function<? super K, ? extends U> transformer, Consumer<? super U> action) {super(p, b, i, f, t);
this.transformer = transformer; this.action = action;
}public final void compute() {final Function<? super K, ? extends U> transformer;
final Consumer<? super U> action;
if ((transformer = this.transformer) != null &&(action = this.action) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
new ForEachTransformedKeyTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
transformer, action).fork();
}for (Node<K,V> p; (p = advance()) != null; ) {U u;
if ((u = transformer.apply(p.key)) != null)action.accept(u);
}propagateCompletion();
}}}@SuppressWarnings("serial")static final class ForEachTransformedValueTask<K,V,U>extends BulkTask<K,V,Void> {final Function<? super V, ? extends U> transformer;
final Consumer<? super U> action;
ForEachTransformedValueTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
Function<? super V, ? extends U> transformer, Consumer<? super U> action) {super(p, b, i, f, t);
this.transformer = transformer; this.action = action;
}public final void compute() {final Function<? super V, ? extends U> transformer;
final Consumer<? super U> action;
if ((transformer = this.transformer) != null &&(action = this.action) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
new ForEachTransformedValueTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
transformer, action).fork();
}for (Node<K,V> p; (p = advance()) != null; ) {U u;
if ((u = transformer.apply(p.val)) != null)action.accept(u);
}propagateCompletion();
}}}@SuppressWarnings("serial")static final class ForEachTransformedEntryTask<K,V,U>extends BulkTask<K,V,Void> {final Function<Map.Entry<K,V>, ? extends U> transformer;
final Consumer<? super U> action;
ForEachTransformedEntryTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
Function<Map.Entry<K,V>, ? extends U> transformer, Consumer<? super U> action) {super(p, b, i, f, t);
this.transformer = transformer; this.action = action;
}public final void compute() {final Function<Map.Entry<K,V>, ? extends U> transformer;
final Consumer<? super U> action;
if ((transformer = this.transformer) != null &&(action = this.action) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
new ForEachTransformedEntryTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
transformer, action).fork();
}for (Node<K,V> p; (p = advance()) != null; ) {U u;
if ((u = transformer.apply(p)) != null)action.accept(u);
}propagateCompletion();
}}}@SuppressWarnings("serial")static final class ForEachTransformedMappingTask<K,V,U>extends BulkTask<K,V,Void> {final BiFunction<? super K, ? super V, ? extends U> transformer;
final Consumer<? super U> action;
ForEachTransformedMappingTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
BiFunction<? super K, ? super V, ? extends U> transformer,
Consumer<? super U> action) {super(p, b, i, f, t);
this.transformer = transformer; this.action = action;
}public final void compute() {final BiFunction<? super K, ? super V, ? extends U> transformer;
final Consumer<? super U> action;
if ((transformer = this.transformer) != null &&(action = this.action) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
new ForEachTransformedMappingTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
transformer, action).fork();
}for (Node<K,V> p; (p = advance()) != null; ) {U u;
if ((u = transformer.apply(p.key, p.val)) != null)action.accept(u);
}propagateCompletion();
}}}@SuppressWarnings("serial")static final class SearchKeysTask<K,V,U>extends BulkTask<K,V,U> {final Function<? super K, ? extends U> searchFunction;
final AtomicReference<U> result;
SearchKeysTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
Function<? super K, ? extends U> searchFunction,
AtomicReference<U> result) {super(p, b, i, f, t);
this.searchFunction = searchFunction; this.result = result;
}public final U getRawResult() { return result.get(); }public final void compute() {final Function<? super K, ? extends U> searchFunction;
final AtomicReference<U> result;
if ((searchFunction = this.searchFunction) != null &&(result = this.result) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {if (result.get() != null)return;
addToPendingCount(1);
new SearchKeysTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
searchFunction, result).fork();
}while (result.get() == null) {U u;
Node<K,V> p;
if ((p = advance()) == null) {propagateCompletion();
break;
}if ((u = searchFunction.apply(p.key)) != null) {if (result.compareAndSet(null, u))quietlyCompleteRoot();
break;
}}}}}@SuppressWarnings("serial")static final class SearchValuesTask<K,V,U>extends BulkTask<K,V,U> {final Function<? super V, ? extends U> searchFunction;
final AtomicReference<U> result;
SearchValuesTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
Function<? super V, ? extends U> searchFunction,
AtomicReference<U> result) {super(p, b, i, f, t);
this.searchFunction = searchFunction; this.result = result;
}public final U getRawResult() { return result.get(); }public final void compute() {final Function<? super V, ? extends U> searchFunction;
final AtomicReference<U> result;
if ((searchFunction = this.searchFunction) != null &&(result = this.result) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {if (result.get() != null)return;
addToPendingCount(1);
new SearchValuesTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
searchFunction, result).fork();
}while (result.get() == null) {U u;
Node<K,V> p;
if ((p = advance()) == null) {propagateCompletion();
break;
}if ((u = searchFunction.apply(p.val)) != null) {if (result.compareAndSet(null, u))quietlyCompleteRoot();
break;
}}}}}@SuppressWarnings("serial")static final class SearchEntriesTask<K,V,U>extends BulkTask<K,V,U> {final Function<Entry<K,V>, ? extends U> searchFunction;
final AtomicReference<U> result;
SearchEntriesTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
Function<Entry<K,V>, ? extends U> searchFunction,
AtomicReference<U> result) {super(p, b, i, f, t);
this.searchFunction = searchFunction; this.result = result;
}public final U getRawResult() { return result.get(); }public final void compute() {final Function<Entry<K,V>, ? extends U> searchFunction;
final AtomicReference<U> result;
if ((searchFunction = this.searchFunction) != null &&(result = this.result) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {if (result.get() != null)return;
addToPendingCount(1);
new SearchEntriesTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
searchFunction, result).fork();
}while (result.get() == null) {U u;
Node<K,V> p;
if ((p = advance()) == null) {propagateCompletion();
break;
}if ((u = searchFunction.apply(p)) != null) {if (result.compareAndSet(null, u))quietlyCompleteRoot();
return;
}}}}}@SuppressWarnings("serial")static final class SearchMappingsTask<K,V,U>extends BulkTask<K,V,U> {final BiFunction<? super K, ? super V, ? extends U> searchFunction;
final AtomicReference<U> result;
SearchMappingsTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
BiFunction<? super K, ? super V, ? extends U> searchFunction,
AtomicReference<U> result) {super(p, b, i, f, t);
this.searchFunction = searchFunction; this.result = result;
}public final U getRawResult() { return result.get(); }public final void compute() {final BiFunction<? super K, ? super V, ? extends U> searchFunction;
final AtomicReference<U> result;
if ((searchFunction = this.searchFunction) != null &&(result = this.result) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {if (result.get() != null)return;
addToPendingCount(1);
new SearchMappingsTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
searchFunction, result).fork();
}while (result.get() == null) {U u;
Node<K,V> p;
if ((p = advance()) == null) {propagateCompletion();
break;
}if ((u = searchFunction.apply(p.key, p.val)) != null) {if (result.compareAndSet(null, u))quietlyCompleteRoot();
break;
}}}}}@SuppressWarnings("serial")static final class ReduceKeysTask<K,V>extends BulkTask<K,V,K> {final BiFunction<? super K, ? super K, ? extends K> reducer;
K result;
ReduceKeysTask<K,V> rights, nextRight;
ReduceKeysTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
ReduceKeysTask<K,V> nextRight,
BiFunction<? super K, ? super K, ? extends K> reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.reducer = reducer;
}public final K getRawResult() { return result; }public final void compute() {final BiFunction<? super K, ? super K, ? extends K> reducer;
if ((reducer = this.reducer) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new ReduceKeysTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, reducer)).fork();
}K r = null;
for (Node<K,V> p; (p = advance()) != null; ) {K u = p.key;
r = (r == null) ? u : u == null ? r : reducer.apply(r, u);
}result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")ReduceKeysTask<K,V>t = (ReduceKeysTask<K,V>)c,
s = t.rights;
while (s != null) {K tr, sr;
if ((sr = s.result) != null)t.result = (((tr = t.result) == null) ? sr :reducer.apply(tr, sr));
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class ReduceValuesTask<K,V>extends BulkTask<K,V,V> {final BiFunction<? super V, ? super V, ? extends V> reducer;
V result;
ReduceValuesTask<K,V> rights, nextRight;
ReduceValuesTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
ReduceValuesTask<K,V> nextRight,
BiFunction<? super V, ? super V, ? extends V> reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.reducer = reducer;
}public final V getRawResult() { return result; }public final void compute() {final BiFunction<? super V, ? super V, ? extends V> reducer;
if ((reducer = this.reducer) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new ReduceValuesTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, reducer)).fork();
}V r = null;
for (Node<K,V> p; (p = advance()) != null; ) {V v = p.val;
r = (r == null) ? v : reducer.apply(r, v);
}result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")ReduceValuesTask<K,V>t = (ReduceValuesTask<K,V>)c,
s = t.rights;
while (s != null) {V tr, sr;
if ((sr = s.result) != null)t.result = (((tr = t.result) == null) ? sr :reducer.apply(tr, sr));
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class ReduceEntriesTask<K,V>extends BulkTask<K,V,Map.Entry<K,V>> {final BiFunction<Map.Entry<K,V>, Map.Entry<K,V>, ? extends Map.Entry<K,V>> reducer;
Map.Entry<K,V> result;
ReduceEntriesTask<K,V> rights, nextRight;
ReduceEntriesTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
ReduceEntriesTask<K,V> nextRight,
BiFunction<Entry<K,V>, Map.Entry<K,V>, ? extends Map.Entry<K,V>> reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.reducer = reducer;
}public final Map.Entry<K,V> getRawResult() { return result; }public final void compute() {final BiFunction<Map.Entry<K,V>, Map.Entry<K,V>, ? extends Map.Entry<K,V>> reducer;
if ((reducer = this.reducer) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new ReduceEntriesTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, reducer)).fork();
}Map.Entry<K,V> r = null;
for (Node<K,V> p; (p = advance()) != null; )r = (r == null) ? p : reducer.apply(r, p);
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")ReduceEntriesTask<K,V>t = (ReduceEntriesTask<K,V>)c,
s = t.rights;
while (s != null) {Map.Entry<K,V> tr, sr;
if ((sr = s.result) != null)t.result = (((tr = t.result) == null) ? sr :reducer.apply(tr, sr));
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceKeysTask<K,V,U>extends BulkTask<K,V,U> {final Function<? super K, ? extends U> transformer;
final BiFunction<? super U, ? super U, ? extends U> reducer;
U result;
MapReduceKeysTask<K,V,U> rights, nextRight;
MapReduceKeysTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceKeysTask<K,V,U> nextRight,
Function<? super K, ? extends U> transformer,
BiFunction<? super U, ? super U, ? extends U> reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.reducer = reducer;
}public final U getRawResult() { return result; }public final void compute() {final Function<? super K, ? extends U> transformer;
final BiFunction<? super U, ? super U, ? extends U> reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceKeysTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, reducer)).fork();
}U r = null;
for (Node<K,V> p; (p = advance()) != null; ) {U u;
if ((u = transformer.apply(p.key)) != null)r = (r == null) ? u : reducer.apply(r, u);
}result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceKeysTask<K,V,U>t = (MapReduceKeysTask<K,V,U>)c,
s = t.rights;
while (s != null) {U tr, sr;
if ((sr = s.result) != null)t.result = (((tr = t.result) == null) ? sr :reducer.apply(tr, sr));
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceValuesTask<K,V,U>extends BulkTask<K,V,U> {final Function<? super V, ? extends U> transformer;
final BiFunction<? super U, ? super U, ? extends U> reducer;
U result;
MapReduceValuesTask<K,V,U> rights, nextRight;
MapReduceValuesTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceValuesTask<K,V,U> nextRight,
Function<? super V, ? extends U> transformer,
BiFunction<? super U, ? super U, ? extends U> reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.reducer = reducer;
}public final U getRawResult() { return result; }public final void compute() {final Function<? super V, ? extends U> transformer;
final BiFunction<? super U, ? super U, ? extends U> reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceValuesTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, reducer)).fork();
}U r = null;
for (Node<K,V> p; (p = advance()) != null; ) {U u;
if ((u = transformer.apply(p.val)) != null)r = (r == null) ? u : reducer.apply(r, u);
}result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceValuesTask<K,V,U>t = (MapReduceValuesTask<K,V,U>)c,
s = t.rights;
while (s != null) {U tr, sr;
if ((sr = s.result) != null)t.result = (((tr = t.result) == null) ? sr :reducer.apply(tr, sr));
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceEntriesTask<K,V,U>extends BulkTask<K,V,U> {final Function<Map.Entry<K,V>, ? extends U> transformer;
final BiFunction<? super U, ? super U, ? extends U> reducer;
U result;
MapReduceEntriesTask<K,V,U> rights, nextRight;
MapReduceEntriesTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceEntriesTask<K,V,U> nextRight,
Function<Map.Entry<K,V>, ? extends U> transformer,
BiFunction<? super U, ? super U, ? extends U> reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.reducer = reducer;
}public final U getRawResult() { return result; }public final void compute() {final Function<Map.Entry<K,V>, ? extends U> transformer;
final BiFunction<? super U, ? super U, ? extends U> reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceEntriesTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, reducer)).fork();
}U r = null;
for (Node<K,V> p; (p = advance()) != null; ) {U u;
if ((u = transformer.apply(p)) != null)r = (r == null) ? u : reducer.apply(r, u);
}result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceEntriesTask<K,V,U>t = (MapReduceEntriesTask<K,V,U>)c,
s = t.rights;
while (s != null) {U tr, sr;
if ((sr = s.result) != null)t.result = (((tr = t.result) == null) ? sr :reducer.apply(tr, sr));
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceMappingsTask<K,V,U>extends BulkTask<K,V,U> {final BiFunction<? super K, ? super V, ? extends U> transformer;
final BiFunction<? super U, ? super U, ? extends U> reducer;
U result;
MapReduceMappingsTask<K,V,U> rights, nextRight;
MapReduceMappingsTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceMappingsTask<K,V,U> nextRight,
BiFunction<? super K, ? super V, ? extends U> transformer,
BiFunction<? super U, ? super U, ? extends U> reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.reducer = reducer;
}public final U getRawResult() { return result; }public final void compute() {final BiFunction<? super K, ? super V, ? extends U> transformer;
final BiFunction<? super U, ? super U, ? extends U> reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceMappingsTask<K,V,U>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, reducer)).fork();
}U r = null;
for (Node<K,V> p; (p = advance()) != null; ) {U u;
if ((u = transformer.apply(p.key, p.val)) != null)r = (r == null) ? u : reducer.apply(r, u);
}result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceMappingsTask<K,V,U>t = (MapReduceMappingsTask<K,V,U>)c,
s = t.rights;
while (s != null) {U tr, sr;
if ((sr = s.result) != null)t.result = (((tr = t.result) == null) ? sr :reducer.apply(tr, sr));
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceKeysToDoubleTask<K,V>extends BulkTask<K,V,Double> {final ToDoubleFunction<? super K> transformer;
final DoubleBinaryOperator reducer;
final double basis;
double result;
MapReduceKeysToDoubleTask<K,V> rights, nextRight;
MapReduceKeysToDoubleTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceKeysToDoubleTask<K,V> nextRight,
ToDoubleFunction<? super K> transformer,
double basis,
DoubleBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Double getRawResult() { return result; }public final void compute() {final ToDoubleFunction<? super K> transformer;
final DoubleBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {double r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceKeysToDoubleTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsDouble(r, transformer.applyAsDouble(p.key));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceKeysToDoubleTask<K,V>t = (MapReduceKeysToDoubleTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsDouble(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceValuesToDoubleTask<K,V>extends BulkTask<K,V,Double> {final ToDoubleFunction<? super V> transformer;
final DoubleBinaryOperator reducer;
final double basis;
double result;
MapReduceValuesToDoubleTask<K,V> rights, nextRight;
MapReduceValuesToDoubleTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceValuesToDoubleTask<K,V> nextRight,
ToDoubleFunction<? super V> transformer,
double basis,
DoubleBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Double getRawResult() { return result; }public final void compute() {final ToDoubleFunction<? super V> transformer;
final DoubleBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {double r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceValuesToDoubleTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsDouble(r, transformer.applyAsDouble(p.val));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceValuesToDoubleTask<K,V>t = (MapReduceValuesToDoubleTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsDouble(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceEntriesToDoubleTask<K,V>extends BulkTask<K,V,Double> {final ToDoubleFunction<Map.Entry<K,V>> transformer;
final DoubleBinaryOperator reducer;
final double basis;
double result;
MapReduceEntriesToDoubleTask<K,V> rights, nextRight;
MapReduceEntriesToDoubleTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceEntriesToDoubleTask<K,V> nextRight,
ToDoubleFunction<Map.Entry<K,V>> transformer,
double basis,
DoubleBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Double getRawResult() { return result; }public final void compute() {final ToDoubleFunction<Map.Entry<K,V>> transformer;
final DoubleBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {double r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceEntriesToDoubleTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsDouble(r, transformer.applyAsDouble(p));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceEntriesToDoubleTask<K,V>t = (MapReduceEntriesToDoubleTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsDouble(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceMappingsToDoubleTask<K,V>extends BulkTask<K,V,Double> {final ToDoubleBiFunction<? super K, ? super V> transformer;
final DoubleBinaryOperator reducer;
final double basis;
double result;
MapReduceMappingsToDoubleTask<K,V> rights, nextRight;
MapReduceMappingsToDoubleTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceMappingsToDoubleTask<K,V> nextRight,
ToDoubleBiFunction<? super K, ? super V> transformer,
double basis,
DoubleBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Double getRawResult() { return result; }public final void compute() {final ToDoubleBiFunction<? super K, ? super V> transformer;
final DoubleBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {double r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceMappingsToDoubleTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsDouble(r, transformer.applyAsDouble(p.key, p.val));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceMappingsToDoubleTask<K,V>t = (MapReduceMappingsToDoubleTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsDouble(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceKeysToLongTask<K,V>extends BulkTask<K,V,Long> {final ToLongFunction<? super K> transformer;
final LongBinaryOperator reducer;
final long basis;
long result;
MapReduceKeysToLongTask<K,V> rights, nextRight;
MapReduceKeysToLongTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceKeysToLongTask<K,V> nextRight,
ToLongFunction<? super K> transformer,
long basis,
LongBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Long getRawResult() { return result; }public final void compute() {final ToLongFunction<? super K> transformer;
final LongBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {long r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceKeysToLongTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsLong(r, transformer.applyAsLong(p.key));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceKeysToLongTask<K,V>t = (MapReduceKeysToLongTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsLong(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceValuesToLongTask<K,V>extends BulkTask<K,V,Long> {final ToLongFunction<? super V> transformer;
final LongBinaryOperator reducer;
final long basis;
long result;
MapReduceValuesToLongTask<K,V> rights, nextRight;
MapReduceValuesToLongTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceValuesToLongTask<K,V> nextRight,
ToLongFunction<? super V> transformer,
long basis,
LongBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Long getRawResult() { return result; }public final void compute() {final ToLongFunction<? super V> transformer;
final LongBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {long r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceValuesToLongTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsLong(r, transformer.applyAsLong(p.val));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceValuesToLongTask<K,V>t = (MapReduceValuesToLongTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsLong(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceEntriesToLongTask<K,V>extends BulkTask<K,V,Long> {final ToLongFunction<Map.Entry<K,V>> transformer;
final LongBinaryOperator reducer;
final long basis;
long result;
MapReduceEntriesToLongTask<K,V> rights, nextRight;
MapReduceEntriesToLongTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceEntriesToLongTask<K,V> nextRight,
ToLongFunction<Map.Entry<K,V>> transformer,
long basis,
LongBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Long getRawResult() { return result; }public final void compute() {final ToLongFunction<Map.Entry<K,V>> transformer;
final LongBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {long r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceEntriesToLongTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsLong(r, transformer.applyAsLong(p));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceEntriesToLongTask<K,V>t = (MapReduceEntriesToLongTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsLong(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceMappingsToLongTask<K,V>extends BulkTask<K,V,Long> {final ToLongBiFunction<? super K, ? super V> transformer;
final LongBinaryOperator reducer;
final long basis;
long result;
MapReduceMappingsToLongTask<K,V> rights, nextRight;
MapReduceMappingsToLongTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceMappingsToLongTask<K,V> nextRight,
ToLongBiFunction<? super K, ? super V> transformer,
long basis,
LongBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Long getRawResult() { return result; }public final void compute() {final ToLongBiFunction<? super K, ? super V> transformer;
final LongBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {long r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceMappingsToLongTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsLong(r, transformer.applyAsLong(p.key, p.val));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceMappingsToLongTask<K,V>t = (MapReduceMappingsToLongTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsLong(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceKeysToIntTask<K,V>extends BulkTask<K,V,Integer> {final ToIntFunction<? super K> transformer;
final IntBinaryOperator reducer;
final int basis;
int result;
MapReduceKeysToIntTask<K,V> rights, nextRight;
MapReduceKeysToIntTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceKeysToIntTask<K,V> nextRight,
ToIntFunction<? super K> transformer,
int basis,
IntBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Integer getRawResult() { return result; }public final void compute() {final ToIntFunction<? super K> transformer;
final IntBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {int r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceKeysToIntTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsInt(r, transformer.applyAsInt(p.key));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceKeysToIntTask<K,V>t = (MapReduceKeysToIntTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsInt(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceValuesToIntTask<K,V>extends BulkTask<K,V,Integer> {final ToIntFunction<? super V> transformer;
final IntBinaryOperator reducer;
final int basis;
int result;
MapReduceValuesToIntTask<K,V> rights, nextRight;
MapReduceValuesToIntTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceValuesToIntTask<K,V> nextRight,
ToIntFunction<? super V> transformer,
int basis,
IntBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Integer getRawResult() { return result; }public final void compute() {final ToIntFunction<? super V> transformer;
final IntBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {int r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceValuesToIntTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsInt(r, transformer.applyAsInt(p.val));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceValuesToIntTask<K,V>t = (MapReduceValuesToIntTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsInt(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceEntriesToIntTask<K,V>extends BulkTask<K,V,Integer> {final ToIntFunction<Map.Entry<K,V>> transformer;
final IntBinaryOperator reducer;
final int basis;
int result;
MapReduceEntriesToIntTask<K,V> rights, nextRight;
MapReduceEntriesToIntTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceEntriesToIntTask<K,V> nextRight,
ToIntFunction<Map.Entry<K,V>> transformer,
int basis,
IntBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Integer getRawResult() { return result; }public final void compute() {final ToIntFunction<Map.Entry<K,V>> transformer;
final IntBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {int r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceEntriesToIntTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsInt(r, transformer.applyAsInt(p));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceEntriesToIntTask<K,V>t = (MapReduceEntriesToIntTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsInt(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}@SuppressWarnings("serial")static final class MapReduceMappingsToIntTask<K,V>extends BulkTask<K,V,Integer> {final ToIntBiFunction<? super K, ? super V> transformer;
final IntBinaryOperator reducer;
final int basis;
int result;
MapReduceMappingsToIntTask<K,V> rights, nextRight;
MapReduceMappingsToIntTask(BulkTask<K,V,?> p, int b, int i, int f, Node<K,V>[] t,
MapReduceMappingsToIntTask<K,V> nextRight,
ToIntBiFunction<? super K, ? super V> transformer,
int basis,
IntBinaryOperator reducer) {super(p, b, i, f, t); this.nextRight = nextRight;
this.transformer = transformer;
this.basis = basis; this.reducer = reducer;
}public final Integer getRawResult() { return result; }public final void compute() {final ToIntBiFunction<? super K, ? super V> transformer;
final IntBinaryOperator reducer;
if ((transformer = this.transformer) != null &&(reducer = this.reducer) != null) {int r = this.basis;
for (int i = baseIndex, f, h; batch > 0 &&(h = ((f = baseLimit) + i) >>> 1) > i;) {addToPendingCount(1);
(rights = new MapReduceMappingsToIntTask<K,V>(this, batch >>>= 1, baseLimit = h, f, tab,
rights, transformer, r, reducer)).fork();
}for (Node<K,V> p; (p = advance()) != null; )r = reducer.applyAsInt(r, transformer.applyAsInt(p.key, p.val));
result = r;
CountedCompleter<?> c;
for (c = firstComplete(); c != null; c = c.nextComplete()) {@SuppressWarnings("unchecked")MapReduceMappingsToIntTask<K,V>t = (MapReduceMappingsToIntTask<K,V>)c,
s = t.rights;
while (s != null) {t.result = reducer.applyAsInt(t.result, s.result);
s = t.rights = s.nextRight;
}}}}}// Unsafe mechanics
private static final sun.misc.Unsafe U;
private static final long SIZECTL;
private static final long TRANSFERINDEX;
private static final long BASECOUNT;
private static final long CELLSBUSY;
private static final long CELLVALUE;
private static final long ABASE;
private static final int ASHIFT;
static {try {U = sun.misc.Unsafe.getUnsafe();
Class<?> k = ConcurrentHashMap.class;
/**
* k.getDeclaredField获取到定义的字段的Field类型
* 然后交由objectFieldOffset获取到内存中的偏移量
*/
SIZECTL = U.objectFieldOffset(k.getDeclaredField("sizeCtl"));
TRANSFERINDEX = U.objectFieldOffset(k.getDeclaredField("transferIndex"));
BASECOUNT = U.objectFieldOffset(k.getDeclaredField("baseCount"));
CELLSBUSY = U.objectFieldOffset(k.getDeclaredField("cellsBusy"));
Class<?> ck = CounterCell.class;
CELLVALUE = U.objectFieldOffset(ck.getDeclaredField("value"));
Class<?> ak = Node[].class;
/**
* 获取数组第一个元素的偏移地址。
*/
ABASE = U.arrayBaseOffset(ak);
/**
* 获取数组第一个元素的大小
*/
int scale = U.arrayIndexScale(ak);
if ((scale & (scale - 1)) != 0)throw new Error("data type scale not a power of two");
/**
* Integer.numberOfLeadingZeros返回二进制中高处的0的个数
* 比如1的二进制前有31个0就返回31，2的二进制前有30个0返回30.
*/
/**
* 这里算出来数组中低位有几位，因为数组后面的元素肯定比第一个元素高，
* 所以index << ASHIFT即在第一个元素后面移index个位置
* 注意：数组中存放的Object是引用，所以假设存入的第一个元素很小，
* 其后存入某一个巨大的元素，那么依旧不会引起偏移量出错，因为存的是引用
*/
ASHIFT = 31 - Integer.numberOfLeadingZeros(scale);
} catch (Exception e) {throw new Error(e);
}}
}
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