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/*******************************************************************************
* ___ _ ____ ____
* / _ \ _ _ ___ ___| |_| _ \| __ )
* | | | | | | |/ _ \/ __| __| | | | _ \
* | |_| | |_| | __/\__ \ |_| |_| | |_) |
* \__\_\\__,_|\___||___/\__|____/|____/
*
* Copyright (c) 2014-2019 Appsicle
* Copyright (c) 2019-2024 QuestDB
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*
******************************************************************************/
package io.questdb.std;
/*
* ORACLE PROPRIETARY/CONFIDENTIAL. Use is subject to license terms.
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*
*/
/*
*
*
*
*
*
* Written by Doug Lea with assistance from members of JCP JSR-166
* Expert Group and released to the public domain, as explained at
* http://creativecommons.org/publicdomain/zero/1.0/
*/
import org.jetbrains.annotations.NotNull;
import java.io.ObjectStreamField;
import java.io.Serializable;
import java.lang.ThreadLocal;
import java.lang.reflect.ParameterizedType;
import java.lang.reflect.Type;
import java.util.Arrays;
import java.util.Collection;
import java.util.Iterator;
import java.util.Map;
import java.util.NoSuchElementException;
import java.util.Set;
import java.util.concurrent.atomic.AtomicInteger;
import java.util.concurrent.atomic.AtomicLong;
import java.util.concurrent.locks.LockSupport;
import java.util.concurrent.locks.ReentrantLock;
import java.util.function.LongFunction;
/**
* Same as {@link ConcurrentHashMap}, but with primitive type long keys.
*/
@SuppressWarnings("SynchronizationOnLocalVariableOrMethodParameter")
public class ConcurrentLongHashMap implements Serializable {
static final long EMPTY_KEY = Long.MIN_VALUE;
/*
* 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 referring 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 -------------- */
static final int HASH_BITS = 0x7fffffff; // usable bits of normal node hash
/**
* 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 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;
/*
* Encodings for Node hash fields. See above for explanation.
*/
static final int MOVED = -1; // hash for forwarding nodes
/**
* Number of CPUS, to place bounds on some sizings
*/
static final int NCPU = Runtime.getRuntime().availableProcessors();
static final int RESERVED = -3; // hash for transient reservations
static final int TREEBIN = -2; // hash for roots of trees
/**
* 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;
/* ---------------- Fields -------------- */
private static final long ABASE;
private static final int ASHIFT;
/*
* 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.
*/
private static final long BASECOUNT;
private static final long CELLSBUSY;
private static final long CELLVALUE;
/**
* The default initial table capacity. Must be a power of 2
* (i.e., at least 1) and at most MAXIMUM_CAPACITY.
*/
private static final int DEFAULT_CAPACITY = 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 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;
/**
* 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.
*/
private static final int MIN_TRANSFER_STRIDE = 16;
private static final long PROBE;
/* ---------------- Nodes -------------- */
/**
* The increment for generating probe values
*/
private static final int PROBE_INCREMENT = 0x9e3779b9;
/* ---------------- Static utilities -------------- */
/**
* The number of bits used for generation stamp in sizeCtl.
* Must be at least 6 for 32bit arrays.
*/
private static final 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;
private static final long SEED;
/* ---------------- Table element access -------------- */
/**
* The increment of seeder per new instance
*/
private static final long SEEDER_INCREMENT = 0xbb67ae8584caa73bL;
private static final long SIZECTL;
private static final long TRANSFERINDEX;
/**
* Generates per-thread initialization/probe field
*/
private static final AtomicInteger probeGenerator = new AtomicInteger();
/**
* The next seed for default constructors.
*/
private static final AtomicLong seeder = new AtomicLong(initialSeed());
/**
* For serialization compatibility.
*/
private static final ObjectStreamField[] serialPersistentFields = {
new ObjectStreamField("segments", Segment[].class),
new ObjectStreamField("segmentMask", Integer.TYPE),
new ObjectStreamField("segmentShift", Integer.TYPE)
};
private static final long serialVersionUID = 7249069246763182397L;
private final java.lang.ThreadLocal> tlTraverser = ThreadLocal.withInitial(Traverser::new);
/**
* The array of bins. Lazily initialized upon first insertion.
* Size is always a power of two. Accessed directly by iterators.
*/
transient volatile Node[] table;
/**
* Base counter value, used mainly when there is no contention,
* but also as a fallback during table initialization
* races. Updated via CAS.
*/
private transient volatile long baseCount;
/**
* Spinlock (locked via CAS) used when resizing and/or creating CounterCells.
*/
private transient volatile int cellsBusy;
/**
* Table of counter cells. When non-null, size is a power of 2.
*/
private transient volatile CounterCell[] counterCells;
// Original (since JDK1.2) Map methods
private transient EntrySetView entrySet;
/* ---------------- Public operations -------------- */
// views
private transient KeySetView keySet;
/**
* The next table to use; non-null only while resizing.
*/
private transient volatile Node[] nextTable;
/**
* 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.
*/
private transient volatile int sizeCtl;
/**
* The next table index (plus one) to split while resizing.
*/
private transient volatile int transferIndex;
private transient ValuesView values;
/**
* 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
* @throws IllegalArgumentException if the initial capacity is
* negative or the load factor or concurrencyLevel are
* nonpositive
*/
public ConcurrentLongHashMap(int initialCapacity, float loadFactor) {
if (!(loadFactor > 0.0f) || initialCapacity < 0)
throw new IllegalArgumentException();
if (initialCapacity < 1) // Use at least as many bins
initialCapacity = 1; // as estimated threads
long size = (long) (1.0 + (long) initialCapacity / loadFactor);
this.sizeCtl = (size >= (long) MAXIMUM_CAPACITY) ?
MAXIMUM_CAPACITY : tableSizeFor((int) size);
}
/**
* Creates a new map with the same mappings as the given map.
*
* @param m the map
*/
public ConcurrentLongHashMap(ConcurrentLongHashMap extends V> m) {
this.sizeCtl = DEFAULT_CAPACITY;
putAll(m);
}
/**
* Creates a new, empty map with the default initial table size (16).
*/
public ConcurrentLongHashMap() {
}
/**
* 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 ConcurrentLongHashMap(int initialCapacity) {
if (initialCapacity < 0)
throw new IllegalArgumentException();
this.sizeCtl = ((initialCapacity >= (MAXIMUM_CAPACITY >>> 1)) ?
MAXIMUM_CAPACITY :
tableSizeFor(initialCapacity + (initialCapacity >>> 1) + 1));
}
/**
* Creates a new {@link Set} backed by a ConcurrentLongHashMap
* from the given type to {@code Boolean.TRUE}.
*
* @return the new set
* @since 1.8
*/
public static KeySetView newKeySet() {
return new KeySetView<>(new ConcurrentLongHashMap<>(), Boolean.TRUE);
}
/**
* Creates a new {@link Set} backed by a ConcurrentLongHashMap
* from the given type to {@code Boolean.TRUE}.
*
* @param initialCapacity The implementation performs internal
* sizing to accommodate this many elements.
* @return the new set
* @throws IllegalArgumentException if the initial capacity of
* elements is negative
* @since 1.8
*/
public static KeySetView newKeySet(int initialCapacity) {
return new KeySetView<>(new ConcurrentLongHashMap<>(initialCapacity), Boolean.TRUE);
}
/**
* Removes all of the mappings from this map.
*/
public void clear() {
long delta = 0L; // negative number of deletions
int i = 0;
Node[] tab = table;
while (tab != null && i < tab.length) {
int fh;
Node 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 p = (fh >= 0 ? f :
(f instanceof TreeBin) ?
((TreeBin) f).first : null);
while (p != null) {
--delta;
p = p.next;
}
setTabAt(tab, i++, null);
}
}
}
}
if (delta != 0L)
addCount(delta, -1);
}
/**
* 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 IllegalArgumentException if the specified key is negative
* @throws NullPointerException if the specified 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(long key, BiLongFunction super V, ? extends V> remappingFunction) {
if (key < 0)
throw new IllegalArgumentException();
if (remappingFunction == null)
throw new NullPointerException();
int h = spread(keyHashCode(key));
V val = null;
int delta = 0;
int binCount = 0;
for (Node[] tab = table; ; ) {
Node 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 r = new ReservationNode<>();
synchronized (r) {
if (casTabAt(tab, i, r)) {
binCount = 1;
Node node = null;
try {
if ((val = remappingFunction.apply(key, null)) != null) {
delta = 1;
node = new Node<>(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 e = f, pred = null; ; ++binCount) {
if (e.hash == h && (e.key == key)) {
val = remappingFunction.apply(key, e.val);
if (val != null)
e.val = val;
else {
delta = -1;
Node 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<>(h, key, val, null);
}
break;
}
}
} else if (f instanceof TreeBin) {
binCount = 1;
TreeBin t = (TreeBin) f;
TreeNode r, p;
if ((r = t.root) != null)
p = r.findTreeNode(h, key);
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(delta, binCount);
return val;
}
/**
* 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 token token to pass to the mapping function
* @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 IllegalArgumentException if the specified key is negative
* @throws NullPointerException if the specified 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(long key, Object token, BiLongFunction