title: 跳錶在手天下我有之ConcurrentSkipListMap tags:
- SkipList
- 跳錶
- JUC
- Concurrent
- ConcurrentSkipList categories: juc date: 2017-10-27 16:19:19
背景
Jdk給我們提供了大量的map來供我們研發使用。通常情況下我們使用HashMap
需要插入順序或者訪問我們可以使用LinkedHashMap 需要排序我們可以使用TreeMap
併發場景下我們可以使用ConcurrentSkipListMap
介紹
跳錶這種資料結構相對來說大家都比較陌生，大學裡面基本也沒有相關的資料結構老師教過。
對於常見的資料結構 大家最熟悉的就是陣列和連結串列 基本上增刪改查不在話下
而對於其他的資料結構 比如二叉樹 平衡樹 紅黑樹 2-3樹 等等可能就沒那麼容易了
相比較其他資料結構的難度 跳錶這種就相對十分容易實現了。講真話其他的資料結構一般業務程式設計師不用搜尋引擎不翻書基本都會翻車。
初次接觸該資料結構是在使用redis中後期在LevelDB的使用中也接觸到了該資料結構。
SkipList顧名思義還是和List有關
一個簡單的連結串列是這樣的
那麼跳錶大概是長這樣的
其抽象出來的模型應該如圖
跳錶具有如下性質：
(1) 由很多層結構組成
(2) 每一層都是一個有序的連結串列
(3) 最底層(Level 1)的連結串列包含所有元素
(4) 如果一個元素出現在 Level i 的連結串列中，則它在 Level i 之下的連結串列也都會出現。
(5) 每個節點包含兩個指標，一個指向同一連結串列中的下一個元素，一個指向下面一層的元素。
原始碼
慣例先上類圖
類圖
/*
* This class implements a tree-like two-dimensionally linked skip
* list in which the index levels are represented in separate
* nodes from the base nodes holding data. There are two reasons
* for taking this approach instead of the usual array-based
* structure: 1) Array based implementations seem to encounter
* more complexity and overhead 2) We can use cheaper algorithms
* for the heavily-traversed index lists than can be used for the
* base lists. Here's a picture of some of the basics for a
* possible list with 2 levels of index:
*
* Head nodes Index nodes
* +-+ right +-+ +-+
* |2|---------------->| |--------------------->| |->null
* +-+ +-+ +-+
* | down | |
* v v v
* +-+ +-+ +-+ +-+ +-+ +-+
* |1|----------->| |->| |------>| |----------->| |------>| |->null
* +-+ +-+ +-+ +-+ +-+ +-+
* v | | | | |
* Nodes next v v v v v
* +-+ +-+ +-+ +-+ +-+ +-+ +-+ +-+ +-+ +-+ +-+ +-+
* | |->|A|->|B|->|C|->|D|->|E|->|F|->|G|->|H|->|I|->|J|->|K|->null
* +-+ +-+ +-+ +-+ +-+ +-+ +-+ +-+ +-+ +-+ +-+ +-+
*
* The base lists use a variant of the HM linked ordered set
* algorithm. See Tim Harris, "A pragmatic implementation of
* non-blocking linked lists"
* http://www.cl.cam.ac.uk/~tlh20/publications.html and Maged
* Michael "High Performance Dynamic Lock-Free Hash Tables and
* List-Based Sets"
* http://www.research.ibm.com/people/m/michael/pubs.htm. The
* basic idea in these lists is to mark the "next" pointers of
* deleted nodes when deleting to avoid conflicts with concurrent
* insertions, and when traversing to keep track of triples
* (predecessor, node, successor) in order to detect when and how
* to unlink these deleted nodes.
*
* Rather than using mark-bits to mark list deletions (which can
* be slow and space-intensive using AtomicMarkedReference), nodes
* use direct CAS'able next pointers. On deletion, instead of
* marking a pointer, they splice in another node that can be
* thought of as standing for a marked pointer (indicating this by
* using otherwise impossible field values). Using plain nodes
* acts roughly like "boxed" implementations of marked pointers,
* but uses new nodes only when nodes are deleted, not for every
* link. This requires less space and supports faster
* traversal. Even if marked references were better supported by
* JVMs, traversal using this technique might still be faster
* because any search need only read ahead one more node than
* otherwise required (to check for trailing marker) rather than
* unmasking mark bits or whatever on each read.
*
* This approach maintains the essential property needed in the HM
* algorithm of changing the next-pointer of a deleted node so
* that any other CAS of it will fail, but implements the idea by
* changing the pointer to point to a different node, not by
* marking it. While it would be possible to further squeeze
* space by defining marker nodes not to have key/value fields, it
* isn't worth the extra type-testing overhead. The deletion
* markers are rarely encountered during traversal and are
* normally quickly garbage collected. (Note that this technique
* would not work well in systems without garbage collection.)
*
* In addition to using deletion markers, the lists also use
* nullness of value fields to indicate deletion, in a style
* similar to typical lazy-deletion schemes. If a node's value is
* null, then it is considered logically deleted and ignored even
* though it is still reachable. This maintains proper control of
* concurrent replace vs delete operations -- an attempted replace
* must fail if a delete beat it by nulling field, and a delete
* must return the last non-null value held in the field. (Note:
* Null, rather than some special marker, is used for value fields
* here because it just so happens to mesh with the Map API
* requirement that method get returns null if there is no
* mapping, which allows nodes to remain concurrently readable
* even when deleted. Using any other marker value here would be
* messy at best.)
*
* Here's the sequence of events for a deletion of node n with
* predecessor b and successor f, initially:
*
* +------+ +------+ +------+
* ... | b |------>| n |----->| f | ...
* +------+ +------+ +------+
*
* 1. CAS n's value field from non-null to null.
* From this point on, no public operations encountering
* the node consider this mapping to exist. However, other
* ongoing insertions and deletions might still modify
* n's next pointer.
*
* 2. CAS n's next pointer to point to a new marker node.
* From this point on, no other nodes can be appended to n.
* which avoids deletion errors in CAS-based linked lists.
*
* +------+ +------+ +------+ +------+
* ... | b |------>| n |----->|marker|------>| f | ...
* +------+ +------+ +------+ +------+
*
* 3. CAS b's next pointer over both n and its marker.
* From this point on, no new traversals will encounter n,
* and it can eventually be GCed.
* +------+ +------+
* ... | b |----------------------------------->| f | ...
* +------+ +------+
*
* A failure at step 1 leads to simple retry due to a lost race
* with another operation. Steps 2-3 can fail because some other
* thread noticed during a traversal a node with null value and
* helped out by marking and/or unlinking. This helping-out
* ensures that no thread can become stuck waiting for progress of
* the deleting thread. The use of marker nodes slightly
* complicates helping-out code because traversals must track
* consistent reads of up to four nodes (b, n, marker, f), not
* just (b, n, f), although the next field of a marker is
* immutable, and once a next field is CAS'ed to point to a
* marker, it never again changes, so this requires less care.
*
* Skip lists add indexing to this scheme, so that the base-level
* traversals start close to the locations being found, inserted
* or deleted -- usually base level traversals only traverse a few
* nodes. This doesn't change the basic algorithm except for the
* need to make sure base traversals start at predecessors (here,
* b) that are not (structurally) deleted, otherwise retrying
* after processing the deletion.
*
* Index levels are maintained as lists with volatile next fields,
* using CAS to link and unlink. Races are allowed in index-list
* operations that can (rarely) fail to link in a new index node
* or delete one. (We can't do this of course for data nodes.)
* However, even when this happens, the index lists remain sorted,
* so correctly serve as indices. This can impact performance,
* but since skip lists are probabilistic anyway, the net result
* is that under contention, the effective "p" value may be lower
* than its nominal value. And race windows are kept small enough
* that in practice these failures are rare, even under a lot of
* contention.
*
* The fact that retries (for both base and index lists) are
* relatively cheap due to indexing allows some minor
* simplifications of retry logic. Traversal restarts are
* performed after most "helping-out" CASes. This isn't always
* strictly necessary, but the implicit backoffs tend to help
* reduce other downstream failed CAS's enough to outweigh restart
* cost. This worsens the worst case, but seems to improve even
* highly contended cases.
*
* Unlike most skip-list implementations, index insertion and
* deletion here require a separate traversal pass occuring after
* the base-level action, to add or remove index nodes. This adds
* to single-threaded overhead, but improves contended
* multithreaded performance by narrowing interference windows,
* and allows deletion to ensure that all index nodes will be made
* unreachable upon return from a public remove operation, thus
* avoiding unwanted garbage retention. This is more important
* here than in some other data structures because we cannot null
* out node fields referencing user keys since they might still be
* read by other ongoing traversals.
*
* Indexing uses skip list parameters that maintain good search
* performance while using sparser-than-usual indices: The
* hardwired parameters k=1, p=0.5 (see method randomLevel) mean
* that about one-quarter of the nodes have indices. Of those that
* do, half have one level, a quarter have two, and so on (see
* Pugh's Skip List Cookbook, sec 3.4). The expected total space
* requirement for a map is slightly less than for the current
* implementation of java.util.TreeMap.
*
* Changing the level of the index (i.e, the height of the
* tree-like structure) also uses CAS. The head index has initial
* level/height of one. Creation of an index with height greater
* than the current level adds a level to the head index by
* CAS'ing on a new top-most head. To maintain good performance
* after a lot of removals, deletion methods heuristically try to
* reduce the height if the topmost levels appear to be empty.
* This may encounter races in which it possible (but rare) to
* reduce and "lose" a level just as it is about to contain an
* index (that will then never be encountered). This does no
* structural harm, and in practice appears to be a better option
* than allowing unrestrained growth of levels.
*
* The code for all this is more verbose than you'd like. Most
* operations entail locating an element (or position to insert an
* element). The code to do this can't be nicely factored out
* because subsequent uses require a snapshot of predecessor
* and/or successor and/or value fields which can't be returned
* all at once, at least not without creating yet another object
* to hold them -- creating such little objects is an especially
* bad idea for basic internal search operations because it adds
* to GC overhead. (This is one of the few times I've wished Java
* had macros.) Instead, some traversal code is interleaved within
* insertion and removal operations. The control logic to handle
* all the retry conditions is sometimes twisty. Most search is
* broken into 2 parts. findPredecessor() searches index nodes
* only, returning a base-level predecessor of the key. findNode()
* finishes out the base-level search. Even with this factoring,
* there is a fair amount of near-duplication of code to handle
* variants.
*
* For explanation of algorithms sharing at least a couple of
* features with this one, see Mikhail Fomitchev's thesis
* (http://www.cs.yorku.ca/~mikhail/), Keir Fraser's thesis
* (http://www.cl.cam.ac.uk/users/kaf24/), and Hakan Sundell's
* thesis (http://www.cs.chalmers.se/~phs/).
*
* Given the use of tree-like index nodes, you might wonder why
* this doesn't use some kind of search tree instead, which would
* support somewhat faster search operations. The reason is that
* there are no known efficient lock-free insertion and deletion
* algorithms for search trees. The immutability of the "down"
* links of index nodes (as opposed to mutable "left" fields in
* true trees) makes this tractable using only CAS operations.
*
* Notation guide for local variables
* Node: b, n, f for predecessor, node, successor
* Index: q, r, d for index node, right, down.
* t for another index node
* Head: h
* Levels: j
* Keys: k, key
* Values: v, value
* Comparisons: c
*/
複製程式碼一段很有意思的註釋詳細說明了skipList的原理
建構函式
/**
* Constructs a new, empty map, sorted according to the
* {@linkplain Comparable natural ordering} of the keys.
*/
public ConcurrentSkipListMap() {
this.comparator = null;
initialize();
}
/**
* Constructs a new, empty map, sorted according to the specified
* comparator.
*
* @param comparator the comparator that will be used to order this map.
* If <tt>null</tt>, the {@linkplain Comparable natural
* ordering} of the keys will be used.
*/
public ConcurrentSkipListMap(Comparator<? super K> comparator) {
this.comparator = comparator;
initialize();
}
/**
* Constructs a new map containing the same mappings as the given map,
* sorted according to the {@linkplain Comparable natural ordering} of
* the keys.
*
* @param m the map whose mappings are to be placed in this map
* @throws ClassCastException if the keys in <tt>m</tt> are not
* {@link Comparable}, or are not mutually comparable
* @throws NullPointerException if the specified map or any of its keys
* or values are null
*/
public ConcurrentSkipListMap(Map<? extends K, ? extends V> m) {
this.comparator = null;
initialize();
putAll(m);
}
/**
* Constructs a new map containing the same mappings and using the
* same ordering as the specified sorted map.
*
* @param m the sorted map whose mappings are to be placed in this
* map, and whose comparator is to be used to sort this map
* @throws NullPointerException if the specified sorted map or any of
* its keys or values are null
*/
public ConcurrentSkipListMap(SortedMap<K, ? extends V> m) {
this.comparator = m.comparator();
initialize();
buildFromSorted(m);
}
複製程式碼事實上都會執行initialize來進行初始化
/**
* Initializes or resets state. Needed by constructors, clone,
* clear, readObject. and ConcurrentSkipListSet.clone.
* (Note that comparator must be separately initialized.)
*/
final void initialize() {
keySet = null;
entrySet = null;
values = null;
descendingMap = null;
randomSeed = seedGenerator.nextInt() | 0x0100; // ensure nonzero
head = new HeadIndex<K,V>(new Node<K,V>(null, BASE_HEADER, null),
null, null, 1);
}
複製程式碼初始化了頭結點
/**
* The topmost head index of the skiplist.
*/
private transient volatile HeadIndex<K,V> head;
複製程式碼需要注意的是都是用了volatile關鍵字【happen-before】這邊涉及到Java記憶體模型可以後再詳細描述（只需要記得該關鍵字修飾的變數在任何執行緒修改完之後其他執行緒都能like讀到最新的值並且禁止了指令重排序）
首先需要介紹三個內部類
Node
/**
* Nodes hold keys and values, and are singly linked in sorted
* order, possibly with some intervening marker nodes. The list is
* headed by a dummy node accessible as head.node. The value field
* is declared only as Object because it takes special non-V
* values for marker and header nodes.
*/
static final class Node<K,V> {
final K key;
volatile Object value;
volatile Node<K,V> next;
/**
* Creates a new regular node.
*/
Node(K key, Object value, Node<K,V> next) {
this.key = key;
this.value = value;
this.next = next;
}
/**
* Creates a new marker node. A marker is distinguished by
* having its value field point to itself. Marker nodes also
* have null keys, a fact that is exploited in a few places,
* but this doesn't distinguish markers from the base-level
* header node (head.node), which also has a null key.
*/
Node(Node<K,V> next) {
this.key = null;
this.value = this;
this.next = next;
}
/**
* compareAndSet value field
*/
boolean casValue(Object cmp, Object val) {
return UNSAFE.compareAndSwapObject(this, valueOffset, cmp, val);
}
/**
* compareAndSet next field
*/
boolean casNext(Node<K,V> cmp, Node<K,V> val) {
return UNSAFE.compareAndSwapObject(this, nextOffset, cmp, val);
}
/**
* Returns true if this node is a marker. This method isn't
* actually called in any current code checking for markers
* because callers will have already read value field and need
* to use that read (not another done here) and so directly
* test if value points to node.
* @param n a possibly null reference to a node
* @return true if this node is a marker node
*/
boolean isMarker() {
return value == this;
}
/**
* Returns true if this node is the header of base-level list.
* @return true if this node is header node
*/
boolean isBaseHeader() {
return value == BASE_HEADER;
}
/**
* Tries to append a deletion marker to this node.
* @param f the assumed current successor of this node
* @return true if successful
*/
boolean appendMarker(Node<K,V> f) {
return casNext(f, new Node<K,V>(f));
}
/**
* Helps out a deletion by appending marker or unlinking from
* predecessor. This is called during traversals when value
* field seen to be null.
* @param b predecessor
* @param f successor
*/
void helpDelete(Node<K,V> b, Node<K,V> f) {
/*
* Rechecking links and then doing only one of the
* help-out stages per call tends to minimize CAS
* interference among helping threads.
*/
if (f == next && this == b.next) {
if (f == null || f.value != f) // not already marked
appendMarker(f);
else
b.casNext(this, f.next);
}
}
/**
* Returns value if this node contains a valid key-value pair,
* else null.
* @return this node's value if it isn't a marker or header or
* is deleted, else null.
*/
V getValidValue() {
Object v = value;
if (v == this || v == BASE_HEADER)
return null;
return (V)v;
}
/**
* Creates and returns a new SimpleImmutableEntry holding current
* mapping if this node holds a valid value, else null.
* @return new entry or null
*/
AbstractMap.SimpleImmutableEntry<K,V> createSnapshot() {
V v = getValidValue();
if (v == null)
return null;
return new AbstractMap.SimpleImmutableEntry<K,V>(key, v);
}
// UNSAFE mechanics
private static final sun.misc.Unsafe UNSAFE;
private static final long valueOffset;
private static final long nextOffset;
static {
try {
UNSAFE = sun.misc.Unsafe.getUnsafe();
Class k = Node.class;
valueOffset = UNSAFE.objectFieldOffset
(k.getDeclaredField("value"));
nextOffset = UNSAFE.objectFieldOffset
(k.getDeclaredField("next"));
} catch (Exception e) {
throw new Error(e);
}
}
}
複製程式碼用來儲存KV同時提供了無鎖化的cas設定對應域的方法
Index
/* ---------------- Indexing -------------- */
/**
* Index nodes represent the levels of the skip list. Note that
* even though both Nodes and Indexes have forward-pointing
* fields, they have different types and are handled in different
* ways, that can't nicely be captured by placing field in a
* shared abstract class.
*/
static class Index<K,V> {
final Node<K,V> node;
final Index<K,V> down;
volatile Index<K,V> right;
/**
* Creates index node with given values.
*/
Index(Node<K,V> node, Index<K,V> down, Index<K,V> right) {
this.node = node;
this.down = down;
this.right = right;
}
/**
* compareAndSet right field
*/
final boolean casRight(Index<K,V> cmp, Index<K,V> val) {
return UNSAFE.compareAndSwapObject(this, rightOffset, cmp, val);
}
/**
* Returns true if the node this indexes has been deleted.
* @return true if indexed node is known to be deleted
*/
final boolean indexesDeletedNode() {
return node.value == null;
}
/**
* Tries to CAS newSucc as successor. To minimize races with
* unlink that may lose this index node, if the node being
* indexed is known to be deleted, it doesn't try to link in.
* @param succ the expected current successor
* @param newSucc the new successor
* @return true if successful
*/
final boolean link(Index<K,V> succ, Index<K,V> newSucc) {
Node<K,V> n = node;
newSucc.right = succ;
return n.value != null && casRight(succ, newSucc);
}
/**
* Tries to CAS right field to skip over apparent successor
* succ. Fails (forcing a retraversal by caller) if this node
* is known to be deleted.
* @param succ the expected current successor
* @return true if successful
*/
final boolean unlink(Index<K,V> succ) {
return !indexesDeletedNode() && casRight(succ, succ.right);
}
// Unsafe mechanics
private static final sun.misc.Unsafe UNSAFE;
private static final long rightOffset;
static {
try {
UNSAFE = sun.misc.Unsafe.getUnsafe();
Class k = Index.class;
rightOffset = UNSAFE.objectFieldOffset
(k.getDeclaredField("right"));
} catch (Exception e) {
throw new Error(e);
}
}
}
複製程式碼Index提供了右和下的索引 當然其包含了對應的Node節點
其中有兩個方法需要特別說明
link
在當前節點右邊連線新的索引通過cas方法將當前節點的右索引連線到新索引的右索引【理解成帶鎖的插入即可】
unLink
將當前的節點有右連線cas換成右連線的有連結【如果當前節點的右連線不為空】【理解成帶鎖的刪除即可】
HeadIndex
/* ---------------- Head nodes -------------- */
/**
* Nodes heading each level keep track of their level.
*/
static final class HeadIndex<K,V> extends Index<K,V> {
final int level;
HeadIndex(Node<K,V> node, Index<K,V> down, Index<K,V> right, int level) {
super(node, down, right);
this.level = level;
}
}
複製程式碼HeadIndex除了右和下連線還提供了level域這個表明當前層級
複製程式碼put
/**
* Associates the specified value with the specified key in this map.
* If the map previously contained a mapping for the key, the old
* value is replaced.
*
* @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 the specified key, or
* <tt>null</tt> if there was no mapping for the key
* @throws ClassCastException if the specified key cannot be compared
* with the keys currently in the map
* @throws NullPointerException if the specified key or value is null
*/
public V put(K key, V value) {
if (value == null)
throw new NullPointerException();
return doPut(key, value, false);
}
/**
* Main insertion method. Adds element if not present, or
* replaces value if present and onlyIfAbsent is false.
* @param kkey the key
* @param value the value that must be associated with key
* @param onlyIfAbsent if should not insert if already present
* @return the old value, or null if newly inserted
*/
private V doPut(K kkey, V value, boolean onlyIfAbsent) {
Comparable<? super K> key = comparable(kkey);
for (;;) {
Node<K,V> b = findPredecessor(key);
Node<K,V> n = b.next;
for (;;) {
if (n != null) {
Node<K,V> f = n.next;
if (n != b.next) // inconsistent read
break;
Object v = n.value;
if (v == null) { // n is deleted
n.helpDelete(b, f);
break;
}
if (v == n || b.value == null) // b is deleted
break;
int c = key.compareTo(n.key);
if (c > 0) {
b = n;
n = f;
continue;
}
if (c == 0) {
if (onlyIfAbsent || n.casValue(v, value))
return (V)v;
else
break; // restart if lost race to replace value
}
// else c < 0; fall through
}
Node<K,V> z = new Node<K,V>(kkey, value, n);
if (!b.casNext(n, z))
break; // restart if lost race to append to b
int level = randomLevel();
if (level > 0)
insertIndex(z, level);
return null;
}
}
}
/**
* If using comparator, return a ComparableUsingComparator, else
* cast key as Comparable, which may cause ClassCastException,
* which is propagated back to caller.
*/
private Comparable<? super K> comparable(Object key)
throws ClassCastException {
if (key == null)
throw new NullPointerException();
if (comparator != null)
return new ComparableUsingComparator<K>((K)key, comparator);
else
return (Comparable<? super K>)key;
}
複製程式碼從上述程式碼來看 對應kv均不支援空
我們來看找到對應前輩節點的程式碼
/**
* Returns a base-level node with key strictly less than given key,
* or the base-level header if there is no such node. Also
* unlinks indexes to deleted nodes found along the way. Callers
* rely on this side-effect of clearing indices to deleted nodes.
* @param key the key
* @return a predecessor of key
*/
private Node<K,V> findPredecessor(Comparable<? super K> key) {
if (key == null)
throw new NullPointerException(); // don't postpone errors
for (;;) {
Index<K,V> q = head;
Index<K,V> r = q.right;
for (;;) {
if (r != null) {
Node<K,V> n = r.node;
K k = n.key;
if (n.value == null) {
if (!q.unlink(r))
break; // restart
r = q.right; // reread r
continue;
}
if (key.compareTo(k) > 0) {
q = r;
r = r.right;
continue;
}
}
Index<K,V> d = q.down;
if (d != null) {
q = d;
r = d.right;
} else
return q.node;
}
}
}
複製程式碼首先查詢都是從head節點開始
由於節點都是有序的 那麼插入節點時有如下規律 右邊節點一定比左邊節點大
因此給定一個key只要出現當右邊的節點大於當前節點則在前一個節點獲取向下的索引
通過該方法我們可以找到前置節點
/* ---------------- Insertion -------------- */
/**
* Main insertion method. Adds element if not present, or
* replaces value if present and onlyIfAbsent is false.
* @param kkey the key
* @param value the value that must be associated with key
* @param onlyIfAbsent if should not insert if already present
* @return the old value, or null if newly inserted
*/
private V doPut(K kkey, V value, boolean onlyIfAbsent) {
Comparable<? super K> key = comparable(kkey);
for (;;) {
Node<K,V> b = findPredecessor(key);
Node<K,V> n = b.next;
for (;;) {
if (n != null) {
Node<K,V> f = n.next;
if (n != b.next) // inconsistent read
break;
Object v = n.value;
if (v == null) { // n is deleted
n.helpDelete(b, f);
break;
}
if (v == n || b.value == null) // b is deleted
break;
int c = key.compareTo(n.key);
if (c > 0) {
b = n;
n = f;
continue;
}
if (c == 0) {
if (onlyIfAbsent || n.casValue(v, value))
return (V)v;
else
break; // restart if lost race to replace value
}
// else c < 0; fall through
}
Node<K,V> z = new Node<K,V>(kkey, value, n);
if (!b.casNext(n, z))
break; // restart if lost race to append to b
int level = randomLevel();
if (level > 0)
insertIndex(z, level);
return null;
}
}
}
複製程式碼從最簡單情況開始分析 假設第一次只有headIndex節點 那麼新的節點進來要插入到headIndex節點之後
此時BaseNode為找到的前置節點。那麼其next為空
那麼新建新的node節點
通過cas方法設定next域【處處可見UNSAFE】為對應的節點
當然如果設定失敗則需要繼續迴圈直到成功為止
要給對應的節點產生level這個就是連結中所說的拋硬幣方法（隨機）
/**
* Returns a random level for inserting a new node.
* Hardwired to k=1, p=0.5, max 31 (see above and
* Pugh's "Skip List Cookbook", sec 3.4).
*
* This uses the simplest of the generators described in George
* Marsaglia's "Xorshift RNGs" paper. This is not a high-quality
* generator but is acceptable here.
*/
private int randomLevel() {
int x = randomSeed;
x ^= x << 13;
x ^= x >>> 17;
randomSeed = x ^= x << 5;
if ((x & 0x80000001) != 0) // test highest and lowest bits
return 0;
int level = 1;
while (((x >>>= 1) & 1) != 0) ++level;
return level;
}
複製程式碼大家可以看到randomSeed每次都會被重新賦值 同樣的道理 仍然是通過volatile來進行保證執行緒可見性的麼？看來不是！
/**
* Seed for simple random number generator. Not volatile since it
* doesn't matter too much if different threads don't see updates.
*/
private transient int randomSeed;
複製程式碼對於seed的要求是不能初始為0否則所有的randomSeed左右移就一直為0了
從上面來看level的層次應該為對應x的末尾1的個數【最多是32層】
此時需要執行真正的插入節點的操作了
/**
* Creates and adds index nodes for the given node.
* @param z the node
* @param level the level of the index
*/
private void insertIndex(Node<K,V> z, int level) {
HeadIndex<K,V> h = head;
int max = h.level;
if (level <= max) {
Index<K,V> idx = null;
for (int i = 1; i <= level; ++i)
idx = new Index<K,V>(z, idx, null);
addIndex(idx, h, level);
} else { // Add a new level
/*
* To reduce interference by other threads checking for
* empty levels in tryReduceLevel, new levels are added
* with initialized right pointers. Which in turn requires
* keeping levels in an array to access them while
* creating new head index nodes from the opposite
* direction.
*/
level = max + 1;
Index<K,V>[] idxs = (Index<K,V>[])new Index[level+1];
Index<K,V> idx = null;
for (int i = 1; i <= level; ++i)
idxs[i] = idx = new Index<K,V>(z, idx, null);
HeadIndex<K,V> oldh;
int k;
for (;;) {
oldh = head;
int oldLevel = oldh.level;
if (level <= oldLevel) { // lost race to add level
k = level;
break;
}
HeadIndex<K,V> newh = oldh;
Node<K,V> oldbase = oldh.node;
for (int j = oldLevel+1; j <= level; ++j)
newh = new HeadIndex<K,V>(oldbase, newh, idxs[j], j);
if (casHead(oldh, newh)) {
k = oldLevel;
break;
}
}
addIndex(idxs[k], oldh, k);
}
}
/**
* Adds given index nodes from given level down to 1.
* @param idx the topmost index node being inserted
* @param h the value of head to use to insert. This must be
* snapshotted by callers to provide correct insertion level
* @param indexLevel the level of the index
*/
private void addIndex(Index<K,V> idx, HeadIndex<K,V> h, int indexLevel) {
// Track next level to insert in case of retries
int insertionLevel = indexLevel;
Comparable<? super K> key = comparable(idx.node.key);
if (key == null) throw new NullPointerException();
// Similar to findPredecessor, but adding index nodes along
// path to key.
for (;;) {
int j = h.level;
Index<K,V> q = h;
Index<K,V> r = q.right;
Index<K,V> t = idx;
for (;;) {
if (r != null) {
Node<K,V> n = r.node;
// compare before deletion check avoids needing recheck
int c = key.compareTo(n.key);
if (n.value == null) {
if (!q.unlink(r))
break;
r = q.right;
continue;
}
if (c > 0) {
q = r;
r = r.right;
continue;
}
}
if (j == insertionLevel) {
// Don't insert index if node already deleted
if (t.indexesDeletedNode()) {
findNode(key); // cleans up
return;
}
if (!q.link(r, t))
break; // restart
if (--insertionLevel == 0) {
// need final deletion check before return
if (t.indexesDeletedNode())
findNode(key);
return;
}
}
if (--j >= insertionLevel && j < indexLevel)
t = t.down;
q = q.down;
r = q.right;
}
}
}
複製程式碼如果當前頭結點的level比上述生成的level小 說明要生成的新的level了 並且不可能跨級生產level【比如第一個節點插入生成的節點level需要設定為10 此時只有一層那麼會將該level重新設定為1 即headIndex.level+1】
正如註釋所說 無鎖化程式設計的難度比較大一個正確無誤的高效能無鎖化併發庫 是jdk提供的免費效能午餐。不過這邊仍然可以看到JDK開發者是怎麼思考和解決的。
由於加了新的Level 新的節點在這一層
如果不考慮併發此時應該
那麼需要該節點包裝和層級數量相同多的Index 其中每一個Index的down連結指向前一個Index
並且新建新的Head的右連結指向最後一個Index 其下連結指向老的HeadIndex
這邊有個疑問
for (int i = 1; i <= level; ++i)
idxs[i] = idx = new Index<K,V>(z, idx, null);
複製程式碼idexs[0] 並沒有賦值為null 應該只是為了和level保持一致 而不需要對應陣列下標-1 使用了idxs[j] 和idxs[k]
HeadIndex<K,V> oldh;
int k;
for (;;) {
oldh = head;
int oldLevel = oldh.level;
if (level <= oldLevel) { // lost race to add level
k = level;
break;
}
HeadIndex<K,V> newh = oldh;
Node<K,V> oldbase = oldh.node;
for (int j = oldLevel+1; j <= level; ++j)
newh = new HeadIndex<K,V>(oldbase, newh, idxs[j], j);
if (casHead(oldh, newh)) {
k = oldLevel;
break;
}
}
addIndex(idxs[k], oldh, k);
複製程式碼插入index和之前找前輩節點類似
get
/**
* Gets value for key using findNode.
* @param okey the key
* @return the value, or null if absent
*/
private V doGet(Object okey) {
Comparable<? super K> key = comparable(okey);
/*
* Loop needed here and elsewhere in case value field goes
* null just as it is about to be returned, in which case we
* lost a race with a deletion, so must retry.
*/
for (;;) {
Node<K,V> n = findNode(key);
if (n == null)
return null;
Object v = n.value;
if (v != null)
return (V)v;
}
}
/**
* Returns node holding key or null if no such, clearing out any
* deleted nodes seen along the way. Repeatedly traverses at
* base-level looking for key starting at predecessor returned
* from findPredecessor, processing base-level deletions as
* encountered. Some callers rely on this side-effect of clearing
* deleted nodes.
*
* Restarts occur, at traversal step centered on node n, if:
*
* (1) After reading n's next field, n is no longer assumed
* predecessor b's current successor, which means that
* we don't have a consistent 3-node snapshot and so cannot
* unlink any subsequent deleted nodes encountered.
*
* (2) n's value field is null, indicating n is deleted, in
* which case we help out an ongoing structural deletion
* before retrying. Even though there are cases where such
* unlinking doesn't require restart, they aren't sorted out
* here because doing so would not usually outweigh cost of
* restarting.
*
* (3) n is a marker or n's predecessor's value field is null,
* indicating (among other possibilities) that
* findPredecessor returned a deleted node. We can't unlink
* the node because we don't know its predecessor, so rely
* on another call to findPredecessor to notice and return
* some earlier predecessor, which it will do. This check is
* only strictly needed at beginning of loop, (and the
* b.value check isn't strictly needed at all) but is done
* each iteration to help avoid contention with other
* threads by callers that will fail to be able to change
* links, and so will retry anyway.
*
* The traversal loops in doPut, doRemove, and findNear all
* include the same three kinds of checks. And specialized
* versions appear in findFirst, and findLast and their
* variants. They can't easily share code because each uses the
* reads of fields held in locals occurring in the orders they
* were performed.
*
* @param key the key
* @return node holding key, or null if no such
*/
private Node<K,V> findNode(Comparable<? super K> key) {
for (;;) {
Node<K,V> b = findPredecessor(key);
Node<K,V> n = b.next;
for (;;) {
if (n == null)
return null;
Node<K,V> f = n.next;
if (n != b.next) // inconsistent read
break;
Object v = n.value;
if (v == null) { // n is deleted
n.helpDelete(b, f);
break;
}
if (v == n || b.value == null) // b is deleted
break;
int c = key.compareTo(n.key);
if (c == 0)
return n;
if (c < 0)
return null;
b = n;
n = f;
}
}
}
複製程式碼依舊是使用findPredecessor找到前置節點 使用compare 如果為0則返回否則表示為空
由於併發 當返回為1的時候表示該節點大於找到的前置節點的下一個節點的值大於查詢的key
此時可能由於併發導致找到的前置節點已經並非最新的結果 因此再次迴圈查詢
remove
/**
* Removes the mapping for the specified key from this map if present.
*
* @param key key for which mapping should be removed
* @return the previous value associated with the specified key, or
* <tt>null</tt> if there was no mapping for the key
* @throws ClassCastException if the specified key cannot be compared
* with the keys currently in the map
* @throws NullPointerException if the specified key is null
*/
public V remove(Object key) {
return doRemove(key, null);
}
/* ---------------- Deletion -------------- */
/**
* Main deletion method. Locates node, nulls value, appends a
* deletion marker, unlinks predecessor, removes associated index
* nodes, and possibly reduces head index level.
*
* Index nodes are cleared out simply by calling findPredecessor.
* which unlinks indexes to deleted nodes found along path to key,
* which will include the indexes to this node. This is done
* unconditionally. We can't check beforehand whether there are
* index nodes because it might be the case that some or all
* indexes hadn't been inserted yet for this node during initial
* search for it, and we'd like to ensure lack of garbage
* retention, so must call to be sure.
*
* @param okey the key
* @param value if non-null, the value that must be
* associated with key
* @return the node, or null if not found
*/
final V doRemove(Object okey, Object value) {
Comparable<? super K> key = comparable(okey);
for (;;) {
Node<K,V> b = findPredecessor(key);
Node<K,V> n = b.next;
for (;;) {
if (n == null)
return null;
Node<K,V> f = n.next;
if (n != b.next) // inconsistent read
break;
Object v = n.value;
if (v == null) { // n is deleted
n.helpDelete(b, f);
break;
}
if (v == n || b.value == null) // b is deleted
break;
int c = key.compareTo(n.key);
if (c < 0)
return null;
if (c > 0) {
b = n;
n = f;
continue;
}
if (value != null && !value.equals(v))
return null;
if (!n.casValue(v, null))
break;
if (!n.appendMarker(f) || !b.casNext(n, f))
findNode(key); // Retry via findNode
else {
findPredecessor(key); // Clean index
if (head.right == null)
tryReduceLevel();
}
return (V)v;
}
}
}
/**
* Possibly reduce head level if it has no nodes. This method can
* (rarely) make mistakes, in which case levels can disappear even
* though they are about to contain index nodes. This impacts
* performance, not correctness. To minimize mistakes as well as
* to reduce hysteresis, the level is reduced by one only if the
* topmost three levels look empty. Also, if the removed level
* looks non-empty after CAS, we try to change it back quick
* before anyone notices our mistake! (This trick works pretty
* well because this method will practically never make mistakes
* unless current thread stalls immediately before first CAS, in
* which case it is very unlikely to stall again immediately
* afterwards, so will recover.)
*
* We put up with all this rather than just let levels grow
* because otherwise, even a small map that has undergone a large
* number of insertions and removals will have a lot of levels,
* slowing down access more than would an occasional unwanted
* reduction.
*/
private void tryReduceLevel() {
HeadIndex<K,V> h = head;
HeadIndex<K,V> d;
HeadIndex<K,V> e;
if (h.level > 3 &&
(d = (HeadIndex<K,V>)h.down) != null &&
(e = (HeadIndex<K,V>)d.down) != null &&
e.right == null &&
d.right == null &&
h.right == null &&
casHead(h, d) && // try to set
h.right != null) // recheck
casHead(d, h); // try to backout
}
複製程式碼當執行remove的時候依然實現找到前置節點
根據該節點的right節點來判斷執行compare是否相同
如果刪除key小於right節點的值那麼可以返回null 說明該節點不存在
如果刪除的key等於right節點的值說明需要刪除
如果刪除的key大於right節點的值說明前置節點需要更新已被修改
這邊刪除很有意思 通過marker來標記 而marker節點仍然是Node
/**
* Tries to append a deletion marker to this node.
* @param f the assumed current successor of this node
* @return true if successful
*/
boolean appendMarker(Node<K,V> f) {
return casNext(f, new Node<K,V>(f));
}
/**
* Creates a new marker node. A marker is distinguished by
* having its value field point to itself. Marker nodes also
* have null keys, a fact that is exploited in a few places,
* but this doesn't distinguish markers from the base-level
* header node (head.node), which also has a null key.
*/
Node(Node<K,V> next) {
this.key = null;
this.value = this;
this.next = next;
}
複製程式碼使用Marker其key為自身 同時一旦建立marker節點成功此時執行b.casNext(n, f) 也就完成了節點的替換【即後繼節點的刪除】
每次刪除完畢後需要check頭節點的右連結為空的話需要刪除一層 即呼叫tryReduceLevel
tryReduceLevel這段註釋寫的也很有趣【必須超過三層才會進行層數的減少】
這邊更多的還是多執行緒之前的競態條件等
如果出現head節點需要再次check 並再次頭結點cas交換
不考慮併發的情況下跳錶的實現還是相對紅黑樹等等是比較容易實現的