cn.nukkit.utils.collection.nb.ConcurrentAutoLongTable Maven / Gradle / Ivy
package cn.nukkit.utils.collection.nb;
import cn.nukkit.api.PowerNukkitXOnly;
import cn.nukkit.api.Since;
import java.io.Serializable;
import java.lang.invoke.MethodHandles;
import java.lang.invoke.VarHandle;
import java.util.concurrent.atomic.AtomicReferenceFieldUpdater;
/**
* An auto-resizing table of {@code longs}, supporting low-contention CAS
* operations. Updates are done with CAS's to no particular table element.
* The intent is to support highly scalable counters, r/w locks, and other
* structures where the updates are associative, loss-free (no-brainer), and
* otherwise happen at such a high volume that the cache contention for
* CAS'ing a single word is unacceptable.
*
* @author Cliff Click, SuperIceCN
* @since 1.5
*/
@Since("1.20.10-r1")
@PowerNukkitXOnly
public class ConcurrentAutoLongTable implements Serializable {
// --- public interface ---
/**
* Add the given value to current counter value. Concurrent updates will
* not be lost, but addAndGet or getAndAdd are not implemented because the
* total counter value (i.e., {@link #get}) is not atomically updated.
* Updates are striped across an array of counters to avoid cache contention
* and has been tested with performance scaling linearly up to 768 CPUs.
*/
public void add(long x) {
add_if(x);
}
/**
* {@link #add} with -1
*/
public void decrement() {
add_if(-1L);
}
/**
* {@link #add} with +1
*/
public void increment() {
add_if(1L);
}
/**
* Atomically set the sum of the striped counters to specified value.
* Rather more expensive than a simple store, in order to remain atomic.
*/
public void set(long x) {
CAT newcat = new CAT(null, 4, x);
// Spin until CAS works
while (!CAS_cat(_cat, newcat)) {/*empty*/}
}
/**
* Current value of the counter. Since other threads are updating furiously
* the value is only approximate, but it includes all counts made by the
* current thread. Requires a pass over the internally striped counters.
*/
public long get() {
return _cat.sum();
}
/**
* Same as {@link #get}, included for completeness.
*/
public int intValue() {
return (int) _cat.sum();
}
/**
* Same as {@link #get}, included for completeness.
*/
public long longValue() {
return _cat.sum();
}
/**
* A cheaper {@link #get}. Updated only once/millisecond, but as fast as a
* simple load instruction when not updating.
*/
public long estimate_get() {
return _cat.estimate_sum();
}
/**
* Return the counter's {@code long} value converted to a string.
*/
public String toString() {
return _cat.toString();
}
/**
* Return the internal counter striping factor. Useful for diagnosing
* performance problems.
*/
public int internal_size() {
return _cat._t.length;
}
// Only add 'x' to some slot in table, hinted at by 'hash'. The sum can
// overflow. Value is CAS'd so no counts are lost. The CAS is retried until
// it succeeds. Returned value is the old value.
private long add_if(long x) {
return _cat.add_if(x, hash(), this);
}
// The underlying array of concurrently updated long counters
private volatile CAT _cat = new CAT(null, 16/*Start Small, Think Big!*/, 0L);
private static AtomicReferenceFieldUpdater _catUpdater =
AtomicReferenceFieldUpdater.newUpdater(ConcurrentAutoLongTable.class, CAT.class, "_cat");
private boolean CAS_cat(CAT oldcat, CAT newcat) {
return _catUpdater.compareAndSet(this, oldcat, newcat);
}
// Hash spreader
private static int hash() {
//int h = (int)Thread.currentThread().getId();
int h = System.identityHashCode(Thread.currentThread());
return h << 3; // Pad out cache lines. The goal is to avoid cache-line contention
}
// --- CAT -----------------------------------------------------------------
private static class CAT implements Serializable {
private static final VarHandle _LHandle = MethodHandles.arrayElementVarHandle(long[].class);
private static boolean CAS(long[] A, int idx, long old, long nnn) {
return _LHandle.compareAndSet(A, idx, old, nnn);
}
//volatile long _resizers; // count of threads attempting a resize
//static private final AtomicLongFieldUpdater _resizerUpdater =
// AtomicLongFieldUpdater.newUpdater(CAT.class, "_resizers");
private final CAT _next;
private volatile long _fuzzy_sum_cache;
private volatile long _fuzzy_time;
private static final int MAX_SPIN = 1;
private final long[] _t; // Power-of-2 array of longs
CAT(CAT next, int sz, long init) {
_next = next;
_t = new long[sz];
_t[0] = init;
}
// Only add 'x' to some slot in table, hinted at by 'hash'. The sum can
// overflow. Value is CAS'd so no counts are lost. The CAS is attempted
// ONCE.
public long add_if(long x, int hash, ConcurrentAutoLongTable master) {
final long[] t = _t;
final int idx = hash & (t.length - 1);
// Peel loop; try once fast
long old = t[idx];
final boolean ok = CAS(t, idx, old, old + x);
if (ok) return old; // Got it
// Try harder
int cnt = 0;
while (true) {
old = t[idx];
if (CAS(t, idx, old, old + x)) break; // Got it!
cnt++;
}
if (cnt < MAX_SPIN) return old; // Allowable spin loop count
if (t.length >= 1024 * 1024) return old; // too big already
// Too much contention; double array size in an effort to reduce contention
//long r = _resizers;
//final int newbytes = (t.length<<1)<<3/*word to bytes*/;
//while( !_resizerUpdater.compareAndSet(this,r,r+newbytes) )
// r = _resizers;
//r += newbytes;
if (master._cat != this) return old; // Already doubled, don't bother
//if( (r>>17) != 0 ) { // Already too much allocation attempts?
// // We could use a wait with timeout, so we'll wakeup as soon as the new
// // table is ready, or after the timeout in any case. Annoyingly, this
// // breaks the non-blocking property - so for now we just briefly sleep.
// //synchronized( this ) { wait(8*megs); } // Timeout - we always wakeup
// try { Thread.sleep(r>>17); } catch( InterruptedException e ) { }
// if( master._cat != this ) return old;
//}
CAT newcat = new CAT(this, t.length * 2, 0);
// Take 1 stab at updating the CAT with the new larger size. If this
// fails, we assume some other thread already expanded the CAT - so we
// do not need to retry until it succeeds.
while (master._cat == this && !master.CAS_cat(this, newcat)) {/*empty*/}
return old;
}
// Return the current sum of all things in the table. Writers can be
// updating the table furiously, so the sum is only locally accurate.
public long sum() {
long sum = _next == null ? 0 : _next.sum(); // Recursively get cached sum
final long[] t = _t;
for (long cnt : t) sum += cnt;
return sum;
}
// Fast fuzzy version. Used a cached value until it gets old, then re-up
// the cache.
public long estimate_sum() {
// For short tables, just do the work
if (_t.length <= 64) return sum();
// For bigger tables, periodically freshen a cached value
long millis = System.currentTimeMillis();
if (_fuzzy_time != millis) { // Time marches on?
_fuzzy_sum_cache = sum(); // Get sum the hard way
_fuzzy_time = millis; // Indicate freshness of cached value
}
return _fuzzy_sum_cache; // Return cached sum
}
public String toString() {
return Long.toString(sum());
}
}
}
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