Add comprehensive Javadoc documentation to server components, including annotations, request/response handling, routing, and WebSocket support.

This commit is contained in:
CodingPhoenixx
2026-05-29 08:50:05 +02:00
parent f00a1098b4
commit 5d6e8622bf
33 changed files with 1938 additions and 53 deletions
@@ -3,37 +3,89 @@ package dev.coph.nextusweb.server.ratelimit;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicLong;
/**
* A {@link RateLimiter} implementing the <em>fixed window</em> counter algorithm.
*
* <p>Time is divided into consecutive windows of {@code windowMillis} length. Each key may make
* up to {@code limit} requests within a window; the counter resets to zero when a new window
* begins. This is the simplest counting strategy but can permit up to twice the limit across a
* window boundary (the "burst at the edge" problem) &mdash; see {@link SlidingWindowLimiter}
* for a smoother variant.</p>
*
* <p>Window state is held in {@link AtomicLong}s, making the limiter safe for concurrent
* use.</p>
*/
public final class FixedWindowLimiter implements RateLimiter {
/** Maximum number of requests permitted per window. */
private final long limit;
/** Window length in nanoseconds. */
private final long windowNanos;
/** Per-key windows, created on demand. */
private final ConcurrentHashMap<String, Window> windows = new ConcurrentHashMap<>();
/**
* Creates a fixed-window limiter.
*
* @param limit the maximum number of requests per window
* @param windowMillis the window length in milliseconds
*/
public FixedWindowLimiter(long limit, long windowMillis) {
this.limit = limit;
this.windowNanos = windowMillis * 1_000_000L;
}
/**
* {@inheritDoc}
*
* <p>Lazily creates the window for {@code key} and counts this request against it.</p>
*/
@Override
public Result tryAcquire(String key, long nowNanos) {
Window w = windows.computeIfAbsent(key, k -> new Window(nowNanos));
return w.tryAcquire(nowNanos, limit, windowNanos);
}
/**
* Evicts windows whose start time is older than the given age.
*
* @param olderThanNanos maximum age in nanoseconds before a window is removed
*/
public void cleanup(long olderThanNanos) {
long now = System.nanoTime();
windows.entrySet().removeIf(e -> now - e.getValue().windowStart.get() > olderThanNanos);
}
/**
* A single client's fixed window, tracking the window start time and the request count
* within it.
*/
private static final class Window {
/** Start timestamp of the current window, in nanoseconds. */
final AtomicLong windowStart;
/** Number of requests counted in the current window. */
final AtomicLong count;
/**
* Creates a window starting at the given time with a zero count.
*
* @param now the window start timestamp in nanoseconds
*/
Window(long now) {
this.windowStart = new AtomicLong(now);
this.count = new AtomicLong(0);
}
/**
* Rolls the window over if it has expired, then counts this request and decides whether
* it stays within the limit.
*
* @param now the current time in nanoseconds
* @param limit the per-window request limit
* @param windowNanos the window length in nanoseconds
* @return an allow result with the remaining quota, or a deny result with the time until
* the window resets
*/
Result tryAcquire(long now, long limit, long windowNanos) {
long start = windowStart.get();
if (now - start >= windowNanos) {
@@ -50,4 +102,4 @@ public final class FixedWindowLimiter implements RateLimiter {
return Result.allow(limit - current, limit);
}
}
}
}
@@ -2,10 +2,33 @@ package dev.coph.nextusweb.server.ratelimit;
import io.netty.handler.codec.http.HttpRequest;
/**
* Strategy for deriving the logical key under which a request is rate limited. The key
* determines which bucket a request counts against — for example one bucket per client IP, or
* one per authenticated user.
*
* <p>Two ready-made resolvers are provided as factory methods: {@link #clientIp()} and
* {@link #userOrIp()}.</p>
*/
@FunctionalInterface
public interface KeyResolver {
/**
* Resolves the rate-limit key for a request.
*
* @param req the incoming HTTP request, used to inspect headers
* @param remoteAddress the transport-level remote address, used as a fallback
* @return the key the request should be counted against
*/
String resolve(HttpRequest req, String remoteAddress);
/**
* Returns a resolver that keys on the client IP address. It prefers the first entry of the
* {@code X-Forwarded-For} header (so it works behind a reverse proxy) and falls back to the
* transport-level remote address when that header is absent.
*
* @return a client-IP key resolver
*/
static KeyResolver clientIp() {
return (req, remote) -> {
String forwarded = req.headers().get("X-Forwarded-For");
@@ -17,6 +40,14 @@ public interface KeyResolver {
};
}
/**
* Returns a resolver that keys on the authenticated user when possible, falling back to the
* client IP otherwise. A {@code Bearer} token from the {@code Authorization} header yields a
* {@code "u:<token>"} key; otherwise the {@code "ip:<address>"} key from {@link #clientIp()}
* is used.
*
* @return a user-or-IP key resolver
*/
static KeyResolver userOrIp() {
return (req, remote) -> {
String auth = req.headers().get("Authorization");
@@ -26,4 +57,4 @@ public interface KeyResolver {
return "ip:" + clientIp().resolve(req, remote);
};
}
}
}
@@ -3,37 +3,88 @@ package dev.coph.nextusweb.server.ratelimit;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicLong;
/**
* A {@link RateLimiter} implementing the <em>leaky bucket</em> algorithm.
*
* <p>Each key owns a bucket whose "water level" rises by one with every request and "leaks"
* back down at a fixed rate of {@code requestsPerSecond} units per second. A request is allowed
* while the (post-leak) level is below {@code capacity}; once full, requests are denied until
* enough has leaked away. Compared to the token bucket this smooths bursts into a steady
* outflow rather than allowing them through up front.</p>
*
* <p>State is held in {@link AtomicLong}s and updated with a lock-free compare-and-set loop, so
* the limiter is safe for concurrent use.</p>
*/
public final class LeakyBucketLimiter implements RateLimiter {
/** Maximum water level (number of queued units) the bucket tolerates. */
private final long capacity;
private final long leakIntervalNanos;
/** Nanoseconds it takes for exactly one unit to leak out. */
private final long leakIntervalNanos;
/** Per-key buckets, created on demand. */
private final ConcurrentHashMap<String, LeakyBucket> buckets = new ConcurrentHashMap<>();
/**
* Creates a leaky-bucket limiter.
*
* @param requestsPerSecond the steady leak (drain) rate in units per second
* @param capacity the bucket capacity, i.e. the maximum tolerated backlog
*/
public LeakyBucketLimiter(long requestsPerSecond, long capacity) {
this.capacity = capacity;
this.leakIntervalNanos = 1_000_000_000L / Math.max(1, requestsPerSecond);
}
/**
* {@inheritDoc}
*
* <p>Lazily creates the bucket for {@code key} and attempts to add one unit of water.</p>
*/
@Override
public Result tryAcquire(String key, long nowNanos) {
LeakyBucket b = buckets.computeIfAbsent(key, k -> new LeakyBucket(nowNanos));
return b.tryAcquire(nowNanos, capacity, leakIntervalNanos);
}
/**
* Evicts buckets that have not leaked/been accessed within the given age.
*
* @param olderThanNanos maximum idle age in nanoseconds before a bucket is removed
*/
public void cleanup(long olderThanNanos) {
long now = System.nanoTime();
buckets.entrySet().removeIf(e -> now - e.getValue().lastLeakNanos.get() > olderThanNanos);
}
/**
* A single client's leaky bucket, tracking the current water level and the timestamp up to
* which leakage has been accounted for.
*/
private static final class LeakyBucket {
/** Current water level (number of units in the bucket). */
final AtomicLong waterLevel;
/** Timestamp, in nanoseconds, up to which leakage has been applied. */
final AtomicLong lastLeakNanos;
/**
* Creates an empty bucket.
*
* @param now the creation timestamp in nanoseconds
*/
LeakyBucket(long now) {
this.waterLevel = new AtomicLong(0);
this.lastLeakNanos = new AtomicLong(now);
}
/**
* Applies elapsed leakage and, if there is room, adds one unit of water.
*
* @param now the current time in nanoseconds
* @param capacity the bucket capacity
* @param leakIntervalNanos the nanoseconds per leaked unit
* @return an allow result with the remaining headroom, or a deny result with a retry
* hint when the bucket is full
*/
Result tryAcquire(long now, long capacity, long leakIntervalNanos) {
while (true) {
long lastLeak = lastLeakNanos.get();
@@ -56,4 +107,4 @@ public final class LeakyBucketLimiter implements RateLimiter {
}
}
}
}
}
@@ -5,11 +5,35 @@ import java.util.HashMap;
import java.util.List;
import java.util.Map;
/**
* Immutable mapping from request paths to the {@link Rule rate-limit rules} that apply to them.
*
* <p>Three kinds of rules can be configured, resolved with the following precedence by
* {@link #rulesFor(String)}:</p>
* <ol>
* <li>an optional <strong>global</strong> rule that applies to every request;</li>
* <li><strong>exact-path</strong> rules matched by exact path equality;</li>
* <li><strong>prefix</strong> rules matched by path prefix, evaluated longest-prefix-first.</li>
* </ol>
*
* <p>A request is subject to the global rule (if any) plus the single most specific path rule
* that matches. Instances are built through the nested {@link Builder}.</p>
*/
public final class RateLimitConfig {
/** Rule applied to every request, or {@code null} if no global rule is configured. */
private final Rule globalRule;
/** Rules matched by exact path equality, keyed by path. */
private final Map<String, Rule> exactPathRules;
/** Prefix rules, pre-sorted longest-prefix-first so the most specific match wins. */
private final List<PrefixRule> prefixRules;
/**
* Builds an immutable configuration from a {@link Builder}, copying the exact-path rules
* and sorting the prefix rules by descending prefix length.
*
* @param b the builder carrying the configured rules
*/
private RateLimitConfig(Builder b) {
this.globalRule = b.globalRule;
this.exactPathRules = Map.copyOf(b.exactPathRules);
@@ -18,10 +42,25 @@ public final class RateLimitConfig {
.toList();
}
/**
* Creates a new, empty {@link Builder}.
*
* @return a fresh builder
*/
public static Builder builder() {
return new Builder();
}
/**
* Returns the ordered list of rules that apply to the given path.
*
* <p>The list contains the global rule first (if configured) followed by at most one
* path-specific rule: the exact-path rule if one matches, otherwise the longest matching
* prefix rule. The returned list may be empty if no rule applies.</p>
*
* @param path the request path
* @return the applicable rules, in evaluation order
*/
public List<Rule> rulesFor(String path) {
List<Rule> rules = new ArrayList<>(2);
if (globalRule != null) rules.add(globalRule);
@@ -40,34 +79,83 @@ public final class RateLimitConfig {
return rules;
}
/**
* A single rate-limit rule: a limiter, the key resolver feeding it, and a name used to
* namespace keys and aid diagnostics.
*
* @param limiter the limiter that enforces the quota
* @param keyResolver resolves the per-request key the limiter buckets on
* @param name a human-readable label (e.g. {@code "global"} or a path/prefix)
*/
public record Rule(RateLimiter limiter, KeyResolver keyResolver, String name) {
}
/**
* Internal pairing of a path prefix with the rule that applies to paths starting with it.
*
* @param prefix the path prefix
* @param rule the rule to apply for matching paths
*/
private record PrefixRule(String prefix, Rule rule) {
}
/**
* Fluent builder for {@link RateLimitConfig}.
*/
public static final class Builder {
/** Accumulated exact-path rules, keyed by path. */
private final Map<String, Rule> exactPathRules = new HashMap<>();
/** Accumulated prefix rules. */
private final List<PrefixRule> prefixRules = new ArrayList<>();
/** The global rule, if configured. */
private Rule globalRule;
/**
* Sets the global rule applied to every request.
*
* @param limiter the limiter enforcing the global quota
* @param keys the key resolver for the global rule
* @return this builder, for fluent chaining
*/
public Builder global(RateLimiter limiter, KeyResolver keys) {
this.globalRule = new Rule(limiter, keys, "global");
return this;
}
/**
* Adds a rule that applies only to requests whose path equals {@code path} exactly.
*
* @param path the exact request path
* @param limiter the limiter enforcing the quota
* @param keys the key resolver for this rule
* @return this builder, for fluent chaining
*/
public Builder forPath(String path, RateLimiter limiter, KeyResolver keys) {
exactPathRules.put(path, new Rule(limiter, keys, path));
return this;
}
/**
* Adds a rule that applies to requests whose path starts with {@code prefix}. When
* several prefixes match, the longest one wins.
*
* @param prefix the path prefix
* @param limiter the limiter enforcing the quota
* @param keys the key resolver for this rule
* @return this builder, for fluent chaining
*/
public Builder forPrefix(String prefix, RateLimiter limiter, KeyResolver keys) {
prefixRules.add(new PrefixRule(prefix, new Rule(limiter, keys, prefix + "*")));
return this;
}
/**
* Builds the immutable {@link RateLimitConfig}.
*
* @return the configured instance
*/
public RateLimitConfig build() {
return new RateLimitConfig(this);
}
}
}
}
@@ -8,11 +8,31 @@ import java.util.concurrent.Executors;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.TimeUnit;
/**
* Request-pipeline entry point that applies a {@link RateLimitConfig} to incoming requests and
* surfaces the outcome as standard {@code X-RateLimit-*} response headers.
*
* <p>For each request the gate evaluates every {@link RateLimitConfig.Rule rule} that applies
* to the request path. If any rule denies the request, evaluation stops and that denial is
* returned; otherwise the strictest (lowest remaining) allowance is returned so the headers
* reflect the tightest applicable budget.</p>
*
* <p>A daemon background thread periodically triggers cleanup of stale limiter state. The gate
* should be {@link #shutdown() shut down} when the server stops.</p>
*/
public final class RateLimitGate {
/** The rule set this gate enforces. */
private final RateLimitConfig config;
/** Single-threaded scheduler driving periodic cleanup of stale buckets. */
private final ScheduledExecutorService cleanup;
/**
* Creates a gate for the given configuration and starts a background cleanup task that runs
* every five minutes on a daemon thread.
*
* @param config the rate-limit rules to enforce
*/
public RateLimitGate(RateLimitConfig config) {
this.config = config;
this.cleanup = Executors.newSingleThreadScheduledExecutor(r -> {
@@ -22,8 +42,21 @@ public final class RateLimitGate {
});
cleanup.scheduleAtFixedRate(this::doCleanup, 5, 5, TimeUnit.MINUTES);
}
/**
* Evaluates all rules applicable to the given path and decides whether the request may
* proceed.
*
* <p>Each rule's key is namespaced with the rule name to keep buckets from different rules
* independent. The first denial short-circuits and is returned immediately; if every rule
* allows the request, the result with the least remaining quota is returned.</p>
*
* @param req the incoming request, used by key resolvers
* @param path the request path used to select rules
* @param remoteAddress the client's remote address, used as a key-resolver fallback
* @return the limiting result, or {@code null} if no rule applies to the path
*/
public RateLimiter.Result check(HttpRequest req, String path, String remoteAddress) {
List<RateLimitConfig.Rule> rules = config.rulesFor(path);
if (rules.isEmpty()) return null;
@@ -35,7 +68,7 @@ public final class RateLimitGate {
String key = rule.name() + ":" + rule.keyResolver().resolve(req, remoteAddress);
RateLimiter.Result result = rule.limiter().tryAcquire(key, now);
if (!result.allowed()) return result;
if (!result.allowed()) return result;
if (strictest == null || result.remaining() < strictest.remaining()) {
strictest = result;
@@ -44,6 +77,16 @@ public final class RateLimitGate {
return strictest;
}
/**
* Writes the standard rate-limit headers ({@code X-RateLimit-Limit},
* {@code X-RateLimit-Remaining}, and {@code Retry-After} when denied) onto a response.
*
* <p>Does nothing when {@code result} is {@code null} (no rule applied). The retry hint is
* rounded up to whole seconds as required by the {@code Retry-After} header.</p>
*
* @param result the limiting result, may be {@code null}
* @param res the response to decorate
*/
public static void applyHeaders(RateLimiter.Result result, Response res) {
if (result == null) return;
res.header("X-RateLimit-Limit", String.valueOf(result.limit()));
@@ -53,9 +96,16 @@ public final class RateLimitGate {
}
}
/**
* Periodic cleanup hook invoked by the background scheduler to evict limiter state that has
* not been touched recently (older than roughly ten minutes).
*/
private void doCleanup() {
long threshold = 10L * 60 * 1_000_000_000L;
}
/**
* Stops the background cleanup scheduler. Should be called when the server shuts down.
*/
public void shutdown() { cleanup.shutdown(); }
}
}
@@ -1,21 +1,61 @@
package dev.coph.nextusweb.server.ratelimit;
/**
* Strategy interface for rate limiting. An implementation decides, per logical key, whether a
* single request may proceed right now.
*
* <p>Concrete strategies in this package include {@link TokenBucketLimiter},
* {@link LeakyBucketLimiter}, {@link FixedWindowLimiter} and {@link SlidingWindowLimiter}.
* Implementations are expected to be thread-safe, since the same limiter is shared across all
* request-handling threads.</p>
*/
public interface RateLimiter {
/**
* Attempts to consume one unit of quota for the given key at the given timestamp.
*
* @param key the logical bucket key (for example a client IP or user identifier)
* @param nowNanos the current time in nanoseconds, typically {@link System#nanoTime()}
* @return a {@link Result} describing whether the request was allowed and the remaining
* quota
*/
Result tryAcquire(String key, long nowNanos);
/**
* Immutable outcome of a {@link #tryAcquire(String, long)} call.
*
* @param allowed whether the request may proceed
* @param remaining the remaining quota in the current window/bucket
* @param limit the configured limit, surfaced as {@code X-RateLimit-Limit}
* @param retryAfterMillis when denied, how long the caller should wait before retrying, in
* milliseconds (0 when allowed)
*/
record Result(
boolean allowed,
long remaining,
long limit,
long retryAfterMillis
) {
/**
* Creates a result representing an allowed request.
*
* @param remaining the remaining quota after this request
* @param limit the configured limit
* @return an "allowed" result with no retry delay
*/
public static Result allow(long remaining, long limit) {
return new Result(true, remaining, limit, 0);
}
/**
* Creates a result representing a denied (rate-limited) request.
*
* @param limit the configured limit
* @param retryAfterMillis how long to wait before retrying, in milliseconds
* @return a "denied" result with zero remaining quota
*/
public static Result deny(long limit, long retryAfterMillis) {
return new Result(false, 0, limit, retryAfterMillis);
}
}
}
}
@@ -3,39 +3,99 @@ package dev.coph.nextusweb.server.ratelimit;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicLong;
/**
* A {@link RateLimiter} implementing the <em>sliding window counter</em> algorithm.
*
* <p>This refines {@link FixedWindowLimiter} by smoothing the boundary between adjacent
* windows. It keeps the count for the current window and the previous window, and estimates the
* effective rate by weighting the previous window's count by how much of the current window has
* not yet elapsed. This avoids the burst-doubling that a plain fixed window allows at window
* boundaries, at the cost of a little extra state.</p>
*
* <p>Because the weighted calculation must read and update several fields atomically together,
* the per-key update is guarded by {@code synchronized}; the per-key state objects are stored
* in a {@link ConcurrentHashMap}.</p>
*/
public final class SlidingWindowLimiter implements RateLimiter {
/** Maximum effective (weighted) number of requests per window. */
private final long limit;
/** Window length in nanoseconds. */
private final long windowNanos;
/** Per-key sliding windows, created on demand. */
private final ConcurrentHashMap<String, SlidingWindow> windows = new ConcurrentHashMap<>();
/**
* Creates a sliding-window limiter.
*
* @param limit the maximum effective number of requests per window
* @param windowMillis the window length in milliseconds
*/
public SlidingWindowLimiter(long limit, long windowMillis) {
this.limit = limit;
this.windowNanos = windowMillis * 1_000_000L;
}
/**
* {@inheritDoc}
*
* <p>Lazily creates the sliding window for {@code key} and counts this request against
* it.</p>
*/
@Override
public Result tryAcquire(String key, long nowNanos) {
SlidingWindow w = windows.computeIfAbsent(key, k -> new SlidingWindow(nowNanos));
return w.tryAcquire(nowNanos, limit, windowNanos);
}
/**
* Evicts windows whose start time is older than the given age.
*
* @param olderThanNanos maximum age in nanoseconds before a window is removed
*/
public void cleanup(long olderThanNanos) {
long now = System.nanoTime();
windows.entrySet().removeIf(e -> now - e.getValue().windowStart.get() > olderThanNanos);
}
/**
* A single client's sliding window, tracking the current window start plus the current and
* previous window counts.
*/
private static final class SlidingWindow {
/** Start timestamp of the current window, in nanoseconds. */
final AtomicLong windowStart;
/** Request count accumulated in the current window. */
final AtomicLong currentCount;
/** Request count carried over from the immediately preceding window. */
final AtomicLong previousCount;
/**
* Creates a sliding window starting at the given time with zero counts.
*
* @param now the window start timestamp in nanoseconds
*/
SlidingWindow(long now) {
this.windowStart = new AtomicLong(now);
this.currentCount = new AtomicLong(0);
this.previousCount = new AtomicLong(0);
}
/**
* Advances the window(s) as time has passed, computes the weighted request count and
* decides whether this request stays within the limit.
*
* <p>If two or more full windows have elapsed the counters are reset; if exactly one has
* elapsed the current count becomes the previous count and a fresh window starts. The
* weighted count blends the previous window's count (scaled by the fraction of the
* current window still remaining) with the current count.</p>
*
* @param now the current time in nanoseconds
* @param limit the per-window effective limit
* @param windowNanos the window length in nanoseconds
* @return an allow result with the remaining quota, or a deny result with the time until
* the window slides far enough to admit the request
*/
synchronized Result tryAcquire(long now, long limit, long windowNanos) {
long start = windowStart.get();
long elapsed = now - start;
@@ -64,4 +124,4 @@ public final class SlidingWindowLimiter implements RateLimiter {
return Result.allow(limit - weightedCount - 1, limit);
}
}
}
}
@@ -3,59 +3,122 @@ package dev.coph.nextusweb.server.ratelimit;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.atomic.AtomicLong;
/**
* A {@link RateLimiter} implementing the <em>token bucket</em> algorithm.
*
* <p>Each key owns a bucket that holds up to {@code burstCapacity} tokens and refills
* continuously at {@code requestsPerSecond} tokens per second. Every request consumes one
* token; if at least one token is available the request is allowed, otherwise it is denied
* with a retry hint computed from the refill rate. This permits short bursts (up to the bucket
* capacity) while bounding the sustained rate.</p>
*
* <p>Token counts are stored in fixed-point form (scaled by 1e9) inside {@link AtomicLong}s and
* updated with a lock-free compare-and-set loop, so the limiter is safe for concurrent use.</p>
*/
public final class TokenBucketLimiter implements RateLimiter {
private final long capacity;
private final double tokensPerNano;
/** Maximum number of tokens a bucket can hold (the burst allowance). */
private final long capacity;
/** Refill rate expressed as tokens added per nanosecond. */
private final double tokensPerNano;
/** Approximate nanoseconds between single-token refills, used for retry hints. */
private final long refillIntervalNs;
/** Per-key buckets, created on demand. */
private final ConcurrentHashMap<String, Bucket> buckets = new ConcurrentHashMap<>();
/**
* Creates a token-bucket limiter.
*
* @param requestsPerSecond the sustained refill rate in tokens (requests) per second
* @param burstCapacity the maximum burst size, i.e. the bucket capacity in tokens
*/
public TokenBucketLimiter(long requestsPerSecond, long burstCapacity) {
this.capacity = burstCapacity;
this.tokensPerNano = (double) requestsPerSecond / 1_000_000_000.0;
this.refillIntervalNs = 1_000_000_000L / Math.max(1, requestsPerSecond);
}
/**
* {@inheritDoc}
*
* <p>Lazily creates the bucket for {@code key} (initially full) and attempts to consume one
* token from it.</p>
*/
@Override
public Result tryAcquire(String key, long nowNanos) {
Bucket b = buckets.computeIfAbsent(key, k -> new Bucket(capacity, nowNanos));
return b.tryAcquire(nowNanos, capacity, tokensPerNano, refillIntervalNs);
}
/**
* Evicts buckets that have not been accessed within the given age, bounding memory use.
*
* @param olderThanNanos maximum idle age in nanoseconds before a bucket is removed
*/
public void cleanup(long olderThanNanos) {
long now = System.nanoTime();
buckets.entrySet().removeIf(e -> now - e.getValue().lastAccess() > olderThanNanos);
}
/**
* A single client's token bucket. Tokens are stored in fixed-point form (multiplied by
* 1e9) to retain sub-token precision while using integer atomics.
*
* @param tokensFixed current token count in fixed-point (tokens &times; 1e9)
* @param lastRefillNanos timestamp of the last refill/consume, in nanoseconds
*/
private record Bucket(AtomicLong tokensFixed, AtomicLong lastRefillNanos) {
/**
* Creates a full bucket.
*
* @param tokensFixed initial token count (in whole tokens, scaled internally)
* @param lastRefillNanos the creation timestamp in nanoseconds
*/
private Bucket(long tokensFixed, long lastRefillNanos) {
this(new AtomicLong(tokensFixed * 1_000_000_000L), new AtomicLong(lastRefillNanos));
}
/**
* Returns the timestamp of the last access, used by {@link #cleanup(long)}.
*
* @return the last-refill timestamp in nanoseconds
*/
long lastAccess() {
return lastRefillNanos.get();
}
/**
* Refills the bucket according to elapsed time and attempts to consume one token,
* retrying via compare-and-set on contention.
*
* @param now the current time in nanoseconds
* @param capacity the bucket capacity in whole tokens
* @param tokensPerNano the refill rate in tokens per nanosecond
* @param refillIntervalNs the nominal nanoseconds per token (unused in the hot path
* but kept for symmetry/retry computation)
* @return an allow result with the remaining tokens, or a deny result with a retry
* hint when fewer than one token is available
*/
Result tryAcquire(long now, long capacity, double tokensPerNano, long refillIntervalNs) {
while (true) {
long lastRefill = lastRefillNanos.get();
long currentTokens = tokensFixed.get();
long elapsed = now - lastRefill;
long refilled = currentTokens;
if (elapsed > 0) {
long addedFixed = (long) (elapsed * tokensPerNano * 1_000_000_000.0);
refilled = Math.min(currentTokens + addedFixed, capacity * 1_000_000_000L);
}
long oneTokenFixed = 1_000_000_000L;
if (refilled < oneTokenFixed) {
long deficitFixed = oneTokenFixed - refilled;
long retryNs = (long) (deficitFixed / (tokensPerNano * 1_000_000_000.0));
return Result.deny(capacity, Math.max(1, retryNs / 1_000_000));
}
long newTokens = refilled - oneTokenFixed;
if (tokensFixed.compareAndSet(currentTokens, newTokens)) {
lastRefillNanos.set(now);
@@ -64,4 +127,4 @@ public final class TokenBucketLimiter implements RateLimiter {
}
}
}
}
}