Redis pub/sub with Lettuce
Implement Redis pub/sub messaging in Java with Lettuce
This guide shows you how to implement a Redis-backed pub/sub broadcaster in Java with the Lettuce client library. It includes a small local web server built on the JDK's com.sun.net.httpserver so you can publish messages to named channels, add and remove subscribers live, and watch Redis fan out each message to every interested listener.
Overview
Pub/sub lets your application broadcast events — chat messages, cache invalidation signals, presence updates, notifications — to many consumers without per-pair wiring. The publisher names a channel; every client currently subscribed to that channel receives the message, in publish order, with sub-millisecond fan-out.
That gives you:
- Many-to-many event delivery with no message storage cost in Redis
- Exact-match subscriptions (
SUBSCRIBE orders:new) for known topics - Pattern subscriptions (
PSUBSCRIBE notifications:*) for whole topic hierarchies - Live server-side introspection through
PUBSUB CHANNELS,PUBSUB NUMSUB, andPUBSUB NUMPAT - At-most-once delivery: subscribers that are offline when a message is published miss it, so durable state should live in keys or a Stream, not in the pub/sub channel itself
In this example, the publisher side calls PUBLISH with a JSON-encoded body and counts how many subscribers Redis reported delivering to. Each in-process subscriber owns its own pub/sub connection and a Lettuce listener that pumps incoming messages into a callback.
How it works
The flow looks like this:
- The application calls
hub.subscribe(name, channels)orhub.psubscribe(name, patterns) - The helper opens a dedicated
StatefulRedisPubSubConnection, attaches aRedisPubSubListener, and issuesSUBSCRIBEorPSUBSCRIBEon it - The application (or another process) calls
hub.publish(channel, message) - Redis fans the message out over every subscribing client's open socket
- Each subscriber's listener wraps the raw message as a
ReceivedMessage, appends it to a per-subscriber ring buffer, and increments the received counter - The publisher receives the integer subscriber count back from
PUBLISH, which is the number of clients Redis delivered to right then
Pattern subscriptions match channels by glob (*, ?, [abc]). A single message that matches both an exact subscription and a pattern subscription is delivered twice — once through RedisPubSubListener.message(channel, msg) and once through RedisPubSubListener.message(pattern, channel, msg).
The pub/sub hub helper
The RedisPubSubHub class wraps the publish, subscribe, and introspection operations
(source):
import io.lettuce.core.RedisClient;
import io.lettuce.core.RedisURI;
import io.lettuce.core.api.StatefulRedisConnection;
import java.util.Arrays;
RedisClient client = RedisClient.create(
RedisURI.builder().withHost("localhost").withPort(6379).build());
StatefulRedisConnection<String, String> connection = client.connect();
RedisPubSubHub hub = new RedisPubSubHub(client, connection);
// Exact-match subscriber.
hub.subscribe("orders-listener", Arrays.asList("orders:new"));
// Pattern subscriber covering an entire topic hierarchy.
hub.psubscribe("all-notifications", Arrays.asList("notifications:*"));
// Publish — returns Redis' delivered count for this PUBLISH.
java.util.Map<String, Object> payload = new java.util.LinkedHashMap<>();
payload.put("order_id", 42);
payload.put("total", 199.0);
int delivered = hub.publish("orders:new", payload);
System.out.printf("Redis delivered to %d subscriber(s)%n", delivered);
// Look at what each subscriber received.
for (RedisPubSubHub.Subscription sub : hub.subscriptions()) {
System.out.println(sub.name() + " " + sub.receivedTotal() + " messages");
for (RedisPubSubHub.ReceivedMessage m : sub.messages(5)) {
System.out.println(" " + m.channel + " " + m.payload);
}
}
hub.unsubscribe("orders-listener");
hub.shutdown(); // closes every remaining subscription
connection.close();
client.shutdown();
Data model
Pub/sub has no Redis keyspace footprint of its own — channels are server-side routing entries, not stored values. The hub keeps its own bookkeeping in process memory:
RedisPubSubHub (in-process)
subscriptions Map<String, Subscription>
publishedTotal AtomicLong
deliveredTotal AtomicLong
channelPublished Map<channel, Long>
Subscription (in-process, one per subscriber)
name String
targets List<channel | pattern>
isPattern boolean
buffer Deque<ReceivedMessage> (capped, default 50)
received long
psConnection StatefulRedisPubSubConnection<String, String>
listener RedisPubSubListener<String, String>
The implementation uses:
PUBLISHto fan a JSON-encoded message out to every subscriber of a channelSUBSCRIBEfor exact-match subscribersPSUBSCRIBEfor glob-style pattern subscribersPUBSUB CHANNELSto list the channels with at least one active exact-match subscriberPUBSUB NUMSUBto count subscribers per channelPUBSUB NUMPATto count active pattern subscriptions server-wide- Lettuce's
RedisPubSubListenerinterface to dispatch messages without writing a thread loop by hand — messages are delivered on a Netty event-loop thread
Publishing messages
publish() JSON-encodes the message body, calls PUBLISH, and updates the per-channel publish counter:
public int publish(String channel, Object message) {
String payload = JsonCodec.encode(message);
long delivered = connection.sync().publish(channel, payload);
publishedTotal.incrementAndGet();
deliveredTotal.addAndGet(delivered);
channelPublished.merge(channel, 1L, Long::sum);
return (int) delivered;
}
The integer returned by PUBLISH is what Redis itself reports — the number of subscribers (direct and pattern) that received the message in that call. It's a useful sanity check that the channel name is actually being listened to: a steady stream of 0s means you have a typo somewhere or your subscriber crashed.
Publishing reuses the shared StatefulRedisConnection, which is thread-safe for individual commands, so concurrent HTTP handlers can publish without coordination.
Subscribing to channels
subscribe() creates a named in-process Subscription that owns its own pub/sub connection:
public Subscription subscribe(String name, List<String> channels) {
return register(name, channels, false);
}
Inside the Subscription constructor, the helper opens a dedicated pub/sub connection, registers a listener, then issues SUBSCRIBE:
this.psConnection = client.connectPubSub();
this.psConnection.addListener(new RedisPubSubListener<String, String>() {
@Override public void message(String channel, String msg) {
record(channel, null, msg);
}
@Override public void message(String pattern, String channel, String msg) {
record(channel, pattern, msg);
}
@Override public void subscribed(String channel, long count) {}
@Override public void psubscribed(String pattern, long count) {}
@Override public void unsubscribed(String channel, long count) {}
@Override public void punsubscribed(String pattern, long count) {}
});
if (isPattern) {
psConnection.sync().psubscribe(targets.toArray(new String[0]));
} else {
psConnection.sync().subscribe(targets.toArray(new String[0]));
}
A few details matter here:
- Each
Subscriptiongets its ownStatefulRedisPubSubConnection(and therefore its own Redis socket). Lettuce switches a pub/sub connection into subscribe-only mode after the firstSUBSCRIBEorPSUBSCRIBE, so sharing one across business-logic subscribers would couple their lifetimes — closing one would close the channel for the others. RedisPubSubListeneroverloadsmessage()twice: the two-argument form for plainSUBSCRIBEdeliveries and the three-argument form forPSUBSCRIBEdeliveries that carry the originating pattern. The helper routes both into a singlerecord()method that writes into a bounded ring buffer.- Messages arrive on a Netty event-loop thread, not on the calling HTTP handler thread. The buffer is guarded with a
synchronizedblock so a polling/staterequest can read it safely while a publish is in flight. - The constructor uses Lettuce's
sync()API (notasync()) so it blocks until Redis acknowledges the SUBSCRIBE for every channel before theSubscriptionis handed back to the caller. With the unawaitedasync()variant, aPUBLISHissued immediately after subscribing could race ahead of the acknowledgement and the first message would be lost.
Pattern subscriptions with PSUBSCRIBE
psubscribe() works the same way but routes messages through PSUBSCRIBE so each binding is a glob, not a literal channel name:
hub.psubscribe("all-notifications", Arrays.asList("notifications:*"));
hub.psubscribe("cache-invalidator", Arrays.asList("cache:invalidate:*"));
When a published channel matches a pattern, Lettuce dispatches through the three-argument message(String pattern, String channel, String body) overload and the helper records both the matched channel and the original pattern:
@Override
public void message(String pattern, String channel, String msg) {
record(channel, pattern, msg); // exact subscriptions pass null for pattern
}
That distinction is useful for routing: a pattern subscriber can do one thing for the whole hierarchy (e.g., increment a counter) and dispatch on the specific channel within its callback (e.g., "invalidate this region's cache").
Inspecting active subscribers
Redis exposes a small set of pub/sub introspection commands that report on subscriber state without traversing any keyspace:
hub.activeChannels("*"); // PUBSUB CHANNELS *
hub.channelSubscriberCounts(Arrays.asList("orders:new")); // PUBSUB NUMSUB ...
hub.patternSubscriberCount(); // PUBSUB NUMPAT
Lettuce exposes these as ordinary commands on RedisCommands: pubsubChannels(pattern), pubsubNumsub(channels...), and pubsubNumpat(). The helper runs each one against the shared StatefulRedisConnection.
PUBSUB CHANNELS only reports channels with at least one exact-match subscriber — pattern subscribers do not appear here. That's a deliberate Redis design choice: a glob like * would otherwise show up as a subscriber to every conceivable channel. PUBSUB NUMPAT covers the pattern side as a single global count.
Stats and history
stats() reports publish and receive counters plus the size of the subscription registry:
public Map<String, Object> stats() {
List<Subscription> subs = subscriptions();
long received = 0;
for (Subscription sub : subs) received += sub.receivedTotal();
Map<String, Object> out = new LinkedHashMap<>();
out.put("published_total", publishedTotal.get());
out.put("delivered_total", deliveredTotal.get()); // sum of PUBLISH return values
out.put("received_total", received);
out.put("active_subscriptions", (long) subs.size());
out.put("channel_published", new LinkedHashMap<>(channelPublished));
out.put("pattern_subscriptions", patternSubscriberCount());
return out;
}
delivered_total is what Redis itself counted; received_total is what this process's in-memory subscribers saw. In a single-process demo they should track each other closely — a sustained divergence usually means a listener threw, or a subscriber's pub/sub connection dropped while a publisher kept publishing. (Pub/sub is at-most-once: if your subscriber wasn't connected at publish time, the message is gone.)
Prerequisites
- Redis 6.2 or later running locally on the default port (6379). Earlier versions still work for plain
PUBLISH/SUBSCRIBE;PUBSUB NUMPATis older than that. - JDK 11 or later.
- The Lettuce JAR (6.1 or later) and its Netty + Reactor dependencies on your classpath. Get them from Maven Central, or via Maven/Gradle in a project setup.
Running the demo
Get the source files
The demo consists of two Java files. Download them from the java-lettuce source folder on GitHub, or grab them with curl:
mkdir pub-sub-demo && cd pub-sub-demo
BASE=https://raw.githubusercontent.com/redis/docs/main/content/develop/use-cases/pub-sub/java-lettuce
curl -O $BASE/RedisPubSubHub.java
curl -O $BASE/DemoServer.java
You also need a lib/ directory containing the Lettuce client and its runtime dependencies — at minimum:
lettuce-core-6.x.jarnetty-buffer-4.1.x.jar,netty-codec-4.1.x.jar,netty-common-4.1.x.jar,netty-handler-4.1.x.jar,netty-resolver-4.1.x.jar,netty-transport-4.1.x.jar,netty-transport-native-unix-common-4.1.x.jarreactor-core-3.x.jar,reactive-streams-1.0.x.jar
The simplest way to collect them is with Maven. Create a minimal pom.xml declaring io.lettuce:lettuce-core as the only dependency, then run mvn dependency:copy-dependencies -DoutputDirectory=lib.
Start the demo server
From the directory containing RedisPubSubHub.java, DemoServer.java, and lib/:
javac -cp 'lib/*' RedisPubSubHub.java DemoServer.java
java -cp '.:lib/*' DemoServer --port 8099 --redis-host localhost --redis-port 6379
You should see:
Redis pub/sub demo server listening on http://127.0.0.1:8099
Using Redis at localhost:6379
Seeded 3 default subscription(s)
Open http://127.0.0.1:8099 in a browser. You can:
- Publish messages of any text to any channel name in any batch size.
- Add named subscribers that listen on either a specific channel (
orders:new) or a glob pattern (notifications:*). A single subscriber can listen on multiple targets — enter them comma-separated. - Watch each subscriber's incoming-message panel update every 800 ms.
- See the server-side view:
PUBSUB CHANNELSlists exact-match channels with subscribers,PUBSUB NUMSUBgives per-channel counts, andPUBSUB NUMPATcounts active pattern subscriptions. - Click Reset to drop every subscription, zero the counters, and re-seed the three default subscribers.
If your Redis server is running elsewhere, start the demo with --redis-host and --redis-port.
Production usage
Pub/sub is at-most-once — pair it with durable state if you need replay
A subscriber that's offline when a message is published misses it permanently. For events you can't afford to lose, write the durable record (the order row, the cache key version, the audit log entry) to its primary store, then PUBLISH a notification so live consumers can pick it up immediately. On reconnect, consumers reconcile by reading the durable store, not by waiting for missed pub/sub messages. If you actually need replay or at-least-once delivery, switch to Redis Streams with consumer groups.
Use a separate StatefulRedisPubSubConnection per subscriber
Lettuce switches a pub/sub connection into subscribe-only mode after SUBSCRIBE or PSUBSCRIBE: ordinary commands (GET, HSET, etc.) on that connection will block or fail. Always create the pub/sub connection from RedisClient.connectPubSub() — separate from the connection you use for PUBLISH and other commands — and give every business-logic subscriber its own. Sharing one pub/sub connection across subscribers couples their lifetimes (closing one closes the channel for the others) and serialises listener invocations on a single Netty event-loop thread.
Don't do heavy work inside the listener callback
RedisPubSubListener.message() runs on a Netty event-loop thread. If your listener blocks (synchronous HTTP call, big computation, slow JDBC write), it parks an I/O thread that should be handling other connections, and the next message on the same socket waits behind it. For heavier work, the listener should hand the message off to an ExecutorService worker pool, a BlockingQueue, or — for true durable handoff — a Redis Streams consumer group.
Choose a topic naming convention up front
A flat namespace gets ugly fast — email, email_high_priority, email_high_priority_billing. Pick a colon-separated hierarchy (notifications:billing:invoice, cache:invalidate:products:p-001) so consumers can subscribe at the right level: a billing service uses notifications:billing:*, the audit logger uses notifications:*. Glob patterns are evaluated for every published message, so don't go wild with multiple wildcards on hot paths — *:*:* matches everything and costs more than a flat notifications:* would.
Tune the subscriber buffer for your traffic shape
The demo caps each subscriber's in-memory message buffer at 50 entries. That's right for showing the recent activity in a UI, but a real subscriber typically processes each message and discards it — the buffer is only there for human inspection. If you keep a buffer, make sure it's bounded; an unbounded ring on a chatty pattern subscriber will eventually OOM the process.
Sharded pub/sub on a Redis Cluster
On a Redis Cluster, plain PUBLISH fans every message out to every node via the cluster bus, which becomes a hotspot at high throughput. Redis 7.0 added sharded pub/sub: channels are hashed to slots, and SPUBLISH / SSUBSCRIBE only touch the shard that owns the slot. Lettuce exposes these as spublish() and ssubscribe() on the cluster connection. If you're scaling pub/sub on a cluster, prefer the sharded commands and pick channel names whose hash distribution matches your traffic.
Inspect pub/sub state directly in Redis
Because pub/sub has no keyspace, KEYS/SCAN won't show you anything. Use the introspection commands instead:
# Which channels currently have at least one exact-match subscriber?
redis-cli pubsub channels '*'
# How many subscribers does each channel have?
redis-cli pubsub numsub orders:new notifications:billing chat:lobby
# How many active pattern subscriptions across the whole server?
redis-cli pubsub numpat
# Subscribe interactively from the CLI to watch traffic on a pattern
redis-cli psubscribe 'orders:*'
redis-cli in subscribe mode only exits with Ctrl-C — it can't issue any other commands while subscribed.
Learn more
This example uses the following Redis commands:
PUBLISHto fan a message out to every subscriber of a channel.SUBSCRIBEandUNSUBSCRIBEfor exact-match topic subscriptions.PSUBSCRIBEandPUNSUBSCRIBEfor glob-style pattern subscriptions.PUBSUB CHANNELSto list channels with at least one active exact-match subscriber.PUBSUB NUMSUBto count subscribers per named channel.PUBSUB NUMPATto count active pattern subscriptions server-wide.
See the Lettuce guide for full client reference, including the StatefulRedisPubSubConnection and RedisPubSubListener types used in this example.