Pulsar Java client

You can use a Pulsar Java client to create the Java producer, consumer, readers and TableView of messages and to perform administrative tasks. The current Java client version is 2.10.0.

All the methods in producer, consumer, readers and TableView of a Java client are thread-safe.

Javadoc for the Pulsar client is divided into two domains by package as follows.

This document focuses only on the client API for producing and consuming messages on Pulsar topics. For how to use the Java admin client, see Pulsar admin interface.

Installation

The latest version of the Pulsar Java client library is available via Maven Central. To use the latest version, add the pulsar-client library to your build configuration.

tip

• pulsar-client and pulsar-client-admin shade dependencies via maven-shade-plugin to avoid conflicts of the underlying dependency packages (such as Netty). If you do not want to manage dependency conflicts manually, you can use them.
• pulsar-client-original and pulsar-client-admin-original does not shade dependencies. If you want to manage dependencies manually, you can use them.

Maven

If you use Maven, add the following information to the pom.xml file.

<!-- in your <properties> block -->
<pulsar.version>2.10.0</pulsar.version>
<!-- in your <dependencies> block -->
<dependency>
  <groupId>org.apache.pulsar</groupId>
  <artifactId>pulsar-client</artifactId>
  <version>${pulsar.version}</version>
</dependency>

Gradle

If you use Gradle, add the following information to the build.gradle file.

def pulsarVersion = '2.10.0'
dependencies {
    compile group: 'org.apache.pulsar', name: 'pulsar-client', version: pulsarVersion
}

Connection URLs

To connect to Pulsar using client libraries, you need to specify a Pulsar protocol URL.

You can assign Pulsar protocol URLs to specific clusters and use the pulsar scheme. The default port is 6650. The following is an example of localhost.

pulsar://localhost:6650

If you have multiple brokers, the URL is as follows.

pulsar://localhost:6550,localhost:6651,localhost:6652

A URL for a production Pulsar cluster is as follows.

pulsar://pulsar.us-west.example.com:6650

If you use TLS authentication, the URL is as follows.

pulsar+ssl://pulsar.us-west.example.com:6651

Client

You can instantiate a PulsarClient object using just a URL for the target Pulsar cluster like this:

PulsarClient client = PulsarClient.builder()
        .serviceUrl("pulsar://localhost:6650")
        .build();

If you have multiple brokers, you can initiate a PulsarClient like this:

PulsarClient client = PulsarClient.builder()
        .serviceUrl("pulsar://localhost:6650,localhost:6651,localhost:6652")
        .build();

Default broker URLs for standalone clusters

If you run a cluster in standalone mode, the broker is available at the pulsar://localhost:6650 URL by default.

If you create a client, you can use the loadConf configuration. The following parameters are available in loadConf.

Check out the Javadoc for the PulsarClient class for a full list of configurable parameters.

In addition to client-level configuration, you can also apply producer and consumer specific configuration as described in sections below.

Client memory allocator configuration

You can set the client memory allocator configurations through Java properties.

Example:

-Dpulsar.allocator.pooled=true
-Dpulsar.allocator.exit_on_oom=false
-Dpulsar.allocator.leak_detection=Disabled
-Dpulsar.allocator.out_of_memory_policy=ThrowException

Cluster-level failover

This chapter describes the concept, benefits, use cases, constraints, usage, working principles, and more information about the cluster-level failover. It contains the following sections:

• What is cluster-level failover?

  • Concept of cluster-level failover

  • Why use cluster-level failover?

  • When to use cluster-level failover?

  • When cluster-level failover is triggered?

  • Why does cluster-level failover fail?

  • What are the limitations of cluster-level failover?

  • What are the relationships between cluster-level failover and geo-replication?

• How to use cluster-level failover?

• How does cluster-level failover work?

What is cluster-level failover

This chapter helps you better understand the concept of cluster-level failover.

Concept of cluster-level failover

• Automatic cluster-level failover
• Controlled cluster-level failover

Automatic cluster-level failover supports Pulsar clients switching from a primary cluster to one or several backup clusters automatically and seamlessly when it detects a failover event based on the configured detecting policy set by users.

Controlled cluster-level failover supports Pulsar clients switching from a primary cluster to one or several backup clusters. The switchover is manually set by administrators.

Once the primary cluster functions again, Pulsar clients can switch back to the primary cluster. Most of the time users won’t even notice a thing. Users can keep using applications and services without interruptions or timeouts.

Why use cluster-level failover?

The cluster-level failover provides fault tolerance, continuous availability, and high availability together. It brings a number of benefits, including but not limited to:

• Reduced cost: services can be switched and recovered automatically with no data loss.

• Simplified management: businesses can operate on an “always-on” basis since no immediate user intervention is required.

• Improved stability and robustness: it ensures continuous performance and minimizes service downtime.

When to use cluster-level failover?

The cluster-level failover protects your environment in a number of ways, including but not limited to:

• Disaster recovery: cluster-level failover can automatically and seamlessly transfer the production workload on a primary cluster to one or several backup clusters, which ensures minimum data loss and reduced recovery time.

• Planned migration: if you want to migrate production workloads from an old cluster to a new cluster, you can improve the migration efficiency with cluster-level failover. For example, you can test whether the data migration goes smoothly in case of a failover event, identify possible issues and risks before the migration.

When cluster-level failover is triggered?

• Automatic cluster-level failover
• Controlled cluster-level failover

Automatic cluster-level failover is triggered when Pulsar clients cannot connect to the primary cluster for a prolonged period of time. This can be caused by any number of reasons including, but not limited to:

• Network failure: internet connection is lost.

• Power failure: shutdown time of a primary cluster exceeds time limits.

• Service error: errors occur on a primary cluster (for example, the primary cluster does not function because of time limits).

• Crashed storage space: the primary cluster does not have enough storage space, but the corresponding storage space on the backup server functions normally.

Controlled cluster-level failover is triggered when administrators set the switchover manually.

Why does cluster-level failover fail?

Obviously, the cluster-level failover does not succeed if the backup cluster is unreachable by active Pulsar clients. This can happen for many reasons, including but not limited to:

• Power failure: the backup cluster is shut down or does not function normally.

• Crashed storage space: primary and backup clusters do not have enough storage space.

• If the failover is initiated, but no cluster can assume the role of an available cluster due to errors, and the primary cluster is not able to provide service normally.

• If you manually initiate a switchover, but services cannot be switched to the backup cluster server, then the system will attempt to switch services back to the primary cluster.

• Fail to authenticate or authorize between 1) primary and backup clusters, or 2) between two backup clusters.

What are the limitations of cluster-level failover?

Currently, cluster-level failover can perform probes to prevent data loss, but it can not check the status of backup clusters. If backup clusters are not healthy, you cannot produce or consume data.

What are the relationships between cluster-level failover and geo-replication?

The cluster-level failover is an extension of geo-replication to improve stability and robustness. The cluster-level failover depends on geo-replication, and they have some differences as below.

How to use cluster-level failover

This section guides you through every step on how to configure cluster-level failover.

Tip

• You should configure cluster-level failover only when the cluster contains sufficient resources to handle all possible consequences. Workload intensity on the backup cluster may increase significantly.

• Connect clusters to an uninterruptible power supply (UPS) unit to reduce the risk of unexpected power loss.

Requirements

• Pulsar client 2.10 or later versions.

• For backup clusters:

  • The number of BooKeeper nodes should be equal to or greater than the ensemble quorum.

  • The number of ZooKeeper nodes should be equal to or greater than 3.

• Turn on geo-replication between the primary cluster and any dependent cluster (primary to backup or backup to backup) to prevent data loss.

• Set replicateSubscriptionState to true when creating consumers.

• Automatic cluster-level failover

• Controlled cluster-level failover

This is an example of how to construct a Java Pulsar client to use automatic cluster-level failover. The switchover is triggered automatically.

  private PulsarClient getAutoFailoverClient() throws PulsarClientException {
        ServiceUrlProvider failover = AutoClusterFailover.builder()
                .primary("pulsar://localhost:6650")
                .secondary(Collections.singletonList("pulsar://other1:6650","pulsar://other2:6650"))
                .failoverDelay(30, TimeUnit.SECONDS)
                .switchBackDelay(60, TimeUnit.SECONDS)
                .checkInterval(1000, TimeUnit.MILLISECONDS)
                .secondaryTlsTrustCertsFilePath("/path/to/ca.cert.pem")
    .secondaryAuthentication("org.apache.pulsar.client.impl.auth.AuthenticationTls",
"tlsCertFile:/path/to/my-role.cert.pem,tlsKeyFile:/path/to/my-role.key-pk8.pem")
                .build();
        PulsarClient pulsarClient = PulsarClient.builder()
                .build();
        failover.initialize(pulsarClient);
        return pulsarClient;
    }

Configure the following parameters:

This is an example of how to construct a Java Pulsar client to use controlled cluster-level failover. The switchover is triggered by administrators manually.

Note: you can have one or several backup clusters but can only specify one.

 public PulsarClient getControlledFailoverClient() throws IOException {
Map<String, String> header = new HashMap(); 
  header.put(“service_user_id”, “my-user”);
  header.put(“service_password”, “tiger”);
  header.put(“clusterA”, “tokenA”);
  header.put(“clusterB”, “tokenB”);
  ServiceUrlProvider provider = 
      ControlledClusterFailover.builder()
        .defaultServiceUrl("pulsar://localhost:6650")
        .checkInterval(1, TimeUnit.MINUTES)
        .urlProvider("http://localhost:8080/test")
        .urlProviderHeader(header)
        .build();
  PulsarClient pulsarClient = 
     PulsarClient.builder()
      .build();
  provider.initialize(pulsarClient);
  return pulsarClient;
}

Here is an example of how urlProviderHeader works.

Assume that you want to connect Pulsar client 1 to cluster A.

1. Pulsar client 1 sends the token t1 to the URL provider service.

2. The URL provider service returns the credential c1 and the cluster A URL to the Pulsar client.

   The URL provider service manages all tokens and credentials. It returns different credentials based on different tokens and different target cluster URLs to different Pulsar clients.

   Note: the credential must be in a JSON file and contain parameters as shown.

   {
   "serviceUrl": "pulsar+ssl://target:6651", 
   "tlsTrustCertsFilePath": "/security/ca.cert.pem",
   "authPluginClassName":"org.apache.pulsar.client.impl.auth.AuthenticationTls",
   "authParamsString": " \"tlsCertFile\": \"/security/client.cert.pem\" 
       \"tlsKeyFile\": \"/security/client-pk8.pem\" "
   }

1. Pulsar client 1 connects to cluster A using credential c1.

How does cluster-level failover work?

This chapter explains the working process of cluster-level failover. For more implementation details, see PIP-121.

• Automatic cluster-level failover
• Controlled cluster-level failover

In automatic failover cluster, the primary cluster and backup cluster are aware of each other’s availability. The automatic failover cluster performs the following actions without administrator intervention:

1. The Pulsar client runs a probe task at intervals defined in checkInterval.

2. If the probe task finds the failure time of the primary cluster exceeds the time set in the failoverDelay parameter, it searches backup clusters for an available healthy cluster.

   2a) If there are healthy backup clusters, the Pulsar client switches to a backup cluster in the order defined in secondary.

   2b) If there is no healthy backup cluster, the Pulsar client does not perform the switchover, and the probe task continues to look for an available backup cluster.

3. The probe task checks whether the primary cluster functions well or not.

   3a) If the primary cluster comes back and the continuous healthy time exceeds the time set in switchBackDelay, the Pulsar client switches back to the primary cluster.

   3b) If the primary cluster does not come back, the Pulsar client does not perform the switchover.

1. The Pulsar client runs a probe task at intervals defined in checkInterval.

2. The probe task fetches the service URL configuration from the URL provider service, which is configured by urlProvider.

   2a) If the service URL configuration is changed, the probe task switches to the target cluster without checking the health status of the target cluster.

   2b) If the service URL configuration is not changed, the Pulsar client does not perform the switchover.

3. If the Pulsar client switches to the target cluster, the probe task continues to fetch service URL configuration from the URL provider service at intervals defined in checkInterval.

   3a) If the service URL configuration is changed, the probe task switches to the target cluster without checking the health status of the target cluster.

   3b) If the service URL configuration is not changed, it does not perform the switchover.

Producer

In Pulsar, producers write messages to topics. Once you’ve instantiated a PulsarClient object (as in the section above), you can create a Producer for a specific Pulsar topic.

Producer<byte[]> producer = client.newProducer()
        .topic("my-topic")
        .create();
// You can then send messages to the broker and topic you specified:
producer.send("My message".getBytes());

By default, producers produce messages that consist of byte arrays. You can produce different types by specifying a message schema.

Producer<String> stringProducer = client.newProducer(Schema.STRING)
        .topic("my-topic")
        .create();
stringProducer.send("My message");

Make sure that you close your producers, consumers, and clients when you do not need them.

producer.close();
consumer.close();
client.close();

Close operations can also be asynchronous:

producer.closeAsync()
   .thenRun(() -> System.out.println("Producer closed"))
   .exceptionally((ex) -> {
       System.err.println("Failed to close producer: " + ex);
       return null;
   });

Configure producer

If you instantiate a Producer object by specifying only a topic name as the example above, the default configuration of producer is used.

If you create a producer, you can use the loadConf configuration. The following parameters are available in loadConf.

You can configure parameters if you do not want to use the default configuration.

For a full list, see the Javadoc for the ProducerBuilder class. The following is an example.

Producer<byte[]> producer = client.newProducer()
    .topic("my-topic")
    .batchingMaxPublishDelay(10, TimeUnit.MILLISECONDS)
    .sendTimeout(10, TimeUnit.SECONDS)
    .blockIfQueueFull(true)
    .create();

Message routing

When using partitioned topics, you can specify the routing mode whenever you publish messages using a producer. For more information on specifying a routing mode using the Java client, see the Partitioned Topics cookbook.

Async send

You can publish messages asynchronously using the Java client. With async send, the producer puts the message in a blocking queue and returns it immediately. Then the client library sends the message to the broker in the background. If the queue is full (max size configurable), the producer is blocked or fails immediately when calling the API, depending on arguments passed to the producer.

The following is an example.

producer.sendAsync("my-async-message".getBytes()).thenAccept(msgId -> {
    System.out.println("Message with ID " + msgId + " successfully sent");
});

As you can see from the example above, async send operations return a MessageId wrapped in a CompletableFuture.

Configure messages

In addition to a value, you can set additional items on a given message:

producer.newMessage()
    .key("my-message-key")
    .value("my-async-message".getBytes())
    .property("my-key", "my-value")
    .property("my-other-key", "my-other-value")
    .send();

You can terminate the builder chain with sendAsync() and get a future return.

Enable chunking

Message chunking enables Pulsar to process large payload messages by splitting the message into chunks at the producer side and aggregating chunked messages at the consumer side.

The message chunking feature is OFF by default. The following is an example about how to enable message chunking when creating a producer.

Producer<byte[]> producer = client.newProducer()
        .topic(topic)
        .enableChunking(true)
        .enableBatching(false)
        .create();

By default, producer chunks the large message based on max message size (maxMessageSize) configured at broker (eg: 5MB). However, client can also configure max chunked size using producer configuration chunkMaxMessageSize.

Note: To enable chunking, you need to disable batching (enableBatching\=false) concurrently.

Consumer

In Pulsar, consumers subscribe to topics and handle messages that producers publish to those topics. You can instantiate a new consumer by first instantiating a PulsarClient object and passing it a URL for a Pulsar broker (as above).

Once you’ve instantiated a PulsarClient object, you can create a Consumer by specifying a topic and a subscription.

Consumer consumer = client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .subscribe();

The subscribe method will auto subscribe the consumer to the specified topic and subscription. One way to make the consumer listen on the topic is to set up a while loop. In this example loop, the consumer listens for messages, prints the contents of any received message, and then acknowledges that the message has been processed. If the processing logic fails, you can use negative acknowledgement to redeliver the message later.

while (true) {
  // Wait for a message
  Message msg = consumer.receive();
  try {
      // Do something with the message
      System.out.println("Message received: " + new String(msg.getData()));
      // Acknowledge the message so that it can be deleted by the message broker
      consumer.acknowledge(msg);
  } catch (Exception e) {
      // Message failed to process, redeliver later
      consumer.negativeAcknowledge(msg);
  }
}

If you don’t want to block your main thread and rather listen constantly for new messages, consider using a MessageListener.

MessageListener myMessageListener = (consumer, msg) -> {
  try {
      System.out.println("Message received: " + new String(msg.getData()));
      consumer.acknowledge(msg);
  } catch (Exception e) {
      consumer.negativeAcknowledge(msg);
  }
}
Consumer consumer = client.newConsumer()
     .topic("my-topic")
     .subscriptionName("my-subscription")
     .messageListener(myMessageListener)
     .subscribe();

Configure consumer

If you instantiate a Consumer object by specifying only a topic and subscription name as in the example above, the consumer uses the default configuration.

When you create a consumer, you can use the loadConf configuration. The following parameters are available in loadConf.

client.newConsumer()
.deadLetterPolicy(DeadLetterPolicy.builder().maxRedeliverCount(10).build())
.subscribe();

client.newConsumer()
.deadLetterPolicy(DeadLetterPolicy.builder().maxRedeliverCount(10)
.deadLetterTopic(“your-topic-name”).build())
.subscribe();

You can configure parameters if you do not want to use the default configuration. For a full list, see the Javadoc for the ConsumerBuilder class.

The following is an example.

Consumer consumer = client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .ackTimeout(10, TimeUnit.SECONDS)
        .subscriptionType(SubscriptionType.Exclusive)
        .subscribe();

Async receive

The receive method receives messages synchronously (the consumer process is blocked until a message is available). You can also use async receive, which returns a CompletableFuture object immediately once a new message is available.

The following is an example.

CompletableFuture<Message> asyncMessage = consumer.receiveAsync();

Async receive operations return a Message wrapped inside of a CompletableFuture.

Batch receive

Use batchReceive to receive multiple messages for each call.

The following is an example.

Messages messages = consumer.batchReceive();
for (Object message : messages) {
  // do something
}
consumer.acknowledge(messages)

note

Batch receive policy limits the number and bytes of messages in a single batch. You can specify a timeout to wait for enough messages. The batch receive is completed if any of the following condition is met: enough number of messages, bytes of messages, wait timeout.

Consumer consumer = client.newConsumer()
.topic("my-topic")
.subscriptionName("my-subscription")
.batchReceivePolicy(BatchReceivePolicy.builder()
.maxNumMessages(100)
.maxNumBytes(1024 * 1024)
.timeout(200, TimeUnit.MILLISECONDS)
.build())
.subscribe();

The default batch receive policy is:

BatchReceivePolicy.builder()
.maxNumMessage(-1)
.maxNumBytes(10 * 1024 * 1024)
.timeout(100, TimeUnit.MILLISECONDS)
.build();

Configure chunking

You can limit the maximum number of chunked messages a consumer maintains concurrently by configuring the maxPendingChunkedMessage and autoAckOldestChunkedMessageOnQueueFull parameters. When the threshold is reached, the consumer drops pending messages by silently acknowledging them or asking the broker to redeliver them later. The expireTimeOfIncompleteChunkedMessage parameter decides the time interval to expire incomplete chunks if the consumer fails to receive all chunks of a message within the specified time period.

The following is an example of how to configure message chunking.

Consumer<byte[]> consumer = client.newConsumer()
        .topic(topic)
        .subscriptionName("test")
        .autoAckOldestChunkedMessageOnQueueFull(true)
        .maxPendingChunkedMessage(100)
        .expireTimeOfIncompleteChunkedMessage(10, TimeUnit.MINUTES)
        .subscribe();

Negative acknowledgment redelivery backoff

The RedeliveryBackoff introduces a redelivery backoff mechanism. You can achieve redelivery with different delays by setting redeliveryCount of messages.

Consumer consumer =  client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .negativeAckRedeliveryBackoff(MultiplierRedeliveryBackoff.builder()
                .minDelayMs(1000)
                .maxDelayMs(60 * 1000)
                .build())
        .subscribe();

Acknowledgement timeout redelivery backoff

The RedeliveryBackoff introduces a redelivery backoff mechanism. You can redeliver messages with different delays by setting the number of times the messages is retried.

Consumer consumer =  client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .ackTimeout(10, TimeUnit.SECOND)
        .ackTimeoutRedeliveryBackoff(MultiplierRedeliveryBackoff.builder()
                .minDelayMs(1000)
                .maxDelayMs(60000)
                .multiplier(2)
                .build())
        .subscribe();

The message redelivery behavior should be as follows.

note

• The negativeAckRedeliveryBackoff does not work with consumer.negativeAcknowledge(MessageId messageId) because you are not able to get the redelivery count from the message ID.
• If a consumer crashes, it triggers the redelivery of unacked messages. In this case, RedeliveryBackoff does not take effect and the messages might get redelivered earlier than the delay time from the backoff.

Multi-topic subscriptions

In addition to subscribing a consumer to a single Pulsar topic, you can also subscribe to multiple topics simultaneously using multi-topic subscriptions. To use multi-topic subscriptions you can supply either a regular expression (regex) or a List of topics. If you select topics via regex, all topics must be within the same Pulsar namespace.

The followings are some examples.

import org.apache.pulsar.client.api.Consumer;
import org.apache.pulsar.client.api.PulsarClient;
import java.util.Arrays;
import java.util.List;
import java.util.regex.Pattern;
ConsumerBuilder consumerBuilder = pulsarClient.newConsumer()
        .subscriptionName(subscription);
// Subscribe to all topics in a namespace
Pattern allTopicsInNamespace = Pattern.compile("public/default/.*");
Consumer allTopicsConsumer = consumerBuilder
        .topicsPattern(allTopicsInNamespace)
        .subscribe();
// Subscribe to a subsets of topics in a namespace, based on regex
Pattern someTopicsInNamespace = Pattern.compile("public/default/foo.*");
Consumer allTopicsConsumer = consumerBuilder
        .topicsPattern(someTopicsInNamespace)
        .subscribe();

In the above example, the consumer subscribes to the persistent topics that can match the topic name pattern. If you want the consumer subscribes to all persistent and non-persistent topics that can match the topic name pattern, set subscriptionTopicsMode to RegexSubscriptionMode.AllTopics.

Pattern pattern = Pattern.compile("public/default/.*");
pulsarClient.newConsumer()
        .subscriptionName("my-sub")
        .topicsPattern(pattern)
        .subscriptionTopicsMode(RegexSubscriptionMode.AllTopics)
        .subscribe();

note

By default, the subscriptionTopicsMode of the consumer is PersistentOnly. Available options of subscriptionTopicsMode are PersistentOnly, NonPersistentOnly, and AllTopics.

You can also subscribe to an explicit list of topics (across namespaces if you wish):

List<String> topics = Arrays.asList(
        "topic-1",
        "topic-2",
        "topic-3"
);
Consumer multiTopicConsumer = consumerBuilder
        .topics(topics)
        .subscribe();
// Alternatively:
Consumer multiTopicConsumer = consumerBuilder
        .topic(
            "topic-1",
            "topic-2",
            "topic-3"
        )
        .subscribe();

You can also subscribe to multiple topics asynchronously using the subscribeAsync method rather than the synchronous subscribe method. The following is an example.

Pattern allTopicsInNamespace = Pattern.compile("persistent://public/default.*");
consumerBuilder
        .topics(topics)
        .subscribeAsync()
        .thenAccept(this::receiveMessageFromConsumer);
private void receiveMessageFromConsumer(Object consumer) {
    ((Consumer)consumer).receiveAsync().thenAccept(message -> {
                // Do something with the received message
                receiveMessageFromConsumer(consumer);
            });
}

Subscription types

Pulsar has various subscription types to match different scenarios. A topic can have multiple subscriptions with different subscription types. However, a subscription can only have one subscription type at a time.

A subscription is identical with the subscription name; a subscription name can specify only one subscription type at a time. To change the subscription type, you should first stop all consumers of this subscription.

Different subscription types have different message distribution types. This section describes the differences of subscription types and how to use them.

In order to better describe their differences, assuming you have a topic named “my-topic”, and the producer has published 10 messages.

Producer<String> producer = client.newProducer(Schema.STRING)
        .topic("my-topic")
        .enableBatching(false)
        .create();
// 3 messages with "key-1", 3 messages with "key-2", 2 messages with "key-3" and 2 messages with "key-4"
producer.newMessage().key("key-1").value("message-1-1").send();
producer.newMessage().key("key-1").value("message-1-2").send();
producer.newMessage().key("key-1").value("message-1-3").send();
producer.newMessage().key("key-2").value("message-2-1").send();
producer.newMessage().key("key-2").value("message-2-2").send();
producer.newMessage().key("key-2").value("message-2-3").send();
producer.newMessage().key("key-3").value("message-3-1").send();
producer.newMessage().key("key-3").value("message-3-2").send();
producer.newMessage().key("key-4").value("message-4-1").send();
producer.newMessage().key("key-4").value("message-4-2").send();

Exclusive

Create a new consumer and subscribe with the Exclusive subscription type.

Consumer consumer = client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .subscriptionType(SubscriptionType.Exclusive)
        .subscribe()

Only the first consumer is allowed to the subscription, other consumers receive an error. The first consumer receives all 10 messages, and the consuming order is the same as the producing order.

note

If topic is a partitioned topic, the first consumer subscribes to all partitioned topics, other consumers are not assigned with partitions and receive an error.

Failover

Create new consumers and subscribe with theFailover subscription type.

Consumer consumer1 = client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .subscriptionType(SubscriptionType.Failover)
        .subscribe()
Consumer consumer2 = client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .subscriptionType(SubscriptionType.Failover)
        .subscribe()
//conumser1 is the active consumer, consumer2 is the standby consumer.
//consumer1 receives 5 messages and then crashes, consumer2 takes over as an  active consumer.

Multiple consumers can attach to the same subscription, yet only the first consumer is active, and others are standby. When the active consumer is disconnected, messages will be dispatched to one of standby consumers, and the standby consumer then becomes active consumer.

If the first active consumer is disconnected after receiving 5 messages, the standby consumer becomes active consumer. Consumer1 will receive:

("key-1", "message-1-1")
("key-1", "message-1-2")
("key-1", "message-1-3")
("key-2", "message-2-1")
("key-2", "message-2-2")

consumer2 will receive:

("key-2", "message-2-3")
("key-3", "message-3-1")
("key-3", "message-3-2")
("key-4", "message-4-1")
("key-4", "message-4-2")

note

If a topic is a partitioned topic, each partition has only one active consumer, messages of one partition are distributed to only one consumer, and messages of multiple partitions are distributed to multiple consumers.

Shared

Create new consumers and subscribe with Shared subscription type.

Consumer consumer1 = client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .subscriptionType(SubscriptionType.Shared)
        .subscribe()
Consumer consumer2 = client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .subscriptionType(SubscriptionType.Shared)
        .subscribe()
//Both consumer1 and consumer 2 is active consumers.

In Shared subscription type, multiple consumers can attach to the same subscription and messages are delivered in a round robin distribution across consumers.

If a broker dispatches only one message at a time, consumer1 receives the following information.

("key-1", "message-1-1")
("key-1", "message-1-3")
("key-2", "message-2-2")
("key-3", "message-3-1")
("key-4", "message-4-1")

consumer2 receives the following information.

("key-1", "message-1-2")
("key-2", "message-2-1")
("key-2", "message-2-3")
("key-3", "message-3-2")
("key-4", "message-4-2")

Shared subscription is different from Exclusive and Failover subscription types. Shared subscription has better flexibility, but cannot provide order guarantee.

Key_shared

This is a new subscription type since 2.4.0 release. Create new consumers and subscribe with Key_Shared subscription type.

Consumer consumer1 = client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .subscriptionType(SubscriptionType.Key_Shared)
        .subscribe()
Consumer consumer2 = client.newConsumer()
        .topic("my-topic")
        .subscriptionName("my-subscription")
        .subscriptionType(SubscriptionType.Key_Shared)
        .subscribe()
//Both consumer1 and consumer2 are active consumers.

Just like in Shared subscription, all consumers in Key_Shared subscription type can attach to the same subscription. But Key_Shared subscription type is different from the Shared subscription. In Key_Shared subscription type, messages with the same key are delivered to only one consumer in order. The possible distribution of messages between different consumers (by default we do not know in advance which keys will be assigned to a consumer, but a key will only be assigned to a consumer at the same time).

consumer1 receives the following information.

("key-1", "message-1-1")
("key-1", "message-1-2")
("key-1", "message-1-3")
("key-3", "message-3-1")
("key-3", "message-3-2")

consumer2 receives the following information.

("key-2", "message-2-1")
("key-2", "message-2-2")
("key-2", "message-2-3")
("key-4", "message-4-1")
("key-4", "message-4-2")

If batching is enabled at the producer side, messages with different keys are added to a batch by default. The broker will dispatch the batch to the consumer, so the default batch mechanism may break the Key_Shared subscription guaranteed message distribution semantics. The producer needs to use the KeyBasedBatcher.

Producer producer = client.newProducer()
        .topic("my-topic")
        .batcherBuilder(BatcherBuilder.KEY_BASED)
        .create();

Or the producer can disable batching.

Producer producer = client.newProducer()
        .topic("my-topic")
        .enableBatching(false)
        .create();

note

If the message key is not specified, messages without key are dispatched to one consumer in order by default.

Reader

With the reader interface, Pulsar clients can “manually position” themselves within a topic and reading all messages from a specified message onward. The Pulsar API for Java enables you to create Reader objects by specifying a topic and a MessageId.

The following is an example.

byte[] msgIdBytes = // Some message ID byte array
MessageId id = MessageId.fromByteArray(msgIdBytes);
Reader reader = pulsarClient.newReader()
        .topic(topic)
        .startMessageId(id)
        .create();
while (true) {
    Message message = reader.readNext();
    // Process message
}

In the example above, a Reader object is instantiated for a specific topic and message (by ID); the reader iterates over each message in the topic after the message is identified by msgIdBytes (how that value is obtained depends on the application).

The code sample above shows pointing the Reader object to a specific message (by ID), but you can also use MessageId.earliest to point to the earliest available message on the topic of MessageId.latest to point to the most recent available message.

Configure reader

When you create a reader, you can use the loadConf configuration. The following parameters are available in loadConf.

Sticky key range reader

In sticky key range reader, broker will only dispatch messages which hash of the message key contains by the specified key hash range. Multiple key hash ranges can be specified on a reader.

The following is an example to create a sticky key range reader.

pulsarClient.newReader()
        .topic(topic)
        .startMessageId(MessageId.earliest)
        .keyHashRange(Range.of(0, 10000), Range.of(20001, 30000))
        .create();

Total hash range size is 65536, so the max end of the range should be less than or equal to 65535.

TableView

The TableView interface serves an encapsulated access pattern, providing a continuously updated key-value map view of the compacted topic data. Messages without keys will be ignored.

With TableView, Pulsar clients can fetch all the message updates from a topic and construct a map with the latest values of each key. These values can then be used to build a local cache of data. In addition, you can register consumers with the TableView by specifying a listener to perform a scan of the map and then receive notifications when new messages are received. Consequently, event handling can be triggered to serve use cases, such as event-driven applications and message monitoring.

Note: Each TableView uses one Reader instance per partition, and reads the topic starting from the compacted view by default. It is highly recommended to enable automatic compaction by configuring the topic compaction policies for the given topic or namespace. More frequent compaction results in shorter startup times because less data is replayed to reconstruct the TableView of the topic.

The following figure illustrates the dynamic construction of a TableView updated with newer values of each key.

Configure TableView

The following is an example of how to configure a TableView.

TableView<String> tv = client.newTableViewBuilder(Schema.STRING)
  .topic("my-tableview")
  .create()

You can use the available parameters in the loadConf configuration or related API to customize your TableView.

Register listeners

You can register listeners for both existing messages on a topic and new messages coming into the topic by using forEachAndListen, and specify to perform operations for all existing messages by using forEach.

The following is an example of how to register listeners with TableView.

// Register listeners for all existing and incoming messages
tv.forEachAndListen((key, value) -> /*operations on all existing and incoming messages*/)
// Register action for all existing messages
tv.forEach((key, value) -> /*operations on all existing messages*/)

Schema

In Pulsar, all message data consists of byte arrays “under the hood.” Message schemas enable you to use other types of data when constructing and handling messages (from simple types like strings to more complex, application-specific types). If you construct, say, a producer without specifying a schema, then the producer can only produce messages of type byte[]. The following is an example.

Producer<byte[]> producer = client.newProducer()
        .topic(topic)
        .create();

The producer above is equivalent to a Producer<byte[]> (in fact, you should always explicitly specify the type). If you’d like to use a producer for a different type of data, you’ll need to specify a schema that informs Pulsar which data type will be transmitted over the topic.

AvroBaseStructSchema example

Let’s say that you have a SensorReading class that you’d like to transmit over a Pulsar topic:

public class SensorReading {
    public float temperature;
    public SensorReading(float temperature) {
        this.temperature = temperature;
    }
    // A no-arg constructor is required
    public SensorReading() {
    }
    public float getTemperature() {
        return temperature;
    }
    public void setTemperature(float temperature) {
        this.temperature = temperature;
    }
}

You could then create a Producer<SensorReading> (or Consumer<SensorReading>) like this:

Producer<SensorReading> producer = client.newProducer(JSONSchema.of(SensorReading.class))
        .topic("sensor-readings")
        .create();

The following schema formats are currently available for Java:

• No schema or the byte array schema (which can be applied using Schema.BYTES):

  Producer<byte[]> bytesProducer = client.newProducer(Schema.BYTES)
      .topic("some-raw-bytes-topic")
      .create();

Or, equivalently:
```
Producer<byte[]> bytesProducer = client.newProducer()
    .topic("some-raw-bytes-topic")
    .create();
```

• String for normal UTF-8-encoded string data. Apply the schema using Schema.STRING:

  Producer<String> stringProducer = client.newProducer(Schema.STRING)
      .topic("some-string-topic")
      .create();

• Create JSON schemas for POJOs using Schema.JSON. The following is an example.

  Producer<MyPojo> pojoProducer = client.newProducer(Schema.JSON(MyPojo.class))
      .topic("some-pojo-topic")
      .create();

• Generate Protobuf schemas using Schema.PROTOBUF. The following example shows how to create the Protobuf schema and use it to instantiate a new producer:

  Producer<MyProtobuf> protobufProducer = client.newProducer(Schema.PROTOBUF(MyProtobuf.class))
      .topic("some-protobuf-topic")
      .create();

• Define Avro schemas with Schema.AVRO. The following code snippet demonstrates how to create and use Avro schema.

  Producer<MyAvro> avroProducer = client.newProducer(Schema.AVRO(MyAvro.class))
      .topic("some-avro-topic")
      .create();

ProtobufNativeSchema example

For example of ProtobufNativeSchema, see SchemaDefinition in Complex type.

Authentication

Pulsar currently supports three authentication schemes: TLS, Athenz, and Oauth2. You can use the Pulsar Java client with all of them.

TLS Authentication

To use TLS, you need to set TLS to true using the setUseTls method, point your Pulsar client to a TLS cert path, and provide paths to cert and key files.

The following is an example.

Map<String, String> authParams = new HashMap();
authParams.put("tlsCertFile", "/path/to/client-cert.pem");
authParams.put("tlsKeyFile", "/path/to/client-key.pem");
Authentication tlsAuth = AuthenticationFactory
        .create(AuthenticationTls.class.getName(), authParams);
PulsarClient client = PulsarClient.builder()
        .serviceUrl("pulsar+ssl://my-broker.com:6651")
        .enableTls(true)
        .tlsTrustCertsFilePath("/path/to/cacert.pem")
        .authentication(tlsAuth)
        .build();

Athenz

To use Athenz as an authentication provider, you need to use TLS and provide values for four parameters in a hash:

• tenantDomain
• tenantService
• providerDomain
• privateKey

You can also set an optional keyId. The following is an example.

Map<String, String> authParams = new HashMap();
authParams.put("tenantDomain", "shopping"); // Tenant domain name
authParams.put("tenantService", "some_app"); // Tenant service name
authParams.put("providerDomain", "pulsar"); // Provider domain name
authParams.put("privateKey", "file:///path/to/private.pem"); // Tenant private key path
authParams.put("keyId", "v1"); // Key id for the tenant private key (optional, default: "0")
Authentication athenzAuth = AuthenticationFactory
        .create(AuthenticationAthenz.class.getName(), authParams);
PulsarClient client = PulsarClient.builder()
        .serviceUrl("pulsar+ssl://my-broker.com:6651")
        .enableTls(true)
        .tlsTrustCertsFilePath("/path/to/cacert.pem")
        .authentication(athenzAuth)
        .build();

Supported pattern formats

The privateKey parameter supports the following three pattern formats:

• file:///path/to/file
• file:/path/to/file
• data:application/x-pem-file;base64,<base64-encoded value>

Oauth2

The following example shows how to use Oauth2 as an authentication provider for the Pulsar Java client.

You can use the factory method to configure authentication for Pulsar Java client.

PulsarClient client = PulsarClient.builder()
    .serviceUrl("pulsar://broker.example.com:6650/")
    .authentication(
        AuthenticationFactoryOAuth2.clientCredentials(this.issuerUrl, this.credentialsUrl, this.audience))
    .build();

In addition, you can also use the encoded parameters to configure authentication for Pulsar Java client.

Authentication auth = AuthenticationFactory
    .create(AuthenticationOAuth2.class.getName(), "{"type":"client_credentials","privateKey":"...","issuerUrl":"...","audience":"..."}");
PulsarClient client = PulsarClient.builder()
    .serviceUrl("pulsar://broker.example.com:6650/")
    .authentication(auth)
    .build();