Package org.apache.kafka.clients.producer

Class KafkaProducer<K,V>

java.lang.Object
org.apache.kafka.clients.producer.KafkaProducer<K,V>
All Implemented Interfaces:
Closeable, AutoCloseable, Producer<K,V>
public class KafkaProducer<K,V> extends Object implements Producer<K,V>
A Kafka client that publishes records to the Kafka cluster.

The producer is thread safe and sharing a single producer instance across threads will generally be faster than having multiple instances.

Here is a simple example of using the producer to send records with strings containing sequential numbers as the key/value pairs. 

 
 Properties props = new Properties();
 props.put("bootstrap.servers", "localhost:9092");
 props.put("linger.ms", 1);
 props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
 props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");

 Producer<String, String> producer = new KafkaProducer<>(props);
 for (int i = 0; i < 100; i++)
     producer.send(new ProducerRecord<String, String>("my-topic", Integer.toString(i), Integer.toString(i)));

 producer.close();

The producer consists of a pool of buffer space that holds records that haven't yet been transmitted to the server as well as a background I/O thread that is responsible for turning these records into requests and transmitting them to the cluster. Failure to close the producer after use will leak these resources.

The send() method is asynchronous. When called, it adds the record to a buffer of pending record sends and immediately returns. This allows the producer to batch together individual records for efficiency.

The acks config controls the criteria under which requests are considered complete. The default setting "all" will result in blocking on the full commit of the record, the slowest but most durable setting.

If the request fails, the producer can automatically retry. The retries setting defaults to Integer.MAX_VALUE, and it's recommended to use delivery.timeout.ms to control retry behavior, instead of retries.

The producer maintains buffers of unsent records for each partition. These buffers are of a size specified by the batch.size config. Making this larger can result in more batching, but requires more memory (since we will generally have one of these buffers for each active partition).

By default a buffer is available to send immediately even if there is additional unused space in the buffer. However if you want to reduce the number of requests you can set linger.ms to something greater than 0. This will instruct the producer to wait up to that number of milliseconds before sending a request in hope that more records will arrive to fill up the same batch. This is analogous to Nagle's algorithm in TCP. For example, in the code snippet above, likely all 100 records would be sent in a single request since we set our linger time to 1 millisecond. However this setting would add 1 millisecond of latency to our request waiting for more records to arrive if we didn't fill up the buffer. Note that records that arrive close together in time will generally batch together even with linger.ms=0. So, under heavy load, batching will occur regardless of the linger configuration; however setting this to something larger than 0 can lead to fewer, more efficient requests when not under maximal load at the cost of a small amount of latency.

The buffer.memory controls the total amount of memory available to the producer for buffering. If records are sent faster than they can be transmitted to the server then this buffer space will be exhausted. When the buffer space is exhausted additional send calls will block. The threshold for time to block is determined by max.block.ms after which it throws a TimeoutException.

The key.serializer and value.serializer instruct how to turn the key and value objects the user provides with their ProducerRecord into bytes. You can use the included ByteArraySerializer or StringSerializer for simple string or byte types.

From Kafka 0.11, the KafkaProducer supports two additional modes: the idempotent producer and the transactional producer. The idempotent producer strengthens Kafka's delivery semantics from at least once to exactly once delivery. In particular producer retries will no longer introduce duplicates. The transactional producer allows an application to send messages to multiple partitions (and topics!) atomically.

From Kafka 3.0, the enable.idempotence configuration defaults to true. When enabling idempotence, retries config will default to Integer.MAX_VALUE and the acks config will default to all. There are no API changes for the idempotent producer, so existing applications will not need to be modified to take advantage of this feature.

To take advantage of the idempotent producer, it is imperative to avoid application level re-sends since these cannot be de-duplicated. As such, if an application enables idempotence, it is recommended to leave the retries config unset, as it will be defaulted to Integer.MAX_VALUE. Additionally, if a send(ProducerRecord) returns an error even with infinite retries (for instance if the message expires in the buffer before being sent), then it is recommended to shut down the producer and check the contents of the last produced message to ensure that it is not duplicated. Finally, the producer can only guarantee idempotence for messages sent within a single session.

To use the transactional producer and the attendant APIs, you must set the transactional.id configuration property. If the transactional.id is set, idempotence is automatically enabled along with the producer configs which idempotence depends on. Further, topics which are included in transactions should be configured for durability. In particular, the replication.factor should be at least 3, and the min.insync.replicas for these topics should be set to 2. Finally, in order for transactional guarantees to be realized from end-to-end, the consumers must be configured to read only committed messages as well.

The purpose of the transactional.id is to enable transaction recovery across multiple sessions of a single producer instance. It would typically be derived from the shard identifier in a partitioned, stateful, application. As such, it should be unique to each producer instance running within a partitioned application.

All the new transactional APIs are blocking and will throw exceptions on failure. The example below illustrates how the new APIs are meant to be used. It is similar to the example above, except that all 100 messages are part of a single transaction. 

 
 Properties props = new Properties();
 props.put("bootstrap.servers", "localhost:9092");
 props.put("transactional.id", "my-transactional-id");
 Producer<String, String> producer = new KafkaProducer<>(props, new StringSerializer(), new StringSerializer());

 producer.initTransactions();

 try {
     producer.beginTransaction();
     for (int i = 0; i < 100; i++)
         producer.send(new ProducerRecord<>("my-topic", Integer.toString(i), Integer.toString(i)));
     producer.commitTransaction();
 } catch (ProducerFencedException | OutOfOrderSequenceException | AuthorizationException e) {
     // We can't recover from these exceptions, so our only option is to close the producer and exit.
     producer.close();
 } catch (KafkaException e) {
     // For all other exceptions, just abort the transaction and try again.
     producer.abortTransaction();
 }
 producer.close();

As is hinted at in the example, there can be only one open transaction per producer. All messages sent between the beginTransaction() and commitTransaction() calls will be part of a single transaction. When the transactional.id is specified, all messages sent by the producer must be part of a transaction.

The transactional producer uses exceptions to communicate error states. In particular, it is not required to specify callbacks for producer.send() or to call .get() on the returned Future: a KafkaException would be thrown if any of the producer.send() or transactional calls hit an irrecoverable error during a transaction. See the send(ProducerRecord) documentation for more details about detecting errors from a transactional send.

By calling producer.abortTransaction() upon receiving a KafkaException we can ensure that any successful writes are marked as aborted, hence keeping the transactional guarantees.

This client can communicate with brokers that are version 0.10.0 or newer. Older or newer brokers may not support certain client features. For instance, the transactional APIs need broker versions 0.11.0 or later. You will receive an UnsupportedVersionException when invoking an API that is not available in the running broker version.

  • Field Details

  • Constructor Details

    • KafkaProducer

      public KafkaProducer(Map<String,Object> configs)
      A producer is instantiated by providing a set of key-value pairs as configuration. Valid configuration strings are documented here. Values can be either strings or Objects of the appropriate type (for example a numeric configuration would accept either the string "42" or the integer 42).

      Note: after creating a KafkaProducer you must always close() it to avoid resource leaks.

      Parameters:
      configs - The producer configs

    • KafkaProducer

      public KafkaProducer(Map<String,Object> configs, Serializer<K> keySerializer, Serializer<V> valueSerializer)
      A producer is instantiated by providing a set of key-value pairs as configuration, a key and a value Serializer. Valid configuration strings are documented here. Values can be either strings or Objects of the appropriate type (for example a numeric configuration would accept either the string "42" or the integer 42).

      Note: after creating a KafkaProducer you must always close() it to avoid resource leaks.

      Parameters:
      configs - The producer configs
      keySerializer - The serializer for key that implements Serializer. The configure() method won't be called in the producer when the serializer is passed in directly.
      valueSerializer - The serializer for value that implements Serializer. The configure() method won't be called in the producer when the serializer is passed in directly.

    • KafkaProducer

      public KafkaProducer(Properties properties)
      A producer is instantiated by providing a set of key-value pairs as configuration. Valid configuration strings are documented here.

      Note: after creating a KafkaProducer you must always close() it to avoid resource leaks.

      Parameters:
      properties - The producer configs

    • KafkaProducer

      public KafkaProducer(Properties properties, Serializer<K> keySerializer, Serializer<V> valueSerializer)
      A producer is instantiated by providing a set of key-value pairs as configuration, a key and a value Serializer. Valid configuration strings are documented here.

      Note: after creating a KafkaProducer you must always close() it to avoid resource leaks.

      Parameters:
      properties - The producer configs
      keySerializer - The serializer for key that implements Serializer. The configure() method won't be called in the producer when the serializer is passed in directly.
      valueSerializer - The serializer for value that implements Serializer. The configure() method won't be called in the producer when the serializer is passed in directly.

  • Method Details

    • initTransactions

      public void initTransactions()
      Needs to be called before any other methods when the transactional.id is set in the configuration. This method does the following: 1. Ensures any transactions initiated by previous instances of the producer with the same transactional.id are completed. If the previous instance had failed with a transaction in progress, it will be aborted. If the last transaction had begun completion, but not yet finished, this method awaits its completion. 2. Gets the internal producer id and epoch, used in all future transactional messages issued by the producer. Note that this method will raise TimeoutException if the transactional state cannot be initialized before expiration of max.block.ms. Additionally, it will raise InterruptException if interrupted. It is safe to retry in either case, but once the transactional state has been successfully initialized, this method should no longer be used.
      Specified by:
      initTransactions in interface Producer<K,V>
      Throws:
      IllegalStateException - if no transactional.id has been configured
      UnsupportedVersionException - fatal error indicating the broker does not support transactions (i.e. if its version is lower than 0.11.0.0)
      AuthorizationException - fatal error indicating that the configured transactional.id is not authorized. See the exception for more details
      KafkaException - if the producer has encountered a previous fatal error or for any other unexpected error
      TimeoutException - if the time taken for initialize the transaction has surpassed max.block.ms.
      InterruptException - if the thread is interrupted while blocked

    • beginTransaction

      public void beginTransaction() throws ProducerFencedException
      Should be called before the start of each new transaction. Note that prior to the first invocation of this method, you must invoke initTransactions() exactly one time.
      Specified by:
      beginTransaction in interface Producer<K,V>
      Throws:
      IllegalStateException - if no transactional.id has been configured or if initTransactions() has not yet been invoked
      ProducerFencedException - if another producer with the same transactional.id is active
      InvalidProducerEpochException - if the producer has attempted to produce with an old epoch to the partition leader. See the exception for more details
      UnsupportedVersionException - fatal error indicating the broker does not support transactions (i.e. if its version is lower than 0.11.0.0)
      AuthorizationException - fatal error indicating that the configured transactional.id is not authorized. See the exception for more details
      KafkaException - if the producer has encountered a previous fatal error or for any other unexpected error

    • sendOffsetsToTransaction

      @Deprecated public void sendOffsetsToTransaction(Map<TopicPartition,OffsetAndMetadata> offsets, String consumerGroupId) throws ProducerFencedException
      Deprecated.
      Since 3.0.0, please use sendOffsetsToTransaction(Map, ConsumerGroupMetadata) instead.
      Sends a list of specified offsets to the consumer group coordinator, and also marks those offsets as part of the current transaction. These offsets will be considered committed only if the transaction is committed successfully. The committed offset should be the next message your application will consume, i.e. lastProcessedMessageOffset + 1.

      This method should be used when you need to batch consumed and produced messages together, typically in a consume-transform-produce pattern. Thus, the specified consumerGroupId should be the same as config parameter group.id of the used consumer. Note, that the consumer should have enable.auto.commit=false and should also not commit offsets manually (via sync or async commits).

      Specified by:
      sendOffsetsToTransaction in interface Producer<K,V>
      Throws:
      IllegalStateException - if no transactional.id has been configured, no transaction has been started
      ProducerFencedException - fatal error indicating another producer with the same transactional.id is active
      UnsupportedVersionException - fatal error indicating the broker does not support transactions (i.e. if its version is lower than 0.11.0.0)
      UnsupportedForMessageFormatException - fatal error indicating the message format used for the offsets topic on the broker does not support transactions
      AuthorizationException - fatal error indicating that the configured transactional.id is not authorized, or the consumer group id is not authorized.
      InvalidProducerEpochException - if the producer has attempted to produce with an old epoch to the partition leader. See the exception for more details
      KafkaException - if the producer has encountered a previous fatal or abortable error, or for any other unexpected error

    • sendOffsetsToTransaction

      public void sendOffsetsToTransaction(Map<TopicPartition,OffsetAndMetadata> offsets, ConsumerGroupMetadata groupMetadata) throws ProducerFencedException
      Sends a list of specified offsets to the consumer group coordinator, and also marks those offsets as part of the current transaction. These offsets will be considered committed only if the transaction is committed successfully. The committed offset should be the next message your application will consume, i.e. lastProcessedMessageOffset + 1.

      This method should be used when you need to batch consumed and produced messages together, typically in a consume-transform-produce pattern. Thus, the specified groupMetadata should be extracted from the used consumer via KafkaConsumer.groupMetadata() to leverage consumer group metadata. This will provide stronger fencing than just supplying the consumerGroupId and passing in new ConsumerGroupMetadata(consumerGroupId), however note that the full set of consumer group metadata returned by KafkaConsumer.groupMetadata() requires the brokers to be on version 2.5 or newer to understand.

      Note, that the consumer should have enable.auto.commit=false and should also not commit offsets manually (via sync or async commits). This method will raise TimeoutException if the producer cannot send offsets before expiration of max.block.ms. Additionally, it will raise InterruptException if interrupted.

      Specified by:
      sendOffsetsToTransaction in interface Producer<K,V>
      Throws:
      IllegalStateException - if no transactional.id has been configured or no transaction has been started.
      ProducerFencedException - fatal error indicating another producer with the same transactional.id is active
      UnsupportedVersionException - fatal error indicating the broker does not support transactions (i.e. if its version is lower than 0.11.0.0) or the broker doesn't support latest version of transactional API with all consumer group metadata (i.e. if its version is lower than 2.5.0).
      UnsupportedForMessageFormatException - fatal error indicating the message format used for the offsets topic on the broker does not support transactions
      AuthorizationException - fatal error indicating that the configured transactional.id is not authorized, or the consumer group id is not authorized.
      CommitFailedException - if the commit failed and cannot be retried (e.g. if the consumer has been kicked out of the group). Users should handle this by aborting the transaction.
      FencedInstanceIdException - if this producer instance gets fenced by broker due to a mis-configured consumer instance id within group metadata.
      InvalidProducerEpochException - if the producer has attempted to produce with an old epoch to the partition leader. See the exception for more details
      KafkaException - if the producer has encountered a previous fatal or abortable error, or for any other unexpected error
      TimeoutException - if the time taken for sending offsets has surpassed max.block.ms.
      InterruptException - if the thread is interrupted while blocked

    • commitTransaction

      public void commitTransaction() throws ProducerFencedException
      Commits the ongoing transaction. This method will flush any unsent records before actually committing the transaction.

      Further, if any of the send(ProducerRecord) calls which were part of the transaction hit irrecoverable errors, this method will throw the last received exception immediately and the transaction will not be committed. So all send(ProducerRecord) calls in a transaction must succeed in order for this method to succeed.

      If the transaction is committed successfully and this method returns without throwing an exception, it is guaranteed that all callbacks for records in the transaction will have been invoked and completed. Note that exceptions thrown by callbacks are ignored; the producer proceeds to commit the transaction in any case.

      Note that this method will raise TimeoutException if the transaction cannot be committed before expiration of max.block.ms. Additionally, it will raise InterruptException if interrupted. It is safe to retry in either case, but it is not possible to attempt a different operation (such as abortTransaction) since the commit may already be in the progress of completing. If not retrying, the only option is to close the producer.

      Specified by:
      commitTransaction in interface Producer<K,V>
      Throws:
      IllegalStateException - if no transactional.id has been configured or no transaction has been started
      ProducerFencedException - fatal error indicating another producer with the same transactional.id is active
      UnsupportedVersionException - fatal error indicating the broker does not support transactions (i.e. if its version is lower than 0.11.0.0)
      AuthorizationException - fatal error indicating that the configured transactional.id is not authorized. See the exception for more details
      InvalidProducerEpochException - if the producer has attempted to produce with an old epoch to the partition leader. See the exception for more details
      KafkaException - if the producer has encountered a previous fatal or abortable error, or for any other unexpected error
      TimeoutException - if the time taken for committing the transaction has surpassed max.block.ms.
      InterruptException - if the thread is interrupted while blocked

    • abortTransaction

      public void abortTransaction() throws ProducerFencedException
      Aborts the ongoing transaction. Any unflushed produce messages will be aborted when this call is made. This call will throw an exception immediately if any prior send(ProducerRecord) calls failed with a ProducerFencedException or an instance of AuthorizationException. Note that this method will raise TimeoutException if the transaction cannot be aborted before expiration of max.block.ms. Additionally, it will raise InterruptException if interrupted. It is safe to retry in either case, but it is not possible to attempt a different operation (such as commitTransaction) since the abort may already be in the progress of completing. If not retrying, the only option is to close the producer.
      Specified by:
      abortTransaction in interface Producer<K,V>
      Throws:
      IllegalStateException - if no transactional.id has been configured or no transaction has been started
      ProducerFencedException - fatal error indicating another producer with the same transactional.id is active
      InvalidProducerEpochException - if the producer has attempted to produce with an old epoch to the partition leader. See the exception for more details
      UnsupportedVersionException - fatal error indicating the broker does not support transactions (i.e. if its version is lower than 0.11.0.0)
      AuthorizationException - fatal error indicating that the configured transactional.id is not authorized. See the exception for more details
      KafkaException - if the producer has encountered a previous fatal error or for any other unexpected error
      TimeoutException - if the time taken for aborting the transaction has surpassed max.block.ms.
      InterruptException - if the thread is interrupted while blocked

    • send

      public Future<RecordMetadata> send(ProducerRecord<K,V> record)
      Asynchronously send a record to a topic. Equivalent to send(record, null). See send(ProducerRecord, Callback) for details.
      Specified by:
      send in interface Producer<K,V>

    • send

      public Future<RecordMetadata> send(ProducerRecord<K,V> record, Callback callback)
      Asynchronously send a record to a topic and invoke the provided callback when the send has been acknowledged.

      The send is asynchronous and this method will return immediately once the record has been stored in the buffer of records waiting to be sent. This allows sending many records in parallel without blocking to wait for the response after each one.

      The result of the send is a RecordMetadata specifying the partition the record was sent to, the offset it was assigned and the timestamp of the record. If the producer is configured with acks = 0, the RecordMetadata will have offset = -1 because the producer does not wait for the acknowledgement from the broker. If CreateTime is used by the topic, the timestamp will be the user provided timestamp or the record send time if the user did not specify a timestamp for the record. If LogAppendTime is used for the topic, the timestamp will be the Kafka broker local time when the message is appended.

      Since the send call is asynchronous it returns a Future for the RecordMetadata that will be assigned to this record. Invoking get() on this future will block until the associated request completes and then return the metadata for the record or throw any exception that occurred while sending the record.

      If you want to simulate a simple blocking call you can call the get() method immediately: 

       
 byte[] key = "key".getBytes();
 byte[] value = "value".getBytes();
 ProducerRecord<byte[],byte[]> record = new ProducerRecord<byte[],byte[]>("my-topic", key, value)
 producer.send(record).get();

      Fully non-blocking usage can make use of the Callback parameter to provide a callback that will be invoked when the request is complete. 

       
 ProducerRecord<byte[],byte[]> record = new ProducerRecord<byte[],byte[]>("the-topic", key, value);
 producer.send(myRecord,
               new Callback() {
                   public void onCompletion(RecordMetadata metadata, Exception e) {
                       if(e != null) {
                          e.printStackTrace();
                       } else {
                          System.out.println("The offset of the record we just sent is: " + metadata.offset());
                       }
                   }
               });
      Callbacks for records being sent to the same partition are guaranteed to execute in order. That is, in the following example callback1 is guaranteed to execute before callback2: 
       
 producer.send(new ProducerRecord<byte[],byte[]>(topic, partition, key1, value1), callback1);
 producer.send(new ProducerRecord<byte[],byte[]>(topic, partition, key2, value2), callback2);

      When used as part of a transaction, it is not necessary to define a callback or check the result of the future in order to detect errors from send. If any of the send calls failed with an irrecoverable error, the final commitTransaction() call will fail and throw the exception from the last failed send. When this happens, your application should call abortTransaction() to reset the state and continue to send data.

      Some transactional send errors cannot be resolved with a call to abortTransaction(). In particular, if a transactional send finishes with a ProducerFencedException, a OutOfOrderSequenceException, a UnsupportedVersionException, or an AuthorizationException, then the only option left is to call close(). Fatal errors cause the producer to enter a defunct state in which future API calls will continue to raise the same underyling error wrapped in a new KafkaException.

      It is a similar picture when idempotence is enabled, but no transactional.id has been configured. In this case, UnsupportedVersionException and AuthorizationException are considered fatal errors. However, ProducerFencedException does not need to be handled. Additionally, it is possible to continue sending after receiving an OutOfOrderSequenceException, but doing so can result in out of order delivery of pending messages. To ensure proper ordering, you should close the producer and create a new instance.

      If the message format of the destination topic is not upgraded to 0.11.0.0, idempotent and transactional produce requests will fail with an UnsupportedForMessageFormatException error. If this is encountered during a transaction, it is possible to abort and continue. But note that future sends to the same topic will continue receiving the same exception until the topic is upgraded.

      Note that callbacks will generally execute in the I/O thread of the producer and so should be reasonably fast or they will delay the sending of messages from other threads. If you want to execute blocking or computationally expensive callbacks it is recommended to use your own Executor in the callback body to parallelize processing.

      Specified by:
      send in interface Producer<K,V>
      Parameters:
      record - The record to send
      callback - A user-supplied callback to execute when the record has been acknowledged by the server (null indicates no callback)
      Throws:
      AuthenticationException - if authentication fails. See the exception for more details
      AuthorizationException - fatal error indicating that the producer is not allowed to write
      IllegalStateException - if a transactional.id has been configured and no transaction has been started, or when send is invoked after producer has been closed.
      InterruptException - If the thread is interrupted while blocked
      SerializationException - If the key or value are not valid objects given the configured serializers
      TimeoutException - If the record could not be appended to the send buffer due to memory unavailable or missing metadata within max.block.ms.
      KafkaException - If a Kafka related error occurs that does not belong to the public API exceptions.

    • flush

      public void flush()
      Invoking this method makes all buffered records immediately available to send (even if linger.ms is greater than 0) and blocks on the completion of the requests associated with these records. The post-condition of flush() is that any previously sent record will have completed (e.g. Future.isDone() == true). A request is considered completed when it is successfully acknowledged according to the acks configuration you have specified or else it results in an error.

      Other threads can continue sending records while one thread is blocked waiting for a flush call to complete, however no guarantee is made about the completion of records sent after the flush call begins.

      This method can be useful when consuming from some input system and producing into Kafka. The flush() call gives a convenient way to ensure all previously sent messages have actually completed.

      This example shows how to consume from one Kafka topic and produce to another Kafka topic: 

       
 for(ConsumerRecord<String, String> record: consumer.poll(100))
     producer.send(new ProducerRecord("my-topic", record.key(), record.value());
 producer.flush();
 consumer.commitSync();
      Note that the above example may drop records if the produce request fails. If we want to ensure that this does not occur we need to set retries=<large_number> in our config.

      Applications don't need to call this method for transactional producers, since the commitTransaction() will flush all buffered records before performing the commit. This ensures that all the send(ProducerRecord) calls made since the previous beginTransaction() are completed before the commit.

      Specified by:
      flush in interface Producer<K,V>
      Throws:
      InterruptException - If the thread is interrupted while blocked

    • partitionsFor

      public List<PartitionInfo> partitionsFor(String topic)
      Get the partition metadata for the given topic. This can be used for custom partitioning.
      Specified by:
      partitionsFor in interface Producer<K,V>
      Throws:
      AuthenticationException - if authentication fails. See the exception for more details
      AuthorizationException - if not authorized to the specified topic. See the exception for more details
      InterruptException - if the thread is interrupted while blocked
      TimeoutException - if metadata could not be refreshed within max.block.ms
      KafkaException - for all Kafka-related exceptions, including the case where this method is called after producer close

    • metrics

      public Map<MetricName,? extends Metric> metrics()
      Get the full set of internal metrics maintained by the producer.
      Specified by:
      metrics in interface Producer<K,V>

    • close

      public void close()
      Close this producer. This method blocks until all previously sent requests complete. This method is equivalent to close(Long.MAX_VALUE, TimeUnit.MILLISECONDS).

      If close() is called from Callback, a warning message will be logged and close(0, TimeUnit.MILLISECONDS) will be called instead. We do this because the sender thread would otherwise try to join itself and block forever.

      Specified by:
      close in interface AutoCloseable
      Specified by:
      close in interface Closeable
      Specified by:
      close in interface Producer<K,V>
      Throws:
      InterruptException - If the thread is interrupted while blocked.
      KafkaException - If a unexpected error occurs while trying to close the client, this error should be treated as fatal and indicate the client is no longer functionable.

    • close

      public void close(Duration timeout)
      This method waits up to timeout for the producer to complete the sending of all incomplete requests.

      If the producer is unable to complete all requests before the timeout expires, this method will fail any unsent and unacknowledged records immediately. It will also abort the ongoing transaction if it's not already completing.

      If invoked from within a Callback this method will not block and will be equivalent to close(Duration.ofMillis(0)). This is done since no further sending will happen while blocking the I/O thread of the producer.

      Specified by:
      close in interface Producer<K,V>
      Parameters:
      timeout - The maximum time to wait for producer to complete any pending requests. The value should be non-negative. Specifying a timeout of zero means do not wait for pending send requests to complete.
      Throws:
      InterruptException - If the thread is interrupted while blocked.
      KafkaException - If a unexpected error occurs while trying to close the client, this error should be treated as fatal and indicate the client is no longer functionable.
      IllegalArgumentException - If the timeout is negative.