kafka producer send method

* If the producer is unable to complete all requests before the timeout expires, this method will fail, * any unsent and unacknowledged records immediately. * The producer is thread safe and sharing a single producer instance across threads will generally be faster than, * Here is a simple example of using the producer to send records with strings containing sequential numbers as the key/value. * This client can communicate with brokers that are version 0.10.0 or newer. If {@link org.apache.kafka.common.record.TimestampType#LOG_APPEND_TIME LogAppendTime} is used for the. In particular. "Retrying append due to new batch creation for topic {} partition {}. * e.printStackTrace(); * 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. PARTITIONER_ADPATIVE_PARTITIONING_ENABLE_CONFIG, PARTITIONER_AVAILABILITY_TIMEOUT_MS_CONFIG, // call close methods if internal objects are already constructed this is to prevent resource leak. Please clear ", " configuration setting to get the default partitioning behavior", "UniformStickyPartitioner is deprecated. The value should be. The post-condition. The configure() method won't be. * This method can be useful when consuming from some input system and producing into Kafka. * {@link org.apache.kafka.common.serialization.StringSerializer} for simple string or byte types. This is done since no further sending will happen while. 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. In particular, * producer retries will no longer introduce duplicates. if its version is lower than 2.5.0). * 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. * however no guarantee is made about the completion of records sent after the flush call begins. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. ", "Proceeding to force close the producer since pending requests could not be completed ". // Append the record to the accumulator. * 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. // calculated there and can be accessed via appendCallbacks.topicPartition. * topic, the timestamp will be the Kafka broker local time when the message is appended.

By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. * does not support transactions (i.e. // handling exceptions and record the errors; // for API exceptions return them in the future, "Exception occurred during message send:", // we notify interceptor about all exceptions, since onSend is called before anything else in this method. * arrive to fill up the same batch. * Fatal errors cause the producer to enter a defunct state in which future API calls will continue to raise. The retries setting defaults to Integer.MAX_VALUE, and. * (i.e. If records, * are sent faster than they can be transmitted to the server then this buffer space will be exhausted. // take into account broker load, the amount of data produced to each partition, etc.). acks=1, the producer will receive a successful response from the What my need is I want the operation to be sync i.e. * since the abort may already be in the progress of completing. * to be realized from end-to-end, the consumers must be configured to read only committed messages as well. if its version is lower than 0.11.0.0), * @throws org.apache.kafka.common.errors.AuthorizationException fatal error indicating that the configured, * transactional.id is not authorized. directly) and so it provides more methods for you to use. * Needs to be called before any other methods when the transactional.id is set in the configuration. ", // hash the keyBytes to choose a partition, "Consumer group metadata could not be null", "Cannot use transactional methods without enabling transactions ". * Note, that the consumer should have {@code enable.auto.commit=false} and should, * also not commit offsets manually (via {@link KafkaConsumer#commitSync(Map) sync} or. // is stale and the number of partitions for this topic has increased in the meantime. The threshold for time to block is determined by max.block.ms after which it throws, * The key.serializer and value.serializer instruct how to turn the key and value objects the user provides with, * their ProducerRecord into bytes. "Closing the Kafka producer with timeoutMillis = {} ms.", // this will keep track of the first encountered exception, "Overriding close timeout {} ms to 0 ms in order to prevent useless blocking due to self-join. see KAFKA-2121, SOCKET_CONNECTION_SETUP_TIMEOUT_MS_CONFIG, SOCKET_CONNECTION_SETUP_TIMEOUT_MAX_MS_CONFIG, // throw an exception if the user explicitly set an inconsistent value, // override deliveryTimeoutMs default value to lingerMs + requestTimeoutMs for backward compatibility, "{} should be equal to or larger than {} + {}. * The idempotent producer strengthens Kafka's delivery semantics from at least once to exactly once delivery. When, * this happens, your application should call {@link #abortTransaction()} to reset the state and continue to send. The flush() call. * to the cluster. Connect and share knowledge within a single location that is structured and easy to search. For retry mechanism, in case of failure in publishing. I have answered this in another question. "Flushing accumulated records in producer.". * non-negative. When the buffer space is, * exhausted additional send calls will block. Partition number should always be non-negative. This can be used for custom partitioning. Please clear ", " to 'true' to get the uniform sticky partitioning behavior", "[Producer clientId=%s, transactionalId=%s] ". * @throws KafkaException if the producer has encountered a previous fatal or abortable error, or for any. Future.isDone() == true). * if the record has partition returns the value otherwise, * if custom partitioner is specified, call it to compute partition. ", "This means you have incorrectly invoked close with a non-zero timeout from the producer call-back. * If the request fails, the producer can automatically retry. // There is no need to do work required for adaptive partitioning, if we use a custom partitioner. * The acks config controls the criteria under which requests are considered complete. * From Kafka 0.11, the KafkaProducer supports two additional modes: the idempotent producer and the transactional producer. Values can be, * either strings or Objects of the appropriate type (for example a numeric configuration would accept either the. * according to the acks configuration you have specified or else it results in an error. // batches from the accumulator until they have been added to the transaction. You will receive an.

What is the difference between Kafka Template and kafka producer? See the exception for more details, * @throws AuthorizationException fatal error indicating that the producer is not allowed to write, * @throws IllegalStateException if a transactional.id has been configured and no transaction has been started, or. * @throws IllegalStateException if no transactional.id has been configured, no transaction has been started, * @throws ProducerFencedException fatal error indicating another producer with the same transactional.id is active, * @throws org.apache.kafka.common.errors.UnsupportedForMessageFormatException fatal error indicating the message, * format used for the offsets topic on the broker does not support transactions. * Note that exceptions thrown by callbacks are ignored; the producer proceeds to commit the transaction in any case.

Further, topics which are included in transactions should be configured, * for durability. * Implementation of asynchronously send a record to a topic. The old partition was {}", // Add the partition to the transaction (if in progress) after it has been successfully, // appended to the accumulator. * be the next message your application will consume, i.e.

* be called in the producer when the serializer is passed in directly. But note that future. * This method will raise {@link TimeoutException} if the producer cannot send offsets before expiration of {@code max.block.ms}. * Some transactional send errors cannot be resolved with a call to {@link #abortTransaction()}. * blocking the I/O thread of the producer. 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. My question is in a spring boot microservice using kafka what is appropriate to use KafkaTemplate.send() or KafkaProducer.send(). * producer.send(new ProducerRecord("my-topic", record.key(), record.value()); * Note that the above example may drop records if the produce request fails. message can't be written to the leader, the producer will receive an Have gone through the documentation of KafkaProducer https://kafka.apache.org/10/javadoc/org/apache/kafka/clients/producer/KafkaProducer.html, https://docs.spring.io/spring-kafka/reference/html/#kafka-template. broker the moment the leader replica received the message. See the NOTICE file distributed with. See the {@link #send(ProducerRecord)}. This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. Invoking {@link java.util.concurrent.Future#get(), * get()} on this future will block until the associated request completes and then return the metadata for the record. * The transactional producer uses exceptions to communicate error states. Setting it to {}. * Valid configuration strings are documented here. If the last transaction had begun completion. * Wait for cluster metadata including partitions for the given topic to be available. How can I use parentheses when there are math parentheses inside? * initialized, this method should no longer be used. * efficient requests when not under maximal load at the cost of a small amount of latency. * If the transaction is committed successfully and this method returns without throwing an exception, it is guaranteed. Difference between HashMap, LinkedHashMap and TreeMap. What are the differences between a HashMap and a Hashtable in Java? // intercept the record, which can be potentially modified; this method does not throw exceptions, // Verify that this producer instance has not been closed. * Note that this method will raise {@link TimeoutException} if the transaction cannot be aborted before expiration, * It is safe to retry in either case, but it is not possible to attempt a different operation (such as commitTransaction). Ensures any transactions initiated by previous instances of the producer with the same, * transactional.id are completed. * when send is invoked after producer has been closed. One db per microservice, on the same storage engine? * if a transactional send finishes with a {@link ProducerFencedException}, a {@link org.apache.kafka.common.errors.OutOfOrderSequenceException}, * a {@link org.apache.kafka.common.errors.UnsupportedVersionException}, or an. Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide, spring kafka is juat wrapper library on apache kafka, you can use either one based on your requirement, personally, i like the KafkaProducer more than the spring wrapper without adding much complexity. * stronger fencing than just supplying the {@code consumerGroupId} and passing in {@code new ConsumerGroupMetadata(consumerGroupId)}, * however note that the full set of consumer group metadata returned by {@link KafkaConsumer#groupMetadata()}. This is necessary in case the metadata. // Only join the sender thread when not calling from callback. There are 3 values for the acks parameter: acks=0, the producer will not wait for a reply from the broker before * @param valueSerializer The serializer for value that implements {@link Serializer}. To subscribe to this RSS feed, copy and paste this URL into your RSS reader. * @throws org.apache.kafka.clients.consumer.CommitFailedException if the commit failed and cannot be retried. * in order to detect errors from send. *

All the new transactional APIs are blocking and will throw exceptions on failure. * of {@code max.block.ms}. Additionally, if a {@link #send(ProducerRecord)}. * If close() is called from {@link Callback}, a warning message will be logged and close(0, TimeUnit.MILLISECONDS), * will be called instead. * 2. Best way to configure retries in Kaka Producer. // Try to calculate partition, but note that after this call it can be RecordMetadata.UNKNOWN_PARTITION, // which means that the RecordAccumulator would pick a partition using built-in logic (which may. See the exception for more details. * @throws KafkaException If a Kafka related error occurs that does not belong to the public API exceptions. This method blocks until all previously sent requests complete. lastProcessedMessageOffset + 1. * A producer is instantiated by providing a set of key-value pairs as configuration. * or throw any exception that occurred while sending the record. It would typically be derived from the shard identifier in a partitioned, stateful, application. * are documented here. * Asynchronously send a record to a topic. Users should handle this by aborting the transaction. Additionally, it will raise {@link InterruptException} if interrupted. You can use the included {@link org.apache.kafka.common.serialization.ByteArraySerializer} or. broker once all in-sync replicas received the message. // Log the message here, because we don't know the partition before that. * 100 messages are part of a single transaction. // A custom partitioner may take advantage on the onNewBatch callback. * @throws IllegalStateException if no transactional.id has been configured or if {@link #initTransactions()}, * @throws ProducerFencedException if another producer with the same transactional.id is active, * @throws org.apache.kafka.common.errors.InvalidProducerEpochException if the producer has attempted to produce with an old epoch, * to the partition leader. Thus, the specified, * {@code consumerGroupId} should be the same as config parameter {@code group.id} of the used, * {@link KafkaConsumer consumer}. * If {@link org.apache.kafka.common.record.TimestampType#CREATE_TIME 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. * @param timeout The maximum time to wait for producer to complete any pending requests. * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * Check if partitioner is deprecated and log a warning if it is. Making statements based on opinion; back them up with references or personal experience. If not retrying, the only option is to close the producer. * @throws TimeoutException if the time taken for initialize the transaction has surpassed max.block.ms. That is, in the. * Note: after creating a {@code KafkaProducer} you must always {@link #close()} it to avoid resource leaks. * following example callback1 is guaranteed to execute before callback2: * producer.send(new ProducerRecord(topic, partition, key1, value1), callback1); * producer.send(new ProducerRecord(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. Failure to close the producer after use will leak these resources. See the exception for more details, * @throws KafkaException if the producer has encountered a previous fatal error or for any other unexpected error. * {@link ProducerFencedException} or an instance of {@link org.apache.kafka.common.errors.AuthorizationException}. * will result in blocking on the full commit of the record, the slowest but most durable setting. These buffers are of a size specified by, * the batch.size config. Additionally, it will raise {@link InterruptException}, * if interrupted. In particular, the replication.factor should be at least 3, and the, * min.insync.replicas for these topics should be set to 2. * Get the partition metadata for the given topic. * 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. * @throws AuthorizationException if not authorized to the specified topic. Additionally, it is possible to continue, * sending after receiving an {@link org.apache.kafka.common.errors.OutOfOrderSequenceException}, but doing so, * can result in out of order delivery of pending messages. It will also abort the ongoing transaction if it's not, * If invoked from within a {@link Callback} this method will not block and will be equivalent to, * close(Duration.ofMillis(0)). * As such, it should be unique to each producer instance running within a partitioned application. 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. * @throws IllegalStateException if no transactional.id has been configured, * @throws org.apache.kafka.common.errors.UnsupportedVersionException fatal error indicating the broker, * does not support transactions (i.e. 465). If the producer is configured with acks = 0, the {@link RecordMetadata}. Note, that the consumer should have {@code enable.auto.commit=false}, * and should also not commit offsets manually (via {@link KafkaConsumer#commitSync(Map) sync} or. * @throws InterruptException if the thread is interrupted while blocked, * Should be called before the start of each new transaction. What is the difference between canonical name, simple name and class name in Java Class? When called, it adds the record to a buffer of pending record sends. * to multiple partitions (and topics!) * successful writes are marked as aborted, hence keeping the transactional guarantees. Equivalent to send(record, null). Finally, in order for transactional guarantees. * documentation for more details about detecting errors from a transactional send.

* This call will throw an exception immediately if any prior {@link #send(ProducerRecord)} calls failed with a. How to encourage melee combat when ranged is a stronger option. Specifying a timeout of zero means do not wait for pending send requests to complete. Note that. This is analogous to Nagle's algorithm in TCP. ", // Rethrow with original maxWaitMs to prevent logging exception with remainingWaitMs, "Topic %s not present in metadata after %d ms.", "Partition %d of topic %s with partition count %d is not present in metadata after %d ms.", * Validate that the record size isn't too large, " bytes when serialized which is larger than ", " bytes when serialized which is larger than the total memory buffer you have configured with the ", * 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. * it's recommended to use delivery.timeout.ms to control retry behavior, instead of retries. I am unable to make a decision like what is ideal to use or atleast the reason of using one over the other is unclear? This method will flush any unsent records before actually committing the transaction. The KafkaTemplate is Spring's implementation of it (although it does not implement Producer 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. * @throws IllegalStateException if no transactional.id has been configured or no transaction has been started. 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.