Status
Current state: Draft
Discussion thread:
JIRA:
Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).
Motivation
MirrorMaker2 is currently implemented on Kafka Connect Framework, more specifically the Source Connector / Task, which do not provide exactly-once semantics (EOS) out-of-the-box, as discussed in https://github.com/confluentinc/kafka-connect-jdbc/issues/461, https://github.com/apache/kafka/pull/5553, and . Therefore MirrorMaker2 currently does not provide EOS.
This proposal is to provide an option to enable EOS for MirrorMaker 2 if no data loss or duplicate data is preferred. The key idea behind this proposal is to extend SinkTask with a brand new MirrorSinkTask implementation, which leverages the consumer from WorkerSinkTask and provides an option to either deliver messages
(1) Exactly-once: by a transactional producer in MirrorSinkTask and consumer offsets are committed within a transaction by the transactional producer
OR
(2) At-least-once: by a non-transactional producer in MirrorSinkTask and consumer offsets are committed by the consumer from WorkerSinkTask separately
The reasons to implement a brand new MirrorSinkTask that extends SinkTask, rather than working on the existing MirrorSourceTask, are the following:
- as mentioned above, Kafka Connect Source Connector / Task do not provide EOS by nature, mostly because of async and periodic source task offset commit, which in MirorrMaker case, the "offset" is consumer offset. So this seems one of the blockers to enable EOS without a lots of changes in WokerSourceTask.
- Since MirrorSinkTask (that extends SinkTask) is a new implementation, we can fully control how a producer is created (transactional v.s. non-transactional) and handle various Exception cases (especially in transactional mode), purely in the new implementation.
- MirrorSinkTask can intentionally return an empty result from preCommit() (defined in SinkTask) by overriding it to disable the consumer offset commit done by WorkerSinkTask, so that the transactional producer is able to commit consumer offset within one transaction.
Public Interfaces
New classes and interfaces include:
MirrorMakerConfig
Name | Type | Default | Doc |
---|---|---|---|
connector.type | string | source | if "source", the existing MirrorSourceConnector will be launched. If "sink", the new MirrorSinkConnector will be launched with further option to enable EOS |
MirrorConnectorConfig
Name | Type | Default | Doc |
---|---|---|---|
transaction.producer | boolean | false | if True, EOS is enabled between consumer and producer |
Proposed Changes
MirrorSinkTask
The following is the pseudocode snippet illustrates the high-level key implementation:
private boolean isTransactional = config.getTransactionalProducer(); private boolean transactionStart = false; protected Map<TopicPartition, OffsetAndMetadata> offsetsMap = new HashMap<>(); protected KafkaProducer<byte[], byte[]> initProducer(boolean isTransactional) { Map<String, Object> producerConfig = config.targetProducerConfig(); if (isTransactional) { log.info("use transactional producer"); producerConfig.put(ProducerConfig.ACKS_CONFIG, "all"); producerConfig.put(ProducerConfig.ENABLE_IDEMPOTENCE_CONFIG, "true"); producerConfig.put(ProducerConfig.TRANSACTIONAL_ID_CONFIG, genTransactionId()); producerConfig.put(ProducerConfig.CLIENT_ID_CONFIG, "trasactional-producer"); } else { producerConfig.put(ProducerConfig.CLIENT_ID_CONFIG, "non-trasactional-producer"); } return MirrorUtils.newProducer(producerConfig); } @Override public void put(Collection<SinkRecord> records) { log.info("receive {} messages from consumer", records.size()); if (records.size() == 0) { return; } try { sendBatch(records, producer); } catch (RebalanceException e) { producer.close(); producer = initProducer(isTransactional); } catch (ResendRecordsException e) { abortTransaction(producer); //TODO: add limited retry sendBatch(e.getRemainingRecords(), producer); } catch (Throwable e) { log.error(getHostName() + " terminating on exception: {}", e); return; } } private void sendBatch(Collection<SinkRecord> records, KafkaProducer<byte[], byte[]> producer) { try { Map<TopicPartition, List<SinkRecord> remainingRecordsMap = new HashMap<>(); offsetsMap.clear(); beginTransaction(producer); SinkRecord record; for ((record = records.peek()) != null) { ProducerRecord<byte[], byte[]> producerRecord = convertToProducerRecord(record); offsetsMap.compute(new TopicPartition(record.topic(), record.kafkaPartition()), (tp, curOffsetMetadata) -> (curOffsetMetadata == null || record.kafkaOffset() > curOffsetMetadata.offset()) ? new OffsetAndMetadata(record.kafkaOffset()) : curOffsetMetadata); Future<RecordMetadata> future = producer.send(producerRecord, (recordMetadata, e) -> { if (e != null) { log.error("{} failed to send record to {}: ", MirrorSinkTask.this, producerRecord.topic(), e); log.debug("{} Failed record: {}", MirrorSinkTask.this, producerRecord); throw new KafkaException(e); } else { log.info("{} Wrote record successfully: topic {} partition {} offset {}", //log.trace MirrorSinkTask.this, recordMetadata.topic(), recordMetadata.partition(), recordMetadata.offset()); commitRecord(record, recordMetadata); } }); futures.add(future); records.poll(); } } catch (KafkaException e) { // Any unsent messages are added to the remaining remainingRecordsMap for re-send for (SinkRecord record = records.poll(); record != null; record = records.poll()) { addConsumerRecordToTopicPartitionRecordsMap(record, remainingRecordsMap); } finally { //TODO: may add more exception handling case for (Future<RecordMetadata> future : futures) { try { future.get(); } catch (Exception e) { SinkRecord record = futureMap.get(future); // Any record failed to send, add to the remainingRecordsMap addConsumerRecordToTopicPartitionRecordsMap(record, remainingRecordsMap); } } } if (isTransactional && remainingRecordsMap.size() == 0) { producer.sendOffsetsToTransaction(offsetsMap, consumerGroupId); commitTransaction(producer); } if (remainingRecordsMap.size() > 0) { // For transaction case, all records should be put into remainingRecords, as the whole transaction should be redone Collection<SinkRecord> recordsToReSend; if (isTransactional) { // Transactional: retry all records, the transaction will have cancelled all of our outputs. recordsToReSend = records; } else { // Non-transactional: only retry failed records, others already were finished and sent. recordsToReSend = remainingRecordsMap; } throw new ResendRecordsException(recordsToReSend); } } @Override public Map<TopicPartition, OffsetAndMetadata> preCommit(Map<TopicPartition, OffsetAndMetadata> offsets) { // if transactional, return empty Map intentionally to disable the offset commit by commitOffsets() in "WorkerSinkTask.java" // so that the transactional producer is able to commit the consumer offsets in a transaction if (isTransactional) return new HashMap<TopicPartition, OffsetAndMetadata>(); else // otherwise, return offsetsMap to let commitOffsets() in "WorkerSinkTask.java" to commit offsets return offsetsMap; } // This commitRecord() follows the same logics as commitRecord() in MirrorSourceTask public void commitRecord(SinkRecord record, RecordMetadata metadata) { try { if (stopping) { return; } if (!metadata.hasOffset()) { log.error("RecordMetadata has no offset -- can't sync offsets for {}.", record.topic()); return; } TopicPartition topicPartition = new TopicPartition(record.topic(), record.kafkaPartition()); long latency = System.currentTimeMillis() - record.timestamp(); metrics.countRecord(topicPartition); metrics.replicationLatency(topicPartition, latency); TopicPartition sourceTopicPartition = MirrorUtils.unwrapPartition(record.sourcePartition()); long upstreamOffset = MirrorUtils.unwrapOffset(record.sourceOffset()); long downstreamOffset = metadata.offset(); maybeSyncOffsets(sourceTopicPartition, upstreamOffset, downstreamOffset); } catch (Throwable e) { log.warn("Failure committing record.", e); } } private void beginTransaction(KafkaProducer<byte[], byte[]> producer) { if (isTransactional) { producer.beginTransaction(); transactionStart = true; } } private void initTransactions(KafkaProducer<byte[], byte[]> producer) { if (isTransactional) { producer.initTransactions(); } } private void commitTransaction(KafkaProducer<byte[], byte[]> producer) { if (isTransactional) { producer.commitTransaction(); transactionStart = false; } } private void abortTransaction(KafkaProducer<byte[], byte[]> producer) { if (isTransactional && transactionStart) { producer.abortTransaction(); transactionStart = false; } } public static class ResendRecordsException extends Exception { private Collection<SinkRecord> remainingRecords; public ResendRecordsException(Collection<SinkRecord> remainingRecords) { super(cause); this.remainingRecords = remainingRecords; } public Collection<SinkRecord> getRemainingRecords() { return remainingRecords; } }
Migration to EOS
Deprecation
A config "connector.type" is proposed to choose which type of Connector (source or sink) to use in MirrorMaker2. So both types of Connectors will co-exist for the near future.
In the long term, if MirrorSinkConnector covers all use cases of MirrorSourceConnector and migration is seamless, then in the future release, deprecation of MirrorSource Connector could be considered.
Rejected Alternatives
https://github.com/apache/kafka/pull/5553, and are relevant efforts in a bigger scope, but it seems none of them proceeded successfully for a quite amount of time.