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ASF GitHub Bot commented on STORM-822: -------------------------------------- Github user revans2 commented on a diff in the pull request: https://github.com/apache/storm/pull/1131#discussion_r53699257 --- Diff: external/storm-kafka-new-consumer-api/src/main/java/org/apache/storm/kafka/spout/KafkaSpout.java --- @@ -0,0 +1,457 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one + * or more contributor license agreements. See the NOTICE file + * distributed with this work for additional information + * regarding copyright ownership. The ASF licenses this file + * to you under the Apache License, Version 2.0 (the + * "License"); you may not use this file except in compliance + * with the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.storm.kafka.spout; + +import org.apache.kafka.clients.consumer.ConsumerRebalanceListener; +import org.apache.kafka.clients.consumer.ConsumerRecord; +import org.apache.kafka.clients.consumer.ConsumerRecords; +import org.apache.kafka.clients.consumer.KafkaConsumer; +import org.apache.kafka.clients.consumer.OffsetAndMetadata; +import org.apache.kafka.common.TopicPartition; +import org.apache.storm.spout.SpoutOutputCollector; +import org.apache.storm.task.TopologyContext; +import org.apache.storm.topology.OutputFieldsDeclarer; +import org.apache.storm.topology.base.BaseRichSpout; +import org.apache.storm.tuple.Values; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.util.Collection; +import java.util.Comparator; +import java.util.HashMap; +import java.util.HashSet; +import java.util.Map; +import java.util.Set; +import java.util.TreeSet; +import java.util.concurrent.Executors; +import java.util.concurrent.ScheduledExecutorService; +import java.util.concurrent.ThreadFactory; +import java.util.concurrent.TimeUnit; +import java.util.concurrent.locks.Lock; +import java.util.concurrent.locks.ReentrantLock; + +public class KafkaSpout<K,V> extends BaseRichSpout { + private static final Logger LOG = LoggerFactory.getLogger(KafkaSpout.class); + private static final Comparator<org.apache.storm.kafka.spout.MessageId> OFFSET_COMPARATOR = new OffsetComparator(); + + // Storm + private Map conf; + private TopologyContext context; + protected SpoutOutputCollector collector; + + // Kafka + private final org.apache.storm.kafka.spout.KafkaSpoutConfig<K, V> kafkaSpoutConfig; + private KafkaConsumer<K, V> kafkaConsumer; + + // Bookkeeping + private org.apache.storm.kafka.spout.KafkaSpoutStream kafkaSpoutStream; + private org.apache.storm.kafka.spout.KafkaTupleBuilder<K,V> tupleBuilder; + private transient ScheduledExecutorService commitOffsetsTask; + private transient Lock ackCommitLock; + private transient volatile boolean commit; + private transient Map<org.apache.storm.kafka.spout.MessageId, Values> emittedTuples; // Keeps a list of emitted tuples that are pending being acked or failed + private transient Map<TopicPartition, Set<org.apache.storm.kafka.spout.MessageId>> failed; // failed tuples. They stay in this list until success or max retries is reached + private transient Map<TopicPartition, OffsetEntry> acked; // emitted tuples that were successfully acked. These tuples will be committed by the commitOffsetsTask or on consumer rebalance + private transient Set<org.apache.storm.kafka.spout.MessageId> blackList; // all the tuples that are in traffic when the rebalance occurs will be added to black list to be disregarded when they are either acked or failed + private transient int maxRetries; + + public KafkaSpout(org.apache.storm.kafka.spout.KafkaSpoutConfig<K,V> kafkaSpoutConfig, org.apache.storm.kafka.spout.KafkaSpoutStream kafkaSpoutStream, org.apache.storm.kafka.spout.KafkaTupleBuilder<K,V> tupleBuilder) { + this.kafkaSpoutConfig = kafkaSpoutConfig; // Pass in configuration + this.kafkaSpoutStream = kafkaSpoutStream; + this.tupleBuilder = tupleBuilder; + } + + @Override + public void open(Map conf, TopologyContext context, SpoutOutputCollector collector) { + // Spout internals + this.conf = conf; + this.context = context; + this.collector = collector; + + // Bookkeeping objects + emittedTuples = new HashMap<>(); + failed = new HashMap<>(); + acked = new HashMap<>(); + blackList = new HashSet<>(); + ackCommitLock = new ReentrantLock(); + maxRetries = kafkaSpoutConfig.getMaxTupleRetries(); + + // Kafka consumer + kafkaConsumer = new KafkaConsumer<>(kafkaSpoutConfig.getKafkaProps(), + kafkaSpoutConfig.getKeyDeserializer(), kafkaSpoutConfig.getValueDeserializer()); + kafkaConsumer.subscribe(kafkaSpoutConfig.getSubscribedTopics(), new KafkaSpoutConsumerRebalanceListener()); + + // Create commit offsets task + if (!kafkaSpoutConfig.isConsumerAutoCommitMode()) { // If it is auto commit, no need to commit offsets manually + createCommitOffsetsTask(); + } + } + + // ======== Commit Offsets Task ======= + + private void createCommitOffsetsTask() { + commitOffsetsTask = Executors.newSingleThreadScheduledExecutor(commitOffsetsThreadFactory()); + commitOffsetsTask.scheduleAtFixedRate(new Runnable() { + @Override + public void run() { + commit = true; + } + }, 1000, kafkaSpoutConfig.getOffsetsCommitFreqMs(), TimeUnit.MILLISECONDS); + } + + private ThreadFactory commitOffsetsThreadFactory() { + return new ThreadFactory() { + @Override + public Thread newThread(Runnable r) { + return new Thread(r, "kafka-spout-commit-offsets-thread"); + } + }; + } + + // ======== Next Tuple ======= + + @Override + public void nextTuple() { + if(commit) { + commitAckedTuples(); + } else if (retry()) { // Don't process new tuples until the failed tuples have all been acked + retryFailedTuples(); + } else { + emitTuples(poll()); + } + } + + private ConsumerRecords<K, V> poll() { + final ConsumerRecords<K, V> consumerRecords = kafkaConsumer.poll(kafkaSpoutConfig.getPollTimeoutMs()); + LOG.debug("Polled [{]} records from Kafka", consumerRecords.count()); + return consumerRecords; + } + + private void emitTuples(ConsumerRecords<K, V> consumerRecords) { + for (TopicPartition tp : consumerRecords.partitions()) { + final Iterable<ConsumerRecord<K, V>> records = consumerRecords.records(tp.topic()); // TODO Decide if want to give flexibility to emmit/poll either per topic or per partition + for (ConsumerRecord<K, V> record : records) { + final Values tuple = tupleBuilder.buildTuple(record); + final org.apache.storm.kafka.spout.MessageId messageId = new org.apache.storm.kafka.spout.MessageId(record); // TODO don't create message for non acking mode. Should we support non acking mode? + collector.emit(kafkaSpoutStream.getStreamId(), tuple, messageId); // emits one tuple per record + emittedTuples.put(messageId, tuple); + LOG.info("HMCL - Emitted tuple for record {}", record); + } + } + } + + private boolean retry() { + return failed.size() > 0; + } + + private void retryFailedTuples() { + for (TopicPartition tp : failed.keySet()) { + for (org.apache.storm.kafka.spout.MessageId msgId : failed.get(tp)) { + if (isInBlackList(msgId)) { + removeFromBlacklist(msgId); + removeFromFailed(tp, msgId); + } else { + final Values tuple = emittedTuples.get(msgId); + LOG.debug("Retrying tuple. [msgId={}, tuple={}]", msgId, tuple); + collector.emit(kafkaSpoutStream.getStreamId(), tuple, msgId); + } + } + } + } + + // all the tuples that are in traffic when the rebalance occurs will be added + // to black list to be disregarded when they are either acked or failed + private boolean isInBlackList(org.apache.storm.kafka.spout.MessageId msgId) { + return blackList.contains(msgId); + } + + private void removeFromBlacklist(org.apache.storm.kafka.spout.MessageId msgId) { + blackList.remove(msgId); + } + + // ======== Ack ======= + + @Override + public void ack(Object messageId) { + final org.apache.storm.kafka.spout.MessageId msgId = (org.apache.storm.kafka.spout.MessageId) messageId; + final TopicPartition tp = msgId.getTopicPartition(); + + if (isInBlackList(msgId)) { + removeFromBlacklist(msgId); + } else { + addAckedTuples(tp, msgId); + // Removed acked tuples from the emittedTuples data structure + emittedTuples.remove(msgId); + // if this acked msg is a retry, remove it from failed data structure + removeFromFailed(tp, msgId); + } + } + + private void addAckedTuples(TopicPartition tp, org.apache.storm.kafka.spout.MessageId msgId) { + // lock because ack and commit happen in different threads + ackCommitLock.lock(); + try { + if (!acked.containsKey(tp)) { + acked.put(tp, new OffsetEntry(tp)); + } + acked.get(tp).add(msgId); + } finally { + ackCommitLock.unlock(); + } + } + + // ======== Fail ======= + + @Override + public void fail(Object messageId) { + final org.apache.storm.kafka.spout.MessageId msgId = (org.apache.storm.kafka.spout.MessageId) messageId; + + if (isInBlackList(msgId)) { + removeFromBlacklist(msgId); + } else { + final TopicPartition tp = msgId.getTopicPartition(); + // limit to max number of retries + if (msgId.numFails() >= maxRetries) { + LOG.debug("Reached the maximum number of retries. Adding [{]} to list of messages to be committed to kafka", msgId); + ack(msgId); + removeFromFailed(tp, msgId); + } else { + addToFailed(tp, msgId); --- End diff -- Why don't we want to just re-emit that failed tuple right here? > As a storm developer I’d like to use the new kafka consumer API (0.8.3) to > reduce dependencies and use long term supported kafka apis > -------------------------------------------------------------------------------------------------------------------------------------- > > Key: STORM-822 > URL: https://issues.apache.org/jira/browse/STORM-822 > Project: Apache Storm > Issue Type: Story > Components: storm-kafka > Reporter: Thomas Becker > Assignee: Hugo Louro > -- This message was sent by Atlassian JIRA (v6.3.4#6332)