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https://issues.apache.org/jira/browse/STORM-822?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15174706#comment-15174706
]
ASF GitHub Bot commented on STORM-822:
--------------------------------------
Github user hmcl commented on a diff in the pull request:
https://github.com/apache/storm/pull/1131#discussion_r54661514
--- Diff:
external/storm-kafka-new-consumer-api/src/main/java/org/apache/storm/kafka/spout/KafkaSpout.java
---
@@ -0,0 +1,445 @@
+/*
+ * 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.kafka.spout.KafkaSpoutConfig.FirstPollOffsetStrategy;
+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.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import java.util.Collection;
+import java.util.Comparator;
+import java.util.HashMap;
+import java.util.Iterator;
+import java.util.List;
+import java.util.Map;
+import java.util.NavigableSet;
+import java.util.TreeSet;
+import java.util.concurrent.TimeUnit;
+
+import static
org.apache.storm.kafka.spout.KafkaSpoutConfig.FirstPollOffsetStrategy.EARLIEST;
+import static
org.apache.storm.kafka.spout.KafkaSpoutConfig.FirstPollOffsetStrategy.LATEST;
+import static
org.apache.storm.kafka.spout.KafkaSpoutConfig.FirstPollOffsetStrategy.UNCOMMITTED_EARLIEST;
+import static
org.apache.storm.kafka.spout.KafkaSpoutConfig.FirstPollOffsetStrategy.UNCOMMITTED_LATEST;
+
+public class KafkaSpout<K,V> extends BaseRichSpout {
+ private static final Logger LOG =
LoggerFactory.getLogger(KafkaSpout.class);
+ private static final Comparator<MessageId> OFFSET_COMPARATOR = new
OffsetComparator();
+
+ // Storm
+ protected SpoutOutputCollector collector;
+
+ // Kafka
+ private final KafkaSpoutConfig<K, V> kafkaSpoutConfig;
+ private KafkaConsumer<K, V> kafkaConsumer;
+ private transient boolean consumerAutoCommitMode;
+ private transient FirstPollOffsetStrategy firstPollOffsetStrategy;
+
+ // Bookkeeping
+ private KafkaSpoutStreams kafkaSpoutStreams;
+ private KafkaTupleBuilder<K,V> tupleBuilder;
+ private transient Timer timer; //
timer == null for auto commit mode
+ 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 int maxRetries; //
Max number of times a tuple is retried
+ private transient boolean initialized; // Flag indicating
that the spout is still undergoing initialization process.
+ // Initialization is
only complete after the first call to
KafkaSpoutConsumerRebalanceListener.onPartitionsAssigned()
+
+
+ public KafkaSpout(KafkaSpoutConfig<K,V> kafkaSpoutConfig,
KafkaSpoutStreams kafkaSpoutStreams, KafkaTupleBuilder<K,V> tupleBuilder) {
+ this.kafkaSpoutConfig = kafkaSpoutConfig; // Pass
in configuration
+ this.kafkaSpoutStreams = kafkaSpoutStreams;
+ this.tupleBuilder = tupleBuilder;
+ }
+
+ @Override
+ public void open(Map conf, TopologyContext context,
SpoutOutputCollector collector) {
+ initialized = false;
+
+ // Spout internals
+ this.collector = collector;
+ maxRetries = kafkaSpoutConfig.getMaxTupleRetries();
+
+ // Offset management
+ firstPollOffsetStrategy =
kafkaSpoutConfig.getFirstPollOffsetStrategy();
+ consumerAutoCommitMode =
kafkaSpoutConfig.isConsumerAutoCommitMode();
+
+ if (!consumerAutoCommitMode) { // If it is auto commit, no
need to commit offsets manually
+ timer = new Timer(kafkaSpoutConfig.getOffsetsCommitFreqMs(),
500, TimeUnit.MILLISECONDS);
+ acked = new HashMap<>();
+ }
+
+ // Kafka consumer
+ kafkaConsumer = new
KafkaConsumer<>(kafkaSpoutConfig.getKafkaProps(),
+ kafkaSpoutConfig.getKeyDeserializer(),
kafkaSpoutConfig.getValueDeserializer());
+ kafkaConsumer.subscribe(kafkaSpoutConfig.getSubscribedTopics(),
new KafkaSpoutConsumerRebalanceListener());
+ // Initial poll to get the consumer registration process going.
+ // KafkaSpoutConsumerRebalanceListener will be called foloowing
this poll upon partition registration
+ kafkaConsumer.poll(0);
+
+ LOG.debug("Kafka Spout opened with the following configuration:
{}", kafkaSpoutConfig.toString());
+ }
+
+ // ======== Next Tuple =======
+
+ @Override
+ public void nextTuple() {
+ if (initialized) {
+ if(commit()) {
+ commitOffsetsForAckedTuples();
+ } else {
+ emitTuples(poll());
+ }
+ } else {
+ LOG.debug("Spout not initialized. Not sending tuples until
initialization completes");
+ }
+ }
+
+ private boolean commit() {
+ return !consumerAutoCommitMode && timer.expired(); // timer !=
null for non auto commit mode
+ }
+
+ 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 (final ConsumerRecord<K, V> record : records) {
+ if (record.offset() == 0 || record.offset() >
acked.get(tp).committedOffset) { // The first poll includes the last
committed offset. This if avoids duplication
+ final List<Object> tuple =
tupleBuilder.buildTuple(record);
+ final MessageId messageId = new MessageId(record,
tuple); // TODO don't create message for non
acking mode. Should we support non acking mode?
+
+ kafkaSpoutStreams.emit(collector, messageId);
// emits one tuple per record
+ LOG.debug("Emitted tuple [{}] for record [{}]", tuple,
record);
+ }
+ }
+ }
+ }
+
+ // ======== Ack =======
+ @Override
+ public void ack(Object messageId) {
+ final MessageId msgId = (MessageId) messageId;
+ final TopicPartition tp = msgId.getTopicPartition();
+
+ if (!consumerAutoCommitMode) { // Only need to keep track of
acked tuples if commits are not done automatically
+ acked.get(tp).add(msgId);
+ LOG.debug("Adding acked message to [{}] to list of messages to
be committed to Kafka", msgId);
+ }
+ }
+
+ // ======== Fail =======
+
+ @Override
+ public void fail(Object messageId) {
+ final MessageId msgId = (MessageId) messageId;
+ if (msgId.numFails() < maxRetries) {
+ msgId.incrementNumFails();
+ kafkaSpoutStreams.emit(collector, msgId);
+ LOG.debug("Retried tuple with message id [{}]", messageId);
+ } else { // limit to max number of retries
+ LOG.debug("Reached maximum number of retries. Message being
marked as acked.");
+ ack(msgId);
+ }
+ }
+
+ // ======== Activate / Deactivate =======
+
+ @Override
+ public void activate() {
+ // Shouldn't have to do anything for now. If specific cases need
to be handled logic will go here
+ }
+
+ @Override
+ public void deactivate() {
+ if(!consumerAutoCommitMode) {
+ commitOffsetsForAckedTuples();
+ }
+ }
+
+ @Override
+ public void close() {
+ try {
+ kafkaConsumer.wakeup();
+ if(!consumerAutoCommitMode) {
+ commitOffsetsForAckedTuples();
+ }
+ } finally {
+ //remove resources
+ kafkaConsumer.close();
+ }
+ }
+
+ // TODO must declare multiple output streams
+ @Override
+ public void declareOutputFields(OutputFieldsDeclarer declarer) {
+ kafkaSpoutStreams.declareOutputFields(declarer);
+ }
+
+ // ====== Private helper methods ======
+
+ private void commitOffsetsForAckedTuples() {
+ final Map<TopicPartition, OffsetAndMetadata> nextCommitOffsets =
new HashMap<>();
+
+ try {
+ for (Map.Entry<TopicPartition, OffsetEntry> tpOffset :
acked.entrySet()) {
+ final OffsetAndMetadata offsetAndMetadata =
tpOffset.getValue().findNextCommitOffset();
+ if (offsetAndMetadata != null) {
+ nextCommitOffsets.put(tpOffset.getKey(),
offsetAndMetadata);
+ }
+ }
+
+ if (!nextCommitOffsets.isEmpty()) {
+ kafkaConsumer.commitSync(nextCommitOffsets);
+ LOG.debug("Offsets successfully committed to Kafka [{}]",
nextCommitOffsets);
+ // Instead of iterating again, we could commit and update
state for each TopicPartition in the prior loop,
+ // but the multiple network calls should be more expensive
than iterating twice over a small loop
+ for (Map.Entry<TopicPartition, OffsetEntry> tpOffset :
acked.entrySet()) {
+ final OffsetEntry offsetEntry = tpOffset.getValue();
+
offsetEntry.updateAckedState(nextCommitOffsets.get(tpOffset.getKey()));
+ }
+ } else {
+ LOG.trace("No offsets to commit. {}", toString());
+ }
+ } catch (Exception e) {
+ LOG.error("Exception occurred while committing to Kafka
offsets of acked tuples", e);
+ }
+ }
+
+ @Override
+ public String toString() {
+ return "{acked=" + acked + "} ";
+ }
+
+ // ======= Offsets Commit Management ==========
+
+ private static class OffsetComparator implements Comparator<MessageId>
{
+ public int compare(MessageId m1, MessageId m2) {
+ return m1.offset() < m2.offset() ? -1 : m1.offset() ==
m2.offset() ? 0 : 1;
+ }
+ }
+
+ /** This class is not thread safe */
+ private class OffsetEntry {
+ private final TopicPartition tp;
+ private long committedOffset; // last offset
committed to Kafka, or initial fetching offset (initial value depends on offset
strategy. See KafkaSpoutConsumerRebalanceListener)
+ private final NavigableSet<MessageId> ackedMsgs = new
TreeSet<>(OFFSET_COMPARATOR); // acked messages sorted by ascending order
of offset
+
+ public OffsetEntry(TopicPartition tp, long committedOffset) {
+ this.tp = tp;
+ this.committedOffset = committedOffset;
+ LOG.debug("Created OffsetEntry for [topic-partition={},
committed-or-initial-fetch-offset={}]", tp, committedOffset);
+ }
+
+ public void add(MessageId msgId) { // O(Log N)
+ ackedMsgs.add(msgId);
+ }
+
+ /**
+ * This method has side effects. The method updateAckedState
should be called after this method.
+ * @return the next OffsetAndMetadata to commit, or null if no
offset is ready to commit.
+ */
+ public OffsetAndMetadata findNextCommitOffset() {
+ boolean found = false;
+ long currOffset;
+ long nextCommitOffset = committedOffset;
+ MessageId nextCommitMsg = null; // this is a convenience
field to make it faster to create OffsetAndMetadata
+
+ for (MessageId currAckedMsg : ackedMsgs) { // complexity is
that of a linear scan on a TreeMap
+ if ((currOffset = currAckedMsg.offset()) == 0 ||
currOffset != nextCommitOffset) { // this is to void duplication because
the first message polled is the last message acked.
+ if (currOffset == nextCommitOffset || currOffset ==
nextCommitOffset + 1) { // found the next offset to commit
+ found = true;
+ nextCommitMsg = currAckedMsg;
+ nextCommitOffset = currOffset;
+ LOG.trace("Found offset to commit [{}]. {}",
currOffset, toString());
+ } else if (currAckedMsg.offset() > nextCommitOffset +
1) { // offset found is not continuous to the offsets listed to go in the
next commit, so stop search
+ LOG.debug("Non continuous offset found [{}]. It
will be processed in a subsequent batch. {}", currOffset, toString());
+ break;
+ } else {
+ LOG.debug("Unexpected offset found [{}]. {}",
currOffset, toString());
+ break;
+ }
+ }
+ }
+
+ OffsetAndMetadata offsetAndMetadata = null;
+ if (found) {
+ offsetAndMetadata = new
OffsetAndMetadata(nextCommitOffset,
nextCommitMsg.getMetadata(Thread.currentThread()));
+ LOG.trace("Offset to be committed next: [{}] {}",
offsetAndMetadata.offset(), toString());
+ } else {
+ LOG.debug("No offsets ready to commit", toString());
+ }
+ return offsetAndMetadata;
+ }
+
+ /**
+ * This method has side effects and should be called after
findNextCommitOffset
+ */
+ public void updateAckedState(OffsetAndMetadata offsetAndMetadata) {
+ if (offsetAndMetadata != null) {
+ committedOffset = offsetAndMetadata.offset();
+ for (Iterator<MessageId> iterator1 = ackedMsgs.iterator();
+ iterator1.hasNext(); ) {
+ if (iterator1.next().offset() <=
offsetAndMetadata.offset()) {
+ iterator1.remove();
+ } else {
+ break;
+ }
+ }
+ }
+ LOG.trace("Object state after update: {}", toString());
+ }
+
+ public boolean isEmpty() {
+ return ackedMsgs.isEmpty();
+ }
+
+ @Override
+ public String toString() {
+ return "OffsetEntry{" +
+ "topic-partition=" + tp +
+ ", committedOffset=" + committedOffset +
+ ", ackedMsgs=" + ackedMsgs +
+ '}';
+ }
+ }
+
+ // =========== Consumer Rebalance Listener - On the same thread as the
caller ===========
+
+ private class KafkaSpoutConsumerRebalanceListener implements
ConsumerRebalanceListener {
+ @Override
+ public void onPartitionsRevoked(Collection<TopicPartition>
partitions) {
+ LOG.debug("Partitions revoked. [consumer-group={},
consumer={}, topic-partitions={}]",
+ kafkaSpoutConfig.getConsumerGroupId(), kafkaConsumer,
partitions);
+ if (!consumerAutoCommitMode && initialized) {
+ initialized = false;
+ commitOffsetsForAckedTuples();
+ }
+ }
+
+ @Override
+ public void onPartitionsAssigned(Collection<TopicPartition>
partitions) {
+ LOG.debug("Partitions reassignment. [consumer-group={},
consumer={}, topic-partitions={}]",
+ kafkaSpoutConfig.getConsumerGroupId(), kafkaConsumer,
partitions);
+
+ initialize(partitions);
+ }
+
+ private void initialize(Collection<TopicPartition> partitions) {
+ acked.keySet().retainAll(partitions); // remove from acked
all partitions that are no longer assigned to this spout
+ for (TopicPartition tp: partitions) {
+ final OffsetAndMetadata committedOffset =
kafkaConsumer.committed(tp);
+ final long fetchOffset = doSeek(tp, committedOffset);
+ setAcked(tp, fetchOffset);
+ }
+ initialized = true;
+ LOG.debug("Initialization complete");
+ }
+
+ /** sets the cursor to the location dictated by the first poll
strategy and returns the fetch offset */
+ private long doSeek(TopicPartition tp, OffsetAndMetadata
committedOffset) {
+ long fetchOffset;
+ if (committedOffset != null) { // fetchOffset was
committed for this TopicPartition
+ if (firstPollOffsetStrategy.equals(EARLIEST)) {
+ kafkaConsumer.seekToBeginning(tp);
+ fetchOffset = kafkaConsumer.position(tp);
+ } else if (firstPollOffsetStrategy.equals(LATEST)) {
+ kafkaConsumer.seekToEnd(tp);
+ fetchOffset = kafkaConsumer.position(tp);
+ } else {
+ // do nothing - by default polling starts at the lat
committed fetchOffset
+ fetchOffset = committedOffset.offset();
+ }
+ } else { // no previous commit occurred, so start at the
beginning or end depending on the strategy
+ if (firstPollOffsetStrategy.equals(EARLIEST) ||
firstPollOffsetStrategy.equals(UNCOMMITTED_EARLIEST)) {
+ kafkaConsumer.seekToBeginning(tp);
+ } else if (firstPollOffsetStrategy.equals(LATEST) ||
firstPollOffsetStrategy.equals(UNCOMMITTED_LATEST)) {
+ kafkaConsumer.seekToEnd(tp);
+ }
+ fetchOffset = kafkaConsumer.position(tp);
+ }
+ return fetchOffset;
+ }
+
+ private void setAcked(TopicPartition tp, long fetchOffset) {
+ if (!consumerAutoCommitMode && !acked.containsKey(tp)) {
// If this partition was previously assigned, leave the acked offsets as
they were to resume where it left off
+ acked.put(tp, new OffsetEntry(tp, fetchOffset));
+ }
+ }
+ }
+
+ // =========== Timer ===========
+
+ private class Timer {
+ private final long frequency;
+ private final long delay;
+ private final TimeUnit timeUnit;
+ private final long frequencyNanos;
+ private long start;
+
+ /** Creates a timer to expire at the given frequency and starting
with the specified time delay.
+ * Frequency and delay must be specified in the same TimeUnit */
+ public Timer(long frequency, long delay, TimeUnit timeUnit) {
+ this.frequency = frequency;
+ this.delay = delay;
+ this.timeUnit = timeUnit;
+
+ frequencyNanos = timeUnit.toNanos(frequency);
+ start = System.nanoTime() + timeUnit.toNanos(delay);
+ }
+
+ public long frequency() {
+ return frequency;
+ }
+
+ public long delay() {
+ return delay;
+ }
+
+ public TimeUnit getTimeUnit() {
+ return timeUnit;
+ }
+
+ /**
+ * If this method returns true, a new timer cycle will start.
+ * @return true if the elapsed time since the last true value call
to this method is greater or
+ * equal to the frequency specified upon creation of this timer.
Returns false otherwise.
+ */
+ public boolean expired() {
--- End diff --
Done. Renamed to isExpiredResetOnTrue()
> 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
>
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