解析storm的KafkaSpout

KafkaSpout的源码

package storm.kafka;

import backtype.storm.Config;
import backtype.storm.metric.api.IMetric;
import backtype.storm.spout.SpoutOutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.base.BaseRichSpout;
import kafka.message.Message;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import storm.kafka.PartitionManager.KafkaMessageId;

import java.util.*;

// TODO: need to add blacklisting
// TODO: need to make a best effort to not re-emit messages if don't have to
public class KafkaSpout extends BaseRichSpout {
    public static class MessageAndRealOffset {
        public Message msg;
        public long offset;

        public MessageAndRealOffset(Message msg, long offset) {
            this.msg = msg;
            this.offset = offset;
        }
    }

    static enum EmitState {
        EMITTED_MORE_LEFT,
        EMITTED_END,
        NO_EMITTED
    }

    public static final Logger LOG = LoggerFactory.getLogger(KafkaSpout.class);

    String _uuid = UUID.randomUUID().toString();
    SpoutConfig _spoutConfig;
    SpoutOutputCollector _collector;
    PartitionCoordinator _coordinator;
    DynamicPartitionConnections _connections;
    ZkState _state;

    long _lastUpdateMs = 0;

    int _currPartitionIndex = 0;

    public KafkaSpout(SpoutConfig spoutConf) {
        _spoutConfig = spoutConf;
    }

    @Override
    public void open(Map conf, final TopologyContext context, final SpoutOutputCollector collector) {
        _collector = collector;

        Map stateConf = new HashMap(conf);
        List<String> zkServers = _spoutConfig.zkServers;
        if (zkServers == null) {
            zkServers = (List<String>) conf.get(Config.STORM_ZOOKEEPER_SERVERS);
        }
        Integer zkPort = _spoutConfig.zkPort;
        if (zkPort == null) {
            zkPort = ((Number) conf.get(Config.STORM_ZOOKEEPER_PORT)).intValue();
        }
        stateConf.put(Config.TRANSACTIONAL_ZOOKEEPER_SERVERS, zkServers);
        stateConf.put(Config.TRANSACTIONAL_ZOOKEEPER_PORT, zkPort);
        stateConf.put(Config.TRANSACTIONAL_ZOOKEEPER_ROOT, _spoutConfig.zkRoot);
        _state = new ZkState(stateConf);

        _connections = new DynamicPartitionConnections(_spoutConfig, KafkaUtils.makeBrokerReader(conf, _spoutConfig));

        // using TransactionalState like this is a hack
        int totalTasks = context.getComponentTasks(context.getThisComponentId()).size();
        if (_spoutConfig.hosts instanceof StaticHosts) {
            _coordinator = new StaticCoordinator(_connections, conf, _spoutConfig, _state, context.getThisTaskIndex(), totalTasks, _uuid);
        } else {
            _coordinator = new ZkCoordinator(_connections, conf, _spoutConfig, _state, context.getThisTaskIndex(), totalTasks, _uuid);
        }

        context.registerMetric("kafkaOffset", new IMetric() {
            KafkaUtils.KafkaOffsetMetric _kafkaOffsetMetric = new KafkaUtils.KafkaOffsetMetric(_spoutConfig.topic, _connections);

            @Override
            public Object getValueAndReset() {
                List<PartitionManager> pms = _coordinator.getMyManagedPartitions();
                Set<Partition> latestPartitions = new HashSet();
                for (PartitionManager pm : pms) {
                    latestPartitions.add(pm.getPartition());
                }
                _kafkaOffsetMetric.refreshPartitions(latestPartitions);
                for (PartitionManager pm : pms) {
                    _kafkaOffsetMetric.setLatestEmittedOffset(pm.getPartition(), pm.lastCompletedOffset());
                }
                return _kafkaOffsetMetric.getValueAndReset();
            }
        }, _spoutConfig.metricsTimeBucketSizeInSecs);

        context.registerMetric("kafkaPartition", new IMetric() {
            @Override
            public Object getValueAndReset() {
                List<PartitionManager> pms = _coordinator.getMyManagedPartitions();
                Map concatMetricsDataMaps = new HashMap();
                for (PartitionManager pm : pms) {
                    concatMetricsDataMaps.putAll(pm.getMetricsDataMap());
                }
                return concatMetricsDataMaps;
            }
        }, _spoutConfig.metricsTimeBucketSizeInSecs);
    }

    @Override
    public void close() {
        _state.close();
    }

    @Override
    public void nextTuple() {
        List<PartitionManager> managers = _coordinator.getMyManagedPartitions();
        for (int i = 0; i < managers.size(); i++) {

            try {
                // in case the number of managers decreased
                _currPartitionIndex = _currPartitionIndex % managers.size();
                EmitState state = managers.get(_currPartitionIndex).next(_collector);
                if (state != EmitState.EMITTED_MORE_LEFT) {
                    _currPartitionIndex = (_currPartitionIndex + 1) % managers.size();
                }
                if (state != EmitState.NO_EMITTED) {
                    break;
                }
            } catch (FailedFetchException e) {
                LOG.warn("Fetch failed", e);
                _coordinator.refresh();
            }
        }

        long now = System.currentTimeMillis();
        if ((now - _lastUpdateMs) > _spoutConfig.stateUpdateIntervalMs) {
            commit();
        }
    }

    @Override
    public void ack(Object msgId) {
        KafkaMessageId id = (KafkaMessageId) msgId;
        PartitionManager m = _coordinator.getManager(id.partition);
        if (m != null) {
            m.ack(id.offset);
        }
    }

    @Override
    public void fail(Object msgId) {
        KafkaMessageId id = (KafkaMessageId) msgId;
        PartitionManager m = _coordinator.getManager(id.partition);
        if (m != null) {
            m.fail(id.offset);
        }
    }

    @Override
    public void deactivate() {
        commit();
    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer declarer) {
        declarer.declare(_spoutConfig.scheme.getOutputFields());
    }

    private void commit() {
        _lastUpdateMs = System.currentTimeMillis();
        for (PartitionManager manager : _coordinator.getMyManagedPartitions()) {
            manager.commit();
        }
    }

}

KafkaSpout在配置使用时必须传入一个SpoutConfig，而这个SpoutConfig里卖弄保存有全部的kafka的配置：

package storm.kafka;

import java.io.Serializable;
import java.util.List;


public class SpoutConfig extends KafkaConfig implements Serializable {
    public List<String> zkServers = null;//记录配置的消费的zk节点信息
    public Integer zkPort = null;//zk的端口
    public String zkRoot = null;//保存kafka消费信息的节点位置
    public String id = null;//当前spout的消费组名称，如果多个spout名称一样，将共享消费进度，否则将不共享消费进度

    // setting for how often to save the current kafka offset to ZooKeeper
    public long stateUpdateIntervalMs = 2000; //设置线程多久将消费进度保存到zk上

    // Exponential back-off retry settings.  These are used when retrying messages after a bolt
    // calls OutputCollector.fail().
    public long retryInitialDelayMs = 0; //设置发送boult中初始化的时间，0为没限制
    public double retryDelayMultiplier = 1.0;
    public long retryDelayMaxMs = 60 * 1000;//发送到boult后超过多长时间为失败

    public SpoutConfig(BrokerHosts hosts, String topic, String zkRoot, String id) {
        super(hosts, topic);
        this.zkRoot = zkRoot;
        this.id = id;
    }
}

从代码里可以看到SpoutConfig继承了KafkaConfig，因为strom需要将代码分发到Supervisor因此实现了Serializable序列化接口，可以将代码发送到各个Supervisor节点上！

package storm.kafka;

import backtype.storm.spout.MultiScheme;
import backtype.storm.spout.RawMultiScheme;

import java.io.Serializable;

public class KafkaConfig implements Serializable {

    public final BrokerHosts hosts;//设置kafka从哪里获取相关的配置信息
    public final String topic;//从哪个topic开始消费
    public final String clientId;//设置客户端标识

    public int fetchSizeBytes = 1024 * 1024;//发给Kafka的每个FetchRequest中，用此指定想要的response中总的消息的大小
    public int socketTimeoutMs = 10000;//设置的超时时间
    public int fetchMaxWait = 10000;//设置的在broker无消息时的等待时间
    public int bufferSizeBytes = 1024 * 1024;//SimpleConsumer所使用的SocketChannel的读缓冲区大小
    public MultiScheme scheme = new RawMultiScheme();//设置从服务器读取的byte[]流反序列化方式
    public boolean ignoreZkOffsets = false;//是否强制从Kafka中offset最小的开始读起
    public long startOffsetTime = kafka.api.OffsetRequest.EarliestTime();//从哪里的offset开始读取消息，默认从消息的最前端开始，有两种方式可选
    public long maxOffsetBehind = Long.MAX_VALUE;//KafkaSpout读取的进度与目标进度相差多少，相差太多，Spout会丢弃中间的消息
    public boolean useStartOffsetTimeIfOffsetOutOfRange = true;//如果所请求的offset对应的消息在Kafka中不存在，是否使用startOffsetTime
    public int metricsTimeBucketSizeInSecs = 60;//多长时间统计一次消息

    public KafkaConfig(BrokerHosts hosts, String topic) {
        this(hosts, topic, kafka.api.OffsetRequest.DefaultClientId());
    }

    public KafkaConfig(BrokerHosts hosts, String topic, String clientId) {
        this.hosts = hosts;
        this.topic = topic;
        this.clientId = clientId;
    }

}

附上Topology

package test;

import java.util.ArrayList;
import java.util.List;
import java.util.Map;

import storm.kafka.BrokerHosts;
import storm.kafka.KafkaSpout;
import storm.kafka.SpoutConfig;
import storm.kafka.StringScheme;
import storm.kafka.ZkHosts;
import backtype.storm.Config;
import backtype.storm.LocalCluster;
import backtype.storm.StormSubmitter;
import backtype.storm.spout.SchemeAsMultiScheme;
import backtype.storm.task.OutputCollector;
import backtype.storm.task.TopologyContext;
import backtype.storm.topology.IRichBolt;
import backtype.storm.topology.OutputFieldsDeclarer;
import backtype.storm.topology.TopologyBuilder;
import backtype.storm.tuple.Fields;
import backtype.storm.tuple.Tuple;

public class TestMain {
    public static void main(String[] args) throws Exception {
        Config conf = new Config();
        conf.setDebug(false);//关闭调试
        String zks = "192.168.0.11:2181";//设置zk的地址
        String topic = "testflume";//消费的topic名称
        String zkRoot = "/kafka"; // 消费信息保存在zk的地址
        String id = "test";//客户端的ID
        BrokerHosts brokerHosts = new ZkHosts(zks, "/brokers");//kafka和zk整合时设置的kafka根路径
        SpoutConfig spoutConf = new SpoutConfig(brokerHosts, topic, zkRoot, id);
        spoutConf.scheme = new SchemeAsMultiScheme(new StringScheme());
        spoutConf.ignoreZkOffsets = false;
//      spoutConf.startOffsetTime = kafka.api.OffsetRequest.LatestTime();//从最新消息的开始读取
         spoutConf.startOffsetTime = kafka.api.OffsetRequest.EarliestTime();//从最旧的消息开始读取
        spoutConf.zkPort = 2181;//设置zk的端口
        List<String> servers = new ArrayList<>();
        servers.add("192.168.0.11");
        spoutConf.zkServers = servers;//设置zk的地址
        TopologyBuilder builder = new TopologyBuilder();
        builder.setSpout("log-reader", new KafkaSpout(spoutConf));//设置spout的名称
        builder.setBolt("bolt1", new Bolt1(), 2).shuffleGrouping("log-reader");//设置bolt的名称和分组的字段
        //提交任务
        if (args != null && args.length > 0) {
            conf.setNumWorkers(3);
            StormSubmitter.submitTopologyWithProgressBar("AGX", conf,
                    builder.createTopology());
        } else {
            conf.setMaxTaskParallelism(3);
            conf.put(Config.TOPOLOGY_MAX_SPOUT_PENDING, 1);
            LocalCluster cluster = new LocalCluster();
            cluster.submitTopology("AGX_STORM", conf, builder.createTopology());
            Thread.sleep(100000000000l);
            cluster.shutdown();
        }
    }

    /**
     * 对kafka发来的数据进行第一次处理
     * 
     * @author hasee
     *
     */
    public static class Bolt1 implements IRichBolt {

        OutputCollector _collector;

        public void prepare(Map stormConf, TopologyContext context,
                OutputCollector collector) {
            _collector = collector;
        }

        public void execute(Tuple input) {

            try {

                String msg = input.getString(0);
                System.out.println("开始消费消息:" + msg);
                _collector.ack(input);
            } catch (Exception e) {
                e.printStackTrace();
            } finally {

            }
        }


        public void declareOutputFields(OutputFieldsDeclarer declarer) {
            declarer.declare(new Fields("id", "click", "browse"));
        }

        @Override
        public void cleanup() {
            // TODO Auto-generated method stub

        }

        @Override
        public Map<String, Object> getComponentConfiguration() {
            // TODO Auto-generated method stub
            return null;
        }
    }
}

附上storm确定开始位置的代码

package storm.kafka;

import backtype.storm.Config;
import backtype.storm.metric.api.CombinedMetric;
import backtype.storm.metric.api.CountMetric;
import backtype.storm.metric.api.MeanReducer;
import backtype.storm.metric.api.ReducedMetric;
import backtype.storm.spout.SpoutOutputCollector;
import com.google.common.collect.ImmutableMap;
import kafka.javaapi.consumer.SimpleConsumer;
import kafka.javaapi.message.ByteBufferMessageSet;
import kafka.message.MessageAndOffset;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import storm.kafka.KafkaSpout.EmitState;
import storm.kafka.KafkaSpout.MessageAndRealOffset;
import storm.kafka.trident.MaxMetric;

import java.util.*;

public class PartitionManager {
    public static final Logger LOG = LoggerFactory.getLogger(PartitionManager.class);

    private final CombinedMetric _fetchAPILatencyMax;
    private final ReducedMetric _fetchAPILatencyMean;
    private final CountMetric _fetchAPICallCount;
    private final CountMetric _fetchAPIMessageCount;
    Long _emittedToOffset;
    // _pending key = Kafka offset, value = time at which the message was first submitted to the topology
    private SortedMap<Long,Long> _pending = new TreeMap<Long,Long>();
    private final FailedMsgRetryManager _failedMsgRetryManager;

    // retryRecords key = Kafka offset, value = retry info for the given message
    Long _committedTo;
    LinkedList<MessageAndRealOffset> _waitingToEmit = new LinkedList<MessageAndRealOffset>();
    Partition _partition;
    SpoutConfig _spoutConfig;
    String _topologyInstanceId;
    SimpleConsumer _consumer;
    DynamicPartitionConnections _connections;
    ZkState _state;
    Map _stormConf;
    long numberFailed, numberAcked;
    public PartitionManager(DynamicPartitionConnections connections, String topologyInstanceId, ZkState state, Map stormConf, SpoutConfig spoutConfig, Partition id) {
        _partition = id;
        _connections = connections;
        _spoutConfig = spoutConfig;
        _topologyInstanceId = topologyInstanceId;
        _consumer = connections.register(id.host, id.partition);
        _state = state;
        _stormConf = stormConf;
        numberAcked = numberFailed = 0;

        _failedMsgRetryManager = new ExponentialBackoffMsgRetryManager(_spoutConfig.retryInitialDelayMs,
                                                                           _spoutConfig.retryDelayMultiplier,
                                                                           _spoutConfig.retryDelayMaxMs);

        String jsonTopologyId = null;
        Long jsonOffset = null;
        //确定开始位置的代码位置在这里
        String path = committedPath();//计算出配置文件的位置
        try {
            Map<Object, Object> json = _state.readJSON(path);//取出配置文件
            LOG.info("Read partition information from: " + path +  "  --> " + json );
            if (json != null) {
                jsonTopologyId = (String) ((Map<Object, Object>) json.get("topology")).get("id");
                jsonOffset = (Long) json.get("offset");//获得上次读取的位置
            }
        } catch (Throwable e) {
            LOG.warn("Error reading and/or parsing at ZkNode: " + path, e);
        }

        Long currentOffset = KafkaUtils.getOffset(_consumer, spoutConfig.topic, id.partition, spoutConfig);//取出kafka最新的offset
//判断配置读取出来的是不是空，如果是空按照kafka的位置开始读取，否则重上次位置开始
        if (jsonTopologyId == null || jsonOffset == null) { // failed to parse JSON?
            _committedTo = currentOffset;
            LOG.info("No partition information found, using configuration to determine offset");
        } else if (!topologyInstanceId.equals(jsonTopologyId) && spoutConfig.ignoreZkOffsets) {
            _committedTo = KafkaUtils.getOffset(_consumer, spoutConfig.topic, id.partition, spoutConfig.startOffsetTime);
            LOG.info("Topology change detected and ignore zookeeper offsets set to true, using configuration to determine offset");
        } else {
            _committedTo = jsonOffset;
            LOG.info("Read last commit offset from zookeeper: " + _committedTo + "; old topology_id: " + jsonTopologyId + " - new topology_id: " + topologyInstanceId );
        }

        if (currentOffset - _committedTo > spoutConfig.maxOffsetBehind || _committedTo <= 0) {
            LOG.info("Last commit offset from zookeeper: " + _committedTo);
            Long lastCommittedOffset = _committedTo;
            _committedTo = currentOffset;
            LOG.info("Commit offset " + lastCommittedOffset + " is more than " +
                    spoutConfig.maxOffsetBehind + " behind latest offset " + currentOffset + ", resetting to startOffsetTime=" + spoutConfig.startOffsetTime);
        }

        LOG.info("Starting Kafka " + _consumer.host() + ":" + id.partition + " from offset " + _committedTo);
        _emittedToOffset = _committedTo;

        _fetchAPILatencyMax = new CombinedMetric(new MaxMetric());
        _fetchAPILatencyMean = new ReducedMetric(new MeanReducer());
        _fetchAPICallCount = new CountMetric();
        _fetchAPIMessageCount = new CountMetric();
    }

    public Map getMetricsDataMap() {
        Map ret = new HashMap();
        ret.put(_partition + "/fetchAPILatencyMax", _fetchAPILatencyMax.getValueAndReset());
        ret.put(_partition + "/fetchAPILatencyMean", _fetchAPILatencyMean.getValueAndReset());
        ret.put(_partition + "/fetchAPICallCount", _fetchAPICallCount.getValueAndReset());
        ret.put(_partition + "/fetchAPIMessageCount", _fetchAPIMessageCount.getValueAndReset());
        return ret;
    }
//开始发送消息
    //returns false if it's reached the end of current batch
    public EmitState next(SpoutOutputCollector collector) {
        if (_waitingToEmit.isEmpty()) {
            fill();
        }
        while (true) {
            MessageAndRealOffset toEmit = _waitingToEmit.pollFirst();
            if (toEmit == null) {
                return EmitState.NO_EMITTED;
            }
            Iterable<List<Object>> tups = KafkaUtils.generateTuples(_spoutConfig, toEmit.msg);
            if ((tups != null) && tups.iterator().hasNext()) {
                for (List<Object> tup : tups) {
                    collector.emit(tup, new KafkaMessageId(_partition, toEmit.offset));
                }
                break;
            } else {
                ack(toEmit.offset);
            }
        }
        if (!_waitingToEmit.isEmpty()) {
            return EmitState.EMITTED_MORE_LEFT;
        } else {
            return EmitState.EMITTED_END;
        }
    }


    private void fill() {
        long start = System.nanoTime();
        Long offset;

        // Are there failed tuples? If so, fetch those first.
        offset = this._failedMsgRetryManager.nextFailedMessageToRetry();
        final boolean processingNewTuples = (offset == null);
        if (processingNewTuples) {
            offset = _emittedToOffset;
        }

        ByteBufferMessageSet msgs = null;
        try {
            msgs = KafkaUtils.fetchMessages(_spoutConfig, _consumer, _partition, offset);
        } catch (TopicOffsetOutOfRangeException e) {
            _emittedToOffset = KafkaUtils.getOffset(_consumer, _spoutConfig.topic, _partition.partition, kafka.api.OffsetRequest.EarliestTime());
            LOG.warn("Using new offset: {}", _emittedToOffset);
            // fetch failed, so don't update the metrics

            //fix bug [STORM-643] : remove outdated failed offsets
            if (!processingNewTuples) {
                // For the case of EarliestTime it would be better to discard
                // all the failed offsets, that are earlier than actual EarliestTime
                // offset, since they are anyway not there.
                // These calls to broker API will be then saved.
                Set<Long> omitted = this._failedMsgRetryManager.clearInvalidMessages(_emittedToOffset);

                LOG.warn("Removing the failed offsets that are out of range: {}", omitted);
            }

            return;
        }
        long end = System.nanoTime();
        long millis = (end - start) / 1000000;
        _fetchAPILatencyMax.update(millis);
        _fetchAPILatencyMean.update(millis);
        _fetchAPICallCount.incr();
        if (msgs != null) {
            int numMessages = 0;

            for (MessageAndOffset msg : msgs) {
                final Long cur_offset = msg.offset();
                if (cur_offset < offset) {
                    // Skip any old offsets.
                    continue;
                }
                if (processingNewTuples || this._failedMsgRetryManager.shouldRetryMsg(cur_offset)) {
                    numMessages += 1;
                    if (!_pending.containsKey(cur_offset)) {
                        _pending.put(cur_offset, System.currentTimeMillis());
                    }
                    _waitingToEmit.add(new MessageAndRealOffset(msg.message(), cur_offset));
                    _emittedToOffset = Math.max(msg.nextOffset(), _emittedToOffset);
                    if (_failedMsgRetryManager.shouldRetryMsg(cur_offset)) {
                        this._failedMsgRetryManager.retryStarted(cur_offset);
                    }
                }
            }
            _fetchAPIMessageCount.incrBy(numMessages);
        }
    }

    public void ack(Long offset) {
        if (!_pending.isEmpty() && _pending.firstKey() < offset - _spoutConfig.maxOffsetBehind) {
            // Too many things pending!
            _pending.headMap(offset - _spoutConfig.maxOffsetBehind).clear();
        }
        _pending.remove(offset);
        this._failedMsgRetryManager.acked(offset);
        numberAcked++;
    }

    public void fail(Long offset) {
        if (offset < _emittedToOffset - _spoutConfig.maxOffsetBehind) {
            LOG.info(
                    "Skipping failed tuple at offset=" + offset +
                            " because it's more than maxOffsetBehind=" + _spoutConfig.maxOffsetBehind +
                            " behind _emittedToOffset=" + _emittedToOffset
            );
        } else {
            LOG.debug("failing at offset=" + offset + " with _pending.size()=" + _pending.size() + " pending and _emittedToOffset=" + _emittedToOffset);
            numberFailed++;
            if (numberAcked == 0 && numberFailed > _spoutConfig.maxOffsetBehind) {
                throw new RuntimeException("Too many tuple failures");
            }

            this._failedMsgRetryManager.failed(offset);
        }
    }

    public void commit() {
        long lastCompletedOffset = lastCompletedOffset();
        if (_committedTo != lastCompletedOffset) {
            LOG.debug("Writing last completed offset (" + lastCompletedOffset + ") to ZK for " + _partition + " for topology: " + _topologyInstanceId);
            Map<Object, Object> data = (Map<Object, Object>) ImmutableMap.builder()
                    .put("topology", ImmutableMap.of("id", _topologyInstanceId,
                            "name", _stormConf.get(Config.TOPOLOGY_NAME)))
                    .put("offset", lastCompletedOffset)
                    .put("partition", _partition.partition)
                    .put("broker", ImmutableMap.of("host", _partition.host.host,
                            "port", _partition.host.port))
                    .put("topic", _spoutConfig.topic).build();
            _state.writeJSON(committedPath(), data);

            _committedTo = lastCompletedOffset;
            LOG.debug("Wrote last completed offset (" + lastCompletedOffset + ") to ZK for " + _partition + " for topology: " + _topologyInstanceId);
        } else {
            LOG.debug("No new offset for " + _partition + " for topology: " + _topologyInstanceId);
        }
    }

    private String committedPath() {
        return _spoutConfig.zkRoot + "/" + _spoutConfig.id + "/" + _partition.getId();
    }

    public long lastCompletedOffset() {
        if (_pending.isEmpty()) {
            return _emittedToOffset;
        } else {
            return _pending.firstKey();
        }
    }

    public Partition getPartition() {
        return _partition;
    }

    public void close() {
        commit();
        _connections.unregister(_partition.host, _partition.partition);
    }

    static class KafkaMessageId {
        public Partition partition;
        public long offset;

        public KafkaMessageId(Partition partition, long offset) {
            this.partition = partition;
            this.offset = offset;
        }
    }
}

最后附上一张kafk保存在zk中的json信息截图