Config就是配置相关信息，下面是KafkaConfig的源码及小弟的相关注释，有错误的地方还望指出

public class KafkaConfig implements Serializable {

	/** 一个借口，实现类有ZkHosts，和StatisHosts	 **/
    public final BrokerHosts hosts; 
    public final String topic; // kafka topic name
    public final String clientId; // 自己取一个唯一的ID吧

    public int fetchSizeBytes = 1024 * 1024; // 每次从kafka读取的byte数，这个变量会在KafkaUtils的fetchMessage方法中看到
    public int socketTimeoutMs = 10000; //  Consumer连接kafka server超时时间
    public int fetchMaxWait = 10000; 
    public int bufferSizeBytes = 1024 * 1024;   //Consumer端缓存大小
    public MultiScheme scheme = new RawMultiScheme(); // 数据发送的序列化和反序列化定义的Scheme，后续会专门有一篇介绍
    public boolean forceFromStart = false;	// 和startOffsetTime，一起用，默认情况下，为false，一旦startOffsetTime被设置，就要置为true
    public long startOffsetTime = kafka.api.OffsetRequest.EarliestTime(); // -2 从kafka头开始  -1 是从最新的开始 0 =无 从ZK开始
    public long maxOffsetBehind = Long.MAX_VALUE;  // 每次kafka会读取一批offset存放在list中，当zk offset比当前本地保存的commitOffse相减大于这个值时，重新设置commitOffset为当前zk offset，代码见PartitionManager
    public boolean useStartOffsetTimeIfOffsetOutOfRange = true;
    public int metricsTimeBucketSizeInSecs = 60;

    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;
    }

}

public class SpoutConfig extends KafkaConfig implements Serializable {
    public List<String> zkServers = null; // zk hosts 列表，格式就是简单ip：xxx.xxx.xxx.xxx,作为zkserver ,后续leader election用
    public Integer zkPort = null;	// zk端口，一般是2181
    public String zkRoot = null;  // 该参数是Consumer消费的meta信息，保存在zk的路径，自己指定
    public String id = null;		// 唯一id 
    public long stateUpdateIntervalMs = 2000; // commit 消费的offset到zk的时间间隔

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

下一节讲述如何构建一个KafkaSpout

（二）storm-kafka源码走读之Config相关类走读