kafka+storm结合存在的一些问题与解决方法

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package org.apache.storm.spout;

import java.nio.ByteBuffer;
import java.util.List;

import org.apache.storm.tuple.Fields;
import org.apache.storm.utils.Utils;


import static org.apache.storm.utils.Utils.tuple;
import static java.util.Arrays.asList;

public class RawMultiScheme implements MultiScheme {
  @Override
  public Iterable<List<Object>> deserialize(ByteBuffer ser) {
    return asList(tuple(Utils.toByteArray(ser)));
  }

  @Override
  public Fields getOutputFields() {
    return new Fields("bytes");
  }
}

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;//与Kafka broker的连接的socket超时时间
public int fetchMaxWait = 10000;   //当服务器没有新消息时，消费者会等待这些时间
public int bufferSizeBytes = 1024 * 1024;//SimpleConsumer所使用的SocketChannel的读缓冲区大小
public MultiScheme scheme = new RawMultiScheme();//从Kafka中取出的byte[]，该如何反序列化
public boolean forceFromStart = false;//是否强制从Kafka中offset最小的开始读起
public long startOffsetTime = kafka.api.OffsetRequest.EarliestTime();//从何时的offset时间开始读，默认为最旧的offset
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metrics