首页  

Jedis客户端分片机制     所属分类 redis 浏览量 1397
启动2个Redis 实例

nohup redis-server --port 6379 &
nohup redis-server --port 6380 &

默认端口 6379

一致性hash算法 虚拟节点数 160
hash算法  Hashing.MURMUR_HASH




redis-server -h
Usage: ./redis-server [/path/to/redis.conf] [options]
       ./redis-server - (read config from stdin)
       ./redis-server -v or --version
       ./redis-server -h or --help
       ./redis-server --test-memory 

Examples:
       ./redis-server (run the server with default conf)
       ./redis-server /etc/redis/6379.conf
       ./redis-server --port 7777
       ./redis-server --port 7777 --replicaof 127.0.0.1 8888
       ./redis-server /etc/myredis.conf --loglevel verbose

Sentinel mode:
       ./redis-server /etc/sentinel.conf --sentinel






        JedisPoolConfig config =new JedisPoolConfig();
		config.setTestOnBorrow(true);
		
		List<JedisShardInfo> shardInfoList =new ArrayList<JedisShardInfo>();
        JedisShardInfo infoA = new JedisShardInfo("127.0.0.1", 6379);
        JedisShardInfo infoB = new JedisShardInfo("127.0.0.1", 6380);
        shardInfoList.add(infoA);
        shardInfoList.add(infoB);
		 
		ShardedJedisPool pool = new  ShardedJedisPool(config,shardInfoList);
		
		jedis = pool.getResource();
		
		final int NUM = 10;
		
		for(int i=0;i<NUM;i++){
			String key = "client_shard_test_key_"+i;
			String value = key+"_value_"+new Date();
			jedis.set(key, value);
		}
		
		for(int i=0;i<NUM;i++){
			String key = "client_shard_test_key_"+i;
			String value = jedis.get(key);
			System.out.println("key="+key+",value="+value);
		}
		
		for(int i=0;i<NUM;i++){
			String key = "client_shard_test_key_"+i;	
            System.out.println("key="+key+",shardInfo="+jedis.getShardInfo(key));
		}
	
  根据key获取分片信息	

  public S getShardInfo(byte[] key) {
    SortedMap<Long, S> tail = nodes.tailMap(algo.hash(key));
    if (tail.isEmpty()) {
      return nodes.get(nodes.firstKey());
    }
    return tail.get(tail.firstKey());
  }
  
 TreeMap<Long, S> nodes
 
 Hashing algo
 
 redis.clients.jedis.util.MurmurHash
 
 
 TreeMap 的 tailMap() firstKey() 方法使用
 
 public SortedMap<K,V> tailMap(K fromKey)

 返回 key 大于或等于 fromKey的部分视图
 
 public SortedMap<K,V> headMap(K toKey)
 返回 key 小于 toKey 的部分视图 
 
 
 public SortedMap<K,V> subMap(K fromKey,K toKey)
 返回 key 从fromKey(包括)到toKey(不包括)的部分视图
 
 
 








key对应的分片信息

key=client_shard_test_key_0,shardInfo=127.0.0.1:6380*1
key=client_shard_test_key_1,shardInfo=127.0.0.1:6380*1
key=client_shard_test_key_2,shardInfo=127.0.0.1:6380*1
key=client_shard_test_key_3,shardInfo=127.0.0.1:6379*1
key=client_shard_test_key_4,shardInfo=127.0.0.1:6380*1
key=client_shard_test_key_5,shardInfo=127.0.0.1:6380*1
key=client_shard_test_key_6,shardInfo=127.0.0.1:6380*1
key=client_shard_test_key_7,shardInfo=127.0.0.1:6379*1
key=client_shard_test_key_8,shardInfo=127.0.0.1:6379*1
key=client_shard_test_key_9,shardInfo=127.0.0.1:6380*1

key数量太少 , 看起来不是很均匀 


分片信息初始化  构建hash环



 public Sharded(List<S> shards, Pattern tagPattern) {
    this(shards, Hashing.MURMUR_HASH, tagPattern); // MD5 is really not good
    // as we works with
    // 64-bits not 128
  }

  public Sharded(List<S> shards, Hashing algo, Pattern tagPattern) {
    this.algo = algo;
    this.tagPattern = tagPattern;
    initialize(shards);
  }

  private void initialize(List<S> shards) {
    nodes = new TreeMap<Long, S>();

    for (int i = 0; i != shards.size(); ++i) {
      final S shardInfo = shards.get(i);
      if (shardInfo.getName() == null) for (int n = 0; n < 160 * shardInfo.getWeight(); n++) {
        nodes.put(this.algo.hash("SHARD-" + i + "-NODE-" + n), shardInfo);
      }
      else for (int n = 0; n < 160 * shardInfo.getWeight(); n++) {
        nodes.put(this.algo.hash(shardInfo.getName() + "*" + n), shardInfo);
      }
      resources.put(shardInfo, shardInfo.createResource());
    }
  }



上一篇     下一篇
B+树 与 B树 索引

B树与红黑树,为什么数据库使用B树索引

联合索引与最左匹配原则

一致性hash与treemap

MapReduce和Tez比较

redis 主从 哨兵 集群机制