Sharded数据分片定位数据
因为每个片是单独的主服务器,分片有一些限制的功能:例如,不能使用事务,pipelining,发布/订阅。然而,通常这些不允许的操作是可行的,只要关心keys在一个相同的片。更进一步的缺点是当前标准实现,在运行中的ShardedJedis不能添加或者移除片。如果需要这个特性,需要重现实现ShardedJedis,允许在一个运行ShardedJedis动态的添加和移除片: yaourt - dynamic sharding implementation
Jedis是Redis官方推荐的Java客户端,更多Redis的客户端可以参考Redis官网 客户端列表 。当业务的数据量非常庞大时,需要考虑将数据存储到多个缓存节点上,如何定位数据应该存储的节点,一般用的是一致性哈希算法。Jedis在客户端角度实现了一致性哈希算法,对数据进行分片,存储到对应的不同的redis实例中。
Jedis对Sharded的实现主要是在 ShardedJedis.java
和 ShardedJedisPool.java
中。本文主要介绍ShardedJedis的实现,ShardedJedisPool是基于apache的common-pool2的对象池实现。
继承关系:
ShardedJedis--->BinaryShardedJedis--->Sharded <Jedis, JedisShardInfo>
构造函数
查看其构造函数
java
public ShardedJedis(List<JedisShardInfo> shards, Hashing algo, Pattern keyTagPattern) {
super(shards, algo, keyTagPattern);
}
构造器参数解释:
-
shards是一个JedisShardInfo的列表,一个JedisShardedInfo类代表一个数据分片的主体。
-
algo是用来进行数据分片的算法
-
keyTagPattern,自定义分片算法所依据的key的形式。例如,可以不针对整个key的字符串做哈希计算,而是类似对 thisisa{key} 中包含在大括号内的字符串进行哈希计算。
JedisShardInfo
是什么样的?
java
public classJedisShardInfo extends ShardInfo<Jedis> {public String toString() {
return host + ":" + port + "*" + getWeight();
}
privateint connectionTimeout;
privateint soTimeout;
private String host;
privateint port;
private String password = null;
private String name = null;
// Default Redis DBprivateint db = 0;
public String getHost() {
return host;
}
publicint getPort() {
return port;
}
public JedisShardInfo(String host) {
super(Sharded.DEFAULT_WEIGHT);
URI uri = URI.create(host);
if (JedisURIHelper.isValid(uri)) {
this.host = uri.getHost();
this.port = uri.getPort();
this.password = JedisURIHelper.getPassword(uri);
this.db = JedisURIHelper.getDBIndex(uri);
} else {
this.host = host;
this.port = Protocol.DEFAULT_PORT;
}
}
public JedisShardInfo(String host, String name) {
this(host, Protocol.DEFAULT_PORT, name);
}
public JedisShardInfo(String host, int port) {
this(host, port, 2000);
}
public JedisShardInfo(String host, int port, String name) {
this(host, port, 2000, name);
}
public JedisShardInfo(String host, int port, int timeout) {
this(host, port, timeout, timeout, Sharded.DEFAULT_WEIGHT);
}
public JedisShardInfo(String host, int port, int timeout, String name) {
this(host, port, timeout, timeout, Sharded.DEFAULT_WEIGHT);
this.name = name;
}
public JedisShardInfo(String host, int port, int connectionTimeout, int soTimeout, int weight) {
super(weight);
this.host = host;
this.port = port;
this.connectionTimeout = connectionTimeout;
this.soTimeout = soTimeout;
}
public JedisShardInfo(String host, String name, int port, int timeout, int weight) {
super(weight);
this.host = host;
this.name = name;
this.port = port;
this.connectionTimeout = timeout;
this.soTimeout = timeout;
}
public JedisShardInfo(URI uri) {
super(Sharded.DEFAULT_WEIGHT);
if (!JedisURIHelper.isValid(uri)) {
thrownew InvalidURIException(String.format(
"Cannot open Redis connection due invalid URI. %s", uri.toString()));
}
this.host = uri.getHost();
this.port = uri.getPort();
this.password = JedisURIHelper.getPassword(uri);
this.db = JedisURIHelper.getDBIndex(uri);
}
@Override
public Jedis createResource() {
returnnew Jedis(this);
}
/**
* 省略setters和getters
**/
}
可见JedisShardInfo包含了一个redis节点ip地址,端口号,name,密码等等相关信息。要构造一个ShardedJedis,提供一个或多个JedisShardInfo。
最终构造函数的实现在其父类 Sharded
里面
java
public Sharded(List<S> shards, Hashing algo, Pattern tagPattern) {
this.algo = algo;
this.tagPattern = tagPattern;
initialize(shards);
}
哈希环的初始化
Sharded类里面维护了一个TreeMap,基于红黑树实现,用来盛放经过一致性哈希计算后的redis节点,另外维护了一个LinkedHashMap,用来保存ShardInfo与Jedis实例的对应关系。
定位的流程如下
先在TreeMap中找到对应key所对应的ShardInfo,然后通过ShardInfo在LinkedHashMap中找到对应的Jedis实例。
Sharded类对这些实例变量的定义如下所示:
java
public staticfinalint DEFAULT_WEIGHT = 1;
private TreeMap<Long, S> nodes;
privatefinal Hashing algo;
privatefinal Map<ShardInfo<R>, R> resources = new LinkedHashMap<ShardInfo<R>, R>();
/**
* The default pattern used for extracting a key tag. The pattern must have
* a group (between parenthesis), which delimits the tag to be hashed. A
* null pattern avoids applying the regular expression for each lookup,
* improving performance a little bit is key tags aren't being used.
*/private Pattern tagPattern = null;
// the tag is anything between {}publicstaticfinal Pattern DEFAULT_KEY_TAG_PATTERN = Pattern.compile("\\{(.+?)\\}");
接下来看其构造函数中的initialize方法
java
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);
}
elsefor (int n = 0; n < 160 * shardInfo.getWeight(); n++) {
nodes.put(
this.algo.hash(shardInfo.getName() + "*"
+ shardInfo.getWeight() + n), shardInfo);
}
resources.put(shardInfo, shardInfo.createResource());
}
}
可以看到,它对每一个ShardInfo通过一定规则计算其哈希值,然后存到TreeMap中,这里它实现了一致性哈希算法中虚拟节点的概念,因为我们可以看到同一个ShardInfo不止一次被放到TreeMap中,数量是,权重*160。增加了虚拟节点的一致性哈希有很多好处,能避免数据在redis节点间分布不均匀。
然后,在LinkedHashMap中放入ShardInfo以及其对应的Jedis实例,通过调用其自身的createSource()来得到jedis实例。
数据定位
从ShardedJedis的代码中可以看到,无论进行什么操作,都要先根据key来找到对应的Redis,然后返回一个可供操作的Jedis实例。
例如其set方法:
java
public String set(String key, String value) {
Jedis j = getShard(key);
return j.set(key, value);
}
而getShard方法则在Sharded.java中实现,其源代码如下所示:
java
public R getShard(byte[] key) {
return resources.get(getShardInfo(key));
}
public R getShard(String key) {
return resources.get(getShardInfo(key));
}
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());
}
public S getShardInfo(String key) {
return getShardInfo(SafeEncoder.encode(getKeyTag(key)));
}
可以看到,先通过getShardInfo方法从TreeMap中获得对应的ShardInfo,然后根据这个ShardInfo就能够再LinkedHashMap中获得对应的Jedis实例了。