885 lines
33 KiB
Markdown
885 lines
33 KiB
Markdown
# Redisson
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## 配置
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### 编程式配置
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可以通过创建Config对象来显式配置redisson，配置示例如下：
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```java
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Config config = new Config();
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config.setTransportMode(TransportMode.EPOLL);
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config.useClusterServers()
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// use "rediss://" for SSL connection
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.addNodeAddress("perredis://127.0.0.1:7181");
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RedissonClient redisson = Redisson.create(config);
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```
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### yml Configuration
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也可以通过yml文件格式来对redisson进行配置：
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```java
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Config config = Config.fromYAML(new File("config-file.yaml"));
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RedissonClient redisson = Redisson.create(config);
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```
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可以通过config.toYAML方法将config转化为yaml格式：
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```java
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Config config = new Config();
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// ... many settings are set here
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String yamlFormat = config.toYAML();
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```
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yml格式中可以引入环境变量
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```yml
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singleServerConfig:
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address: "redis://127.0.0.1:${REDIS_PORT}"
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```
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### Common Settings
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如下设置用于配置config对象，并且适用于各种redis模式
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#### codec
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默认值：org.redisson.codec.Kryo5Codec
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#### connectionListener
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默认值：null
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connection listener，当redisson连接到redis-server或与redis-server断开连接时被触发
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#### nettyThreads
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默认值：32
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redisson所有redis client共享的线程总数。netty thread用于redis相应的解码和命令的发送。
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#### transportMode
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默认值：TransportMode.NIO
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可选的值如下：
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- TransportMode.NIO（默认）
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- TransportMode.EPOLL
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- TransportMode.KQUEUE
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#### threads
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由Rtopic object listener所共享的线程数量
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#### lockWatchdogTimeout
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默认值：30000
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RLock watchdog timeout，单位为ms。该参数仅当RLock在获取时没有指定leaseTimeout时使用。当watchdog没有延长持有锁时间到下一个watchdogTimeout间隔时，当前watchdogTimeout到期后锁会过期。watchdog避免了由于客户端崩溃或其他原因造成一直持有锁的情况。
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### Mode
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#### single instance mode
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可以通过如下方式来配置单实例模式：
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```java
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// connects to 127.0.0.1:6379 by default
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RedissonClient redisson = Redisson.create();
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Config config = new Config();
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config.useSingleServer().setAddress("redis://myredisserver:6379");
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RedissonClient redisson = Redisson.create(config);
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```
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yml配置单实例模式如下：
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```yaml
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singleServerConfig:
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idleConnectionTimeout: 10000
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connectTimeout: 10000
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timeout: 3000
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retryAttempts: 3
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retryInterval: 1500
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password: null
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subscriptionsPerConnection: 5
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clientName: null
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address: "redis://127.0.0.1:6379"
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subscriptionConnectionMinimumIdleSize: 1
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subscriptionConnectionPoolSize: 50
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connectionMinimumIdleSize: 24
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connectionPoolSize: 64
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database: 0
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dnsMonitoringInterval: 5000
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threads: 16
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nettyThreads: 32
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codec: !<org.redisson.codec.Kryo5Codec> {}
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transportMode: "NIO"
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```
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## Operation Execution
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redisson支持自动重试策略，并且在每次尝试时都会发送命令。重试策略通过retryAttempts（默认情况下为3）、retryInterval（默认情况下为1000ms）来设置。多次尝试之间间隔retryInterval。
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redisson实例是线程安全的，如下是RAtomicLong对象的使用示例：
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```java
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RedissonClient client = Redisson.create(config);
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RAtomicLong longObject = client.getAtomicLong('myLong');
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// sync way
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longObject.compareAndSet(3, 401);
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// async way
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RFuture<Boolean> result = longObject.compareAndSetAsync(3, 401);
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RedissonReactiveClient client = Redisson.createReactive(config);
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RAtomicLongReactive longObject = client.getAtomicLong('myLong');
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// reactive way
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Mono<Boolean> result = longObject.compareAndSet(3, 401);
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RedissonRxClient client = Redisson.createRx(config);
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RAtomicLongRx longObject= client.getAtomicLong("myLong");
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// RxJava2 way
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Flowable<Boolean result = longObject.compareAndSet(3, 401);
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```
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### Async方式
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大多数redisson object继承了异步接口，可以调用异步方法实现异步操作，如下：
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```java
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// RAtomicLong extends RAtomicLongAsync
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RAtomicLongAsync longObject = client.getAtomicLong("myLong");
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RFuture<Boolean> future = longObject.compareAndSetAsync(1, 401);
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```
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RFuture对象继承了Future接口和CompletionStage接口，可以像CompleteableFuture一样使用：
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```java
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future.whenComplete((res, exception) -> {
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// handle both result and exception
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});
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// or
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future.thenAccept(res -> {
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// handle result
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}).exceptionally(exception -> {
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// handle exception
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});
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```
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因该避免在future listener中使用同步方法，这样可能会造成redis请求/相应处理时的错误，应使用如下方式执行：
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```java
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future.whenCompleteAsync((res, exception) -> {
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// handle both result and exception
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}, executor);
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// or
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future.thenAcceptAsync(res -> {
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// handle result
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}, executor).exceptionallyAsync(exception -> {
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// handle exception
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}, executor);
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```
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## Redisson Object的公共操作
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所有redisson object都实现了RObject和RExpiration接口，使用示例如下：
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```java
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RObject object = redisson.get...()
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object.sizeInMemory();
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object.delete();
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object.rename("newname");
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object.isExists();
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// catch expired event
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object.addListener(new ExpiredObjectListener() {
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...
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});
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// catch delete event
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object.addListener(new DeletedObjectListener() {
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...
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});
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```
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redisson object的name属性即是在redis中的key：
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```java
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RMap map = redisson.getMap("mymap");
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map.getName(); // = mymap
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```
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和redis key相关的所有操作都通过RKeys接口暴露，使用示例如下：
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```java
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RKeys keys = redisson.getKeys();
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Iterable<String> allKeys = keys.getKeys();
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Iterable<String> foundedKeys = keys.getKeysByPattern('key*');
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long numOfDeletedKeys = keys.delete("obj1", "obj2", "obj3");
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long deletedKeysAmount = keys.deleteByPattern("test?");
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String randomKey = keys.randomKey();
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long keysAmount = keys.count();
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keys.flushall();
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keys.flushdb();
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```
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## 分布式对象
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### object holder
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#### RBucket
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RBucket的java实现类是一个hodler，可以持有任何类型的java对象。RBucket的大小限制为512MB.
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RBucket的使用示例如下所示：
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```java
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RBucket<AnyObject> bucket = redisson.getBucket("anyObject");
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bucket.set(new AnyObject(1));
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AnyObject obj = bucket.get();
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bucket.trySet(new AnyObject(3));
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bucket.compareAndSet(new AnyObject(4), new AnyObject(5));
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bucket.getAndSet(new AnyObject(6));
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```
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#### RBuckets
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可以通过RBuckets对象来操作多个RBucket对象，RBuckets使用示例如下：
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```java
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RBuckets buckets = redisson.getBuckets();
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// get all bucket values
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Map<String, V> loadedBuckets = buckets.get("myBucket1", "myBucket2", "myBucket3");
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Map<String, Object> map = new HashMap<>();
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map.put("myBucket1", new MyObject());
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map.put("myBucket2", new MyObject());
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// sets all or nothing if some bucket is already exists
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buckets.trySet(map);
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// store all at once
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buckets.set(map);
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```
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### Binary Stream Holder
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RBinaryStream类型的对象用于存储字节序列。RBinaryStream实现了RBucket接口，并且其大小限制也是512MB.
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RBinaryStream的使用示例如下：
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```java
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RBinaryStream stream = redisson.getBinaryStream("anyStream");
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byte[] content = ...
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stream.set(content);
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stream.getAndSet(content);
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stream.trySet(content);
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stream.compareAndSet(oldContent, content);
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```
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RBinaryStream可以和InputStream与OutputStream混用，使用如下：
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```java
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RBinaryStream stream = redisson.getBinaryStream("anyStream");
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InputStream is = stream.getInputStream();
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byte[] readBuffer = ...
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is.read(readBuffer);
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OutputStream os = stream.getOuputStream();
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byte[] contentToWrite = ...
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os.write(contentToWrite);
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```
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### BitSet
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RBitSet实现提供了和java中BitSet类似的api，其大小限制是4 294 967 295 bits.
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RBitSet使用如下所示：
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```java
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RBitSet set = redisson.getBitSet("simpleBitset");
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set.set(0, true);
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set.set(1812, false);
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set.clear(0);
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set.and("anotherBitset");
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set.xor("anotherBitset");
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```
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### AtomicLong
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RAtomicLong实现提供了和java中AtomicLong类似的api，其使用类似如下：
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```java
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RAtomicLong atomicLong = redisson.getAtomicLong("myAtomicLong");
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atomicLong.set(3);
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atomicLong.incrementAndGet();
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atomicLong.get();
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```
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### AtomicDouble
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RAtomicDouble实现提供了和java中AtomicDouble类似的api，其使用示例如下：
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```java
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RAtomicDouble atomicDouble = redisson.getAtomicDouble("myAtomicDouble");
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atomicDouble.set(2.81);
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atomicDouble.addAndGet(4.11);
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atomicDouble.get();
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```
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### Topic
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RTopic实现提供了发布/订阅机制，其允许订阅由同名RTopic对象发布的事件。
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当重新连接到redis或redis错误切换之后，listener会被重新订阅，在重新订阅之前，所有被发布的消息都会丢失。
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RTopic的使用如下所示：
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```java
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RTopic topic = redisson.getTopic("myTopic");
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int listenerId = topic.addListener(SomeObject.class, new MessageListener<SomeObject>() {
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@Override
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public void onMessage(String channel, SomeObject message) {
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//...
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}
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});
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// in other thread or JVM
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RTopic topic = redisson.getTopic("myTopic");
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long clientsReceivedMessage = topic.publish(new SomeObject());
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```
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### Reliable Topic
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RRelieableTopic在实现发布/订阅模式的情况下，还实现了消息的可靠传输。当redis连接断开的情况下，所有消息都会被存储，当重新连接到redis时，消息会被重新传送。
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每个RReliableTopic对象实例都由一个watchdog，当第一个listener注册之后，watchdog就会被启用。当订阅者超过reliableTopicWatchdogTimeout之后，且watchdog没有为其延续过期时间，那么订阅将会超时。（该机制是为了防止client长时间崩溃之后存储的消息持续增长）。
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**当重新连接到redis之后，listener会被重新注册**
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```java
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RReliableTopic topic = redisson.getReliableTopic("anyTopic");
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topic.addListener(SomeObject.class, new MessageListener<SomeObject>() {
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@Override
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public void onMessage(CharSequence channel, SomeObject message) {
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//...
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}
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});
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// in other thread or JVM
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RReliableTopic topic = redisson.getReliableTopic("anyTopic");
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long subscribersReceivedMessage = topic.publish(new SomeObject());
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```
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### Topic Pattern
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RPatternTopic允许订阅多个Rtopic，在重新连接到redis或redis错误切换之后，listener会被重新订阅。
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Pattern使用如下：
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- topic?： subscribes to topic1, topicA ...
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- topic?_my： subscribes to topic_my, topic123_my, topicTEST_my ...
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- topic[ae]： subscribes to topica and topice only
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使用示例如下：
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```java
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// subscribe to all topics by `topic*` pattern
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RPatternTopic patternTopic = redisson.getPatternTopic("topic*");
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int listenerId = patternTopic.addListener(Message.class, new PatternMessageListener<Message>() {
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@Override
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public void onMessage(String pattern, String channel, Message msg) {
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//...
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}
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});
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```
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### Bloom Filter
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RBloomFilter中最多含有2^32个bit。
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在使用之前，必须通过tryInit(expectedInsertions, falseProbability)来初始化capacity。
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RBloomFilter使用示例如下：
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```java
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RBloomFilter<SomeObject> bloomFilter = redisson.getBloomFilter("sample");
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// initialize bloom filter with
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// expectedInsertions = 55000000
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// falseProbability = 0.03
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bloomFilter.tryInit(55000000L, 0.03);
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bloomFilter.add(new SomeObject("field1Value", "field2Value"));
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bloomFilter.add(new SomeObject("field5Value", "field8Value"));
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bloomFilter.contains(new SomeObject("field1Value", "field8Value"));
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bloomFilter.count();
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```
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### HyperLogLog
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RHyperLogLog能以较低的空间维护大数量的项目，计算其去重后的数量，其使用如下所示：
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```java
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RHyperLogLog<Integer> log = redisson.getHyperLogLog("log");
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log.add(1);
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log.add(2);
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log.add(3);
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log.count();
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```
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### LongAdder
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RLongAdder提供了java中LongAdder的实现，其在client端维护了LongAdder，增加和减少的性能较AtomicLong来说都有极大的提升（至多可提升12000倍）。其使用如下所示：
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```java
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RLongAdder atomicLong = redisson.getLongAdder("myLongAdder");
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atomicLong.add(12);
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atomicLong.increment();
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atomicLong.decrement();
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atomicLong.sum();
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```
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当LongAdder不再使用之后，应该调用destroy方法手动进行销毁：
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```java
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RLongAdder atomicLong = ...
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atomicLong.destroy();
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```
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### DoubleAdder
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RDoubleAdder提供了java中DoubleAdder的分布式实现，其性能相对于AtomicDouble也有很大提升。
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其使用如下所示：
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```java
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RLongDouble atomicDouble = redisson.getLongDouble("myLongDouble");
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atomicDouble.add(12);
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atomicDouble.increment();
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atomicDouble.decrement();
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atomicDouble.sum();
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```
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### id generator
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RIdGenerator实现允许产生唯一的id，但其生成算法不是简单的递增，而是在第一次请求时，一系列id就已经被分配并且缓存到java端，直到其用完。该方法能够减少和redis的通信次数，产生id的速率比RAtomicLong快。
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默认情况下allocate size是2000，并且值从0开始。
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RIdGenerator的使用如下所示：
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```java
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RIdGenerator generator = redisson.getIdGenerator("generator");
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// Initialize with start value = 12 and allocation size = 20000
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generator.tryInit(12, 20000);
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long id = generator.nextId();
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```
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### Json Object Holder
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RJsonBucket类型用于存储json数据，通过redis 的JSON.*命令来实现。Json数据通过JsonCodec来进行编码和解码。可用的实现是org.redisson.codec.JacksonCodec。
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#### local cache
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redisson提供了带有本地缓存的json object holder版本。
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local cache用于加速读取操作从而较少网络请求次数，其将整个json对象缓存在redisson侧，执行读取操作比无缓存快45倍。
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| redission client method name | local cache | Ultra-fast read/write |
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| :-: | :-: | :-: |
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| getJsonBucket() open-source version | false | false |
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| getJsonBucket() Redisson PRO version | false | true |
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| getLocalCachedJsonBucket() Redisson PRO version | true | true |
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RJsonBucket使用如下所示：
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```java
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RJsonBucket<AnyObject> bucket = redisson.getJsonBucket("anyObject", new JacksonCodec<>(AnyObject.class));
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bucket.set(new AnyObject(1));
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AnyObject obj = bucket.get();
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bucket.trySet(new AnyObject(3));
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bucket.compareAndSet(new AnyObject(4), new AnyObject(5));
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bucket.getAndSet(new AnyObject(6));
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List<String> values = bucket.get(new JacksonCodec<>(new TypeReference<List<String>>() {}), "values");
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long aa = bucket.arrayAppend("$.obj.values", "t3", "t4");
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```
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## 分布式集合
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### Map
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基于Redis的分布式Map对象实现了ConcurrentMap接口。
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如果Map主要用于读取数据，或者像尽量避免网络请求，可以使用带有local cache的map，使用示例如下：
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```java
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RMap<String, SomeObject> map = redisson.getMap("anyMap");
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SomeObject prevObject = map.put("123", new SomeObject());
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SomeObject currentObject = map.putIfAbsent("323", new SomeObject());
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SomeObject obj = map.remove("123");
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// use fast* methods when previous value is not required
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map.fastPut("a", new SomeObject());
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map.fastPutIfAbsent("d", new SomeObject());
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map.fastRemove("b");
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RFuture<SomeObject> putAsyncFuture = map.putAsync("321");
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RFuture<Void> fastPutAsyncFuture = map.fastPutAsync("321");
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map.fastPutAsync("321", new SomeObject());
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map.fastRemoveAsync("321");
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```
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RMap支持为每个key绑定一个lock/readwritelock/semaphore/countdownlatch，使用如下：
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```java
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RMap<MyKey, MyValue> map = redisson.getMap("anyMap");
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MyKey k = new MyKey();
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RLock keyLock = map.getLock(k);
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keyLock.lock();
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try {
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MyValue v = map.get(k);
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// process value ...
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} finally {
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keyLock.unlock();
|
||
}
|
||
|
||
RReadWriteLock rwLock = map.getReadWriteLock(k);
|
||
rwLock.readLock().lock();
|
||
try {
|
||
MyValue v = map.get(k);
|
||
// process value ...
|
||
} finally {
|
||
keyLock.readLock().unlock();
|
||
}
|
||
```
|
||
Redisson支持不同的Map结构实现，不同的实现主要包含如下三个特性：
|
||
- local cache: local cache通过将map entry缓存在redisson端来减少网络请求，从而提升读操作的性能。拥有相同name的local cache实例会连接到相同的发布/订阅channel，该channel用于在local cache实例之间交换更新/失效的事件。
|
||
- eviction：支持对每个map entry指定ttl和max idle time
|
||
|
||
如下是所有的RMap可用实现：
|
||
| RedissonClient method | local cache | eviction |
|
||
| :-: | :-: | :-: |
|
||
| getMap() | false | false |
|
||
| getMapCache() | false | true |
|
||
| getLocalCachedMap() | true | false |
|
||
|
||
#### eviction
|
||
带有eviction功能的map实现了RMapCache接口，并且实现了ConcurrentMap接口。
|
||
当前redis并不支持淘汰map entry的功能，故而超时的map entry是通过EvictionScheduler来时不时进行清理的。其会一次性移除100条超时的entry。任务启动的时间会自动调整，根据上次任务删除过期entry的数量，时间会在5s到半小时之间变化。
|
||
建议在每个redisson实例中都使用具有相同名称的MapCache对象：
|
||
```java
|
||
RMapCache<String, SomeObject> map = redisson.getMapCache("anyMap");
|
||
// or
|
||
RMapCache<String, SomeObject> map = redisson.getLocalCachedMapCache("anyMap", LocalCachedMapOptions.defaults());
|
||
// or
|
||
RMapCache<String, SomeObject> map = redisson.getClusteredLocalCachedMapCache("anyMap", LocalCachedMapOptions.defaults());
|
||
// or
|
||
RMapCache<String, SomeObject> map = redisson.getClusteredMapCache("anyMap");
|
||
|
||
|
||
// ttl = 10 minutes,
|
||
map.put("key1", new SomeObject(), 10, TimeUnit.MINUTES);
|
||
// ttl = 10 minutes, maxIdleTime = 10 seconds
|
||
map.put("key1", new SomeObject(), 10, TimeUnit.MINUTES, 10, TimeUnit.SECONDS);
|
||
|
||
// ttl = 3 seconds
|
||
map.putIfAbsent("key2", new SomeObject(), 3, TimeUnit.SECONDS);
|
||
// ttl = 40 seconds, maxIdleTime = 10 seconds
|
||
map.putIfAbsent("key2", new SomeObject(), 40, TimeUnit.SECONDS, 10, TimeUnit.SECONDS);
|
||
|
||
// if object is not used anymore
|
||
map.destroy();
|
||
```
|
||
#### local cache
|
||
带有local cache功能的map实现实现了RLocalCachedMap接口，同时也实现了ConcurrentMap接口。
|
||
推荐在所有的redisson client中使用具有相同name的LocalCachedMap，并且为所有具有相同名称的LocalCachedMap指定相同的LocalCachedMapOptions。
|
||
如下是在创建localcachedmap时可以指定的options：
|
||
```java
|
||
LocalCachedMapOptions options = LocalCachedMapOptions.defaults()
|
||
|
||
// Defines whether to store a cache miss into the local cache.
|
||
// Default value is false.
|
||
.storeCacheMiss(false);
|
||
|
||
// Defines store mode of cache data.
|
||
// Follow options are available:
|
||
// LOCALCACHE - store data in local cache only and use Redis only for data update/invalidation.
|
||
// LOCALCACHE_REDIS - store data in both Redis and local cache.
|
||
.storeMode(StoreMode.LOCALCACHE_REDIS)
|
||
|
||
// Defines Cache provider used as local cache store.
|
||
// Follow options are available:
|
||
// REDISSON - uses Redisson own implementation
|
||
// CAFFEINE - uses Caffeine implementation
|
||
.cacheProvider(CacheProvider.REDISSON)
|
||
|
||
// Defines local cache eviction policy.
|
||
// Follow options are available:
|
||
// LFU - Counts how often an item was requested. Those that are used least often are discarded first.
|
||
// LRU - Discards the least recently used items first
|
||
// SOFT - Uses weak references, entries are removed by GC
|
||
// WEAK - Uses soft references, entries are removed by GC
|
||
// NONE - No eviction
|
||
.evictionPolicy(EvictionPolicy.NONE)
|
||
|
||
// If cache size is 0 then local cache is unbounded.
|
||
.cacheSize(1000)
|
||
|
||
// Defines strategy for load missed local cache updates after Redis connection failure.
|
||
//
|
||
// Follow reconnection strategies are available:
|
||
// CLEAR - Clear local cache if map instance has been disconnected for a while.
|
||
// LOAD - Store invalidated entry hash in invalidation log for 10 minutes
|
||
// Cache keys for stored invalidated entry hashes will be removed
|
||
// if LocalCachedMap instance has been disconnected less than 10 minutes
|
||
// or whole cache will be cleaned otherwise.
|
||
// NONE - Default. No reconnection handling
|
||
.reconnectionStrategy(ReconnectionStrategy.NONE)
|
||
|
||
// Defines local cache synchronization strategy.
|
||
//
|
||
// Follow sync strategies are available:
|
||
// INVALIDATE - Default. Invalidate cache entry across all LocalCachedMap instances on map entry change
|
||
// UPDATE - Insert/update cache entry across all LocalCachedMap instances on map entry change
|
||
// NONE - No synchronizations on map changes
|
||
.syncStrategy(SyncStrategy.INVALIDATE)
|
||
|
||
// time to live for each map entry in local cache
|
||
.timeToLive(10000)
|
||
// or
|
||
.timeToLive(10, TimeUnit.SECONDS)
|
||
|
||
// max idle time for each map entry in local cache
|
||
.maxIdle(10000)
|
||
// or
|
||
.maxIdle(10, TimeUnit.SECONDS);
|
||
```
|
||
localcachedmap对象在不再使用之后应该调用destroy方法进行销毁：
|
||
```java
|
||
RLocalCachedMap<String, Integer> map = ...
|
||
map.destroy();
|
||
```
|
||
#### Map Persistence
|
||
redisson允许将map中的数据存储到除了redis以外的空间，其通常用于和应用和数据库之间的缓存，类似于spring cache。
|
||
##### read-through策略
|
||
当请求的条目在redisson map object中不存在时，其会使用MapLoader对象来进行加载，示例代码如下：
|
||
```java
|
||
MapLoader<String, String> mapLoader = new MapLoader<String, String>() {
|
||
|
||
@Override
|
||
public Iterable<String> loadAllKeys() {
|
||
List<String> list = new ArrayList<String>();
|
||
Statement statement = conn.createStatement();
|
||
try {
|
||
ResultSet result = statement.executeQuery("SELECT id FROM student");
|
||
while (result.next()) {
|
||
list.add(result.getString(1));
|
||
}
|
||
} finally {
|
||
statement.close();
|
||
}
|
||
|
||
return list;
|
||
}
|
||
|
||
@Override
|
||
public String load(String key) {
|
||
PreparedStatement preparedStatement = conn.prepareStatement("SELECT name FROM student where id = ?");
|
||
try {
|
||
preparedStatement.setString(1, key);
|
||
ResultSet result = preparedStatement.executeQuery();
|
||
if (result.next()) {
|
||
return result.getString(1);
|
||
}
|
||
return null;
|
||
} finally {
|
||
preparedStatement.close();
|
||
}
|
||
}
|
||
};
|
||
```
|
||
配置map的示例如下：
|
||
```java
|
||
MapOptions<K, V> options = MapOptions.<K, V>defaults()
|
||
.loader(mapLoader);
|
||
|
||
RMap<K, V> map = redisson.getMap("test", options);
|
||
// or
|
||
RMapCache<K, V> map = redisson.getMapCache("test", options);
|
||
// or with boost up to 45x times
|
||
RLocalCachedMap<K, V> map = redisson.getLocalCachedMap("test", options);
|
||
// or with boost up to 45x times
|
||
RLocalCachedMapCache<K, V> map = redisson.getLocalCachedMapCache("test", options);
|
||
```
|
||
##### write-through(sync)策略
|
||
如果map entry被更新，那么更新方法不会返回，直到通过MapWriter对象将entry更新写入到外部存储中：
|
||
```java
|
||
MapWriter<String, String> mapWriter = new MapWriter<String, String>() {
|
||
|
||
@Override
|
||
public void write(Map<String, String> map) {
|
||
PreparedStatement preparedStatement = conn.prepareStatement("INSERT INTO student (id, name) values (?, ?)");
|
||
try {
|
||
for (Entry<String, String> entry : map.entrySet()) {
|
||
preparedStatement.setString(1, entry.getKey());
|
||
preparedStatement.setString(2, entry.getValue());
|
||
preparedStatement.addBatch();
|
||
}
|
||
preparedStatement.executeBatch();
|
||
} finally {
|
||
preparedStatement.close();
|
||
}
|
||
}
|
||
|
||
@Override
|
||
public void delete(Collection<String> keys) {
|
||
PreparedStatement preparedStatement = conn.prepareStatement("DELETE FROM student where id = ?");
|
||
try {
|
||
for (String key : keys) {
|
||
preparedStatement.setString(1, key);
|
||
preparedStatement.addBatch();
|
||
}
|
||
preparedStatement.executeBatch();
|
||
} finally {
|
||
preparedStatement.close();
|
||
}
|
||
}
|
||
};
|
||
```
|
||
write-through策略配置如下：
|
||
```java
|
||
MapOptions<K, V> options = MapOptions.<K, V>defaults()
|
||
.writer(mapWriter)
|
||
.writeMode(WriteMode.WRITE_BEHIND)
|
||
.writeBehindDelay(5000)
|
||
.writeBehindBatchSize(100);
|
||
|
||
RMap<K, V> map = redisson.getMap("test", options);
|
||
// or
|
||
RMapCache<K, V> map = redisson.getMapCache("test", options);
|
||
// or with boost up to 45x times
|
||
RLocalCachedMap<K, V> map = redisson.getLocalCachedMap("test", options);
|
||
// or with boost up to 45x times
|
||
RLocalCachedMapCache<K, V> map = redisson.getLocalCachedMapCache("test", options);
|
||
```
|
||
##### write-behind策略(async)
|
||
在使用write-behind之后，对于map object的修改是批量累计的，并且按定义的延迟异步被MapWriter写入到外部存储中。
|
||
writeBehindDelay是批量写入或删除的延迟，默认情况下值为1000ms。writeBehindBatchSize是batch的容量，每个batch都包含写入和删除的命令集合，默认情况下size是50 .
|
||
配置代码如下所示：
|
||
```java
|
||
MapOptions<K, V> options = MapOptions.<K, V>defaults()
|
||
.writer(mapWriter)
|
||
.writeMode(WriteMode.WRITE_BEHIND)
|
||
.writeBehindDelay(5000)
|
||
.writeBehindBatchSize(100);
|
||
|
||
RMap<K, V> map = redisson.getMap("test", options);
|
||
// or
|
||
RMapCache<K, V> map = redisson.getMapCache("test", options);
|
||
// or with boost up to 45x times
|
||
RLocalCachedMap<K, V> map = redisson.getLocalCachedMap("test", options);
|
||
// or with boost up to 45x times
|
||
RLocalCachedMapCache<K, V> map = redisson.getLocalCachedMapCache("test", options);
|
||
```
|
||
#### Map Listener
|
||
Redisson允许为实现RMapCache接口的Map对象绑定监听器，监听如下的map事件：
|
||
- entry创建：org.redisson.api.map.event.EntryCreatedListener
|
||
- entry过期：org.redisson.api.map.event.EntryExpiredListener
|
||
- entry移除：org.redisson.api.map.event.EntryRemovedListener
|
||
- entry更新：org.redisson.api.map.event.EntryUpdatedListener
|
||
|
||
使用实例如下所示：
|
||
```java
|
||
RMapCache<String, SomeObject> map = redisson.getMapCache("anyMap");
|
||
// or
|
||
RMapCache<String, SomeObject> map = redisson.getLocalCachedMapCache("anyMap", LocalCachedMapOptions.defaults());
|
||
// or
|
||
RMapCache<String, SomeObject> map = redisson.getClusteredLocalCachedMapCache("anyMap", LocalCachedMapOptions.defaults());
|
||
// or
|
||
RMapCache<String, SomeObject> map = redisson.getClusteredMapCache("anyMap");
|
||
|
||
|
||
int updateListener = map.addListener(new EntryUpdatedListener<Integer, Integer>() {
|
||
@Override
|
||
public void onUpdated(EntryEvent<Integer, Integer> event) {
|
||
event.getKey(); // key
|
||
event.getValue() // new value
|
||
event.getOldValue() // old value
|
||
// ...
|
||
}
|
||
});
|
||
|
||
int createListener = map.addListener(new EntryCreatedListener<Integer, Integer>() {
|
||
@Override
|
||
public void onCreated(EntryEvent<Integer, Integer> event) {
|
||
event.getKey(); // key
|
||
event.getValue() // value
|
||
// ...
|
||
}
|
||
});
|
||
|
||
int expireListener = map.addListener(new EntryExpiredListener<Integer, Integer>() {
|
||
@Override
|
||
public void onExpired(EntryEvent<Integer, Integer> event) {
|
||
event.getKey(); // key
|
||
event.getValue() // value
|
||
// ...
|
||
}
|
||
});
|
||
|
||
int removeListener = map.addListener(new EntryRemovedListener<Integer, Integer>() {
|
||
@Override
|
||
public void onRemoved(EntryEvent<Integer, Integer> event) {
|
||
event.getKey(); // key
|
||
event.getValue() // value
|
||
// ...
|
||
}
|
||
});
|
||
|
||
map.removeListener(updateListener);
|
||
map.removeListener(createListener);
|
||
map.removeListener(expireListener);
|
||
map.removeListener(removeListener);
|
||
```
|
||
#### LRU/LFU bounded Map
|
||
实现了RMapCache接口的Map对象支持按LRU或LFU顺序进行绑定。绑定了LRU或LFU的Map可以存储固定数量的entry，并且按照LRU或LFU的顺序淘汰entry。
|
||
```java
|
||
RMapCache<String, SomeObject> map = redisson.getMapCache("anyMap");
|
||
// or
|
||
RMapCache<String, SomeObject> map = redisson.getLocalCachedMapCache("anyMap", LocalCachedMapOptions.defaults());
|
||
// or
|
||
RMapCache<String, SomeObject> map = redisson.getClusteredLocalCachedMapCache("anyMap", LocalCachedMapOptions.defaults());
|
||
// or
|
||
RMapCache<String, SomeObject> map = redisson.getClusteredMapCache("anyMap");
|
||
|
||
|
||
// tries to set limit map to 10 entries using LRU eviction algorithm
|
||
map.trySetMaxSize(10);
|
||
// ... using LFU eviction algorithm
|
||
map.trySetMaxSize(10, EvictionMode.LFU);
|
||
|
||
// set or change limit map to 10 entries using LRU eviction algorithm
|
||
map.setMaxSize(10);
|
||
// ... using LFU eviction algorithm
|
||
map.setMaxSize(10, EvictionMode.LFU);
|
||
|
||
map.put("1", "2");
|
||
map.put("3", "3", 1, TimeUnit.SECONDS);
|
||
```
|
||
### MultiMap
|
||
基于Redis的MultiMap支持为一个key绑定多个value
|
||
#### Set based MultiMap
|
||
基于set的multimap实现对于相同的key不允许出现重复的value：
|
||
```java
|
||
RSetMultimap<SimpleKey, SimpleValue> map = redisson.getSetMultimap("myMultimap");
|
||
map.put(new SimpleKey("0"), new SimpleValue("1"));
|
||
map.put(new SimpleKey("0"), new SimpleValue("2"));
|
||
map.put(new SimpleKey("3"), new SimpleValue("4"));
|
||
|
||
Set<SimpleValue> allValues = map.get(new SimpleKey("0"));
|
||
|
||
List<SimpleValue> newValues = Arrays.asList(new SimpleValue("7"), new SimpleValue("6"), new SimpleValue("5"));
|
||
Set<SimpleValue> oldValues = map.replaceValues(new SimpleKey("0"), newValues);
|
||
|
||
Set<SimpleValue> removedValues = map.removeAll(new SimpleKey("0"));
|
||
```
|
||
#### List based MultiMap
|
||
基于List的MultiMap允许对相同的key存在多个相同value，并且对同一个key其value按插入顺序存储：
|
||
```java
|
||
RListMultimap<SimpleKey, SimpleValue> map = redisson.getListMultimap("test1");
|
||
map.put(new SimpleKey("0"), new SimpleValue("1"));
|
||
map.put(new SimpleKey("0"), new SimpleValue("2"));
|
||
map.put(new SimpleKey("0"), new SimpleValue("1"));
|
||
map.put(new SimpleKey("3"), new SimpleValue("4"));
|
||
|
||
List<SimpleValue> allValues = map.get(new SimpleKey("0"));
|
||
|
||
Collection<SimpleValue> newValues = Arrays.asList(new SimpleValue("7"), new SimpleValue("6"), new SimpleValue("5"));
|
||
List<SimpleValue> oldValues = map.replaceValues(new SimpleKey("0"), newValues);
|
||
|
||
List<SimpleValue> removedValues = map.removeAll(new SimpleKey("0"));
|
||
```
|
||
#### MultiMap eviction
|
||
对于实现了MultimapCache接口的map对象，分别支持基于list和基于set的evicition。
|
||
过期的entry清除由EvictionScheduler执行，其一次性会移除100条过期的entry。Task启动时间会根据上次任务删除的条目数目自动进行调整，时间间隔在1s和2h之间进行调整。
|
||
MultiMap eviction使用示例如下所示：
|
||
```java
|
||
RSetMultimapCache<String, String> multimap = redisson.getSetMultimapCache("myMultimap");
|
||
multimap.put("1", "a");
|
||
multimap.put("1", "b");
|
||
multimap.put("1", "c");
|
||
|
||
multimap.put("2", "e");
|
||
multimap.put("2", "f");
|
||
|
||
multimap.expireKey("2", 10, TimeUnit.MINUTES);
|
||
```
|
||
### Set
|
||
基于redis的set object实现了java.util.set接口。
|
||
redis set的使用如下所示：
|
||
```java
|
||
RSet<SomeObject> set = redisson.getSet("anySet");
|
||
set.add(new SomeObject());
|
||
set.remove(new SomeObject());
|
||
```
|
||
根据是否支持数据淘汰，可以分为如下方法：
|
||
| Redisson Client method | Eviction Support |
|
||
| :-: | :-: |
|
||
| getSet() | false |
|
||
|getSetCache() | true |
|
||
#### eviction
|
||
支持淘汰功能的Set对象实现了RSetCache接口，当前redis尚不支持淘汰set中的值，故而淘汰是由EvictionScheduler实现的，其一次性移除300条entry，根据上次task淘汰的key数量，下次执行task的间隔在1s到1h之间调整。
|
||
```java
|
||
RSetCache<SomeObject> set = redisson.getSetCache("mySet");
|
||
// or
|
||
RMapCache<SomeObject> set = redisson.getClusteredSetCache("mySet");
|
||
|
||
// ttl = 10 minutes,
|
||
set.add(new SomeObject(), 10, TimeUnit.MINUTES);
|
||
|
||
// if object is not used anymore
|
||
set.destroy();
|
||
```
|
||
#### SortedSet
|
||
基于Redis的SortedSet实现了java.util.SortedSet接口，其通过比较元素来确保元素的在set中的唯一性。对于String数据类型，更推荐使用LexSortedSet，其性能表现更好。
|
||
RSortedSet的使用示例如下所示：
|
||
```java
|
||
RSortedSet<Integer> set = redisson.getSortedSet("anySet");
|
||
set.trySetComparator(new MyComparator()); // set object comparator
|
||
set.add(3);
|
||
set.add(1);
|
||
set.add(2);
|
||
|
||
set.removeAsync(0);
|
||
set.addAsync(5);
|
||
```
|
||
#### ScoredSortedSet
|
||
基于redis的分布式ScoredSortedSet根据插入元素时的score来对元素进行排序。使用示例如下所示：
|
||
```java
|
||
set.add(0.13, new SomeObject(a, b));
|
||
set.addAsync(0.251, new SomeObject(c, d));
|
||
set.add(0.302, new SomeObject(g, d));
|
||
|
||
set.pollFirst();
|
||
set.pollLast();
|
||
|
||
int index = set.rank(new SomeObject(g, d)); // get element index
|
||
Double score = set.getScore(new SomeObject(g, d)); // get element score
|
||
``` |