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7. Distributed collections
Redis based distributed Map object for Java implements ConcurrentMap interface. This object is thread-safe. Consider to use Live Object service to store POJO object as Redis Map. Redis uses serialized state to check key uniqueness instead of key's hashCode()/equals() methods.
If Map used mostly for read operations and/or network roundtrips are undesirable use Map with Local cache support.
Code examples:
RMap<String, SomeObject> map = redisson.getMap("anyMap");
SomeObject prevObject = map.put("123", new SomeObject());
SomeObject currentObject = map.putIfAbsent("323", new SomeObject());
SomeObject obj = map.remove("123");
// use fast* methods when previous value is not required
map.fastPut("a", new SomeObject());
map.fastPutIfAbsent("d", new SomeObject());
map.fastRemove("b");
RFuture<SomeObject> putAsyncFuture = map.putAsync("321");
RFuture<Void> fastPutAsyncFuture = map.fastPutAsync("321");
map.fastPutAsync("321", new SomeObject());
map.fastRemoveAsync("321");RMap object allows to bind a Lock/ReadWriteLock/Semaphore/CountDownLatch object per key:
RMap<MyKey, MyValue> map = redisson.getMap("anyMap");
MyKey k = new MyKey();
RLock keyLock = map.getLock(k);
keyLock.lock();
try {
MyValue v = map.get(k);
// process value ...
} finally {
keyLock.unlock();
}
RReadWriteLock rwLock = map.getReadWriteLock(k);
rwLock.readLock().lock();
try {
MyValue v = map.get(k);
// process value ...
} finally {
keyLock.readLock().unlock();
}Redisson provides various Map structure implementations with multiple important features:
local cache - so called near cache used to speed up read operations and avoid network roundtrips. It caches Map entries on Redisson side and executes read operations up to 45x faster in comparison with common implementation. Local cache instances with the same name connected to the same pub/sub channel. This channel is used for exchanging of update/invalidate events between all instances. Local cache store doesn't use hashCode()/equals() methods of key object, instead it uses hash of serialized state. It's recommended to use each local cached instance as a singleton per unique name since it has own state for local cache.
data partitioning - although any Map object is cluster compatible its content isn't scaled/partitioned across multiple Redis master nodes in cluster. Data partitioning allows to scale available memory, read/write operations and entry eviction process for individual Map instance in Redis cluster.
1. No eviction
Each object implements RMap, Async, Reactive and RxJava3 interfaces.
Available implementations:
| RedissonClient method name |
Local cache |
Data partitioning |
Ultra-fast read/write |
|---|---|---|---|
| getMap() open-source version |
❌ | ❌ | ❌ |
| getLocalCachedMap() open-source version |
✔️ | ❌ | ❌ |
| getMap() Redisson PRO version |
❌ | ❌ | ✔️ |
| getLocalCachedMap() Redisson PRO version |
✔️ | ❌ | ✔️ |
| getClusteredMap() available only in Redisson PRO |
❌ | ✔️ | ✔️ |
| getClusteredLocalCachedMap() available only in Redisson PRO |
✔️ | ✔️ | ✔️ |
2. Scripted eviction
Allows to define time to live or max idle time parameters per map entry. Redis hash structure doesn't support eviction thus it's done on Redisson side through a custom scheduled task which removes expired entries using Lua script. Eviction task is started once per unique object name at the moment of getting Map instance. If instance isn't used and has expired entries it should be get again to start the eviction process. This leads to extra Redis calls and eviction task per unique map object name.
Entries are cleaned time to time by org.redisson.eviction.EvictionScheduler. By default, it removes 100 expired entries at a time. This can be changed through cleanUpKeysAmount setting. Task launch time tuned automatically and depends on expired entries amount deleted in previous time and varies between 5 second to 30 minutes by default. This time interval can be changed through minCleanUpDelay and maxCleanUpDelay. For example, if clean task deletes 100 entries each time it will be executed every 5 seconds (minimum execution delay). But if current expired entries amount is lower than previous one then execution delay will be increased by 1.5 times and decreased otherwise.
Each object implements RMapCache, Async, Reactive and RxJava3 interfaces.
Available implementations:
| RedissonClient method name |
Local cache |
Data partitioning |
Ultra-fast read/write |
|---|---|---|---|
| getMapCache() open-source version |
❌ | ❌ | ❌ |
| getMapCache() Redisson PRO version |
❌ | ❌ | ✔️ |
| getLocalCachedMapCache() available only in Redisson PRO |
✔️ | ❌ | ✔️ |
| getClusteredMapCache() available only in Redisson PRO |
❌ | ✔️ | ✔️ |
| getClusteredLocalCachedMapCache() available only in Redisson PRO |
✔️ | ✔️ | ✔️ |
3. Advanced eviction
Allows to define time to live parameter per map entry. Doesn't use an entry eviction task, entries are cleaned on Redis side.
Each object implements RMapCacheV2, Async, Reactive and RxJava3 interfaces.
Available implementations:
| RedissonClient method name |
Local cache |
Data partitioning |
Ultra-fast read/write |
|---|---|---|---|
| getMapCacheV2() available only in Redisson PRO |
❌ | ✔️ | ✔️ |
| getLocalCachedMapCacheV2() available only in Redisson PRO |
✔️ | ✔️ | ✔️ |
4. Native eviction
Allows to define time to live parameter per map entry. Doesn't use an entry eviction task, entries are cleaned on Redis side. Requires Redis 7.4+.
Each object implements RMapCacheNative, Async, Reactive and RxJava3 interfaces.
Available implementations:
| RedissonClient method name |
Local cache |
Data partitioning |
Ultra-fast read/write |
|---|---|---|---|
| getMapCacheNative() open-source version |
❌ | ❌ | ❌ |
| getMapCacheNative() Redisson PRO version |
❌ | ❌ | ✔️ |
| getLocalCachedMapCacheNative() available only in Redisson PRO |
✔️ | ❌ | ✔️ |
| getClusteredMapCacheNative() available only in Redisson PRO |
❌ | ✔️ | ✔️ |
Redisson also provides Spring Cache and JCache implementations.
It's recommended to use single instance of Map instance with the same name for each Redisson client instance.
Code example:
RMapCache<String, SomeObject> map = redisson.getMapCache("anyMap");
// or
RMapCache<String, SomeObject> map = redisson.getMapCache("anyMap", MapCacheOptions.defaults());
// or
RMapCacheV2<String, SomeObject> map = redisson.getMapCacheV2("anyMap");
// or
RMapCacheV2<String, SomeObject> map = redisson.getMapCacheV2("anyMap", MapOptions.defaults());
// 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");
// or
RMapCache<String, SomeObject> map = redisson.getClusteredMapCache("anyMap", MapCacheOptions.defaults());
// 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();Map object with local cache support implements org.redisson.api.RLocalCachedMap which extends java.util.concurrent.ConcurrentMap interface. This object is thread-safe.
It's recommended to use single instance of LocalCachedMap instance per name for each Redisson client instance. Same LocalCachedMapOptions object should be used across all instances with the same name.
Follow options can be supplied during object creation:
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 soft references, entries are removed by GC
// WEAK - Uses weak 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);Code example:
RLocalCachedMap<String, Integer> map = redisson.getLocalCachedMap("test", LocalCachedMapOptions.defaults());
// or
RLocalCachedMap<String, SomeObject> map = redisson.getLocalCachedMapCache("anyMap", LocalCachedMapCacheOptions.defaults());
// or
RLocalCachedMap<String, SomeObject> map = redisson.getClusteredLocalCachedMapCache("anyMap", LocalCachedMapCacheOptions.defaults());
// or
RLocalCachedMap<String, SomeObject> map = redisson.getClusteredLocalCachedMap("anyMap", LocalCachedMapOptions.defaults());
String prevObject = map.put("123", 1);
String currentObject = map.putIfAbsent("323", 2);
String obj = map.remove("123");
// use fast* methods when previous value is not required
map.fastPut("a", 1);
map.fastPutIfAbsent("d", 32);
map.fastRemove("b");
RFuture<String> putAsyncFuture = map.putAsync("321");
RFuture<Void> fastPutAsyncFuture = map.fastPutAsync("321");
map.fastPutAsync("321", new SomeObject());
map.fastRemoveAsync("321");Object should be destroyed if it not used anymore, but it's not necessary to call destroy method if Redisson goes shutdown.
RLocalCachedMap<String, Integer> map = ...
map.destroy();Code example:
public void loadData(String cacheName, Map<String, String> data) {
RLocalCachedMap<String, String> clearMap = redisson.getLocalCachedMap(cacheName,
LocalCachedMapOptions.defaults().cacheSize(1).syncStrategy(SyncStrategy.INVALIDATE));
RLocalCachedMap<String, String> loadMap = redisson.getLocalCachedMap(cacheName,
LocalCachedMapOptions.defaults().cacheSize(1).syncStrategy(SyncStrategy.NONE));
loadMap.putAll(data);
clearMap.clearLocalCache();
}Map object with data partitioning support implements org.redisson.api.RClusteredMap which extends java.util.concurrent.ConcurrentMap interface. Read more details about data partitioning here.
Code example:
RClusteredMap<String, SomeObject> map = redisson.getClusteredMap("anyMap");
// or
RClusteredMap<String, SomeObject> map = redisson.getClusteredLocalCachedMapCache("anyMap", LocalCachedMapCacheOptions.defaults());
// or
RClusteredMap<String, SomeObject> map = redisson.getClusteredLocalCachedMap("anyMap", LocalCachedMapOptions.defaults());
// or
RClusteredMap<String, SomeObject> map = redisson.getClusteredMapCache("anyMap");
SomeObject prevObject = map.put("123", new SomeObject());
SomeObject currentObject = map.putIfAbsent("323", new SomeObject());
SomeObject obj = map.remove("123");
map.fastPut("321", new SomeObject());
map.fastRemove("321");Redisson allows to store Map data in external storage along with Redis store.
Use cases:
- Redisson Map object as a cache between an application and external storage.
- Increase durability of Redisson Map data and life-span of evicted entries.
- Caching for databases, web services or any other data source.
If requested entry doesn't exist in the Redisson Map object when it will be loaded using provided MapLoader object. Code example:
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();
}
}
};Configuration example:
MapOptions<K, V> options = MapOptions.<K, V>defaults()
.loader(mapLoader);
MapCacheOptions<K, V> mcoptions = MapCacheOptions.<K, V>defaults()
.loader(mapLoader);
RMap<K, V> map = redisson.getMap("test", options);
// or
RMapCache<K, V> map = redisson.getMapCache("test", mcoptions);
// or with performance boost up to 45x times
RLocalCachedMap<K, V> map = redisson.getLocalCachedMap("test", options);
// or with performance boost up to 45x times
RLocalCachedMapCache<K, V> map = redisson.getLocalCachedMapCache("test", mcoptions);When the Map entry is being updated method won't return until Redisson update it in an external storage using MapWriter object. Code example:
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();
}
}
};Configuration example:
MapOptions<K, V> options = MapOptions.<K, V>defaults()
.writer(mapWriter)
.writeMode(WriteMode.WRITE_THROUGH);
MapCacheOptions<K, V> mcoptions = MapCacheOptions.<K, V>defaults()
.writer(mapWriter)
.writeMode(WriteMode.WRITE_THROUGH);
RMap<K, V> map = redisson.getMap("test", options);
// or
RMapCache<K, V> map = redisson.getMapCache("test", mcoptions);
// or with performance boost up to 45x times
RLocalCachedMap<K, V> map = redisson.getLocalCachedMap("test", options);
// or with performance boost up to 45x times
RLocalCachedMapCache<K, V> map = redisson.getLocalCachedMapCache("test", mcoptions);Updates of Map object are accumulated in batches and asynchronously written with defined delay to external storage through MapWriter object.
writeBehindDelay - delay of batched write or delete operation. Default value is 1000 milliseconds.
writeBehindBatchSize - size of batch. Each batch contains Map Entry write or delete commands. Default value is 50.
MapOptions<K, V> options = MapOptions.<K, V>defaults()
.writer(mapWriter)
.writeMode(WriteMode.WRITE_BEHIND)
.writeBehindDelay(5000)
.writeBehindBatchSize(100);
MapCacheOptions<K, V> mcoptions = MapCacheOptions.<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", mcoptions);
// or with performance boost up to 45x times
RLocalCachedMap<K, V> map = redisson.getLocalCachedMap("test", options);
// or with performance boost up to 45x times
RLocalCachedMapCache<K, V> map = redisson.getLocalCachedMapCache("test", mcoptions);This feature available for RMap, RMapCache, RLocalCachedMap and RLocalCachedMapCache objects.
Usage of RLocalCachedMap and RLocalCachedMapCache objects boost Redis read-operations up to 45x times and give almost instant speed for database, web service or any other data source.
Redisson allows to bind listeners per RMap object.
RMap object allows to track follow events over the data.
| Listener class name | Event description |
|---|---|
| org.redisson.api.listener.TrackingListener | Entry created/removed/updated after read operation |
| org.redisson.api.listener.MapPutListener | Entry created/updated |
| org.redisson.api.listener.MapRemoveListener | Entry removed |
| org.redisson.api.ExpiredObjectListener |
RMap object expired |
| org.redisson.api.DeletedObjectListener |
RMap object deleted |
Usage examples:
RMap<String, SomeObject> map = redisson.getMap("anyMap");
int listenerId = map.addListener(new DeletedObjectListener() {
@Override
public void onDeleted(String name) {
// ...
}
});
int listenerId = map.addListener(new ExpiredObjectListener() {
@Override
public void onExpired(String name) {
// ...
}
});
int listenerId = map.addListener(new MapPutListener() {
@Override
public void onPut(String name) {
// ...
}
});
int listenerId = map.addListener(new MapRemoveListener() {
@Override
public void onRemove(String name) {
// ...
}
});
map.removeListener(listenerId);RMapCache object allows to track additional events over the data.
| Listener class name | Event description |
|---|---|
| org.redisson.api.map.event.EntryCreatedListener | Entry created |
| org.redisson.api.map.event.EntryExpiredListener | Entry expired |
| org.redisson.api.map.event.EntryRemovedListener | Entry removed |
| org.redisson.api.map.event.EntryUpdatedListener | Entry updated |
Usage examples:
RMapCache<String, SomeObject> map = redisson.getMapCache("anyMap");
// or
RMapCache<String, SomeObject> map = redisson.getLocalCachedMapCache(LocalCachedMapCacheOptions.name("anyMap"));
// or
RMapCache<String, SomeObject> map = redisson.getClusteredLocalCachedMapCache("anyMap", LocalCachedMapOptions.defaults());
// or
RMapCache<String, SomeObject> map = redisson.getClusteredMapCache("anyMap");
int listenerId = 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 listenerId = map.addListener(new EntryCreatedListener<Integer, Integer>() {
@Override
public void onCreated(EntryEvent<Integer, Integer> event) {
event.getKey(); // key
event.getValue() // value
// ...
}
});
int listenerId = map.addListener(new EntryExpiredListener<Integer, Integer>() {
@Override
public void onExpired(EntryEvent<Integer, Integer> event) {
event.getKey(); // key
event.getValue() // value
// ...
}
});
int listenerId = map.addListener(new EntryRemovedListener<Integer, Integer>() {
@Override
public void onRemoved(EntryEvent<Integer, Integer> event) {
event.getKey(); // key
event.getValue() // value
// ...
}
});
map.removeListener(listenerId);Map object which implements RMapCache interface could be bounded using Least Recently Used (LRU) or Least Frequently Used (LFU) order. Bounded Map allows to store map entries within defined limit and retire entries in defined order.
Use cases: limited Redis memory.
RMapCache<String, SomeObject> map = redisson.getMapCache("anyMap");
// or
RMapCache<String, SomeObject> map = redisson.getMapCache("anyMap", MapCacheOptions.defaults());
// 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");
// or
RMapCache<String, SomeObject> map = redisson.getClusteredMapCache("anyMap", MapCacheOptions.defaults());
// 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);Redis based Multimap for Java allows to bind multiple values per key. This object is thread-safe. Keys amount limited by Redis to 4 294 967 295 elements. Redis uses serialized state to check key uniqueness instead of key's hashCode()/equals() methods.
It has Async, Reactive and RxJava3 interfaces.
Set based Multimap doesn't allow duplications for values per key.
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 object for Java stores entries in insertion order and allows duplicates for values mapped to key.
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 distributed object for Java with eviction support implemented by separated MultimapCache object. There are RSetMultimapCache and RListMultimapCache objects for Set and List based Multimaps respectively.
Eviction task is started once per unique object name at the moment of getting Multimap instance. If instance isn't used and has expired entries it should be get again to start the eviction process. This leads to extra Redis calls and eviction task per unique map object name.
Entries are cleaned time to time by org.redisson.eviction.EvictionScheduler. By default, it removes 100 expired entries at a time. This can be changed through cleanUpKeysAmount setting. Task launch time tuned automatically and depends on expired entries amount deleted in previous time and varies between 5 second to 30 minutes by default. This time interval can be changed through minCleanUpDelay and maxCleanUpDelay. For example, if clean task deletes 100 entries each time it will be executed every 5 seconds (minimum execution delay). But if current expired entries amount is lower than previous one then execution delay will be increased by 1.5 times and decreased otherwise.
RSetMultimapCache example:
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);
// if object is not used anymore
multimap.destroy();Redis based Set object for Java implements Set interface. This object is thread-safe. Keeps elements uniqueness via element state comparison. Set size limited by Redis to 4 294 967 295 elements. Redis uses serialized state to check value uniqueness instead of value's hashCode()/equals() methods.
It has Async, Reactive and RxJava3 interfaces.
RSet<SomeObject> set = redisson.getSet("anySet");
set.add(new SomeObject());
set.remove(new SomeObject());RSet object allows to bind a Lock/ReadWriteLock/Semaphore/CountDownLatch object per value:
RSet<MyObject> set = redisson.getSet("anySet");
MyObject value = new MyObject();
RLock lock = map.getLock(value);
lock.lock();
try {
// process value ...
} finally {
lock.unlock();
}
Redisson provides various Set structure implementations with a few important features:
data partitioning - although any Set object is cluster compatible its content isn't scaled/partitioned across multiple Redis master nodes in cluster. Data partitioning allows to scale available memory, read/write operations and entry eviction process for individual Set instance in Redis cluster.
entry eviction - allows to define time to live parameter per SetCache entry. Redis set structure doesn't support eviction thus it's done on Redisson side through a custom scheduled task which removes expired entries using Lua script. Eviction task is started once per unique object name at the moment of getting SetCache instance. If instance isn't used and has expired entries it should be get again to start the eviction process. This leads to extra Redis calls and eviction task per unique SetCache object name.
Entries are cleaned time to time by org.redisson.eviction.EvictionScheduler. By default, it removes 100 expired entries at a time. This can be changed through cleanUpKeysAmount setting. Task launch time tuned automatically and depends on expired entries amount deleted in previous time and varies between 5 second to 30 minutes by default. This time interval can be changed through minCleanUpDelay and maxCleanUpDelay. For example, if clean task deletes 100 entries each time it will be executed every 5 seconds (minimum execution delay). But if current expired entries amount is lower than previous one then execution delay will be increased by 1.5 times and decreased otherwise.
advanced entry eviction - improved version of the entry eviction process. Doesn't use an entry eviction task.
Set object with eviction support implements RSetCache, Async, Reactive and RxJava3 interfaces.
Code example:
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
map.destroy();Map object with data partitioning support implements org.redisson.api.RClusteredSet. Read more details about data partitioning here.
Code example:
RClusteredSet<SomeObject> set = redisson.getClusteredSet("mySet");
// or
RClusteredSet<SomeObject> set = redisson.getClusteredSetCache("mySet");
// ttl = 10 minutes,
map.add(new SomeObject(), 10, TimeUnit.MINUTES);Below is the list of all available Set implementations:
| RedissonClient method name |
Data partitioning |
Entry eviction |
Advanced entry eviction |
Ultra-fast read/write |
|---|---|---|---|---|
| getSet() open-source version |
❌ | ❌ | ❌ | ❌ |
| getSetCache() open-source version |
❌ | ✔️ | ❌ | ❌ |
| getSet() Redisson PRO version |
❌ | ❌ | ❌ | ✔️ |
| getSetCache() Redisson PRO version |
❌ | ✔️ | ❌ | ✔️ |
| getSetCacheV2() available only in Redisson PRO |
✔️ | ❌ | ✔️ | ✔️ |
| getClusteredSet() available only in Redisson PRO |
✔️ | ❌ | ❌ | ✔️ |
| getClusteredSetCache() available only in Redisson PRO |
✔️ | ✔️ | ❌ | ✔️ |
Redisson allows to bind listeners per RSet object.
| Listener class name | Event description |
|---|---|
| org.redisson.api.listener.TrackingListener | Element added/removed/updated after read operation |
| org.redisson.api.ExpiredObjectListener |
RSet object expired |
| org.redisson.api.DeletedObjectListener |
RSet object deleted |
| org.redisson.api.listener.SetAddListener | Element added |
| org.redisson.api.listener.SetRemoveListener | Element removed |
| org.redisson.api.listener.SetRemoveRandomListener | Element randomly removed |
Usage example:
RSet<String> set = redisson.getSet("anySet");
int listenerId = set.addListener(new DeletedObjectListener() {
@Override
public void onDeleted(String name) {
// ...
}
});
// ...
set.removeListener(listenerId);Redis based distributed SortedSet for Java implements java.util.SortedSet interface. This object is thread-safe. It uses comparator to sort elements and keep uniqueness. For String data type it's recommended to use LexSortedSet object due to performance gain.
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);Redis based distributed ScoredSortedSet object. Sorts elements by score defined during element insertion. Keeps elements uniqueness via element state comparison.
It has Async, Reactive and RxJava3 interfaces. Set size is limited by Redis to 4 294 967 295 elements.
RScoredSortedSet<SomeObject> set = redisson.getScoredSortedSet("simple");
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 scoreAlthough 'RScoredSortedSet' object is cluster compatible its content isn't scaled across multiple Redis master nodes. RScoredSortedSet data partitioning available only in cluster mode and implemented by separate RClusteredScoredSortedSet object. Size is limited by whole Redis Cluster memory. More about partitioning here.
Below is the list of all available RScoredSortedSet implementations:
| RedissonClient method name |
Data partitioning support |
Ultra-fast read/write |
|---|---|---|
| getScoredSortedSet() open-source version |
❌ | ❌ |
| getScoredSortedSet() Redisson PRO version |
❌ | ✔️ |
| getClusteredScoredSortedSet() available only in Redisson PRO |
✔️ | ✔️ |
Code example:
RClusteredScoredSortedSet set = redisson.getClusteredScoredSortedSet("simpleBitset");
set.add(1.1, "v1");
set.add(1.2, "v2");
set.add(1.3, "v3");
ScoredEntry<String> s = set.firstEntry();
ScoredEntry<String> e = set.pollFirstEntry();Redisson allows to bind listeners per RScoredSortedSet object.
| Listener class name | Event description |
|---|---|
| org.redisson.api.listener.TrackingListener | Element created/removed/updated after read operation |
| org.redisson.api.listener.ScoredSortedSetAddListener | Element created/updated |
| org.redisson.api.listener.ScoredSortedSetRemoveListener | Element removed |
| org.redisson.api.ExpiredObjectListener |
RScoredSortedSet object expired |
| org.redisson.api.DeletedObjectListener |
RScoredSortedSet object deleted |
Usage example:
RScoredSortedSet<String> set = redisson.getScoredSortedSet("anySet");
int listenerId = set.addListener(new DeletedObjectListener() {
@Override
public void onDeleted(String name) {
// ...
}
});
// ...
set.removeListener(listenerId);Redis based distributed Set object for Java allows String objects only and implements java.util.Set<String> interface. It keeps elements in lexicographical order and maintain elements uniqueness via element state comparison.
It has Async, Reactive and RxJava3 interfaces.
RLexSortedSet set = redisson.getLexSortedSet("simple");
set.add("d");
set.addAsync("e");
set.add("f");
set.rangeTail("d", false);
set.countHead("e");
set.range("d", true, "z", false);Redisson allows to bind listeners per RLexSortedSet object.
| Listener class name | Event description |
|---|---|
| org.redisson.api.listener.TrackingListener | Element created/removed/updated after read operation |
| org.redisson.api.listener.ScoredSortedSetAddListener | Element created/updated |
| org.redisson.api.listener.ScoredSortedSetRemoveListener | Element removed |
| org.redisson.api.ExpiredObjectListener |
RScoredSortedSet object expired |
| org.redisson.api.DeletedObjectListener |
RScoredSortedSet object deleted |
Usage example:
RLexSortedSet<String> set = redisson.getLexSortedSet("anySet");
int listenerId = set.addListener(new DeletedObjectListener() {
@Override
public void onDeleted(String name) {
// ...
}
});
// ...
set.removeListener(listenerId);Redis based distributed List object for Java implements java.util.List interface. It keeps elements in insertion order.
It has Async, Reactive and RxJava3 interfaces. List size is limited by Redis to 4 294 967 295 elements.
RList<SomeObject> list = redisson.getList("anyList");
list.add(new SomeObject());
list.get(0);
list.remove(new SomeObject());Redisson allows to bind listeners per RList object.
| Listener class name | Event description |
|---|---|
| org.redisson.api.listener.TrackingListener | Element created/removed/updated after read operation |
| org.redisson.api.listener.ListAddListener | Element created |
| org.redisson.api.listener.ListInsertListener | Element inserted |
| org.redisson.api.listener.ListSetListener | Element set/updated |
| org.redisson.api.listener.ListRemoveListener | Element removed |
| org.redisson.api.listener.ListTrimListener | List trimmed |
| org.redisson.api.ExpiredObjectListener |
RList object expired |
| org.redisson.api.DeletedObjectListener |
RList object deleted |
Usage example:
RList<String> list = redisson.getList("anyList");
int listenerId = list.addListener(new DeletedObjectListener() {
@Override
public void onDeleted(String name) {
// ...
}
});
// ...
list.removeListener(listenerId);Redis based distributed unbounded Queue object for Java implements java.util.Queue interface. This object is thread-safe.
It has Async, Reactive and RxJava3 interfaces.
RQueue<SomeObject> queue = redisson.getQueue("anyQueue");
queue.add(new SomeObject());
SomeObject obj = queue.peek();
SomeObject someObj = queue.poll();Redisson allows to bind listeners per RQueue object.
| Listener class name | Event description |
|---|---|
| org.redisson.api.listener.TrackingListener | Element created/removed/updated after read operation |
| org.redisson.api.listener.ListAddListener | Element created |
| org.redisson.api.listener.ListRemoveListener | Element removed |
| org.redisson.api.ExpiredObjectListener |
RQueue object expired |
| org.redisson.api.DeletedObjectListener |
RQueue object deleted |
Usage example:
RQueue<String> queue = redisson.getQueue("anyList");
int listenerId = queue.addListener(new DeletedObjectListener() {
@Override
public void onDeleted(String name) {
// ...
}
});
// ...
queue.removeListener(listenerId);Redis based distributed unbounded Deque object for Java implements java.util.Deque interface. This object is thread-safe.
It has Async, Reactive and RxJava3 interfaces.
RDeque<SomeObject> queue = redisson.getDeque("anyDeque");
queue.addFirst(new SomeObject());
queue.addLast(new SomeObject());
SomeObject obj = queue.removeFirst();
SomeObject someObj = queue.removeLast();Redisson allows to bind listeners per RDeque object.
| Listener class name | Event description |
|---|---|
| org.redisson.api.listener.TrackingListener | Element created/removed/updated after read operation |
| org.redisson.api.listener.ListAddListener | Element created |
| org.redisson.api.listener.ListRemoveListener | Element removed |
| org.redisson.api.ExpiredObjectListener |
RDeque object expired |
| org.redisson.api.DeletedObjectListener |
RDeque object deleted |
Usage example:
RDeque<String> deque = redisson.getDeque("anyList");
int listenerId = deque.addListener(new DeletedObjectListener() {
@Override
public void onDeleted(String name) {
// ...
}
});
// ...
deque.removeListener(listenerId);Redis based distributed unbounded BlockingQueue object for Java implements java.util.concurrent.BlockingQueue interface. This object is thread-safe.
It has Async, Reactive and RxJava3 interfaces.
RBlockingQueue<SomeObject> queue = redisson.getBlockingQueue("anyQueue");
queue.offer(new SomeObject());
SomeObject obj = queue.peek();
SomeObject obj = queue.poll();
SomeObject obj = queue.poll(10, TimeUnit.MINUTES);poll, pollFromAny, pollLastAndOfferFirstTo and take methods are resubscribed automatically during re-connection to Redis server or failover.
Redis based distributed BoundedBlockingQueue for Java implements java.util.concurrent.BlockingQueue interface. BoundedBlockingQueue size limited by Redis to 4 294 967 295 elements. This object is thread-safe.
Queue capacity should be defined once by trySetCapacity() method before the usage:
RBoundedBlockingQueue<SomeObject> queue = redisson.getBoundedBlockingQueue("anyQueue");
// returns `true` if capacity set successfully and `false` if it already set.
queue.trySetCapacity(2);
queue.offer(new SomeObject(1));
queue.offer(new SomeObject(2));
// will be blocked until free space available in queue
queue.put(new SomeObject());
SomeObject obj = queue.peek();
SomeObject someObj = queue.poll();
SomeObject ob = queue.poll(10, TimeUnit.MINUTES);poll, pollFromAny, pollLastAndOfferFirstTo and take methods will be resubscribed automatically during reconnection to Redis server or Redis server failover.
Java implementation of Redis based BlockingDeque implements java.util.concurrent.BlockingDeque interface. This object is thread-safe.
It has Async, Reactive and RxJava3 interfaces.
RBlockingDeque<Integer> deque = redisson.getBlockingDeque("anyDeque");
deque.putFirst(1);
deque.putLast(2);
Integer firstValue = queue.takeFirst();
Integer lastValue = queue.takeLast();
Integer firstValue = queue.pollFirst(10, TimeUnit.MINUTES);
Integer lastValue = queue.pollLast(3, TimeUnit.MINUTES);poll, pollFromAny, pollLastAndOfferFirstTo and take methods are resubscribed automatically during re-connection to Redis server or failover.
Redis based distributed BlockingFairQueue for Java implements java.util.concurrent.BlockingQueue interface. This object is thread-safe.
When queue consumers in different parts of network: some of them closer to redis and some further. "further" consumers will get lower amount of messages from queue due to network delays. In turn "closer" consumers will get higher amount and this could lead to client overloading.
Blocking queue with fair polling guarantees access order for poll and take methods and allows to get uniformly distributed consumption.
RBlockingFairQueue queue = redisson.getBlockingFairQueue("myQueue");
queue.offer(new SomeObject());
SomeObject element = queue.peek();
SomeObject element = queue.poll();
SomeObject element = queue.poll(10, TimeUnit.MINUTES);
SomeObject element = queue.take();This feature available only in Redisson PRO edition.
Redis based distributed BlockingFairDeque for Java implements java.util.concurrent.BlockingDeque interface. This object is thread-safe.
When deque consumers in different parts of network: some of them closer to redis and some further. "further" consumers will get lower amount of messages from queue due to network delays. In turn "closer" consumers will get higher amount and this could lead to client overloading.
Blocking deque with fair polling guarantees access order for poll, take, pollFirst, takeFirst, pollLast and takeLast methods and allows to get uniformly distributed consumption.
RBlockingFairDeque deque = redisson.getBlockingFairDeque("myDeque");
deque.offer(new SomeObject());
SomeObject firstElement = queue.peekFirst();
SomeObject firstElement = queue.pollFirst();
SomeObject firstElement = queue.pollFirst(10, TimeUnit.MINUTES);
SomeObject firstElement = queue.takeFirst();
SomeObject lastElement = queue.peekLast();
SomeObject lastElement = queue.pollLast();
SomeObject lastElement = queue.pollLast(10, TimeUnit.MINUTES);
SomeObject lastElement = queue.takeLast();This feature available only in Redisson PRO edition.
Redis based DelayedQueue object for Java allows to transfer each element to destination queue with specified delay. Destination queue could be any queue implemented RQueue interface. This object is thread-safe.
Could be useful for exponential backoff strategy used for message delivery to consumer. If application is restarted, an instance of delayed queue should created in order for the pending items to be added to the destination queue.
RBlockingQueue<String> distinationQueue = ...
RDelayedQueue<String> delayedQueue = getDelayedQueue(distinationQueue);
// move object to distinationQueue in 10 seconds
delayedQueue.offer("msg1", 10, TimeUnit.SECONDS);
// move object to distinationQueue in 1 minutes
delayedQueue.offer("msg2", 1, TimeUnit.MINUTES);
// msg1 will appear in 10 seconds
distinationQueue.poll(15, TimeUnit.SECONDS);
// msg2 will appear in 2 seconds
distinationQueue.poll(2, TimeUnit.SECONDS);Object should be destroyed if it not used anymore, but it's not necessary to call destroy method if Redisson goes shutdown.
RDelayedQueue<String> delayedQueue = ...
delayedQueue.destroy();Java implementation of Redis based PriorityQueue implements java.util.Queue interface. Elements are ordered according to natural order of java.lang.Comparable interface or defined java.util.Comparator. This object is thread-safe.
Use trySetComparator() method to define own java.util.Comparator.
Code example:
public class Entry implements Comparable<Entry>, Serializable {
private String key;
private Integer value;
public Entry(String key, Integer value) {
this.key = key;
this.value = value;
}
@Override
public int compareTo(Entry o) {
return key.compareTo(o.key);
}
}
RPriorityQueue<Entry> queue = redisson.getPriorityQueue("anyQueue");
queue.add(new Entry("b", 1));
queue.add(new Entry("c", 1));
queue.add(new Entry("a", 1));
// Entry [a:1]
Entry e = queue.poll();
// Entry [b:1]
Entry e = queue.poll();
// Entry [c:1]
Entry e = queue.poll();Java implementation of Redis based PriorityDeque implements java.util.Deque interface. Elements are ordered according to natural order of java.lang.Comparable interface or defined java.util.Comparator. This object is thread-safe.
Use trySetComparator() method to define own java.util.Comparator.
Code example:
public class Entry implements Comparable<Entry>, Serializable {
private String key;
private Integer value;
public Entry(String key, Integer value) {
this.key = key;
this.value = value;
}
@Override
public int compareTo(Entry o) {
return key.compareTo(o.key);
}
}
RPriorityDeque<Entry> queue = redisson.getPriorityDeque("anyQueue");
queue.add(new Entry("b", 1));
queue.add(new Entry("c", 1));
queue.add(new Entry("a", 1));
// Entry [a:1]
Entry e = queue.pollFirst();
// Entry [c:1]
Entry e = queue.pollLast();Java implementation of Redis based PriorityBlockingQueue similar to JDK java.util.concurrent.PriorityBlockingQueue object. Elements are ordered according to natural order of java.lang.Comparable interface or defined java.util.Comparator. This object is thread-safe.
Use trySetComparator() method to define own java.util.Comparator.
poll, pollLastAndOfferFirstTo and take methods are resubscribed automatically during re-connection to Redis server or failover.
Code example:
public class Entry implements Comparable<Entry>, Serializable {
private String key;
private Integer value;
public Entry(String key, Integer value) {
this.key = key;
this.value = value;
}
@Override
public int compareTo(Entry o) {
return key.compareTo(o.key);
}
}
RPriorityBlockingQueue<Entry> queue = redisson.getPriorityBlockingQueue("anyQueue");
queue.add(new Entry("b", 1));
queue.add(new Entry("c", 1));
queue.add(new Entry("a", 1));
// Entry [a:1]
Entry e = queue.take();Java implementation of Redis based PriorityBlockingDeque implements java.util.concurrent.BlockingDeque interface. Elements are ordered according to natural order of java.lang.Comparable interface or defined java.util.Comparator. This object is thread-safe.
Use trySetComparator() method to define own java.util.Comparator.
poll, pollLastAndOfferFirstTo, take methods are resubscribed automatically during re-connection to Redis server or failover.
Code example:
public class Entry implements Comparable<Entry>, Serializable {
private String key;
private Integer value;
public Entry(String key, Integer value) {
this.key = key;
this.value = value;
}
@Override
public int compareTo(Entry o) {
return key.compareTo(o.key);
}
}
RPriorityBlockingDeque<Entry> queue = redisson.getPriorityBlockingDeque("anyQueue");
queue.add(new Entry("b", 1));
queue.add(new Entry("c", 1));
queue.add(new Entry("a", 1));
// Entry [a:1]
Entry e = queue.takeFirst();
// Entry [c:1]
Entry e = queue.takeLast();Java implementation of Redis based Stream object wraps Redis Stream feature. Basically it allows to create Consumers Group which consume data added by Producers. This object is thread-safe.
RStream<String, String> stream = redisson.getStream("test");
StreamMessageId sm = stream.add(StreamAddArgs.entry("0", "0"));
stream.createGroup("testGroup");
StreamId id1 = stream.add(StreamAddArgs.entry("1", "1"));
StreamId id2 = stream.add(StreamAddArgs.entry("2", "2"));
Map<StreamId, Map<String, String>> group = stream.readGroup("testGroup", "consumer1", StreamReadGroupArgs.neverDelivered());
// return entries in pending state after read group method execution
Map<StreamMessageId, Map<String, String>> pendingData = stream.pendingRange("testGroup", "consumer1", StreamMessageId.MIN, StreamMessageId.MAX, 100);
// transfer ownership of pending messages to a new consumer
List<StreamMessageId> transferedIds = stream.fastClaim("testGroup", "consumer2", 1, TimeUnit.MILLISECONDS, id1, id2);
// mark pending entries as correctly processed
long amount = stream.ack("testGroup", id1, id2);Code example of Async interface usage:
RStream<String, String> stream = redisson.getStream("test");
RFuture<StreamMessageId> smFuture = stream.addAsync(StreamAddArgs.entry("0", "0"));
RFuture<Void> groupFuture = stream.createGroupAsync("testGroup");
RFuture<StreamId> id1Future = stream.addAsync(StreamAddArgs.entry("1", "1"));
RFuture<StreamId> id2Future = stream.addAsync(StreamAddArgs.entry("2", "2"));
RFuture<Map<StreamId, Map<String, String>>> groupResultFuture = stream.readGroupAsync("testGroup", "consumer1", StreamReadGroupArgs.neverDelivered());
// return entries in pending state after read group method execution
RFuture<Map<StreamMessageId, Map<String, String>>> pendingDataFuture = stream.pendingRangeAsync("testGroup", "consumer1", StreamMessageId.MIN, StreamMessageId.MAX, 100);
// transfer ownership of pending messages to a new consumer
RFuture<List<StreamMessageId>> transferedIdsFuture = stream.fastClaim("testGroup", "consumer2", 1, TimeUnit.MILLISECONDS, id1, id2);
// mark pending entries as correctly processed
RFuture<Long> amountFuture = stream.ackAsync("testGroup", id1, id2);
amountFuture.whenComplete((res, exception) -> {
// ...
});Code example of Reactive interface usage:
RedissonReactiveClient redisson = redissonClient.reactive();
RStreamReactive<String, String> stream = redisson.getStream("test");
Mono<StreamMessageId> smMono = stream.add(StreamAddArgs.entry("0", "0"));
Mono<Void> groupMono = stream.createGroup("testGroup");
Mono<StreamId> id1Mono = stream.add(StreamAddArgs.entry("1", "1"));
Mono<StreamId> id2Mono = stream.add(StreamAddArgs.entry("2", "2"));
Mono<Map<StreamId, Map<String, String>>> groupMono = stream.readGroup("testGroup", "consumer1", StreamReadGroupArgs.neverDelivered());
// return entries in pending state after read group method execution
Mono<Map<StreamMessageId, Map<String, String>>> pendingDataMono = stream.pendingRange("testGroup", "consumer1", StreamMessageId.MIN, StreamMessageId.MAX, 100);
// transfer ownership of pending messages to a new consumer
Mono<List<StreamMessageId>> transferedIdsMono = stream.fastClaim("testGroup", "consumer2", 1, TimeUnit.MILLISECONDS, id1, id2);
// mark pending entries as correctly processed
Mono<Long> amountMono = stream.ack("testGroup", id1, id2);
amountMono.doOnNext(res -> {
// ...
}).subscribe();Code example of RxJava3 interface usage:
RedissonRxClient redisson = redissonClient.rxJava();
RStreamRx<String, String> stream = redisson.getStream("test");
Single<StreamMessageId> smRx = stream.add(StreamAddArgs.entry("0", "0"));
Completable groupRx = stream.createGroup("testGroup");
Single<StreamId> id1Rx = stream.add(StreamAddArgs.entry("1", "1"));
Single<StreamId> id2Rx = stream.add(StreamAddArgs.entry("2", "2"));
Single<Map<StreamId, Map<String, String>>> groupRx = stream.readGroup("testGroup", "consumer1", StreamReadGroupArgs.neverDelivered());
// return entries in pending state after read group method execution
Single<Map<StreamMessageId, Map<String, String>>> pendingDataRx = stream.pendingRange("testGroup", "consumer1", StreamMessageId.MIN, StreamMessageId.MAX, 100);
// transfer ownership of pending messages to a new consumer
Single<List<StreamMessageId>> transferedIdsRx = stream.fastClaim("testGroup", "consumer2", 1, TimeUnit.MILLISECONDS, id1, id2);
// mark pending entries as correctly processed
Single<Long> amountRx = stream.ack("testGroup", id1, id2);
amountRx.doOnSuccess(res -> {
// ...
}).subscribe();Redisson allows to bind listeners per RStream object.
| Listener class name | Event description |
|---|---|
| org.redisson.api.listener.TrackingListener | Element added/removed/updated after read operation |
| org.redisson.api.ExpiredObjectListener |
RStream object expired |
| org.redisson.api.DeletedObjectListener |
RStream object deleted |
| org.redisson.api.listener.StreamAddListener | Element added |
| org.redisson.api.listener.StreamRemoveListener | Element removed |
| org.redisson.api.listener.StreamCreateGroupListener | Group created |
| org.redisson.api.listener.StreamRemoveGroupListener | Group removed |
| org.redisson.api.listener.StreamCreateConsumerListener | Consumer created |
| org.redisson.api.listener.StreamRemoveConsumerListener | Consumer removed |
| org.redisson.api.listener.StreamTrimListener | Stream trimmed |
Usage example:
RStream<String, String> stream = redisson.getStream("anySet");
int listenerId = stream.addListener(new DeletedObjectListener() {
@Override
public void onDeleted(String name) {
// ...
}
});
int listenerId = stream.addListener(new StreamAddListener() {
@Override
public void onAdd(String name) {
// ...
}
});
// ...
stream.removeListener(listenerId);Java implementation of Redis based RingBuffer implements java.util.Queue interface. This structure evicts elements from the head if queue capacity became full. This object is thread-safe.
Should be initialized with capacity size by trySetCapacity() method before usage.
Code example:
RRingBuffer<Integer> buffer = redisson.getRingBuffer("test");
// buffer capacity is 4 elements
buffer.trySetCapacity(4);
buffer.add(1);
buffer.add(2);
buffer.add(3);
buffer.add(4);
// buffer state is 1, 2, 3, 4
buffer.add(5);
buffer.add(6);
// buffer state is 3, 4, 5, 6Code example of Async interface usage:
RRingBuffer<Integer> buffer = redisson.getRingBuffer("test");
// buffer capacity is 4 elements
RFuture<Boolean> capacityFuture = buffer.trySetCapacityAsync(4);
RFuture<Boolean> addFuture = buffer.addAsync(1);
RFuture<Boolean> addFuture = buffer.addAsync(2);
RFuture<Boolean> addFuture = buffer.addAsync(3);
RFuture<Boolean> addFuture = buffer.addAsync(4);
// buffer state is 1, 2, 3, 4
RFuture<Boolean> addFuture = buffer.addAsync(5);
RFuture<Boolean> addFuture = buffer.addAsync(6);
// buffer state is 3, 4, 5, 6
addFuture.whenComplete((res, exception) -> {
// ...
});Code example of Reactive interface usage:
RedissonReactiveClient redisson = redissonClient.reactive();
RRingBufferReactive<Integer> buffer = redisson.getRingBuffer("test");
// buffer capacity is 4 elements
Mono<Boolean> capacityMono = buffer.trySetCapacity(4);
Mono<Boolean> addMono = buffer.add(1);
Mono<Boolean> addMono = buffer.add(2);
Mono<Boolean> addMono = buffer.add(3);
Mono<Boolean> addMono = buffer.add(4);
// buffer state is 1, 2, 3, 4
Mono<Boolean> addMono = buffer.add(5);
Mono<Boolean> addMono = buffer.add(6);
// buffer state is 3, 4, 5, 6
addMono.doOnNext(res -> {
// ...
}).subscribe();Code example of RxJava3 interface usage:
RedissonRxClient redisson = redissonClient.rxJava();
RRingBufferRx<Integer> buffer = redisson.getRingBuffer("test");
// buffer capacity is 4 elements
Single<Boolean> capacityRx = buffer.trySetCapacity(4);
Single<Boolean> addRx = buffer.add(1);
Single<Boolean> addRx = buffer.add(2);
Single<Boolean> addRx = buffer.add(3);
Single<Boolean> addRx = buffer.add(4);
// buffer state is 1, 2, 3, 4
Single<Boolean> addRx = buffer.add(5);
Single<Boolean> addRx = buffer.add(6);
// buffer state is 3, 4, 5, 6
addRx.doOnSuccess(res -> {
// ...
}).subscribe();Redisson allows to bind listeners per RRingBuffer object.
| Listener class name | Event description |
|---|---|
| org.redisson.api.listener.TrackingListener | Element created/removed/updated after read operation |
| org.redisson.api.listener.ListAddListener | Element created |
| org.redisson.api.listener.ListRemoveListener | Element removed |
| org.redisson.api.ExpiredObjectListener |
RRingBuffer object expired |
| org.redisson.api.DeletedObjectListener |
RRingBuffer object deleted |
Usage example:
RRingBuffer<String> queue = redisson.getRingBuffer("anyList");
int listenerId = queue.addListener(new DeletedObjectListener() {
@Override
public void onDeleted(String name) {
// ...
}
});
// ...
queue.removeListener(listenerId);Java implementation of Redis based TransferQueue implements java.util.concurrent.TransferQueue interface. Provides set of transfer methods which return only when value was successfully hand off to consumer. This object is thread-safe.
poll and take methods are resubscribed automatically during re-connection to Redis server or failover.
Code example:
RTransferQueue<String> queue = redisson.getTransferQueue("myCountDownLatch");
queue.transfer("data");
// or try transfer immediately
queue.tryTransfer("data");
// or try transfer up to 10 seconds
queue.tryTransfer("data", 10, TimeUnit.SECONDS);
// in other thread or JVM
queue.take();
// or
queue.poll();Code example of Async interface usage:
RTransferQueue<String> queue = redisson.getTransferQueue("myCountDownLatch");
RFuture<Void> future = queue.transferAsync("data");
// or try transfer immediately
RFuture<Boolean> future = queue.tryTransferAsync("data");
// or try transfer up to 10 seconds
RFuture<Boolean> future = queue.tryTransferAsync("data", 10, TimeUnit.SECONDS);
// in other thread or JVM
RFuture<String> future = queue.takeAsync();
// or
RFuture<String> future = queue.pollAsync();
future.whenComplete((res, exception) -> {
// ...
});Code example of Reactive interface usage:
RedissonReactiveClient redisson = redissonClient.reactive();
RTransferQueueReactive<String> queue = redisson.getTransferQueue("myCountDownLatch");
Mono<Void> mono = queue.transfer("data");
// or try transfer immediately
Mono<Boolean> mono = queue.tryTransfer("data");
// or try transfer up to 10 seconds
Mono<Boolean> mono = queue.tryTransfer("data", 10, TimeUnit.SECONDS);
// in other thread or JVM
Mono<String> mono = queue.take();
// or
Mono<String> mono = queue.poll();
mono.doOnNext(res -> {
// ...
}).subscribe();Code example of RxJava3 interface usage:
RedissonRxClient redisson = redissonClient.rxJava();
RTransferQueueRx<String> queue = redisson.getTransferQueue("myCountDownLatch");
Completable res = queue.transfer("data");
// or try transfer immediately
Single<Boolean> resRx = queue.tryTransfer("data");
// or try transfer up to 10 seconds
Single<Boolean> resRx = queue.tryTransfer("data", 10, TimeUnit.SECONDS);
// in other thread or JVM
Single<String> resRx = queue.take();
// or
Maybe<String> resRx = queue.poll();
resRx.doOnSuccess(res -> {
// ...
}).subscribe();Java implementation of Redis based TimeSeries object allows to store value by timestamp and define TTL(time-to-live) per entry. Values are ordered by timestamp. This object is thread-safe.
Code example:
RTimeSeries<String> ts = redisson.getTimeSeries("myTimeSeries");
ts.add(201908110501, "10%");
ts.add(201908110502, "30%");
ts.add(201908110504, "10%");
ts.add(201908110508, "75%");
// entry time-to-live is 10 hours
ts.add(201908110510, "85%", 10, TimeUnit.HOURS);
ts.add(201908110510, "95%", 10, TimeUnit.HOURS);
String value = ts.get(201908110508);
ts.remove(201908110508);
Collection<String> values = ts.pollFirst(2);
Collection<String> range = ts.range(201908110501, 201908110508);Code example of Async interface usage:
RTimeSeries<String> ts = redisson.getTimeSeries("myTimeSeries");
RFuture<Void> future = ts.addAsync(201908110501, "10%");
RFuture<Void> future = ts.addAsync(201908110502, "30%");
RFuture<Void> future = ts.addAsync(201908110504, "10%");
RFuture<Void> future = ts.addAsync(201908110508, "75%");
// entry time-to-live is 10 hours
RFuture<Void> future = ts.addAsync(201908110510, "85%", 10, TimeUnit.HOURS);
RFuture<Void> future = ts.addAsync(201908110510, "95%", 10, TimeUnit.HOURS);
RFuture<String> future = ts.getAsync(201908110508);
RFuture<Boolean> future = ts.removeAsync(201908110508);
RFuture<Collection<String>> future = t.pollFirstAsync(2);
RFuture<Collection<String>> future = t.rangeAsync(201908110501, 201908110508);
future.whenComplete((res, exception) -> {
// ...
});Code example of Reactive interface usage:
RedissonReactiveClient redisson = redissonClient.reactive();
RTimeSeriesReactive<String> ts = redisson.getTimeSeries("myTimeSeries");
Mono<Void> mono = ts.add(201908110501, "10%");
Mono<Void> mono = ts.add(201908110502, "30%");
Mono<Void> mono = ts.add(201908110504, "10%");
Mono<Void> mono = ts.add(201908110508, "75%");
// entry time-to-live is 10 hours
Mono<Void> mono = ts.add(201908110510, "85%", 10, TimeUnit.HOURS);
Mono<Void> mono = ts.add(201908110510, "95%", 10, TimeUnit.HOURS);
Mono<String> mono = ts.get(201908110508);
Mono<Boolean> mono = ts.remove(201908110508);
Mono<Collection<String>> mono = ts.pollFirst(2);
Mono<Collection<String>> mono = ts.range(201908110501, 201908110508);
mono.doOnNext(res -> {
// ...
}).subscribe();Code example of RxJava3 interface usage:
RedissonRxClient redisson = redissonClient.rxJava();
RTimeSeriesRx<String> ts = redisson.getTimeSeries("myTimeSeries");
Completable rx = ts.add(201908110501, "10%");
Completable rx = ts.add(201908110502, "30%");
Completable rx = ts.add(201908110504, "10%");
Completable rx = ts.add(201908110508, "75%");
// entry time-to-live is 10 hours
Completable rx = ts.add(201908110510, "85%", 10, TimeUnit.HOURS);
Completable rx = ts.add(201908110510, "95%", 10, TimeUnit.HOURS);
Maybe<String> rx = ts.get(201908110508);
Single<Boolean> rx = ts.remove(201908110508);
Single<Collection<String>> rx = ts.pollFirst(2);
Single<Collection<String>> rx = ts.range(201908110501, 201908110508);
rx.doOnSuccess(res -> {
// ...
}).subscribe();This feature is available only in Redisson PRO edition.
Distributed Java implementation of Redis based Key Value store for JSON objects. This object is thread-safe. Allows to store JSON value mapped by key. Operations can be executed per key or group of keys. Value is stored/retrieved using JSON.* Redis commands. Both key and value are POJO objects.
Allows to define time to live parameter per entry. Doesn't use an entry eviction task, entries are cleaned on Redis side.
Implements Async, Reactive and RxJava3 interfaces.
Data write code example:
RJsonStore<String, MyObject> store = redisson.getJsonStore("test", StringCodec.INSTANCE, new JacksonCodec(MyObject.class));
MyObject t1 = new MyObject();
t1.setName("name1");
MyObject t2 = new MyObject();
t2.setName("name2");
Map<String, MyObject> entries = new HashMap<>();
entries.put("1", t1);
entries.put("2", t2);
// multiple entries at once
store.set(entries);
// or set entry per call
store.set("1", t1);
store.set("2", t2);
// with ttl
store.set("1", t1, Duration.ofSeconds(100));
// set if not set previously
store.setIfAbsent("1", t1);
// set if entry already exists
store.setIfExists("1", t1);Data read code example:
RJsonStore<String, MyObject> store = redisson.getJsonStore("test", StringCodec.INSTANCE, new JacksonCodec(MyObject.class));
// multiple entries at once
Map<String, MyObject> entries = store.get(Set.of("1", "2"));
// or read entry per call
MyObject value1 = store.get("1");
MyObject value2 = store.get("2");Data deletion code example:
RJsonStore<String, MyObject> store = redisson.getJsonStore("test", StringCodec.INSTANCE, new JacksonCodec(MyObject.class));
// multiple entries at once
long deleted = store.delete(Set.of("1", "2"));
// or delete entry per call
boolean status = store.delete("1");
boolean status = store.delete("2");For data searching index prefix should be defined in <object_name>: format. For example for object name "test" prefix is "test:".
Data search code example:
RSearch s = redisson.getSearch();
s.createIndex("idx", IndexOptions.defaults()
.on(IndexType.JSON)
.prefix(Arrays.asList("test:")),
FieldIndex.text("name"));
RJsonStore<String, MyObject> store = redisson.getJsonStore("test", StringCodec.INSTANCE, new JacksonCodec(MyObject.class));
MyObject t1 = new MyObject();
t1.setName("name1");
MyObject t2 = new MyObject();
t2.setName("name2");
Map<String, MyObject> entries = new HashMap<>();
entries.put("1", t1);
entries.put("2", t2);
store.set(entries);
// search
SearchResult r = s.search("idx", "*", QueryOptions.defaults()
.returnAttributes(new ReturnAttribute("name")));
// aggregation
AggregationResult ar = s.aggregate("idx", "*", AggregationOptions.defaults()
.withCursor().load("name"));Keys access code examples:
RJsonStore<String, MyObject> store = redisson.getJsonStore("test", StringCodec.INSTANCE, new JacksonCodec(MyObject.class));
// iterate keys
Set<String> keys = store.keySet();
// read all keys at once
Set<String> keys = store.readAllKeySet();Redisson provides JSON Store implementation with local cache.
local cache - so called near cache used to speed up read operations and avoid network roundtrips. It caches JSON Store entries on Redisson side and executes read operations up to 45x faster in comparison with regular implementation. Local cached instances with the same name are connected to the same pub/sub channel. This channel is used for exchanging of update/invalidate events between all instances. Local cache store doesn't use hashCode()/equals() methods of key object, instead it uses hash of serialized state. It's recommended to use each local cached instance as a singleton per unique name since it has own state for local cache.
It's recommended to use a single instance of RLocalCachedJsonStore instance per name for each Redisson client instance. Same LocalCachedJsonStoreOptions object should be used across all instances with the same name.
Follow options can be supplied during object creation:
LocalCachedJsonStoreOptions options = LocalCachedJsonStoreOptions.name("object_name_example")
// Defines codec used for key
.keyCodec(codec)
// Defines codec used for JSON value
.valueCodec(codec)
// 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 soft references, entries are removed by GC
// WEAK - Uses weak 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.
// 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 RLocalCachedJsonStore instances on map entry change
// UPDATE - Insert/update cache entry across all RLocalCachedJsonStore instances on map entry change
// NONE - No synchronizations on map changes
.syncStrategy(SyncStrategy.INVALIDATE)
// time to live for each entry in local cache
.timeToLive(Duration.ofSeconds(10))
// max idle time for each entry in local cache
.maxIdle(Duration.ofSeconds(10));
// Defines how to listen expired event sent by Redis upon this instance deletion
//
// Follow expiration policies are available:
// DONT_SUBSCRIBE - Don't subscribe on expire event
// SUBSCRIBE_WITH_KEYEVENT_PATTERN - Subscribe on expire event using __keyevent@*:expired pattern
// SUBSCRIBE_WITH_KEYSPACE_CHANNEL - Subscribe on expire event using __keyspace@N__:name channel
.expirationEventPolicy(ExpirationEventPolicy.SUBSCRIBE_WITH_KEYEVENT_PATTERN)Data write code example:
LocalCachedJsonStoreOptions ops = LocalCachedJsonStoreOptions.name("test")
.keyCodec(StringCodec.INSTANCE)
.valueCodec(new JacksonCodec<>(MyObject.class));
RLocalCachedJsonStore<String, MyObject> store = redisson.getLocalCachedJsonStore(ops);
MyObject t1 = new MyObject();
t1.setName("name1");
MyObject t2 = new MyObject();
t2.setName("name2");
Map<String, MyObject> entries = new HashMap<>();
entries.put("1", t1);
entries.put("2", t2);
Map<String, MyObject> entries = new HashMap<>();
entries.put("1", t1);
entries.put("2", t2);
// multiple entries at once
store.set(entries);
// or set entry per call
store.set("1", t1);
store.set("2", t2);
// with ttl
store.set("1", t1, Duration.ofSeconds(100));
// set if not set previously
store.setIfAbsent("1", t1);
// set if entry already exists
store.setIfExists("1", t1);Data read code example:
LocalCachedJsonStoreOptions ops = LocalCachedJsonStoreOptions.name("test")
.keyCodec(StringCodec.INSTANCE)
.valueCodec(new JacksonCodec<>(MyObject.class));
RLocalCachedJsonStore<String, MyObject> store = redisson.getLocalCachedJsonStore(ops);
// multiple entries at once
Map<String, MyObject> entries = store.get(Set.of("1", "2"));
// or read entry per call
MyObject value1 = store.get("1");
MyObject value2 = store.get("2");Data deletion code example:
LocalCachedJsonStoreOptions ops = LocalCachedJsonStoreOptions.name("test")
.keyCodec(StringCodec.INSTANCE)
.valueCodec(new JacksonCodec<>(MyObject.class));
RLocalCachedJsonStore<String, MyObject> store = redisson.getLocalCachedJsonStore(ops);
// multiple entries at once
long deleted = store.delete(Set.of("1", "2"));
// or delete entry per call
boolean status = store.delete("1");
boolean status = store.delete("2");For data searching index prefix should be defined in <object_name>: format. For example for object name "test" prefix is "test:".
Data search code example:
RSearch s = redisson.getSearch();
s.createIndex("idx", IndexOptions.defaults()
.on(IndexType.JSON)
.prefix(Arrays.asList("test:")),
FieldIndex.text("name"));
LocalCachedJsonStoreOptions ops = LocalCachedJsonStoreOptions.name("test")
.keyCodec(StringCodec.INSTANCE)
.valueCodec(new JacksonCodec<>(MyObject.class));
RLocalCachedJsonStore<String, MyObject> store = redisson.getLocalCachedJsonStore(ops);
MyObject t1 = new MyObject();
t1.setName("name1");
MyObject t2 = new MyObject();
t2.setName("name2");
Map<String, MyObject> entries = new HashMap<>();
entries.put("1", t1);
entries.put("2", t2);
store.set(entries);
// search
SearchResult r = s.search("idx", "*", QueryOptions.defaults()
.returnAttributes(new ReturnAttribute("name")));
// aggregation
AggregationResult ar = s.aggregate("idx", "*", AggregationOptions.defaults()
.withCursor().load("name"));Keys access code examples:
LocalCachedJsonStoreOptions ops = LocalCachedJsonStoreOptions.name("test")
.keyCodec(StringCodec.INSTANCE)
.valueCodec(new JacksonCodec<>(MyObject.class));
RLocalCachedJsonStore<String, MyObject> store = redisson.getLocalCachedJsonStore(ops);
// iterate keys
Set<String> keys = store.keySet();
// read all keys at once
Set<String> keys = store.readAllKeySet();