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Population
Caffeine provides four types of population strategies: manual, loading synchronously, and asynchronous variants.
Cache<Key, Graph> cache = Caffeine.newBuilder()
.expireAfterWrite(10, TimeUnit.MINUTES)
.maximumSize(10_000)
.build();
// Lookup an entry, or null if not found
Graph graph = cache.getIfPresent(key);
// Lookup and compute an entry if absent, or null if not computable
graph = cache.get(key, k -> createExpensiveGraph(key));
// Insert or update an entry
cache.put(key, graph);
// Remove an entry
cache.invalidate(key);
The Cache
interface allows for explicit control of retrieving, updating, and invalidating entries.
Prefer using cache.get(key, k -> value)
to atomically compute and insert the value into the cache if absent, or else return the existing value. A cache.put(key, value)
may be used to directly insert or update an entry, overwriting any previous value in the cache for the specified key. Note that a cache.get
may return null
if the entry was not computable or throw an exception if the computation failed.
Changes can also be made to the cache using any of the ConcurrentMap methods exposed by the Cache.asMap()
view.
LoadingCache<Key, Graph> cache = Caffeine.newBuilder()
.maximumSize(10_000)
.expireAfterWrite(10, TimeUnit.MINUTES)
.build(key -> createExpensiveGraph(key));
// Lookup and compute an entry if absent, or null if not computable
Graph graph = cache.get(key);
// Lookup and compute entries that are absent
Map<Key, Graph> graphs = cache.getAll(keys);
A LoadingCache
is a Cache
built with an attached CacheLoader
.
Bulk lookups can be performed with the method getAll
. By default, getAll
will issue a separate call to CacheLoader.load
for each key which is absent from the cache. When bulk retrieval is more efficient than many individual lookups, you can override CacheLoader.loadAll
to exploit this.
Note that you can write a CacheLoader.loadAll
implementation that loads values for keys that were not specifically requested. For example, if computing the value of any key from some group gives you the value for all keys in the group, loadAll
might load the rest of the group at the same time.
AsyncCache<Key, Graph> cache = Caffeine.newBuilder()
.expireAfterWrite(10, TimeUnit.MINUTES)
.maximumSize(10_000)
.buildAsync();
// Lookup an entry, or null if not found
CompletableFuture<Graph> graph = cache.getIfPresent(key);
// Lookup and asynchronously compute an entry if absent
graph = cache.get(key, k -> createExpensiveGraph(key));
// Insert or update an entry
cache.put(key, graph);
// Remove an entry
cache.synchronous().invalidate(key);
A AsyncCache
is a Cache
variant that computes entries on an Executor and returns a CompletableFuture. This allows utilizing caches with the popular reactive programming model.
The synchronous()
view provides a Cache
that blocks until the asynchronous computation completes.
Changes can also be made to the cache using any of the ConcurrentMap methods exposed by the AsyncCache.asMap()
view.
The default executor is ForkJoinPool.commonPool() and can be overridden via Caffeine.executor(Executor)
.
AsyncLoadingCache<Key, Graph> cache = Caffeine.newBuilder()
.maximumSize(10_000)
.expireAfterWrite(10, TimeUnit.MINUTES)
// Either: Build with a synchronous computation that is wrapped as asynchronous
.buildAsync(key -> createExpensiveGraph(key));
// Or: Build with a asynchronous computation that returns a future
.buildAsync((key, executor) -> createExpensiveGraphAsync(key, executor));
// Lookup and asynchronously compute an entry if absent
CompletableFuture<Graph> graph = cache.get(key);
// Lookup and asynchronously compute entries that are absent
CompletableFuture<Map<Key, Graph>> graphs = cache.getAll(keys);
A AsyncLoadingCache
is a AsyncCache
built with an attached AsyncCacheLoader
.
A CacheLoader
should be supplied when the computation is best expressed in a synchronous fashion. Alternatively, a AsyncCacheLoader
should be supplied when the computation is expressed asynchronously and returns a CompletableFuture.
Bulk lookups can be performed with the method getAll
. By default, getAll
will issue a separate call to AsyncCacheLoader.asyncLoad
for each key which is absent from the cache. When bulk retrieval is more efficient than many individual lookups, you can override AsyncCacheLoader.asyncLoadAll
to exploit this.
Note that you can write a AsyncCacheLoader.asyncLoadAll
implementation that loads values for keys that were not specifically requested. For example, if computing the value of any key from some group gives you the value for all keys in the group, asyncLoadAll
might load the rest of the group at the same time.