import java.util.HashMap;
import java.util.LinkedHashMap;
import java.util.Map;

/**
 * {@link HashMap} with an upper limit on the number of entries. When a new entry is added, the oldest entry is discarded using LRU if the limit is exceeded.
 *
 * @author koichik
 * @param <K> the key type
 * @param <V> the value type
 */
public class LruHashMap<K, V> extends LinkedHashMap<K, V> {

            .ticker(ticker)
            .build(loader);
    runRemovalScheduler(cache, removalListener, loader, ticker, KEY_PREFIX, EXPIRING_TIME);
  }

  public void testExpirationOrder_access() {
    // test lru within a single segment
    FakeTicker ticker = new FakeTicker();
    IdentityLoader<Integer> loader = identityLoader();
    LoadingCache<Integer, Integer> cache =
        CacheBuilder.newBuilder()

 */
public class LruHashSet<E> extends AbstractSet<E> implements Set<E>, java.io.Serializable {
    private static final long serialVersionUID = 1L;

    /**
     * The internal LRU hash map used to store elements.
     */
    private final LruHashMap<E, Object> map;

    // Dummy value to associate with an Object in the backing Map
    private static final Object PRESENT = new Object();

    /**

- **Collections** (`org.codelibs.core.collection`) - Enhanced collection utilities, array operations, and specialized map/set implementations including LRU caches and case-insensitive collections
- **I/O Operations** (`org.codelibs.core.io`) - File handling, resource management, stream utilities, and traversal utilities for efficient resource processing

### Creating the `Settings` only once with `lru_cache` { #creating-the-settings-only-once-with-lru-cache }

Reading a file from disk is normally a costly (slow) operation, so you probably want to do it only once and then reuse the same settings object, instead of reading it for each request.

But every time we do:

 * and field configuration handling during the document transformation process.
 */
public interface FessTransformer {

    /**
     * Synchronized LRU cache for storing parent URL encodings.
     * Maps session+parent URL keys to their corresponding character encodings.
     */
    Map<String, String> parentEncodingMap = Collections.synchronizedMap(new LruHashMap<>(1000));

        }).orElse(StringUtil.EMPTY_STRINGS);
    }

    /**
     * Retrieves or creates the result document IDs cache from the session.
     * The cache is implemented as an LRU map to limit memory usage.
     *
     * @param session the HTTP session
     * @return the result document IDs cache map
     */
    private Map<String, String[]> getResultDocIdsCache(final HttpSession session) {

	github.com/hashicorp/errwrap v1.1.0 // indirect
	github.com/hashicorp/go-multierror v1.1.1 // indirect
	github.com/hashicorp/go-uuid v1.0.3 // indirect
	github.com/hashicorp/golang-lru v1.0.2 // indirect
	github.com/jcmturner/aescts/v2 v2.0.0 // indirect
	github.com/jcmturner/dnsutils/v2 v2.0.0 // indirect
	github.com/jcmturner/gofork v1.7.6 // indirect
	github.com/jcmturner/gokrb5/v8 v8.4.4 // indirect

        // Verify caching behavior
        assertTrue(file.canCacheWrite());
    }
}
```

## 9. Performance Considerations

### 9.1 Memory Management
- Lease entries should be evicted based on LRU when max leases reached
- Implement periodic cleanup of expired leases

### 9.2 Thread Safety
- Use concurrent data structures for lease storage
- Minimize lock contention in hot paths
- Async handling of lease breaks

	NowFunc func() time.Time
	// DryRun generate sql without execute
	DryRun bool
	// PrepareStmt executes the given query in cached statement
	PrepareStmt bool
	// PrepareStmt cache support LRU expired,
	// default maxsize=int64 Max value and ttl=1h
	PrepareStmtMaxSize int
	PrepareStmtTTL     time.Duration

	// DisableAutomaticPing
	DisableAutomaticPing bool
	// DisableForeignKeyConstraintWhenMigrating