systemNetworkInternodeCollectorPath collectorPath = "/system/network/internode"
	systemDriveCollectorPath            collectorPath = "/system/drive"
	systemMemoryCollectorPath           collectorPath = "/system/memory"
	systemCPUCollectorPath              collectorPath = "/system/cpu"
	systemProcessCollectorPath          collectorPath = "/system/process"

	debugGoCollectorPath collectorPath = "/debug/go"

 *    Otherwise it would compress values in a way that servers could not decompress.
 *  * If `server_max_window_bits` is less than 15, OkHttp will waste memory on an oversized buffer.
 *
 * See [RFC 7692, 7.1][rfc_7692] for details on negotiation process.
 *
 * [rfc_7692]: https://tools.ietf.org/html/rfc7692#section-7.1
 */

## Caveat { #caveat }

If you need to perform heavy background computation and you don't necessarily need it to be run by the same process (for example, you don't need to share memory, variables, etc), you might benefit from using other bigger tools like <a href="https://docs.celeryq.dev" class="external-link" target="_blank">Celery</a>.

        try {
            // Force release the handle with null checks
            if (this.usageCount != null) {
                this.usageCount.set(0);
            }

            // Clear references to prevent memory leaks
            try {
                if (this.treeConnection != null) {
                    // Release the tree connection if possible
                    log.debug("Releasing tree connection during emergency cleanup");

import org.codelibs.fess.crawler.entity.AccessResultImpl;
import org.codelibs.fess.crawler.entity.UrlQueueImpl;

/**
 * The {@code MemoryDataHelper} class provides a helper for managing crawler data in memory.
 * It stores URL queues, access results, and URL patterns for inclusion and exclusion.
 * This class is designed to be used in a single-threaded environment or with external synchronization.
 *

 * traditional {@code LinkedHashMap} implementation which stores keys and count values as map
 * entries, {@code ObjectCountLinkedHashMap} minimizes object allocation and reduces memory
 * footprint.
 */
@GwtCompatible
@NullMarked
final class ObjectCountLinkedHashMap<K extends @Nullable Object> extends ObjectCountHashMap<K> {
  /** Creates an empty {@code ObjectCountLinkedHashMap} instance. */

  public
  static HashCode hash(File file, HashFunction hashFunction) throws IOException {
    return asByteSource(file).hash(hashFunction);
  }

  /**
   * Fully maps a file read-only in to memory as per {@link
   * FileChannel#map(java.nio.channels.FileChannel.MapMode, long, long)}.
   *
   * <p>Files are mapped from offset 0 to its length.
   *
   * <p>This only works for files ≤ {@link Integer#MAX_VALUE} bytes.

            this.decryptionKey = null;

            log.debug("Keys stored in SecureKeyManager for session: {}", sessionId);
        } else {
            // Fall back to traditional in-memory storage
            this.encryptionKey = encryptionKey.clone();
            this.decryptionKey = decryptionKey.clone();
        }
    }

    /**
     * Get the negotiated cipher identifier

```

/// tip

The app above is a minimal and simple example to demonstrate how to handle and broadcast messages to several WebSocket connections.

But keep in mind that, as everything is handled in memory, in a single list, it will only work while the process is running, and will only work with a single process.

     * <p>This method returns all duplicate host configurations in the system,
     * ordered by sort order, regular name, and duplicate hostname. The results
     * are limited by the configured maximum fetch size to prevent memory issues.</p>
     *
     * @return a list of all DuplicateHost entities
     */
    public List<DuplicateHost> getDuplicateHostList() {

        return duplicateHostBhv.selectList(cb -> {