* java.util.LinkedHashSet}. Generally speaking, this class reduces object allocation and memory
 * consumption at the price of moderately increased constant factors of CPU. Only use this class
 * when there is a specific reason to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 */
@GwtIncompatible // not worth using in GWT for now

- **Caching** - Bean descriptors and reflection metadata are cached for improved performance
- **Lazy initialization** - Resources and expensive operations are initialized only when needed  
- **Memory efficient** - Specialized collections like `LruHashMap` and `ArrayMap` for memory-conscious applications
- **Java 21 features** - Switch expressions and pattern matching for reduced overhead

## 🧪 Building and Testing

### Development Setup
```bash

set FESS_MIN_MEM=%FESS_HEAP_SIZE%
set FESS_MAX_MEM=%FESS_HEAP_SIZE%
)

REM min and max heap sizes should be set to the same value to avoid
REM stop-the-world GC pauses during resize, and so that we can lock the
REM heap in memory on startup to prevent any of it from being swapped
REM out.
set FESS_JAVA_OPTS=%FESS_JAVA_OPTS% -Xms%FESS_MIN_MEM% -Xmx%FESS_MAX_MEM%
set FESS_JAVA_OPTS=%FESS_JAVA_OPTS% -XX:MaxMetaspaceSize=256m -XX:CompressedClassSpaceSize=32m

        byte[] data = "Hello, World!".getBytes();
        ContentCache cache = new ContentCache(data);

        // Memory-based cache close should not throw exception
        cache.close();

        // Should still be able to get input stream after close for memory cache
        try (InputStream stream = cache.getInputStream()) {
            assertNotNull(stream);
        }
    }

    @Test

 *
 * Features:
 * - Secure key storage with optional KeyStore integration
 * - Automatic key cleanup on close
 * - Thread-safe key management
 * - Key derivation utilities
 * - Memory wiping capabilities
 */
public class SecureKeyManager implements AutoCloseable {

    private static final Logger log = LoggerFactory.getLogger(SecureKeyManager.class);

- Reduced server startup time. For IAM encryption with the root credentials, MinIO had
   to use a memory-hard function (Argon2) that (on purpose) consumes a lot of memory and CPU.
   The new KMS-based approach can use a key derivation function that is orders of magnitudes
   cheaper w.r.t. memory and CPU.
- Root credentials can now be changed easily. Before, a two-step process was required to

* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

## Memory { #memory }

If you run **a single process per container** you will have a more or less well-defined, stable, and limited amount of memory consumed by each of those containers (more than one if they are replicated).

    }

    /**
     * Returns a {@link ByteBuffer} that maps the file channel to memory.
     *
     * @param channel
     *            The file channel. Must not be {@literal null}.
     * @param mode
     *            The mode. Must not be {@literal null}.
     * @return A {@link ByteBuffer} that maps the file channel to memory.
     */
    public static ByteBuffer map(final FileChannel channel, final MapMode mode) {

* 403: `status.HTTP_403_FORBIDDEN`
* etc.

It can be convenient to quickly access HTTP (and WebSocket) status codes in your app, using autocompletion for the name without having to remember the integer status codes by memory.

Read more about it in the [FastAPI docs about Response Status Code](https://fastapi.tiangolo.com/tutorial/response-status-code/).

## Example

```python
from fastapi import FastAPI, status

app = FastAPI()

FESS_LOG_PATH=${packaging.fess.log.dir}
FESS_CONF_PATH=${packaging.fess.conf.dir}
FESS_VAR_PATH=${packaging.fess.var.dir}

FESS_DICTIONARY_PATH=/var/lib/opensearch/config/

# Port
FESS_PORT=8080

# Heap Memory
FESS_HEAP_SIZE=512m

# Elasticsearch Path
SEARCH_ENGINE_HOME=/usr/share/opensearch/

# Elasticsearch URL