fun byteStream(): InputStream = source().inputStream()

  abstract fun source(): BufferedSource

  /**
   * Returns the response as a byte array.
   *
   * This method loads entire response body into memory. If the response body is very large this
   * may trigger an [OutOfMemoryError]. Prefer to stream the response body if this is a
   * possibility for your response.
   */

    }

    /**
     * Initializes the analyzer settings.
     * If the analyzer settings index does not exist, it creates it with default settings and mappings.
     * It also loads analyzer names and field analyzer mappings.
     */
    public synchronized void init() {
        try {
            final IndicesExistsResponse response =

     */
    protected volatile Map<String, Map<String, List<Tuple3<String, QueryBuilder, ScoreFunctionBuilder<?>>>>> keyMatchQueryMap =
            Collections.emptyMap();

    /**
     * Initializes the helper.
     * It loads KeyMatch settings from the database.
     */
    @PostConstruct
    public void init() {
        if (logger.isDebugEnabled()) {
            logger.debug("Initializing {}", this.getClass().getSimpleName());
        }

            """
        ),
    ] = None,
) -> HTMLResponse:
    """
    Generate and return the HTML  that loads Swagger UI for the interactive
    API docs (normally served at `/docs`).

    You would only call this function yourself if you needed to override some parts,

            throw new IORuntimeException(e);
        }
    }

    /**
     * Reads the contents of a file into a byte array and returns it.
     * <p>
     * <strong>Note:</strong> This method loads the entire file into memory.
     * For files larger than {@value #MAX_BUF_SIZE} bytes (10MB), an
     * {@link IORuntimeException} will be thrown to prevent OutOfMemoryError.
     * For large files, use streaming APIs instead.

	buckets     []string
}

// NewMetricsGroup creates a new MetricsGroup. To create a metrics group for
// metrics with a `bucket` dimension (label), use `NewBucketMetricsGroup`.
//
// The `loader` function loads metrics from the cache and the system.
func NewMetricsGroup(path collectorPath, descriptors []MetricDescriptor,
	loader MetricsLoaderFn,
) *MetricsGroup {
	mg := &MetricsGroup{
		CollectorPath: path,

func (b *BucketMetadata) SetCreatedAt(createdAt time.Time) {
	if b.Created.IsZero() {
		b.Created = UTCNow()
	}
	if !createdAt.IsZero() {
		b.Created = createdAt.UTC()
	}
}

// Load - loads the metadata of bucket by name from ObjectLayer api.
// If an error is returned the returned metadata will be default initialized.
func readBucketMetadata(ctx context.Context, api ObjectLayer, name string) (BucketMetadata, error) {

### Memory per Process { #memory-per-process }

Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.

        // Default constructor - initialization is done in init() method
    }

    /**
     * Initializes the rank fusion processor after construction.
     * Sets up the window size based on configuration and loads available searchers.
     * This method is called automatically after the bean is constructed.
     */
    @PostConstruct
    public void init() {
        final FessConfig fessConfig = ComponentUtil.getFessConfig();

  public void testGetChecked_classUnloading() throws Exception {
    WeakReference<?> classUsedByGetChecked = doTestClassUnloading();
    GcFinalization.awaitClear(classUsedByGetChecked);
  }

  /**
   * Loads {@link WillBeUnloadedException} in a separate {@code ClassLoader}, calls {@code
   * getChecked(future, WillBeUnloadedException.class)}, and returns the loader. The caller can then