* If you didn't use FastAPI and used Starlette directly (or another tool, like Sanic, Flask, Responder, etc) you would have to implement all the data validation and serialization yourself. So, your final application would still have the same overhead as if it was built using FastAPI. And in many cases, this data validation and serialization...

            private static final long serialVersionUID = 1L;

            @Override
            public int getCrawlingThreadCount() {
                return 1; // Reduced from 2 to minimize thread overhead
            }

            @Override
            public String getIndexFieldConfigId() {
                return "config_id";
            }

            @Override

This is due to Java's use of reflection and the need to maintain a lot of metadata.

- **Size of Serialized Data:**
Java serialization tends to produce larger serialized objects because it includes class metadata and other overhead.

- **Flexibility and Control:**
Java serialization offers limited control over the serialization process, such as excluding certain fields, customizing naming conventions, and handling complex data structures more gracefully.

   * intended to be used as a metric: smaller headers are more efficient to encode and transmit.
   */
  fun byteCount(): Long {
    // Each header name has 2 bytes of overhead for ': ' and every header value has 2 bytes of
    // overhead for '\r\n'.
    var result = (namesAndValues.size * 2).toLong()

    for (i in 0 until namesAndValues.size) {
      result += namesAndValues[i].length.toLong()
    }

  /** Returns the original request that initiated this web socket. */
  fun request(): Request

  /**
   * Returns the size in bytes of all messages enqueued to be transmitted to the server. This
   * doesn't include framing overhead. If compression is enabled, uncompressed messages size
   * is used to calculate this value. It also doesn't include any bytes buffered by the operating

 * type is determined by the crawler data serializer configuration.
 * </p>
 * <p>
 * The class is thread-safe and uses ThreadLocal to maintain Kryo instances
 * per thread to avoid synchronization overhead.
 * </p>
 *
 */
public class DataSerializer {

    /** Logger for this class. */
    private static final Logger logger = LogManager.getLogger(DataSerializer.class);

 * form}), the memory requirement is 8*N bytes for the copy of the dataset plus an overhead which is
 * independent of N (but depends on the quantiles being computed). When calling {@link
 * ScaleAndIndex#computeInPlace computeInPlace} (in {@linkplain ScaleAndIndexes#computeInPlace
 * either form}), only the overhead is required. The number of object allocations is independent of
 * N in both cases.
 *

        byte[] decompressed = searchHelper.gzipDecompress(compressed);

        assertEquals(testData, new String(decompressed));
        // For small strings, gzip overhead might make compressed data larger
        // So we just verify that compression/decompression works correctly
        assertNotNull(compressed);
        assertTrue(compressed.length > 0);
    }

/**
 * A high-performance utility class for encrypting and decrypting data using cached {@link Cipher} instances.
 * <p>
 * This class provides efficient encryption/decryption by pooling and reusing cipher instances,
 * reducing the overhead of repeated cipher initialization. It supports both string-based keys
 * and {@link Key} objects, with configurable algorithms and character encodings.
 * </p>
 * <p>
 * <strong>Key Features:</strong>
 * </p>
 * <ul>

 *       allocating garbage).
 * </ul>
 *
 * <p>Disadvantages compared to {@code long[]}:
 *
 * <ul>
 *   <li>Memory footprint has a fixed overhead (about 24 bytes per instance).
 *   <li><i>Some</i> construction use cases force the data to be copied (though several construction
 *       APIs are offered that don't).