val frame3 = peer.takeFrame()
    assertThat(frame3.type).isEqualTo(Http2.TYPE_RST_STREAM)
    assertThat(connection.readBytes.acknowledged).isEqualTo(0L)
    assertThat(connection.readBytes.total).isEqualTo(2048L)
  }

  @Test fun receiveGoAwayHttp2() {
    // Write the mocking script.
    peer.sendFrame().settings(Settings())
    peer.acceptFrame() // ACK
    peer.acceptFrame() // SYN_STREAM 3

        if (logger.isDebugEnabled()) {
            logger.debug("[updateMemberOf] Direct groups retrieved. Total groups: {}, Total roles: {}, Group IDs for parent lookup: {}",
                    groupList.size(), roleList.size(), groupIdsForParentLookup.size());
        }

        // Set initial groups

- **Custom Systems** - REST API for bulk document indexing

---

## Pre-Migration Planning

### 1. Assessment Phase

Before starting migration, assess your current system:

- **Document Count**: Total number of indexed documents
- **Index Size**: Storage requirements for search indices
- **Crawl Sources**: URLs, file shares, databases being indexed
- **Custom Configurations**: URL patterns, security rules, metadata fields

     *
     * @param params The search request parameters
     * @param cursor Function to process each document in the result set
     * @param userBean Optional user information for permission checking
     * @return Total number of documents processed
     */
    public long scrollSearch(final SearchRequestParams params, final BooleanFunction<Map<String, Object>> cursor,
            final OptionalThing<FessUserBean> userBean) {

Por ejemplo, si tu código carga un modelo de Machine Learning con **1 GB de tamaño**, cuando ejecutas un proceso con tu API, consumirá al menos 1 GB de RAM. Y si inicias **4 procesos** (4 workers), cada uno consumirá 1 GB de RAM. Así que, en total, tu API consumirá **4 GB de RAM**.

Y si tu servidor remoto o máquina virtual solo tiene 3 GB de RAM, intentar cargar más de 4 GB de RAM causará problemas. 🚨

        suggester.indexer().addElevateWord(elevateWord, true);
        suggester.refresh();

        // Minimal sleep to ensure timestamp separation (reduced from 2000ms to 100ms total)
        Thread.sleep(50);
        ZonedDateTime threshold = ZonedDateTime.now();
        Thread.sleep(50);

        // Index new data after threshold

   * absent, it will fall back to a heavyweight operation that will open a stream, read (or {@link
   * InputStream#skip(long) skip}, if possible) to the end of the stream and return the total number
   * of bytes that were read.
   *
   * <p>Note that for some sources that implement {@link #sizeIfKnown} to provide a more efficient

	}); result.Error != nil || result.RowsAffected != 6 {
		t.Errorf("Failed to batch find, got error %v, rows affected: %v", result.Error, result.RowsAffected)
	}

	if totalBatch != 6 {
		t.Errorf("incorrect total batch, expects: %v, got %v", 6, totalBatch)
	}

	var count int64
	DB.Model(&User{}).Where("name = ?", "find_in_batches_new").Count(&count)
	if count != 6 {

    OkHttp 2 uses the new `Request` class for this.

 *  **Dispatcher** is a new class that manages the queue of asynchronous calls. It
    implements limits on total in-flight calls and in-flight calls per host.

#### Implementation changes

 * Support Android `TrafficStats` socket tagging.
 * Drop authentication headers on redirect.
 * Added support for compressed data frames.

E se o seu servidor remoto ou máquina virtual tiver apenas 3 GB de RAM, tentar carregar mais de 4 GB de RAM causará problemas. 🚨