* nearly drop-in replacement. Note that it is not available for Android or GWT/J2CL and that it may
 * have <a href="https://github.com/ben-manes/caffeine/wiki/Guava">different (usually better)
 * behavior</a> when multiple threads attempt concurrent mutations. Its equivalent to {@code
 * CacheBuilder} is its <a

  /**
   * Cached value of #publicSuffixIndex(). Do not use directly.
   *
   * <p>Since this field isn't {@code volatile}, if an instance of this class is shared across
   * threads before it is initialized, then each thread is likely to compute their own copy of the
   * value.
   */
  @SuppressWarnings("Immutable")
  @LazyInit
  private int publicSuffixIndexCache = SUFFIX_NOT_INITIALIZED;

    return valueField;
  }

  /** Returns the head of the listener stack, using a volatile read. */
  final @Nullable Listener listeners() {
    return listenersField;
  }

  /** Releases all threads in the {@link #waitersField} list, and clears the list. */
  final void releaseWaiters() {
    Waiter head = gasWaiters(Waiter.TOMBSTONE);

            SECONDS,
            new ArrayBlockingQueue<Runnable>(1000));
    executorService.prestartAllCoreThreads();
    AtomicInteger integer = new AtomicInteger();
    // Execute a bunch of tasks to ensure that our threads are allocated and hot
    for (int i = 0; i < NUM_THREADS * 10; i++) {
      @SuppressWarnings("unused") // https://errorprone.info/bugpattern/FutureReturnValueIgnored
      Future<?> possiblyIgnoredError =

    //
    // TODO(user): Consider using
    // java/lang/management/OperatingSystemMXBean.html#getSystemLoadAverage()
    //
    // TODO(user): Consider scaling by number of mutator threads,
    // e.g. using Thread#activeCount()
    return max(10L, Runtime.getRuntime().totalMemory() / (32L * 1024L * 1024L));
  }

  /**

But before that, handling asynchronous code was quite more complex and difficult.

In previous versions of Python, you could have used threads or <a href="https://www.gevent.org/" class="external-link" target="_blank">Gevent</a>. But the code is way more complex to understand, debug, and think about.

                    assertNotNull(children);
                }
            });
            readThreads[i].start();
        }

        // Wait for all threads
        for (Thread thread : updateThreads) {
            thread.join(5000);
        }
        for (Thread thread : readThreads) {
            thread.join(5000);
        }

        // Verify final state

    client,
    suggester.settings(),
    "content-index",        // source index
    "document"             // document type
);

suggester.indexer()
    .indexFromDocument(reader, 2, 100)  // threads=2, batch=100
    .getResponse();
```

### Index from Query Logs

```java
import org.codelibs.fess.suggest.index.contents.querylog.QueryLog;

// Add suggestions from search query logs

 * <strong>Performance</strong>).
 *
 * <p><strong>Cycle Detection</strong>
 *
 * <p>Deadlocks can arise when locks are acquired in an order that forms a cycle. In a simple
 * example involving two locks and two threads, deadlock occurs when one thread acquires Lock A, and
 * then Lock B, while another thread acquires Lock B, and then Lock A:
 *
 * <pre>
 * Thread1: acquire(LockA) --X acquire(LockB)

Mas antes disso, controlar código assíncrono era bem mais complexo e difícil.

Nas versões anteriores do Python, você poderia utilizar threads ou <a href="https://www.gevent.org/" class="external-link" target="_blank">Gevent</a>. Mas o código é bem mais complexo de entender, debugar, e pensar sobre.