volatile @Nullable Waiter waitersField;

  /** Non-volatile write of the thread to the {@link Waiter#thread} field. */
  private static void putThread(Waiter waiter, Thread newValue) {
    ATOMIC_HELPER.putThread(waiter, newValue);
  }

  /** Non-volatile write of the waiter to the {@link Waiter#next} field. */
  private static void putNext(Waiter waiter, @Nullable Waiter newValue) {

   * equivalently, if this inverse view contains a key that is equal to {@code value}).
   *
   * <p>Due to the property that values in a BiMap are unique, this will tend to execute in
   * faster-than-linear time.
   *
   * @param value the object to search for in the values of this BiMap
   * @return true if a mapping exists from a key to the specified value
   */
  @Override

All of the cashiers doing all the work with one client after the other 👨‍💼⏯.

And you have to wait 🕙 in the line for a long time or you lose your turn.

You probably wouldn't want to take your crush 😍 with you to run errands at the bank 🏦.

### Burger Conclusion { #burger-conclusion }

 * iterators that don't support {@code remove()}. Otherwise, all optional operations are supported.
 * Null row keys, columns keys, and values are not supported.
 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs

    long singleChannelTime = measureReadTime(file, false);
    
    // Measure multi-channel throughput
    long multiChannelTime = measureReadTime(file, true);
    
    // Multi-channel should be faster
    assertTrue(multiChannelTime < singleChannelTime * 0.7);  // At least 30% improvement
}
```

## 8. Performance Metrics

### 8.1 Channel Statistics
```java

		return metaCacheEntriesSorted{o: m}
	}
	sort.Slice(m, m.less)
	return metaCacheEntriesSorted{o: m}
}

// isSorted returns whether the objects are sorted.
// This is usually orders of magnitude faster than actually sorting.
func (m metaCacheEntries) isSorted() bool {
	return sort.SliceIsSorted(m, m.less)
}

// shallowClone will create a shallow clone of the array objects,

 *  **Okio dependency added.** OkHttp now depends on
    [Okio](https://github.com/square/okio), an I/O library that makes it easier
    to access, store and process data. Using this library internally makes OkHttp
    faster while consuming less memory. You can write a `RequestBody` as an Okio
    `BufferedSink` and a `ResponseBody` as an Okio `BufferedSource`. Standard

    calls and that can receive data faster than they can process it. Previously, OkHttp limited
    HTTP/2 to 16 MiB of unacknowledged data per connection. With this fix there is a limit of 16 MiB
    of unacknowledged data per stream and no per-connection limit.

 *  Fix: Don't operate on a connection after it's been returned to the pool. This race occurred
    on failed web socket connection attempts.

## Version 5.0.0-alpha.4

_2022-02-01_

**This release introduces fast fallback to better support mixed IPv4+IPv6 networks.** Fast fallback
is what we're calling our implementation of Happy Eyeballs, [RFC 8305][rfc_8305]. With this
feature OkHttp will attempt both IPv6 and IPv4 connections concurrently, keeping whichever connects
first. Fast fallback gives IPv6 connections a 250 ms head start so IPv6 is preferred on networks

	beforeDrives := formatsToDrivesInfo(s.endpoints.Endpoints, formats, sErrs)

	res.After.Drives = make([]madmin.HealDriveInfo, len(beforeDrives))
	res.Before.Drives = make([]madmin.HealDriveInfo, len(beforeDrives))
	// Copy "after" drive state too from before.
	for k, v := range beforeDrives {
		res.Before.Drives[k] = v
		res.After.Drives[k] = v
	}

	if countErrs(sErrs, errUnformattedDisk) == 0 {