n := int(b[i+directoryEndLen-2]) | int(b[i+directoryEndLen-1])<<8
			if n+directoryEndLen+i > len(b) {
				// Truncated comment.
				// Some parsers (such as Info-ZIP) ignore the truncated comment
				// rather than treating it as a hard error.
				return -1
			}
			return i
		}
	}
	return -1
}

type readBuf []byte

func (b *readBuf) uint8() uint8 {
	v := (*b)[0]
	*b = (*b)[1:]
	return v

- Fix a bug on the endpoints controller that does not reconcile the Endpoint object after this is truncated (it gets more than 1000 endpoints addresses) ([#127417](https://github.com/kubernetes/kubernetes/pull/127417), [@aojea](https://github.com/aojea)) [SIG Apps, Network and Testing]

105A..1099    ; valid                                  # 5.1  MYANMAR LETTER MON NGA..MYANMAR SHAN DIGIT NINE
109A..109D    ; valid                                  # 5.2  MYANMAR SIGN KHAMTI TONE-1..MYANMAR VOWEL SIGN AITON AI
109E..109F    ; valid                  ;      ; NV8    # 5.1  MYANMAR SYMBOL SHAN ONE..MYANMAR SYMBOL SHAN EXCLAMATION

              }
            });

    List<String> actual = newArrayList(result);
    List<String> expected = asList("1", "2", "null", "3");
    assertEquals(expected, actual);
  }

  // Far less exhaustive than the tests in IteratorsTest
  public void testCycle() {
    Iterable<String> cycle = Iterables.cycle("a", "b");

    int howManyChecked = 0;
    for (String string : cycle) {

你可以同時利用並行性和平行性，進一步提升效能，這比大多數已測試的 NodeJS 框架都更快，並且與 Go 語言相當，而 Go 是一種更接近 C 的編譯語言（[感謝 Starlette](https://www.techempower.com/benchmarks/#section=data-r17&hw=ph&test=query&l=zijmkf-1)）。

### 並行比平行更好嗎？ { #is-concurrency-better-than-parallelism }

不是的！這不是故事的本意。

並行與平行不同。並行在某些 **特定** 的需要大量等待的情境下表現更好。正因如此，並行在 Web 應用程式開發中通常比平行更有優勢。但並不是所有情境都如此。

因此，為了平衡報導，想像下面這個短故事

> 你需要打掃一間又大又髒的房子。

*是的，這就是全部的故事。*

---

你可以同时拥有并行性和异步性，你可以获得比大多数经过测试的 NodeJS 框架更高的性能，并且与 Go 不相上下， Go 是一种更接近于 C 的编译语言（[全部归功于 Starlette](https://www.techempower.com/benchmarks/#section=data-r17&hw=ph&test=query&l=zijmkf-1)）。

### 并发比并行好吗？ { #is-concurrency-better-than-parallelism }

不！这不是故事的本意。

并发不同于并行。而是在需要大量等待的特定场景下效果更好。因此，在 Web 应用程序开发中，它通常比并行要好得多，但这并不意味着全部。

因此，为了平衡这一点，想象一下下面的短篇故事：

> 你必须打扫一个又大又脏的房子。

*是的，这就是完整的故事。*

---

   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.
   *
   * This implementation uses a per-segment queue to record a memento of the additions, removals,

- Fix concurrent map access causing panics when logging timed-out API calls. (#106124, @marseel) [SIG API Machinery]
- Support more than 100 disk mounts on Windows (#105673, @andyzhangx) [SIG Storage and Windows]

## Dependencies

### Added
_Nothing has changed._

### Changed
- k8s.io/kube-openapi: d219536 → 83f114c

### Removed

   * This inserts a bunch of synthetic 250 ms delays into both client and server and confirms that
   * the same delays make it back into the events.
   *
   * We've had bugs where we report an event when we request data rather than when the data actually
   * arrives. https://github.com/square/okhttp/issues/5578
   */
  private fun timeToFirstByte() {
    val applicationInterceptorDelay = 250L
    val networkInterceptorDelay = 250L

  public void testExplicit_withDuplicates() {
    assertThrows(IllegalArgumentException.class, () -> Ordering.explicit(1, 2, 3, 4, 2));
  }

  // A more limited test than the one that follows, but this one uses the
  // actual public API.
  @J2ktIncompatible // Ordering.arbitrary
  public void testArbitrary_withoutCollisions() {
    List<Object> list = new ArrayList<>();