return entries, err
	}

	// Marker points to before the prefix, just ignore it.
	if o.Marker < o.Prefix {
		o.Marker = ""
	}

	// Marker is set validate pre-condition.
	if o.Marker != "" && o.Prefix != "" {
		// Marker not common with prefix is not implemented. Send an empty response
		if !HasPrefix(o.Marker, o.Prefix) {
			return entries, io.EOF
		}
	}

      Map<R, Map<C, V>> backingMap, Supplier<? extends Map<C, V>> factory) {
    checkArgument(backingMap.isEmpty());
    checkNotNull(factory);
    // TODO(jlevy): Wrap factory to validate that the supplied maps are empty?
    return new StandardTable<>(backingMap, factory);
  }

  /**
   * Returns a view of a table where each value is transformed by a function. All other properties

## Dépendances facultatives

Utilisées par Pydantic:

* <a href="https://github.com/JoshData/python-email-validator" target="_blank"><code>email-validator</code></a> - pour la validation des adresses email.

Utilisées par Starlette :

想了解更多訊息，可以參考 <a href="https://fastapi.tiangolo.com/benchmarks/" class="internal-link" target="_blank">測試結果</a>。

## 可選的依賴套件

用於 Pydantic：

- <a href="https://github.com/JoshData/python-email-validator" target="_blank"><code>email-validator</code></a> - 用於電子郵件驗證。
- <a href="https://docs.pydantic.dev/latest/usage/pydantic_settings/" target="_blank"><code>pydantic-settings</code></a> - 用於設定管理。

	if group == "" {
		return updatedAt, errInvalidArgument
	}

	cache := store.lock()
	defer store.unlock()

	// Validate that all members exist.
	for _, member := range members {
		u, ok := cache.iamUsersMap[member]
		if !ok {
			return updatedAt, errNoSuchUser
		}
		cr := u.Credentials

		return nil, err
	}
	return &req, nil
}

// validate a RestoreObjectRequest as per AWS S3 spec https://docs.aws.amazon.com/AmazonS3/latest/API/API_RestoreObject.html
func (r *RestoreObjectRequest) validate(ctx context.Context, objAPI ObjectLayer) error {
	if r.Type != SelectRestoreRequest && !r.SelectParameters.IsEmpty() {

* Deleting federation-push.sh ([#27400](https://github.com/kubernetes/kubernetes/pull/27400), [@nikhiljindal](https://github.com/nikhiljindal))
* Validate-cluster finishes shortly after at most ALLOWED_NOTREADY_NODE… ([#26778](https://github.com/kubernetes/kubernetes/pull/26778), [@gmarek](https://github.com/gmarek))

    e.g., setting the environment variable `TF_ENABLE_MKL_NATIVE_FORMAT` will
    not have any effect.

*   TensorFlow has been validated on Windows Subsystem for Linux 2 (aka WSL 2)
    for both GPUs and CPUs.

*   Due to security issues (see section below), all boosted trees code has been
    deprecated. Users should switch to

## **4. Run Sample Applications**

After installing Hive, Hadoop and Spark successfully, we can now proceed to run some sample applications to see if they are configured appropriately.  We can use Spark Pi and Spark WordCount programs to validate our Spark installation. We can also explore how to run Spark jobs from the command line and Spark shell.

### **4.1 Spark Pi**

func TestScanRune(t *testing.T) {
	for n, test := range scanTests {
		buf := strings.NewReader(test)
		s := NewScanner(buf)
		s.Split(ScanRunes)
		var i, runeCount int
		var expect rune
		// Use a string range loop to validate the sequence of runes.
		for i, expect = range test {
			if !s.Scan() {
				break
			}
			runeCount++
			got, _ := utf8.DecodeRune(s.Bytes())
			if got != expect {