}
    String string = sb.toString();
    sb.setLength(0);
    data = ByteSource.wrap(string.getBytes(charset));
  }

  @Benchmark
  public int timeCopy(int reps) throws IOException {
    int r = 0;
    Charset localCharset = charset;
    ByteSource localData = data;
    ReadStrategy localStrategy = strategy;
    for (int i = 0; i < reps; i++) {

/**
 * An {@link OutputStream} that maintains a hash of the data written to it.
 *
 * @author Zoe Piepmeier
 * @since 16.0
 */
@Beta
public final class HashingOutputStream extends FilterOutputStream {
  private final Hasher hasher;

  /**
   * Creates an output stream that hashes using the given {@link HashFunction}, and forwards all
   * data written to it to the underlying {@link OutputStream}.
   *

Declare the **query parameters** that you need in a **Pydantic model**, and then declare the parameter as `Query`:

{* ../../docs_src/query_param_models/tutorial001_an_py310.py hl[9:13,17] *}

**FastAPI** will **extract** the data for **each field** from the **query parameters** in the request and give you the Pydantic model you defined.

## Check the Docs { #check-the-docs }

You can see the query parameters in the docs UI at `/docs`:

        if (Character.isDigit(this.calledName.charAt(0))) {
            int i, len, dots;
            char[] data;

            i = dots = 0; /* quick IP address validation */
            len = this.calledName.length();
            data = this.calledName.toCharArray();
            while (i < len && Character.isDigit(data[i++])) {
                if (i == len && dots == 3) {
                    // probably an IP address

     */
    @Override
    public Logger getLogger() {
        return logger;
    }

    /**
     * Gets the appropriate extractor for the given response data.
     * Selects an extractor based on the MIME type of the file.
     *
     * @param responseData the response data containing the file to extract
     * @return the extractor instance for processing the file
     * @throws FessSystemException if no suitable extractor factory can be found

 * underlying (implementation specific) data structures to be shared.
 *
 * <p>The size of the data structure used by ArrayBasedCharEscaper and ArrayBasedUnicodeEscaper is
 * proportional to the highest valued character that has a replacement. For example a replacement
 * map containing the single character '{@literal \}u1000' will require approximately 16K of memory.

            return null;
        })).status(Status.OK).result());
    }

    /**
     * Creates a new related query setting.
     *
     * @param body the related query configuration data to create
     * @return JSON response containing the created related query ID and status
     */
    // POST /api/admin/relatedquery/setting
    @Execute

   *
   * <p>You may also consider the equivalent {@code
   * MultimapBuilder.hashKeys().arrayListValues().build()}, which provides more control over the
   * underlying data structure.
   */
  public static <K extends @Nullable Object, V extends @Nullable Object>
      ArrayListMultimap<K, V> create() {
    return new ArrayListMultimap<>();
  }

  /**

     * @param fileId
     *            the file ID to read from
     * @param outputBuffer
     *            the buffer to read data into
     * @param outputBufferOffset
     *            the offset in the output buffer to start writing data
     */
    public Smb2ReadRequest(final Configuration config, final byte[] fileId, final byte[] outputBuffer, final int outputBufferOffset) {

When using Veeam Backup and Replication, you can use S3 compatible object storage such as MinIO as a capacity tier for backups.  This disaggregates storage for the Veeam infrastructure and allows you to retain control of your data. With the ease of use of setup and administration of MinIO, it allows a Veeam backup admin to easily deploy their own object store for capacity tiering.

## Prerequisites