import org.lastaflute.core.message.UserMessages;
import org.opensearch.index.query.QueryBuilder;

/**
 * Query command implementation for handling Boost queries.
 * Processes Lucene BoostQuery objects and applies boost factors.
 */
public class BoostQueryCommand extends QueryCommand {
    /**
     * Default constructor for BoostQueryCommand.
     */
    public BoostQueryCommand() {
        super();
    }

 * <p>This class should not be assumed to be universally superior to {@code
 * java.util.LinkedHashMap}. Generally speaking, this class reduces object allocation and memory
 * consumption at the price of moderately increased constant factors of CPU. Only use this class
 * when there is a specific reason to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 */
@J2ktIncompatible // no support for access-order mode in LinkedHashMap delegate

 * <p>This class should not be assumed to be universally superior to {@code
 * java.util.LinkedHashSet}. Generally speaking, this class reduces object allocation and memory
 * consumption at the price of moderately increased constant factors of CPU. Only use this class
 * when there is a specific reason to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 */
@GwtIncompatible // not worth using in GWT for now

 * <p>This class should not be assumed to be universally superior to {@code
 * java.util.LinkedHashSet}. Generally speaking, this class reduces object allocation and memory
 * consumption at the price of moderately increased constant factors of CPU. Only use this class
 * when there is a specific reason to prioritize memory over CPU.
 *
 * @author Louis Wasserman
 */
@GwtIncompatible // not worth using in GWT for now

- *If total drives has many common divisors the algorithm chooses the minimum amounts of erasure sets possible for a erasure set size of any N*.  In the example with 1024 drives - 4, 8, 16 are GCD factors. With 16 drives we get a total of 64 possible sets, with 8 drives we get a total of 128 possible sets, with 4 drives we get a total of 256 possible sets. So algorithm automatically chooses 64 sets, which is *16* 64 = 1024* drives in total.

    }
  }

  public void testDaemon_false() {
    ThreadFactory factory = builder.setDaemon(false).build();
    Thread thread = factory.newThread(monitoredRunnable);
    assertFalse(thread.isDaemon());
  }

  public void testDaemon_true() {
    ThreadFactory factory = builder.setDaemon(true).build();
    Thread thread = factory.newThread(monitoredRunnable);

    }
  }

  public void testDaemon_false() {
    ThreadFactory factory = builder.setDaemon(false).build();
    Thread thread = factory.newThread(monitoredRunnable);
    assertFalse(thread.isDaemon());
  }

  public void testDaemon_true() {
    ThreadFactory factory = builder.setDaemon(true).build();
    Thread thread = factory.newThread(monitoredRunnable);

    /** List of registered crawler client factories */
    protected List<CrawlerClientFactory> clientFactoryList = new LinkedList<>();

    /**
     * The maximum size of the client factory list.
     */
    protected int maxClientFactorySize = 10000;

    /**
     * Registers a CrawlerClientFactory with this creator.
     * All existing client mappings will be loaded into the new factory.

Veamos todo esto con un ejemplo.

Imagina que desarrollas una aplicación que permite crear facturas.

Estas facturas tendrán un `id`, `title` (opcional), `customer` y `total`.

El usuario de tu API (un desarrollador externo) creará una factura en tu API con un request POST.

Luego tu API (imaginemos):

* Enviará la factura a algún cliente del desarrollador externo.
* Recogerá el dinero.

     *
     * @param factory
     *            {@link SchemaFactory}. Must not be {@literal null}.
     * @param schema
     *            Schema file. Must not be {@literal null}.
     * @return {@link Schema}
     */
    public static Schema newSchema(final SchemaFactory factory, final File schema) {
        assertArgumentNotNull("factory", factory);
        assertArgumentNotNull("schema", schema);