The [Hasher] interface type defines the contract between values of a
particular type and future hash-based data structures such as hash

   * across different segments.
   *
   * The page replacement algorithm's data structures are kept casually consistent with the map. The
   * ordering of writes to a segment is sequentially consistent. An update to the map and recording
   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The

   * across different segments.
   *
   * The page replacement algorithm's data structures are kept casually consistent with the map. The
   * ordering of writes to a segment is sequentially consistent. An update to the map and recording
   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The

   * exceeded.
   *
   * The page replacement algorithm's data structures are kept casually consistent with the map. The
   * ordering of writes to a segment is sequentially consistent. An update to the map and recording
   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The

   * exceeded.
   *
   * The page replacement algorithm's data structures are kept casually consistent with the map. The
   * ordering of writes to a segment is sequentially consistent. An update to the map and recording
   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The

        TensorList operations.
    *   `tf.custom_gradient` can now be applied to functions that accept nested
        structures of `tensors` as inputs (instead of just a list of tensors).
        Note that Python structures such as tuples and lists now won't be
        treated as tensors, so if you still want them to be treated that way,
        you need to wrap them with `tf.convert_to_tensor`.

<p>
For an equation of the form <code>X ≡<sub>A</sub> Y</code>,
where <code>X</code> and <code>Y</code> are types involved
in an assignment (including parameter passing and return statements),
the top-level type structures may unify loosely but element types
must unify exactly, matching the rules for assignments.
</p>

<p>
For an equation of the form <code>P ≡<sub>C</sub> C</code>,

* ♻️ Refactor and simplify internal `analyze_param()` to structure data with dataclasses instead of tuple. PR [#12099](https://github.com/fastapi/fastapi/pull/12099) by [@tiangolo](https://github.com/tiangolo).
* ♻️ Refactor and simplify dependencies data structures with dataclasses. PR [#12098](https://github.com/fastapi/fastapi/pull/12098) by [@tiangolo](https://github.com/tiangolo).

import org.opensearch.index.query.QueryBuilders;

/**
 * Job for exporting indexed search documents to the filesystem.
 * Each document is exported as a single file with URL structure mapped to directory structure.
 */
public class IndexExportJob {

    private static final Logger logger = LogManager.getLogger(IndexExportJob.class);

    private static final int MAX_PATH_COMPONENT_LENGTH = 200;

import org.lastaflute.web.util.LaRequestUtil;
import org.lastaflute.web.validation.VaMessenger;

import jakarta.servlet.http.HttpServletRequest;

/**
 * This class represents the base response structure for API results.
 * It encapsulates the API response and provides methods to build different types of API responses.
 */
public class ApiResult {

    /**
     * The API response object.
     */