// Timed Get
  // There are a few design constraints to consider
  // * We want to be responsive to small timeouts, unpark() has non trivial latency overheads (I
  //   have observed 12 micros on 64-bit linux systems to wake up a parked thread). So if the
  //   timeout is small we shouldn't park(). This needs to be traded off with the cpu overhead of
  //   spinning, so we use SPIN_THRESHOLD_NANOS which is what AbstractQueuedSynchronizer uses for

import jakarta.servlet.ServletContext;

/**
 * CrawlJob is responsible for executing the crawling process in Fess.
 * This job launches a separate crawler process that can crawl web sites, file systems,
 * and data sources based on the configured crawling settings.
 *
 * <p>The job supports selective crawling by specifying configuration IDs for different

* **Uvicorn** with `--workers`
    * One Uvicorn **process manager** would listen on the **IP** and **port**, and it would start **multiple Uvicorn worker processes**.
* **Kubernetes** and other distributed **container systems**
    * Something in the **Kubernetes** layer would listen on the **IP** and **port**. The replication would be by having **multiple containers**, each with **one Uvicorn process** running.
* **Cloud services** that handle this for you

  // Timed Get
  // There are a few design constraints to consider
  // * We want to be responsive to small timeouts, unpark() has non trivial latency overheads (I
  //   have observed 12 micros on 64-bit linux systems to wake up a parked thread). So if the
  //   timeout is small we shouldn't park(). This needs to be traded off with the cpu overhead of
  //   spinning, so we use SPIN_THRESHOLD_NANOS which is what AbstractQueuedSynchronizer uses for

            assertEquals(21474836480L, fileFsSizeInfo.getFree()); // 20GB
        }

        @Test
        @DisplayName("Should handle large file systems")
        void shouldHandleLargeFileSystems() throws SMBProtocolDecodingException {
            // Given - 10TB file system with 4KB clusters
            long totalClusters = 2684354560L; // 10TB / 4KB

            // that the temporary file is in the same file system as the destination because the
            // File.renameTo operation doesn't really work across file systems.
            // So we will attempt to do a File.renameTo for efficiency and atomicity, if this fails
            // then we will use a brute force copy and delete the temporary file.
            if (!temp.renameTo(destination)) {

 * - Scroll search for large result sets
 * - Document retrieval by ID
 * - Bulk document updates
 * - Search parameter serialization/deserialization for cookies
 * - Integration with search engines and logging systems
 */
public class SearchHelper {

    // ===================================================================================
    //                                                                            Constant

            assertEquals(21474836480L, fileFsFullSizeInfo.getFree()); // 20GB
        }

        @Test
        @DisplayName("Should handle large file systems")
        void shouldHandleLargeFileSystems() throws SMBProtocolDecodingException {
            // Given - 10TB file system with 4KB clusters
            long totalClusters = 2684354560L; // 10TB / 4KB

* Converteer automatisch van en naar JSON.
* Documenteer alles met OpenAPI, dat gebruikt kan worden door:
    * Interactieve documentatiesystemen.
    * Automatische client code generatie systemen, voor vele talen.
* Biedt 2 interactieve documentatie-webinterfaces aan.

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Dit was nog maar een snel overzicht, maar je zou nu toch al een idee moeten hebben over hoe het allemaal werkt.

Mais vous pouvez aussi profiter du parallélisme et multiprocessing afin de gérer des charges **CPU bound** qui sont récurrentes dans les systèmes de *Machine Learning*.