labels.crawling_info_DataCrawlExecTime=Crawl Execution Time (Data Store)
labels.crawling_info_DataCrawlStartTime=Crawl Start Time (Data Store)
labels.crawling_info_DataCrawlEndTime=Crawl End Time (Data Store)
labels.crawling_info_DataIndexExecTime=Indexing Execution Time (Data Store)
labels.crawling_info_DataIndexSize=Index Size (Data Store)
labels.webauth_configuration=Web Authentication
labels.webauth_list_hostname=Hostname

labels.crawling_info_DataCrawlExecTime=Crawl Execution Time (Data Store)
labels.crawling_info_DataCrawlStartTime=Crawl Start Time (Data Store)
labels.crawling_info_DataCrawlEndTime=Crawl End Time (Data Store)
labels.crawling_info_DataIndexExecTime=Indexing Execution Time (Data Store)
labels.crawling_info_DataIndexSize=Index Size (Data Store)
labels.webauth_configuration=Web Authentication
labels.webauth_list_hostname=Hostname

* `org.gradle.caching`
* `org.gradle.configuration-cache`

## Consequences

* Internal properties must start with `org.gradle.internal.`
* Properties of pre-incubation features must start with `org.gradle.experimental.`

}

// Debug start debug mode
func (db *DB) Debug() (tx *DB) {
	tx = db.getInstance()
	return tx.Session(&Session{
		Logger: db.Logger.LogMode(logger.Info),
	})
}

// Set store value with key into current db instance's context
func (db *DB) Set(key string, value interface{}) *DB {
	tx := db.getInstance()
	tx.Statement.Settings.Store(key, value)
	return tx
}

    }

    // Test overwriting existing data store
    @Test
    public void test_overwriteExistingDataStore() {
        TestDataStore dataStore1 = new TestDataStore("Store1");
        TestDataStore dataStore2 = new TestDataStore("Store2");

        dataStoreFactory.add("store", dataStore1);
        assertSame(dataStore1, dataStoreFactory.getDataStore("store"));

        dataStoreFactory.add("store", dataStore2);

The fast food store has 8 processors (cashiers/cooks). While the concurrent burgers store might have had only 2 (one cashier and one cook).

But still, the final experience is not the best. 😞

---

This would be the parallel equivalent story for burgers. 🍔

For a more "real life" example of this, imagine a bank.

 *         } catch (TimeoutException timeout) {
 *           // stopping timed out
 *         }
 *       }
 *     });
 *     manager.startAsync(); // start all the services asynchronously
 *   }
 * }
 * }
 *
 * <p>This class uses the ServiceManager's methods to start all of its services, to respond to
 * service failure and to ensure that when the JVM is shutting down all the services are stopped.
 *
 * @author Luke Sandberg

     *
     * @param id the ID of the scheduled job to start
     * @return JSON response with {@code jobLogId} (nullable) and status
     */
    // PUT /api/admin/scheduler/{id}/start
    @Execute(urlPattern = "{}/@word")
    public JsonResponse<ApiResult> put$start(final String id) {
        final String[] jobLogId = { null };

    long startTime = System.nanoTime();
    long ns = millis * 1000 * 1000;
    for (; ; ) {
      if (millis > 0L) {
        Thread.sleep(millis);
      } else {
        // too short to sleep
        Thread.yield();
      }
      long d = ns - (System.nanoTime() - startTime);
      if (d > 0L) {
        millis = d / (1000 * 1000);
      } else {
        break;
      }
    }

      result |= (input[offset + i] & 0xFFL) << (i * 8);
    }
    return result;
  }

  /**
   * Store 8 bytes into the provided array at the indicated offset, using the value provided.
   *
   * @param sink the output byte array
   * @param offset the offset into the array at which to start writing
   * @param value the value to write
   */
  static void store64(byte[] sink, int offset, long value) {