// we try hard to make them robust in practice.  We could additionally try to add in a system
    // load timeout multiplier.  Or we could try to use a CPU time bound instead of wall clock time
    // bound.  But these ideas are harder to implement.  We do not try to detect or handle a
    // user-specified -XX:+DisableExplicitGC.
    //
    // TODO(user): Consider using

    // we try hard to make them robust in practice.  We could additionally try to add in a system
    // load timeout multiplier.  Or we could try to use a CPU time bound instead of wall clock time
    // bound.  But these ideas are harder to implement.  We do not try to detect or handle a
    // user-specified -XX:+DisableExplicitGC.
    //
    // TODO(user): Consider using

     * by concurrently running mojo executions. To prevent race conditions, an aggregating execution will block
     * all other executions until finished.
     * We also lock on a given project to forbid a forked lifecycle to be executed concurrently with the project.
     * TODO: ideally, the builder should take care of the ordering in a smarter way

    valueRef.clear();
    assertNotSame(value, map.get(key, loader));
    assertEquals(1, loader.getCount());
    assertEquals(1, segment.count);
  }

  @AndroidIncompatible // Perhaps emulator clock does not update between the two get() calls?
  public void testComputeExpiredEntry() throws ExecutionException {
    CacheBuilder<Object, Object> builder =
        createCacheBuilder().expireAfterWrite(1, TimeUnit.NANOSECONDS);

    valueRef.clear();
    assertNotSame(value, map.get(key, loader));
    assertEquals(1, loader.getCount());
    assertEquals(1, segment.count);
  }

  @AndroidIncompatible // Perhaps emulator clock does not update between the two get() calls?
  public void testComputeExpiredEntry() throws ExecutionException {
    CacheBuilder<Object, Object> builder =
        createCacheBuilder().expireAfterWrite(1, TimeUnit.NANOSECONDS);

   * ListenableFuture} listeners, should take care not to do so while holding a lock. Additionally,
   * as a further line of defense, prefer not to perform any locking inside a task that will be run
   * under {@code directExecutor}: Not only might the wait for a lock be long, but if the running
   * thread was holding a lock, the listener may deadlock or break lock isolation.
   *
   * <p>This instance is equivalent to:
   *

   * needed.
   *
   * A single spinlock ("busy") is used for initializing and
   * resizing the table, as well as populating slots with new Cells.
   * There is no need for a blocking lock; when the lock is not
   * available, threads try other slots (or the base).  During these
   * retries, there is increased contention and reduced locality,
   * which is still better than alternatives.
   *

        } else if (SearchLogPager.LOG_TYPE_CLICK.equalsIgnoreCase(pager.logType)) {
            list = (EsPagingResultBean<?>) clickLogBhv.selectPage(cb -> {
                cb.paging(pager.getPageSize(), pager.getCurrentPageNumber());
                cb.query().addOrderBy_RequestedAt_Desc();
                createClickLogCondition(pager, cb);
            });
        } else if (SearchLogPager.LOG_TYPE_CLICK_COUNT.equalsIgnoreCase(pager.logType)) {

    //                                                                          ==========
    protected final String _tableDbName = "click_log";
    protected final String _tableDispName = "click_log";
    protected final String _tablePropertyName = "ClickLog";

    public String getTableDbName() {
        return _tableDbName;
    }

    @Override

   * 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
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.