}

        try {
            dataIndexHelper.crawl("test-session-force-stop");
            assertTrue("Should exit quickly when force stopped", true);
        } catch (Exception e) {
            assertTrue("Force stop should handle exceptions quickly", true);
        }
    }

    public void test_crawl_with_short_intervals() {
        try {
            // Test with minimal interval

        assertTrue(end - start < 50); // Should return quickly

        // Test with rule that has no delay
        helper.addIntervalRule("01:30", "15:15", "*", 0);
        start = System.currentTimeMillis();
        helper.delayByRules();
        end = System.currentTimeMillis();
        assertTrue(end - start < 50); // Should return quickly

            assertNotNull(jobProcess2);
            // Since echo command completes quickly, processes might already be finished
            // So we just verify that processes were created without errors

            Set<String> sessionIds = processHelper.getRunningSessionIdSet();
            // Since echo commands complete quickly, we may not catch them running
            // Just verify no exceptions occurred

  /**
   * Returns the value corresponding to the specified row and column indices. The same value is
   * returned by {@code get(rowKeyList().get(rowIndex), columnKeyList().get(columnIndex))}, but this
   * method runs more quickly.
   *
   * @param rowIndex position of the row key in {@link #rowKeyList()}
   * @param columnIndex position of the row key in {@link #columnKeyList()}
   * @return the value with the specified row and column

 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *
 * <p>Because a {@code TreeBasedTable} has unique sorted values for a given row, both {@code

 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *
 * <p>Because a {@code TreeBasedTable} has unique sorted values for a given row, both {@code

   */
  public String join(Iterable<?> parts) {
    /*
     * If we can quickly determine how many elements there are likely to be, then we can use the
     * fastest possible implementation, which delegates to the array overload of String.join.
     *
     * In theory, we can quickly determine the size of any Collection. However, thanks to

                        site:

 * the configuration properties of the original map. During deserialization, if the original map had
 * used weak references, the entries are reconstructed as they were, but it's not unlikely they'll
 * be quickly garbage-collected before they are ever accessed.
 *
 * <p>{@code new MapMaker().weakKeys().makeMap()} is a recommended replacement for {@link

   *
   * <p>The expected (but not guaranteed) performance of the special implementation differs from
   * {@code getStackTrace} in one main way: The {@code lazyStackTrace} call itself returns quickly
   * by delaying the per-stack-frame work until each element is accessed. Roughly speaking:
   *
   * <ul>
   *   <li>{@code getStackTrace} takes {@code stackSize} time to return but then negligible time to