}

        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

![GitHub Release](https://img.shields.io/github/v/release/codelibs/fess)


## Overview

Fess is a very powerful and easily deployable Enterprise Search Server. You can quickly install and run Fess on any platform where you can run the Java Runtime Environment. Fess is provided under the [Apache License 2.0](LICENSE).

 *
 * <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>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.
 *

  /**
   * 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

 * 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