","x2","xmlns","y","y1","y2","z","zoomandpan"]),F=i(["accent","accentunder","align","bevelled","close","columnsalign","columnlines","columnspan","denomalign","depth","dir","display","displaystyle","encoding","fence","frame","height","href","id","largeop","length","linethickness","lspace","lquote","mathbackground","mathcolor","mathsize","mathvariant","maxsize","minsize","movablelimits","notation","numalign","open","rowalign","rowlines","rowspacing","rowspan","rspace","rquote","scriptlevel","scrip...

        // Create a larger set of documents
        final Map<String, Object> requestBody = new HashMap<>();
        final List<Map<String, Object>> documents = new ArrayList<>();

        for (int i = 100; i < 120; i++) {
            final Map<String, Object> doc = new HashMap<>();
            doc.put("title", NAME_PREFIX + "large_" + i);

        }
    }

    @Test
    public void test_execute_withVeryLargeBoost() {
        // Test executing BoostQuery with very large boost value
        Term term = new Term("field", "large");
        TermQuery termQuery = new TermQuery(term);
        BoostQuery boostQuery = new BoostQuery(termQuery, Float.MAX_VALUE);

        QueryContext context = new QueryContext("test", false);

        String result3 = aggregateLogJob.execute();
        assertEquals("", result3);
    }

    @Test
    public void test_execute_performanceWithLargeErrorMessage() {
        // Test with very large error message
        final StringBuilder largeMessage = new StringBuilder();
        for (int i = 0; i < 1000; i++) {
            largeMessage.append("Error detail ").append(i).append(" ");
        }

            assertEquals("ThreadLocal Kryo should work correctly", original, deserialized);
        }
    }

    /**
     * Test serialization with large data
     */
    @Test
    public void test_serializeDeserialize_largeData() {
        List<String> original = new ArrayList<>();
        for (int i = 0; i < 1000; i++) {
            original.add("Item number " + i);

        scoreUpdater.addScoreBooster(booster);

        String result = scoreUpdater.execute();
        assertTrue(result.contains("Runtime exception message"));
    }

    // Test large number of boosters
    @Test
    public void test_execute_manyBoosters() {
        for (int i = 0; i < 100; i++) {
            TestScoreBooster booster = new TestScoreBooster(i);

        RescorerBuilder<?> result = ltrQueryRescorer.evaluate(params);
        assertNotNull(result);
        assertEquals(10, ((QueryRescorerBuilder) result).windowSize().intValue());

        // Test with large window size
        ComponentUtil.setFessConfig(new FessConfig.SimpleImpl() {
            @Override
            public String getLtrModelName() {
                return testModelName;
            }

            }
        }
        return documentItems;
    }

    /**
     * Performs a scroll search for processing large result sets efficiently.
     *
     * This method uses OpenSearch scroll API to iterate through large numbers of
     * documents without loading them all into memory at once.
     *
     * @param params The search request parameters

        // Note: This is a rough check - exact performance depends on JVM, hardware, etc.
        // We expect Set lookup to be at least as fast as array lookup for large datasets
        assertTrue("Set-based lookup should be faster or comparable to array-based lookup for large datasets",
                setDuration <= arrayDuration * 2); // Allow 2x margin for test stability
    }

    /**
     * Helper method to create a test FessConfig.

            assertNotNull(results);
            assertEquals(0, results.size());
        }
    }

    /**
     * Test search with very large page size.
     */
    @Test
    public void test_searchWithLargePageSize() throws Exception {
        try (RankFusionProcessor processor = new RankFusionProcessor()) {