} else {
		bs.XferRateSml.addSize(sz, duration)
	}
}

// RMetricName - name of replication metric
type RMetricName string

const (
	// Large - objects larger than 128MiB
	Large RMetricName = "Large"
	// Small - objects smaller than 128MiB
	Small RMetricName = "Small"
	// Total - metric pertaining to totals
	Total RMetricName = "Total"
)

        }
    }

    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);
    }

    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(" ");
        }

* It uses a "spooled" file:
    * A file stored in memory up to a maximum size limit, and after passing this limit it will be stored in disk.
* This means that it will work well for large files like images, videos, large binaries, etc. without consuming all the memory.
* You can get metadata from the uploaded file.

		{"FFFFFFFFFFFFFFFF", 1<<64 - 1, ""},
		{"000000000000bogus", 0, "invalid byte in chunk length"},
		{"00000000000000000", 0, "http chunk length too large"}, // could accept if we wanted
		{"10000000000000000", 0, "http chunk length too large"},
		{"00000000000000001", 0, "http chunk length too large"}, // could accept if we wanted
	}
	for i := uint64(0); i <= 1234; i++ {
		tests = append(tests, testCase{in: fmt.Sprintf("%x", i), want: i})
	}

    int NT_STATUS_PENDING = 0x00000103;
    /** A notify change request is being completed and information is being returned */
    int NT_STATUS_NOTIFY_ENUM_DIR = 0x0000010C;
    /** The data was too large to fit into the specified buffer */
    int NT_STATUS_BUFFER_OVERFLOW = 0x80000005;
    /** The requested operation was unsuccessful */
    int NT_STATUS_UNSUCCESSFUL = 0xC0000001;

        axesSizeProduct[i] = Math.multiplyExact(axesSizeProduct[i + 1], axes.get(i).size());
      }
    } catch (ArithmeticException e) {
      throw new IllegalArgumentException(
          "Cartesian product too large; must have size at most Integer.MAX_VALUE");
    }
    this.axesSizeProduct = axesSizeProduct;
  }

  private int getAxisIndexForProductIndex(int index, int axis) {

        assertNotNull(deserialized.getData());
    }

    /**
     * Test transformer with large data
     */
    public void test_transformerWithLargeData() {
        TestTransformer transformer = new TestTransformer("largeDataTransformer");

        // Create large response data
        byte[] largeBody = new byte[10 * 1024 * 1024]; // 10MB
        for (int i = 0; i < largeBody.length; i++) {

  "durations" : [ {
    "testProject" : "excludeRuleMergingBuild",
    "linux" : 232
  } ]
}, {
  "scenario" : "org.gradle.performance.regression.corefeature.LargeDependencyGraphPerformanceTest.resolve large dependency graph (parallel = false, locking = true)",
  "durations" : [ {

        when(mockChannelManager.getHealthyChannels()).thenReturn(Arrays.asList(channel1, channel2));

        ChannelInfo selected = loadBalancer.selectChannel(largeRead);
        // Should prefer higher bandwidth channel for large transfers
        assertEquals(channel2, selected);
    }

    @Test
    void testAdaptiveStrategyMetadataOperation() throws Exception {
        loadBalancer.setStrategy(LoadBalancingStrategy.ADAPTIVE);