public void testSum() {
    assertThat(emptyAccumulator.sum()).isWithin(0.0).of(0.0);
    assertThat(emptyAccumulatorByAddAllEmptyIterable.sum()).isWithin(0.0).of(0.0);
    assertThat(emptyAccumulatorByAddAllEmptyStats.sum()).isWithin(0.0).of(0.0);
    assertThat(oneValueAccumulator.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);
    assertThat(oneValueAccumulatorByAddAllEmptyStats.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);

  }

  public void testSum() {
    assertThat(EMPTY_STATS_VARARGS.sum()).isEqualTo(0.0);
    assertThat(EMPTY_STATS_ITERABLE.sum()).isEqualTo(0.0);
    assertThat(ONE_VALUE_STATS.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);
    assertThat(TWO_VALUES_STATS.sum()).isWithin(ALLOWED_ERROR).of(TWO_VALUES_MEAN * 2);
    assertThat(MANY_VALUES_STATS_VARARGS.sum())
        .isWithin(ALLOWED_ERROR)

  public void testSum() {
    assertThat(emptyAccumulator.sum()).isWithin(0.0).of(0.0);
    assertThat(emptyAccumulatorByAddAllEmptyIterable.sum()).isWithin(0.0).of(0.0);
    assertThat(emptyAccumulatorByAddAllEmptyStats.sum()).isWithin(0.0).of(0.0);
    assertThat(oneValueAccumulator.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);
    assertThat(oneValueAccumulatorByAddAllEmptyStats.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);

				return 0, SizeTooLarge{Want: r.expectedMax, Got: r.bytesRead}
			}
		}

		if r.sha256 != nil {
			if sum := r.sha256.Sum(nil); !bytes.Equal(r.contentSHA256, sum) {
				return n, SHA256Mismatch{
					ExpectedSHA256:   hex.EncodeToString(r.contentSHA256),
					CalculatedSHA256: hex.EncodeToString(sum),
				}
			}
		}
		if r.contentHasher != nil {
			if r.contentHash.Type.Trailing() {
				var err error

  }

  public void testSum() {
    assertThat(EMPTY_STATS_VARARGS.sum()).isEqualTo(0.0);
    assertThat(EMPTY_STATS_ITERABLE.sum()).isEqualTo(0.0);
    assertThat(ONE_VALUE_STATS.sum()).isWithin(ALLOWED_ERROR).of(ONE_VALUE);
    assertThat(TWO_VALUES_STATS.sum()).isWithin(ALLOWED_ERROR).of(TWO_VALUES_MEAN * 2);
    assertThat(MANY_VALUES_STATS_VARARGS.sum())
        .isWithin(ALLOWED_ERROR)

      }
    }
  }

  /**
   * Returns the sum of all values in this map.
   *
   * <p>This method is not atomic: the sum may or may not include other concurrent operations.
   */
  public long sum() {
    long sum = 0L;
    for (AtomicLong value : map.values()) {
      sum = sum + value.get();
    }
    return sum;
  }

  @LazyInit @CheckForNull private transient Map<K, Long> asMap;

        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    assertThat(twoValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    assertThat(manyValuesAccumulator.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);

        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    assertThat(twoValuesAccumulatorByAddAllPartitionedPairedStats.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    assertThat(manyValuesAccumulator.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / MANY_VALUES_COUNT);

    // We define the arithmetic means X_n = 1/n \sum_{i=1}^n x_i, and Y_n = 1/n \sum_{i=1}^n y_i.
    // We also define the sum of the products of the differences from the means
    //           C_n = \sum_{i=1}^n x_i y_i - n X_n Y_n
    // for all n >= 1. Then for all n > 1:
    //       C_{n-1} = \sum_{i=1}^{n-1} x_i y_i - (n-1) X_{n-1} Y_{n-1}

        },
        {
          "datasource": {
            "type": "prometheus",
            "uid": "${datasource}"
          },
          "expr": "sum(irate(istio_response_bytes_sum{source_workload_namespace!=\"istio-system\", reporter=\"source\"}[1m])) + sum(irate(istio_request_bytes_sum{source_workload_namespace!=\"istio-system\", reporter=\"source\"}[1m]))",
          "format": "time_series",
          "intervalFactor": 1,