result.combine(e.DateDiff.Timestamp2.analyze(s))
		return result

	// Handle aggregation function calls
	case aggFnAvg, aggFnMax, aggFnMin, aggFnSum, aggFnCount:
		// Initialize accumulator
		e.aggregate = newAggVal(funcName)

		var exprA qProp
		if funcName == aggFnCount {
			if e.Count.StarArg {
				return qProp{isAggregation: true}
			}

			exprA = e.Count.ExprArg.analyze(s)
		} else {

All metrics returned are from server-side reports. This means that latencies
and error rates are from the perspective of the service itself and not of an
individual client (or aggregate set of clients). Rates and latencies are
calculated over a time interval of 1 minute.
`,
		Example: `  # Retrieve workload metrics for productpage-v1 workload
  istioctl experimental metrics productpage-v1

	atomic.AddUint64(&m.bytesSinceLastWindow, bytes)
}

// updateExponentialMovingAverage processes the measurements captured so far.
func (m *rateMeasurement) updateExponentialMovingAverage(endTime time.Time) {
	// Calculate aggregate avg bandwidth and exp window avg
	m.lock.Lock()
	defer func() {
		m.startTime = endTime
		m.lock.Unlock()
	}()

	if m.startTime.IsZero() {
		return
	}

	if endTime.Before(m.startTime) {
		return

	Trim      *TrimFunc      `parser:"| @@"`
	DateAdd   *DateAddFunc   `parser:"| @@"`
	DateDiff  *DateDiffFunc  `parser:"| @@"`

	// Used during evaluation for aggregation funcs
	aggregate *aggVal
}

// SimpleArgFunc represents functions with simple expression
// arguments.
type SimpleArgFunc struct {

```
sudo pip install yq
alias kv-pairify='yq ".configuration[]" | jq ".[]" | jq -r ".name + \"=\" + .value"'
```

Let's take for example a set of 12 compute nodes with an aggregate memory of _1.2TiB_, we need to do following settings for optimal results. Add the following optimal entries for _core-site.xml_ to configure _s3a_ with **MinIO**. Most important options here are

```

            try {
                c.accept(pluginDescriptor);
            } catch (IllegalStateException e) {
                prerequisiteExceptions.add(e);
            }
        });
        // aggregate all exceptions
        if (!prerequisiteExceptions.isEmpty()) {
            String messages = prerequisiteExceptions.stream()
                    .map(IllegalStateException::getMessage)

  // and not for correctness. The only downside of keeping this 1 seems to be
  // that the gradient accumulation is unbounded and we will never
  // aggressively aggregate accumulated gradients to recover memory.
  // Revisit and fix.
  return 1;
}

// Consumes references to the tensors in the gradient_tensors list and returns
// a tensor with the result.

          listener.stopped();
        }

        @Override
        public String toString() {
          return "stopped()";
        }
      };

  /**
   * A listener for the aggregate state changes of the services that are under management. Users
   * that need to listen to more fine-grained events (such as when each particular {@linkplain

          <defaultValue>false</defaultValue>
        </field>
        <field>
          <name>aggregator</name>
          <version>1.0.0+</version>
          <type>boolean</type>
          <description>
            Flags this Mojo to run it in a multi-module way, i.e. aggregate the build with the set of projects
            listed as modules.
          </description>

		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrParseNonUnaryAggregateFunctionCall: {
		Code:           "ParseNonUnaryAggregateFunctionCall",
		Description:    "Only one argument is supported for aggregate functions in the SQL expression.",
		HTTPStatusCode: http.StatusBadRequest,
	},
	ErrParseMalformedJoin: {
		Code:           "ParseMalformedJoin",
		Description:    "JOIN is not supported in the SQL expression.",