Beispiel #1
0
// MakeTxnMetrics returns a TxnMetrics struct that contains metrics whose
// windowed portions retain data for approximately sampleInterval.
func MakeTxnMetrics(sampleInterval time.Duration) TxnMetrics {
	return TxnMetrics{
		Aborts:     metric.NewCounterWithRates(metaAbortsRates),
		Commits:    metric.NewCounterWithRates(metaCommitsRates),
		Commits1PC: metric.NewCounterWithRates(metaCommits1PCRates),
		Abandons:   metric.NewCounterWithRates(metaAbandonsRates),
		Durations:  metric.NewLatency(metaDurationsHistograms, sampleInterval),
		Restarts:   metric.NewHistogram(metaRestartsHistogram, sampleInterval, 100, 3),
	}
}
Beispiel #2
0
// TestMetricsRecorder verifies that the metrics recorder properly formats the
// statistics from various registries, both for Time Series and for Status
// Summaries.
func TestMetricsRecorder(t *testing.T) {
	defer leaktest.AfterTest(t)()

	// ========================================
	// Construct a series of fake descriptors for use in test.
	// ========================================
	nodeDesc := roachpb.NodeDescriptor{
		NodeID: roachpb.NodeID(1),
	}
	storeDesc1 := roachpb.StoreDescriptor{
		StoreID: roachpb.StoreID(1),
		Capacity: roachpb.StoreCapacity{
			Capacity:  100,
			Available: 50,
		},
	}
	storeDesc2 := roachpb.StoreDescriptor{
		StoreID: roachpb.StoreID(2),
		Capacity: roachpb.StoreCapacity{
			Capacity:  200,
			Available: 75,
		},
	}

	// ========================================
	// Create registries and add them to the recorder (two node-level, two
	// store-level).
	// ========================================
	reg1 := metric.NewRegistry()
	store1 := fakeStore{
		storeID:  roachpb.StoreID(1),
		desc:     storeDesc1,
		registry: metric.NewRegistry(),
	}
	store2 := fakeStore{
		storeID:  roachpb.StoreID(2),
		desc:     storeDesc2,
		registry: metric.NewRegistry(),
	}
	manual := hlc.NewManualClock(100)
	recorder := NewMetricsRecorder(hlc.NewClock(manual.UnixNano, time.Nanosecond))
	recorder.AddStore(store1)
	recorder.AddStore(store2)
	recorder.AddNode(reg1, nodeDesc, 50)

	// Ensure the metric system's view of time does not advance during this test
	// as the test expects time to not advance too far which would age the actual
	// data (e.g. in histogram's) unexpectedly.
	defer metric.TestingSetNow(func() time.Time {
		return time.Unix(0, manual.UnixNano()).UTC()
	})()

	// ========================================
	// Generate Metrics Data & Expected Results
	// ========================================

	// Flatten the four registries into an array for ease of use.
	regList := []struct {
		reg    *metric.Registry
		prefix string
		source int64
		isNode bool
	}{
		{
			reg:    reg1,
			prefix: "one.",
			source: 1,
			isNode: true,
		},
		{
			reg:    reg1,
			prefix: "two.",
			source: 1,
			isNode: true,
		},
		{
			reg:    store1.registry,
			prefix: "",
			source: int64(store1.storeID),
			isNode: false,
		},
		{
			reg:    store2.registry,
			prefix: "",
			source: int64(store2.storeID),
			isNode: false,
		},
	}

	// Every registry will have a copy of the following metrics.
	metricNames := []struct {
		name string
		typ  string
		val  int64
	}{
		{"testGauge", "gauge", 20},
		{"testGaugeFloat64", "floatgauge", 20},
		{"testCounter", "counter", 5},
		{"testCounterWithRates", "counterwithrates", 2},
		{"testHistogram", "histogram", 10},
		{"testLatency", "latency", 10},

		// Stats needed for store summaries.
		{"ranges", "counter", 1},
		{"replicas.leaders", "gauge", 1},
		{"replicas.leaseholders", "gauge", 1},
		{"ranges", "gauge", 1},
		{"ranges.available", "gauge", 1},
	}

	// Add the metrics to each registry and set their values. At the same time,
	// generate expected time series results and status summary metric values.
	var expected []tspb.TimeSeriesData
	expectedNodeSummaryMetrics := make(map[string]float64)
	expectedStoreSummaryMetrics := make(map[string]float64)

	// addExpected generates expected data for a single metric data point.
	addExpected := func(prefix, name string, source, time, val int64, isNode bool) {
		// Generate time series data.
		tsPrefix := "cr.node."
		if !isNode {
			tsPrefix = "cr.store."
		}
		expect := tspb.TimeSeriesData{
			Name:   tsPrefix + prefix + name,
			Source: strconv.FormatInt(source, 10),
			Datapoints: []tspb.TimeSeriesDatapoint{
				{
					TimestampNanos: time,
					Value:          float64(val),
				},
			},
		}
		expected = append(expected, expect)

		// Generate status summary data.
		if isNode {
			expectedNodeSummaryMetrics[prefix+name] = float64(val)
		} else {
			// This can overwrite the previous value, but this is expected as
			// all stores in our tests have identical values; when comparing
			// status summaries, the same map is used as expected data for all
			// stores.
			expectedStoreSummaryMetrics[prefix+name] = float64(val)
		}
	}

	for _, reg := range regList {
		for _, data := range metricNames {
			switch data.typ {
			case "gauge":
				g := metric.NewGauge(metric.Metadata{Name: reg.prefix + data.name})
				reg.reg.AddMetric(g)
				g.Update(data.val)
				addExpected(reg.prefix, data.name, reg.source, 100, data.val, reg.isNode)
			case "floatgauge":
				g := metric.NewGaugeFloat64(metric.Metadata{Name: reg.prefix + data.name})
				reg.reg.AddMetric(g)
				g.Update(float64(data.val))
				addExpected(reg.prefix, data.name, reg.source, 100, data.val, reg.isNode)
			case "counter":
				c := metric.NewCounter(metric.Metadata{Name: reg.prefix + data.name})
				reg.reg.AddMetric(c)
				c.Inc((data.val))
				addExpected(reg.prefix, data.name, reg.source, 100, data.val, reg.isNode)
			case "counterwithrates":
				r := metric.NewCounterWithRates(metric.Metadata{Name: reg.prefix + data.name})
				reg.reg.AddMetric(r)
				r.Inc(data.val)
				addExpected(reg.prefix, data.name, reg.source, 100, data.val, reg.isNode)
			case "histogram":
				h := metric.NewHistogram(metric.Metadata{Name: reg.prefix + data.name}, time.Second, 1000, 2)
				reg.reg.AddMetric(h)
				h.RecordValue(data.val)
				for _, q := range recordHistogramQuantiles {
					addExpected(reg.prefix, data.name+q.suffix, reg.source, 100, data.val, reg.isNode)
				}
			case "latency":
				l := metric.NewLatency(metric.Metadata{Name: reg.prefix + data.name}, time.Hour)
				reg.reg.AddMetric(l)
				l.RecordValue(data.val)
				// Latency is simply three histograms (at different resolution
				// time scales).
				for _, q := range recordHistogramQuantiles {
					addExpected(reg.prefix, data.name+q.suffix, reg.source, 100, data.val, reg.isNode)
				}
			default:
				t.Fatalf("unexpected: %+v", data)
			}
		}
	}

	// ========================================
	// Verify time series data
	// ========================================
	actual := recorder.GetTimeSeriesData()

	// Actual comparison is simple: sort the resulting arrays by time and name,
	// and use reflect.DeepEqual.
	sort.Sort(byTimeAndName(actual))
	sort.Sort(byTimeAndName(expected))
	if a, e := actual, expected; !reflect.DeepEqual(a, e) {
		t.Errorf("recorder did not yield expected time series collection; diff:\n %v", pretty.Diff(e, a))
	}

	// ========================================
	// Verify node summary generation
	// ========================================
	expectedNodeSummary := &NodeStatus{
		Desc:      nodeDesc,
		BuildInfo: build.GetInfo(),
		StartedAt: 50,
		UpdatedAt: 100,
		Metrics:   expectedNodeSummaryMetrics,
		StoreStatuses: []StoreStatus{
			{
				Desc:    storeDesc1,
				Metrics: expectedStoreSummaryMetrics,
			},
			{
				Desc:    storeDesc2,
				Metrics: expectedStoreSummaryMetrics,
			},
		},
	}

	nodeSummary := recorder.GetStatusSummary()
	if nodeSummary == nil {
		t.Fatalf("recorder did not return nodeSummary")
	}

	sort.Sort(byStoreDescID(nodeSummary.StoreStatuses))
	if a, e := nodeSummary, expectedNodeSummary; !reflect.DeepEqual(a, e) {
		t.Errorf("recorder did not produce expected NodeSummary; diff:\n %v", pretty.Diff(e, a))
	}
}