use of org.apache.kafka.common.metrics.stats.Avg in project kafka by apache.
the class StreamsMetricsImpl method addLatencyMetrics.
private void addLatencyMetrics(String scopeName, Sensor sensor, String entityName, String opName, Map<String, String> tags) {
maybeAddMetric(sensor, metrics.metricName(entityName + "-" + opName + "-latency-avg", groupNameFromScope(scopeName), "The average latency of " + entityName + " " + opName + " operation.", tags), new Avg());
maybeAddMetric(sensor, metrics.metricName(entityName + "-" + opName + "-latency-max", groupNameFromScope(scopeName), "The max latency of " + entityName + " " + opName + " operation.", tags), new Max());
addThroughputMetrics(scopeName, sensor, entityName, opName, tags);
}
use of org.apache.kafka.common.metrics.stats.Avg in project kafka by apache.
the class MetricsTest method testSampledStatInitialValue.
@Test
public void testSampledStatInitialValue() {
// initialValue from each SampledStat is set as the initialValue on its Sample.
// The only way to test the initialValue is to infer it by having a SampledStat
// with expired Stats, because their values are reset to the initial values.
// Most implementations of combine on SampledStat end up returning the default
// value, so we can use this. This doesn't work for Percentiles though.
// This test looks a lot like testOldDataHasNoEffect because it's the same
// flow that leads to this state.
Max max = new Max();
Min min = new Min();
Avg avg = new Avg();
Count count = new Count();
Rate.SampledTotal sampledTotal = new Rate.SampledTotal();
long windowMs = 100;
int samples = 2;
MetricConfig config = new MetricConfig().timeWindow(windowMs, TimeUnit.MILLISECONDS).samples(samples);
max.record(config, 50, time.milliseconds());
min.record(config, 50, time.milliseconds());
avg.record(config, 50, time.milliseconds());
count.record(config, 50, time.milliseconds());
sampledTotal.record(config, 50, time.milliseconds());
time.sleep(samples * windowMs);
assertEquals(Double.NEGATIVE_INFINITY, max.measure(config, time.milliseconds()), EPS);
assertEquals(Double.MAX_VALUE, min.measure(config, time.milliseconds()), EPS);
assertEquals(0.0, avg.measure(config, time.milliseconds()), EPS);
assertEquals(0, count.measure(config, time.milliseconds()), EPS);
assertEquals(0.0, sampledTotal.measure(config, time.milliseconds()), EPS);
}
use of org.apache.kafka.common.metrics.stats.Avg in project kafka by apache.
the class MetricsTest method testSimpleStats.
@Test
public void testSimpleStats() throws Exception {
ConstantMeasurable measurable = new ConstantMeasurable();
metrics.addMetric(metrics.metricName("direct.measurable", "grp1", "The fraction of time an appender waits for space allocation."), measurable);
Sensor s = metrics.sensor("test.sensor");
s.add(metrics.metricName("test.avg", "grp1"), new Avg());
s.add(metrics.metricName("test.max", "grp1"), new Max());
s.add(metrics.metricName("test.min", "grp1"), new Min());
s.add(metrics.metricName("test.rate", "grp1"), new Rate(TimeUnit.SECONDS));
s.add(metrics.metricName("test.occurences", "grp1"), new Rate(TimeUnit.SECONDS, new Count()));
s.add(metrics.metricName("test.count", "grp1"), new Count());
s.add(new Percentiles(100, -100, 100, BucketSizing.CONSTANT, new Percentile(metrics.metricName("test.median", "grp1"), 50.0), new Percentile(metrics.metricName("test.perc99_9", "grp1"), 99.9)));
Sensor s2 = metrics.sensor("test.sensor2");
s2.add(metrics.metricName("s2.total", "grp1"), new Total());
s2.record(5.0);
int sum = 0;
int count = 10;
for (int i = 0; i < count; i++) {
s.record(i);
sum += i;
}
// prior to any time passing
double elapsedSecs = (config.timeWindowMs() * (config.samples() - 1)) / 1000.0;
assertEquals(String.format("Occurrences(0...%d) = %f", count, count / elapsedSecs), count / elapsedSecs, metrics.metrics().get(metrics.metricName("test.occurences", "grp1")).value(), EPS);
// pretend 2 seconds passed...
long sleepTimeMs = 2;
time.sleep(sleepTimeMs * 1000);
elapsedSecs += sleepTimeMs;
assertEquals("s2 reflects the constant value", 5.0, metrics.metrics().get(metrics.metricName("s2.total", "grp1")).value(), EPS);
assertEquals("Avg(0...9) = 4.5", 4.5, metrics.metrics().get(metrics.metricName("test.avg", "grp1")).value(), EPS);
assertEquals("Max(0...9) = 9", count - 1, metrics.metrics().get(metrics.metricName("test.max", "grp1")).value(), EPS);
assertEquals("Min(0...9) = 0", 0.0, metrics.metrics().get(metrics.metricName("test.min", "grp1")).value(), EPS);
assertEquals("Rate(0...9) = 1.40625", sum / elapsedSecs, metrics.metrics().get(metrics.metricName("test.rate", "grp1")).value(), EPS);
assertEquals(String.format("Occurrences(0...%d) = %f", count, count / elapsedSecs), count / elapsedSecs, metrics.metrics().get(metrics.metricName("test.occurences", "grp1")).value(), EPS);
assertEquals("Count(0...9) = 10", (double) count, metrics.metrics().get(metrics.metricName("test.count", "grp1")).value(), EPS);
}
use of org.apache.kafka.common.metrics.stats.Avg in project kafka by apache.
the class MetricsTest method testDuplicateMetricName.
@Test(expected = IllegalArgumentException.class)
public void testDuplicateMetricName() {
metrics.sensor("test").add(metrics.metricName("test", "grp1"), new Avg());
metrics.sensor("test2").add(metrics.metricName("test", "grp1"), new Total());
}
use of org.apache.kafka.common.metrics.stats.Avg in project kafka by apache.
the class MetricsBench method main.
public static void main(String[] args) {
long iters = Long.parseLong(args[0]);
Metrics metrics = new Metrics();
try {
Sensor parent = metrics.sensor("parent");
Sensor child = metrics.sensor("child", parent);
for (Sensor sensor : Arrays.asList(parent, child)) {
sensor.add(metrics.metricName(sensor.name() + ".avg", "grp1"), new Avg());
sensor.add(metrics.metricName(sensor.name() + ".count", "grp1"), new Count());
sensor.add(metrics.metricName(sensor.name() + ".max", "grp1"), new Max());
sensor.add(new Percentiles(1024, 0.0, iters, BucketSizing.CONSTANT, new Percentile(metrics.metricName(sensor.name() + ".median", "grp1"), 50.0), new Percentile(metrics.metricName(sensor.name() + ".p_99", "grp1"), 99.0)));
}
long start = System.nanoTime();
for (int i = 0; i < iters; i++) parent.record(i);
double ellapsed = (System.nanoTime() - start) / (double) iters;
System.out.println(String.format("%.2f ns per metric recording.", ellapsed));
} finally {
metrics.close();
}
}
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