예제 #1
0
    def test_gauge(self):
        ag_interval = 2
        stats = MetricsBucketAggregator('myhost', interval=ag_interval)
        self.wait_for_bucket_boundary(ag_interval)

        # Track some counters.
        stats.submit_packets('my.first.gauge:1|g')
        stats.submit_packets('my.first.gauge:5|g')
        stats.submit_packets('my.second.gauge:1.5|g')

        # Ensure that gauges roll up correctly.
        self.sleep_for_interval_length(ag_interval)
        metrics = self.sort_metrics(stats.flush())
        nt.assert_equals(len(metrics), 2)

        first, second = metrics

        nt.assert_equals(first['metric'], 'my.first.gauge')
        nt.assert_equals(first['points'][0][1], 5)
        nt.assert_equals(first['host'], 'myhost')

        nt.assert_equals(second['metric'], 'my.second.gauge')
        nt.assert_equals(second['points'][0][1], 1.5)

        # Ensure that old gauges get dropped due to old timestamps
        stats.submit_metric('my.first.gauge', 5, 'g')
        stats.submit_metric('my.first.gauge', 1, 'g', timestamp=1000000000)
        stats.submit_metric('my.second.gauge', 20, 'g', timestamp=1000000000)

        self.sleep_for_interval_length(ag_interval)
        metrics = self.sort_metrics(stats.flush())
        nt.assert_equals(len(metrics), 1)

        first = metrics[0]

        nt.assert_equals(first['metric'], 'my.first.gauge')
        nt.assert_equals(first['points'][0][1], 5)
        nt.assert_equals(first['host'], 'myhost')
예제 #2
0
    def test_recent_point_threshold(self):
        ag_interval = 1
        threshold = 100
        # The min is not enabled by default
        stats = MetricsBucketAggregator(
            'myhost',
            recent_point_threshold=threshold,
            interval=ag_interval,
            histogram_aggregates=DEFAULT_HISTOGRAM_AGGREGATES + ['min'])
        timestamp_beyond_threshold = time.time() - threshold * 2

        # Ensure that old gauges get dropped due to old timestamps
        stats.submit_metric('my.first.gauge', 5, 'g')
        stats.submit_metric('my.first.gauge',
                            1,
                            'g',
                            timestamp=timestamp_beyond_threshold)
        stats.submit_metric('my.second.gauge',
                            20,
                            'g',
                            timestamp=timestamp_beyond_threshold)

        self.sleep_for_interval_length(ag_interval)
        metrics = self.sort_metrics(stats.flush())
        assert len(metrics) == 1

        first = metrics[0]
        nt.assert_equals(first['metric'], 'my.first.gauge')
        nt.assert_equals(first['points'][0][1], 5)
        nt.assert_equals(first['host'], 'myhost')

        timestamp_within_threshold = time.time() - threshold / 2
        bucket_for_timestamp_within_threshold = timestamp_within_threshold - (
            timestamp_within_threshold % ag_interval)
        stats.submit_metric('my.1.gauge', 5, 'g')
        stats.submit_metric('my.1.gauge',
                            1,
                            'g',
                            timestamp=timestamp_within_threshold)
        stats.submit_metric('my.2.counter',
                            20,
                            'c',
                            timestamp=timestamp_within_threshold)
        stats.submit_metric('my.3.set',
                            20,
                            's',
                            timestamp=timestamp_within_threshold)
        stats.submit_metric('my.4.histogram',
                            20,
                            'h',
                            timestamp=timestamp_within_threshold)

        self.sleep_for_interval_length(ag_interval)
        flush_timestamp = time.time()
        # The bucket timestamp is the beginning of the bucket that ended before we flushed
        bucket_timestamp = flush_timestamp - (flush_timestamp %
                                              ag_interval) - ag_interval
        metrics = self.sort_metrics(stats.flush())
        nt.assert_equal(len(metrics), 11)

        first, first_b, second, second_b, third, h1, h2, h3, h4, h5, h6 = metrics
        nt.assert_equals(first['metric'], 'my.1.gauge')
        nt.assert_equals(first['points'][0][1], 1)
        nt.assert_equals(first['host'], 'myhost')
        self.assert_almost_equal(first['points'][0][0],
                                 bucket_for_timestamp_within_threshold, 0.1)
        nt.assert_equals(first_b['metric'], 'my.1.gauge')
        nt.assert_equals(first_b['points'][0][1], 5)
        self.assert_almost_equal(first_b['points'][0][0], bucket_timestamp,
                                 0.1)

        nt.assert_equals(second['metric'], 'my.2.counter')
        nt.assert_equals(second['points'][0][1], 20)
        self.assert_almost_equal(second['points'][0][0],
                                 bucket_for_timestamp_within_threshold, 0.1)
        nt.assert_equals(second_b['metric'], 'my.2.counter')
        nt.assert_equals(second_b['points'][0][1], 0)
        self.assert_almost_equal(second_b['points'][0][0], bucket_timestamp,
                                 0.1)

        nt.assert_equals(third['metric'], 'my.3.set')
        nt.assert_equals(third['points'][0][1], 1)
        self.assert_almost_equal(third['points'][0][0],
                                 bucket_for_timestamp_within_threshold, 0.1)

        nt.assert_equals(h1['metric'], 'my.4.histogram.95percentile')
        nt.assert_equals(h1['points'][0][1], 20)
        self.assert_almost_equal(h1['points'][0][0],
                                 bucket_for_timestamp_within_threshold, 0.1)
        nt.assert_equal(h1['points'][0][0], h2['points'][0][0])
        nt.assert_equal(h1['points'][0][0], h3['points'][0][0])
        nt.assert_equal(h1['points'][0][0], h4['points'][0][0])
        nt.assert_equal(h1['points'][0][0], h5['points'][0][0])