Examples with AbstractMetric org.apache.hadoop.metrics2.AbstractMetric used on opensource projects

Example 26 with AbstractMetric

use of org.apache.hadoop.metrics2.AbstractMetric in project hadoop by apache.

the class GangliaSink30 method putMetrics.

@Override
public void putMetrics(MetricsRecord record) {
    // of metrics of sparse (only on change) publish of metrics
    try {
        String recordName = record.name();
        String contextName = record.context();
        StringBuilder sb = new StringBuilder();
        sb.append(contextName);
        sb.append('.');
        sb.append(recordName);
        appendPrefix(record, sb);
        String groupName = sb.toString();
        sb.append('.');
        int sbBaseLen = sb.length();
        String type = null;
        GangliaSlope slopeFromMetric = null;
        GangliaSlope calculatedSlope = null;
        Record cachedMetrics = null;
        // reset the buffer to the beginning
        resetBuffer();
        if (!isSupportSparseMetrics()) {
            // for sending dense metrics, update metrics cache
            // and get the updated data
            cachedMetrics = metricsCache.update(record);
            if (cachedMetrics != null && cachedMetrics.metricsEntrySet() != null) {
                for (Map.Entry<String, AbstractMetric> entry : cachedMetrics.metricsEntrySet()) {
                    AbstractMetric metric = entry.getValue();
                    sb.append(metric.name());
                    String name = sb.toString();
                    // visit the metric to identify the Ganglia type and
                    // slope
                    metric.visit(gangliaMetricVisitor);
                    type = gangliaMetricVisitor.getType();
                    slopeFromMetric = gangliaMetricVisitor.getSlope();
                    GangliaConf gConf = getGangliaConfForMetric(name);
                    calculatedSlope = calculateSlope(gConf, slopeFromMetric);
                    // send metric to Ganglia
                    emitMetric(groupName, name, type, metric.value().toString(), gConf, calculatedSlope);
                    // reset the length of the buffer for next iteration
                    sb.setLength(sbBaseLen);
                }
            }
        } else {
            // we support sparse updates
            Collection<AbstractMetric> metrics = (Collection<AbstractMetric>) record.metrics();
            if (metrics.size() > 0) {
                // we got metrics. so send the latest
                for (AbstractMetric metric : record.metrics()) {
                    sb.append(metric.name());
                    String name = sb.toString();
                    // visit the metric to identify the Ganglia type and
                    // slope
                    metric.visit(gangliaMetricVisitor);
                    type = gangliaMetricVisitor.getType();
                    slopeFromMetric = gangliaMetricVisitor.getSlope();
                    GangliaConf gConf = getGangliaConfForMetric(name);
                    calculatedSlope = calculateSlope(gConf, slopeFromMetric);
                    // send metric to Ganglia
                    emitMetric(groupName, name, type, metric.value().toString(), gConf, calculatedSlope);
                    // reset the length of the buffer for next iteration
                    sb.setLength(sbBaseLen);
                }
            }
        }
    } catch (IOException io) {
        throw new MetricsException("Failed to putMetrics", io);
    }
}

Example 27 with AbstractMetric

use of org.apache.hadoop.metrics2.AbstractMetric in project hadoop by apache.

the class TestMetricsCache method testUpdate.

@SuppressWarnings("deprecation")
@Test
public void testUpdate() {
    MetricsCache cache = new MetricsCache();
    MetricsRecord mr = makeRecord("r", Arrays.asList(makeTag("t", "tv")), Arrays.asList(makeMetric("m", 0), makeMetric("m1", 1)));
    MetricsCache.Record cr = cache.update(mr);
    verify(mr).name();
    verify(mr).tags();
    verify(mr).metrics();
    assertEquals("same record size", cr.metrics().size(), ((Collection<AbstractMetric>) mr.metrics()).size());
    assertEquals("same metric value", 0, cr.getMetric("m"));
    MetricsRecord mr2 = makeRecord("r", Arrays.asList(makeTag("t", "tv")), Arrays.asList(makeMetric("m", 2), makeMetric("m2", 42)));
    cr = cache.update(mr2);
    assertEquals("contains 3 metric", 3, cr.metrics().size());
    checkMetricValue("updated metric value", cr, "m", 2);
    checkMetricValue("old metric value", cr, "m1", 1);
    checkMetricValue("new metric value", cr, "m2", 42);
    MetricsRecord mr3 = makeRecord("r", // different tag value
    Arrays.asList(makeTag("t", "tv3")), Arrays.asList(makeMetric("m3", 3)));
    // should get a new record
    cr = cache.update(mr3);
    assertEquals("contains 1 metric", 1, cr.metrics().size());
    checkMetricValue("updated metric value", cr, "m3", 3);
    // tags cache should be empty so far
    assertEquals("no tags", 0, cr.tags().size());
    // until now
    cr = cache.update(mr3, true);
    assertEquals("Got 1 tag", 1, cr.tags().size());
    assertEquals("Tag value", "tv3", cr.getTag("t"));
    checkMetricValue("Metric value", cr, "m3", 3);
}

Example 28 with AbstractMetric

use of org.apache.hadoop.metrics2.AbstractMetric in project hadoop by apache.

the class TestMetricsCache method makeRecord.

private MetricsRecord makeRecord(String name, Collection<MetricsTag> tags, Collection<AbstractMetric> metrics) {
    MetricsRecord mr = mock(MetricsRecord.class);
    when(mr.name()).thenReturn(name);
    when(mr.tags()).thenReturn(tags);
    when(mr.metrics()).thenReturn(metrics);
    return mr;
}

Example 29 with AbstractMetric

use of org.apache.hadoop.metrics2.AbstractMetric in project hadoop by apache.

the class FileSink method putMetrics.

@Override
public void putMetrics(MetricsRecord record) {
    writer.print(record.timestamp());
    writer.print(" ");
    writer.print(record.context());
    writer.print(".");
    writer.print(record.name());
    String separator = ": ";
    for (MetricsTag tag : record.tags()) {
        writer.print(separator);
        separator = ", ";
        writer.print(tag.name());
        writer.print("=");
        writer.print(tag.value());
    }
    for (AbstractMetric metric : record.metrics()) {
        writer.print(separator);
        separator = ", ";
        writer.print(metric.name());
        writer.print("=");
        writer.print(metric.value());
    }
    writer.println();
}

Example 30 with AbstractMetric

use of org.apache.hadoop.metrics2.AbstractMetric in project hadoop by apache.

the class KafkaSink method putMetrics.

@Override
public void putMetrics(MetricsRecord record) {
    if (producer == null) {
        throw new MetricsException("Producer in KafkaSink is null!");
    }
    // Create the json object.
    StringBuilder jsonLines = new StringBuilder();
    long timestamp = record.timestamp();
    Instant instant = Instant.ofEpochMilli(timestamp);
    LocalDateTime ldt = LocalDateTime.ofInstant(instant, zoneId);
    String date = ldt.format(dateFormat);
    String time = ldt.format(timeFormat);
    // Collect datapoints and populate the json object.
    jsonLines.append("{\"hostname\": \"" + hostname);
    jsonLines.append("\", \"timestamp\": " + timestamp);
    jsonLines.append(", \"date\": \"" + date);
    jsonLines.append("\",\"time\": \"" + time);
    jsonLines.append("\",\"name\": \"" + record.name() + "\" ");
    for (MetricsTag tag : record.tags()) {
        jsonLines.append(", \"" + tag.name().toString().replaceAll("[\\p{Cc}]", "") + "\": ");
        jsonLines.append(" \"" + tag.value().toString() + "\"");
    }
    for (AbstractMetric metric : record.metrics()) {
        jsonLines.append(", \"" + metric.name().toString().replaceAll("[\\p{Cc}]", "") + "\": ");
        jsonLines.append(" \"" + metric.value().toString() + "\"");
    }
    jsonLines.append("}");
    LOG.debug("kafka message: " + jsonLines.toString());
    // Create the record to be sent from the json.
    ProducerRecord<Integer, byte[]> data = new ProducerRecord<Integer, byte[]>(topic, jsonLines.toString().getBytes(Charset.forName("UTF-8")));
    // Send the data to the Kafka broker. Here is an example of this data:
    // {"hostname": "...", "timestamp": 1436913651516,
    // "date": "2015-6-14","time": "22:40:51","context": "yarn","name":
    // "QueueMetrics, "running_0": "1", "running_60": "0", "running_300": "0",
    // "running_1440": "0", "AppsSubmitted": "1", "AppsRunning": "1",
    // "AppsPending": "0", "AppsCompleted": "0", "AppsKilled": "0",
    // "AppsFailed": "0", "AllocatedMB": "134656", "AllocatedVCores": "132",
    // "AllocatedContainers": "132", "AggregateContainersAllocated": "132",
    // "AggregateContainersReleased": "0", "AvailableMB": "0",
    // "AvailableVCores": "0", "PendingMB": "275456", "PendingVCores": "269",
    // "PendingContainers": "269", "ReservedMB": "0", "ReservedVCores": "0",
    // "ReservedContainers": "0", "ActiveUsers": "1", "ActiveApplications": "1"}
    Future<RecordMetadata> future = producer.send(data);
    jsonLines.setLength(0);
    try {
        future.get();
    } catch (InterruptedException e) {
        throw new MetricsException("Error sending data", e);
    } catch (ExecutionException e) {
        throw new MetricsException("Error sending data", e);
    }
}