Examples with AggregatedMetricValues com.linkedin.cruisecontrol.monitor.sampling.aggregator.AggregatedMetricValues used on opensource projects

Example 1 with AggregatedMetricValues

use of com.linkedin.cruisecontrol.monitor.sampling.aggregator.AggregatedMetricValues in project cruise-control by linkedin.

the class PreferredLeaderElectionGoalTest method createReplicaAndSetLoad.

private void createReplicaAndSetLoad(ClusterModel clusterModel, String rack, int brokerId, TopicPartition tp, int index, boolean isLeader) {
    clusterModel.createReplica(rack, brokerId, tp, index, isLeader);
    MetricValues metricValues = new MetricValues(1);
    Map<Integer, MetricValues> metricValuesByResource = new HashMap<>();
    Resource.cachedValues().forEach(r -> metricValuesByResource.put(KafkaCruiseControlMetricDef.resourceToMetricId(r), metricValues));
    clusterModel.setReplicaLoad(rack, brokerId, tp, new AggregatedMetricValues(metricValuesByResource), Collections.singletonList(1L));
}

Example 2 with AggregatedMetricValues

use of com.linkedin.cruisecontrol.monitor.sampling.aggregator.AggregatedMetricValues in project cruise-control by linkedin.

the class LoadMonitor method populateSnapshots.

private void populateSnapshots(Cluster kafkaCluster, ClusterModel clusterModel, TopicPartition tp, ValuesAndExtrapolations valuesAndExtrapolations) {
    PartitionInfo partitionInfo = kafkaCluster.partition(tp);
    // If partition info does not exist, the topic may have been deleted.
    if (partitionInfo != null) {
        for (int index = 0; index < partitionInfo.replicas().length; index++) {
            Node replica = partitionInfo.replicas()[index];
            boolean isLeader;
            if (partitionInfo.leader() == null) {
                LOG.warn("Detected offline partition {}-{}, skipping", partitionInfo.topic(), partitionInfo.partition());
                continue;
            } else {
                isLeader = replica.id() == partitionInfo.leader().id();
            }
            String rack = getRackHandleNull(replica);
            // Note that we assume the capacity resolver can still return the broker capacity even if the broker
            // is dead. We need this to get the host resource capacity.
            Map<Resource, Double> brokerCapacity = _brokerCapacityConfigResolver.capacityForBroker(rack, replica.host(), replica.id());
            clusterModel.createReplicaHandleDeadBroker(rack, replica.id(), tp, index, isLeader, brokerCapacity);
            AggregatedMetricValues aggregatedMetricValues = valuesAndExtrapolations.metricValues();
            clusterModel.setReplicaLoad(rack, replica.id(), tp, isLeader ? aggregatedMetricValues : MonitorUtils.toFollowerMetricValues(aggregatedMetricValues), valuesAndExtrapolations.windows());
        }
    }
}

Example 3 with AggregatedMetricValues

use of com.linkedin.cruisecontrol.monitor.sampling.aggregator.AggregatedMetricValues in project cruise-control by linkedin.

the class KafkaCruiseControlUnitTestUtils method getAggregatedMetricValues.

/**
 * Get the aggregated metric values with the given resource usage.
 */
public static AggregatedMetricValues getAggregatedMetricValues(double cpuUsage, double networkInBoundUsage, double networkOutBoundUsage, double diskUsage) {
    double[] values = new double[Resource.cachedValues().size()];
    values[KafkaCruiseControlMetricDef.resourceToMetricId(CPU)] = cpuUsage;
    values[KafkaCruiseControlMetricDef.resourceToMetricId(NW_IN)] = networkInBoundUsage;
    values[KafkaCruiseControlMetricDef.resourceToMetricId(NW_OUT)] = networkOutBoundUsage;
    values[KafkaCruiseControlMetricDef.resourceToMetricId(DISK)] = diskUsage;
    AggregatedMetricValues aggregateMetricValues = new AggregatedMetricValues();
    for (Resource r : Resource.cachedValues()) {
        int metricId = KafkaCruiseControlMetricDef.resourceToMetricId(r);
        MetricValues metricValues = new MetricValues(1);
        metricValues.set(0, values[metricId]);
        aggregateMetricValues.add(metricId, metricValues);
    }
    return aggregateMetricValues;
}

Example 4 with AggregatedMetricValues

use of com.linkedin.cruisecontrol.monitor.sampling.aggregator.AggregatedMetricValues in project cruise-control by linkedin.

the class ExcludedTopicsTest method unbalanced.

// two racks, three brokers, two partitions, one replica.
private static ClusterModel unbalanced() {
    List<Integer> orderedRackIdsOfBrokers = Arrays.asList(0, 0, 1);
    ClusterModel cluster = DeterministicCluster.getHomogeneousDeterministicCluster(2, orderedRackIdsOfBrokers, TestConstants.BROKER_CAPACITY);
    // Create topic partition.
    TopicPartition pInfoT10 = new TopicPartition("T1", 0);
    TopicPartition pInfoT20 = new TopicPartition("T2", 0);
    // Create replicas for topic: T1.
    cluster.createReplica("0", 0, pInfoT10, 0, true);
    cluster.createReplica("0", 0, pInfoT20, 0, true);
    AggregatedMetricValues aggregatedMetricValues = KafkaCruiseControlUnitTestUtils.getAggregatedMetricValues(TestConstants.TYPICAL_CPU_CAPACITY / 2, TestConstants.LARGE_BROKER_CAPACITY / 2, TestConstants.MEDIUM_BROKER_CAPACITY / 2, TestConstants.LARGE_BROKER_CAPACITY / 2);
    // Create snapshots and push them to the cluster.
    cluster.setReplicaLoad("0", 0, pInfoT10, aggregatedMetricValues, Collections.singletonList(1L));
    cluster.setReplicaLoad("0", 0, pInfoT20, aggregatedMetricValues, Collections.singletonList(1L));
    return cluster;
}

Example 5 with AggregatedMetricValues

use of com.linkedin.cruisecontrol.monitor.sampling.aggregator.AggregatedMetricValues in project cruise-control by linkedin.

the class ExcludedTopicsTest method unbalanced2.

// two racks, three brokers, six partitions, one replica.
private static ClusterModel unbalanced2() {
    ClusterModel cluster = unbalanced();
    // Create topic partition.
    TopicPartition pInfoT30 = new TopicPartition("T1", 1);
    TopicPartition pInfoT40 = new TopicPartition("T2", 1);
    TopicPartition pInfoT50 = new TopicPartition("T1", 2);
    TopicPartition pInfoT60 = new TopicPartition("T2", 2);
    // Create replicas for topic: T1.
    cluster.createReplica("0", 1, pInfoT30, 0, true);
    cluster.createReplica("0", 0, pInfoT40, 0, true);
    cluster.createReplica("0", 0, pInfoT50, 0, true);
    cluster.createReplica("0", 0, pInfoT60, 0, true);
    AggregatedMetricValues aggregatedMetricValues = KafkaCruiseControlUnitTestUtils.getAggregatedMetricValues(TestConstants.LARGE_BROKER_CAPACITY / 2, TestConstants.LARGE_BROKER_CAPACITY / 2, TestConstants.MEDIUM_BROKER_CAPACITY / 2, TestConstants.LARGE_BROKER_CAPACITY / 2);
    // Create snapshots and push them to the cluster.
    cluster.setReplicaLoad("0", 1, pInfoT30, aggregatedMetricValues, Collections.singletonList(1L));
    cluster.setReplicaLoad("0", 0, pInfoT40, aggregatedMetricValues, Collections.singletonList(1L));
    cluster.setReplicaLoad("0", 0, pInfoT50, aggregatedMetricValues, Collections.singletonList(1L));
    cluster.setReplicaLoad("0", 0, pInfoT60, aggregatedMetricValues, Collections.singletonList(1L));
    return cluster;
}