gyfora commented on code in PR #484: URL: https://github.com/apache/flink-kubernetes-operator/pull/484#discussion_r1050901964
########## flink-kubernetes-operator/src/main/java/org/apache/flink/kubernetes/operator/autoscaler/ScalingMetricCollector.java: ########## @@ -0,0 +1,443 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.flink.kubernetes.operator.autoscaler; + +import org.apache.flink.annotation.VisibleForTesting; +import org.apache.flink.api.common.JobID; +import org.apache.flink.api.java.tuple.Tuple2; +import org.apache.flink.client.program.rest.RestClusterClient; +import org.apache.flink.configuration.Configuration; +import org.apache.flink.kubernetes.operator.api.AbstractFlinkResource; +import org.apache.flink.kubernetes.operator.autoscaler.config.AutoScalerOptions; +import org.apache.flink.kubernetes.operator.autoscaler.metrics.CollectedMetrics; +import org.apache.flink.kubernetes.operator.autoscaler.metrics.FlinkMetric; +import org.apache.flink.kubernetes.operator.autoscaler.metrics.ScalingMetric; +import org.apache.flink.kubernetes.operator.autoscaler.metrics.ScalingMetrics; +import org.apache.flink.kubernetes.operator.autoscaler.topology.JobTopology; +import org.apache.flink.kubernetes.operator.service.FlinkService; +import org.apache.flink.runtime.jobgraph.JobVertexID; +import org.apache.flink.runtime.rest.messages.EmptyRequestBody; +import org.apache.flink.runtime.rest.messages.JobIDPathParameter; +import org.apache.flink.runtime.rest.messages.JobVertexIdPathParameter; +import org.apache.flink.runtime.rest.messages.job.JobDetailsInfo; +import org.apache.flink.runtime.rest.messages.job.metrics.AggregatedMetric; +import org.apache.flink.runtime.rest.messages.job.metrics.AggregatedSubtaskMetricsHeaders; +import org.apache.flink.runtime.rest.messages.job.metrics.AggregatedSubtaskMetricsParameters; +import org.apache.flink.util.Preconditions; + +import io.javaoperatorsdk.operator.processing.event.ResourceID; +import lombok.SneakyThrows; +import org.jetbrains.annotations.NotNull; +import org.slf4j.Logger; +import org.slf4j.LoggerFactory; + +import java.time.Clock; +import java.time.Duration; +import java.time.Instant; +import java.util.ArrayList; +import java.util.Collection; +import java.util.HashMap; +import java.util.HashSet; +import java.util.List; +import java.util.Map; +import java.util.Optional; +import java.util.Set; +import java.util.SortedMap; +import java.util.concurrent.ConcurrentHashMap; +import java.util.stream.Collectors; + +import static org.apache.flink.kubernetes.operator.autoscaler.config.AutoScalerOptions.SOURCE_SCALING_ENABLED; + +/** Metric collector using flink rest api. */ +public abstract class ScalingMetricCollector implements Cleanup { + private static final Logger LOG = LoggerFactory.getLogger(ScalingMetricCollector.class); + + private final Map<ResourceID, Tuple2<Long, Map<JobVertexID, Map<String, FlinkMetric>>>> + availableVertexMetricNames = new ConcurrentHashMap<>(); + + private final Map<ResourceID, SortedMap<Instant, Map<JobVertexID, Map<ScalingMetric, Double>>>> + histories = new ConcurrentHashMap<>(); + + private final Map<ResourceID, JobTopology> topologies = new ConcurrentHashMap<>(); + + private Clock clock = Clock.systemDefaultZone(); + + public CollectedMetrics getMetricsHistory( + AbstractFlinkResource<?, ?> cr, + AutoScalerInfo scalingInformation, + FlinkService flinkService, + Configuration conf) + throws Exception { + + var resourceID = ResourceID.fromResource(cr); + var currentJobStartTs = + Instant.ofEpochMilli(Long.parseLong(cr.getStatus().getJobStatus().getStartTime())); + + if (!currentJobStartTs.equals( + scalingInformation.getJobStartTs().orElse(currentJobStartTs))) { + scalingInformation.clearMetricHistory(); + cleanup(cr); + } + + // Initialize metric history + var scalingMetricHistory = + histories.compute( + resourceID, + (k, h) -> { + if (h == null) { + h = scalingInformation.getMetricHistory(); + } + return h.tailMap( + clock.instant() + .minus(conf.get(AutoScalerOptions.METRICS_WINDOW))); + }); + + var topology = getJobTopology(flinkService, cr, conf); + + // The filtered list of metrics we want to query for each vertex + var filteredVertexMetricNames = queryFilteredMetricNames(flinkService, cr, conf, topology); + + // Aggregated job vertex metrics collected from Flink based on the filtered metric names + var collectedVertexMetrics = + queryAllAggregatedMetrics(cr, flinkService, conf, filteredVertexMetricNames); + + // The computed scaling metrics based on the collected aggregated vertex metrics + var scalingMetrics = + convertToScalingMetrics(resourceID, collectedVertexMetrics, topology, conf); + + // Add scaling metrics to history if they were computed successfully + scalingMetricHistory.put(clock.instant(), scalingMetrics); + scalingInformation.updateMetricHistory(currentJobStartTs, scalingMetricHistory); + + return new CollectedMetrics(topology, scalingMetricHistory); + } + + protected JobTopology getJobTopology( + FlinkService flinkService, AbstractFlinkResource<?, ?> cr, Configuration conf) + throws Exception { + + try (var restClient = (RestClusterClient<String>) flinkService.getClusterClient(conf)) { + var jobId = JobID.fromHexString(cr.getStatus().getJobStatus().getJobId()); + var topology = + topologies.computeIfAbsent( + ResourceID.fromResource(cr), r -> queryJobTopology(restClient, jobId)); + updateKafkaSourceMaxParallelisms(restClient, jobId, topology); + return topology; + } + } + + @VisibleForTesting + protected JobTopology queryJobTopology(RestClusterClient<String> restClient, JobID jobId) { + try { + var jobDetailsInfo = restClient.getJobDetails(jobId).get(); + + Map<JobVertexID, Integer> maxParallelismMap = + jobDetailsInfo.getJobVertexInfos().stream() + .collect( + Collectors.toMap( + JobDetailsInfo.JobVertexDetailsInfo::getJobVertexID, + JobDetailsInfo.JobVertexDetailsInfo + ::getMaxParallelism)); + + return JobTopology.fromJsonPlan(jobDetailsInfo.getJsonPlan(), maxParallelismMap); + } catch (Exception e) { + throw new RuntimeException(e); + } + } + + private void updateKafkaSourceMaxParallelisms( + RestClusterClient<String> restClient, JobID jobId, JobTopology topology) + throws Exception { + for (Map.Entry<JobVertexID, Set<JobVertexID>> entry : topology.getInputs().entrySet()) { + if (entry.getValue().isEmpty()) { + var sourceVertex = entry.getKey(); + queryAggregatedMetricNames(restClient, jobId, sourceVertex).stream() + .map(AggregatedMetric::getId) + .filter(s -> s.endsWith(".currentOffset")) + .mapToInt( + s -> { + // We extract the partition from the pattern: Review Comment: it is marked kafka specific in the method name -- This is an automated message from the Apache Git Service. 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