johnjcasey commented on code in PR #32402:
URL: https://github.com/apache/beam/pull/32402#discussion_r1777178411
##########
runners/google-cloud-dataflow-java/worker/src/main/java/org/apache/beam/runners/dataflow/worker/streaming/StageInfo.java:
##########
@@ -118,7 +118,9 @@ public List<PerStepNamespaceMetrics>
extractPerWorkerMetricValues() {
private void translateKnownPerWorkerCounters(List<PerStepNamespaceMetrics>
metrics) {
for (PerStepNamespaceMetrics perStepnamespaceMetrics : metrics) {
if (!BigQuerySinkMetrics.METRICS_NAMESPACE.equals(
- perStepnamespaceMetrics.getMetricsNamespace())) {
+ perStepnamespaceMetrics.getMetricsNamespace())
+ &&
!org.apache.beam.sdk.io.kafka.KafkaSinkMetrics.METRICS_NAMESPACE.equals(
Review Comment:
Can we import this to cleanup the full path?
##########
sdks/java/io/kafka/src/main/java/org/apache/beam/sdk/io/kafka/KafkaUnboundedReader.java:
##########
@@ -509,6 +521,13 @@ String name() {
List<TopicPartition> partitions =
Preconditions.checkArgumentNotNull(source.getSpec().getTopicPartitions());
+
+ // Each source has a single unique topic.
Review Comment:
Is this true? I would think that its possible for a source to consume from
multiple topics, depending on how the work was split
##########
runners/google-cloud-dataflow-java/worker/src/main/java/org/apache/beam/runners/dataflow/worker/MetricsToPerStepNamespaceMetricsConverter.java:
##########
@@ -65,7 +67,10 @@ private static Optional<MetricValue>
convertCounterToMetricValue(
MetricName metricName,
Long value,
Map<MetricName, LabeledMetricNameUtils.ParsedMetricName>
parsedPerWorkerMetricsCache) {
- if (value == 0 ||
!metricName.getNamespace().equals(BigQuerySinkMetrics.METRICS_NAMESPACE)) {
+
Review Comment:
This is fine for now, but we probably want a better system for this check if
we expand these metrics
##########
sdks/java/io/kafka/src/main/java/org/apache/beam/sdk/io/kafka/KafkaMetrics.java:
##########
@@ -0,0 +1,126 @@
+/*
+ * 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.beam.sdk.io.kafka;
+
+import com.google.auto.value.AutoValue;
+import java.time.Duration;
+import java.util.HashMap;
+import java.util.Map;
+import java.util.concurrent.ConcurrentLinkedQueue;
+import java.util.concurrent.atomic.AtomicBoolean;
+import org.apache.beam.sdk.metrics.Histogram;
+import org.apache.beam.sdk.util.Preconditions;
+
+/** Stores and exports metrics for a batch of Kafka Client RPCs. */
+public interface KafkaMetrics {
+
+ void updateSuccessfulRpcMetrics(String topic, Duration elapsedTime);
+
+ void updateKafkaMetrics();
+
+ /** No-op implementation of {@code KafkaResults}. */
+ class NoOpKafkaMetrics implements KafkaMetrics {
+ private NoOpKafkaMetrics() {}
+
+ @Override
+ public void updateSuccessfulRpcMetrics(String topic, Duration elapsedTime)
{}
+
+ @Override
+ public void updateKafkaMetrics() {}
+
+ private static NoOpKafkaMetrics singleton = new NoOpKafkaMetrics();
+
+ static NoOpKafkaMetrics getInstance() {
+ return singleton;
+ }
+ }
+
+ /**
+ * Metrics of a batch of RPCs. Member variables are thread safe; however,
this class does not have
+ * atomicity across member variables.
+ *
+ * <p>Expected usage: A number of threads record metrics in an instance of
this class with the
+ * member methods. Afterwards, a single thread should call {@code
updateStreamingInsertsMetrics}
+ * which will export all counters metrics and RPC latency distribution
metrics to the underlying
+ * {@code perWorkerMetrics} container. Afterwards, metrics should not be
written/read from this
+ * object.
+ */
+ @AutoValue
+ abstract class KafkaMetricsImpl implements KafkaMetrics {
+
+ static HashMap<String, Histogram> latencyHistograms = new HashMap<String,
Histogram>();
+
+ abstract HashMap<String, ConcurrentLinkedQueue<Duration>>
perTopicRpcLatencies();
+
+ abstract AtomicBoolean isWritable();
+
+ public static KafkaMetricsImpl create() {
+ return new AutoValue_KafkaMetrics_KafkaMetricsImpl(
+ new HashMap<String, ConcurrentLinkedQueue<Duration>>(), new
AtomicBoolean(true));
+ }
+
+ /** Record the rpc status and latency of a successful Kafka poll RPC call.
*/
+ @Override
+ public void updateSuccessfulRpcMetrics(String topic, Duration elapsedTime)
{
+ if (isWritable().get()) {
+ ConcurrentLinkedQueue<Duration> latencies =
perTopicRpcLatencies().get(topic);
+ if (latencies == null) {
+ latencies = new ConcurrentLinkedQueue<Duration>();
+ latencies.add(elapsedTime);
+ perTopicRpcLatencies().put(topic, latencies);
+ } else {
+ latencies.add(elapsedTime);
+ }
+ }
+ }
+
+ /** Record rpc latency histogram metrics for all recorded topics. */
+ private void recordRpcLatencyMetrics() {
+ for (Map.Entry<String, ConcurrentLinkedQueue<Duration>> topicLatencies :
+ perTopicRpcLatencies().entrySet()) {
+ Histogram topicHistogram;
+ if (latencyHistograms.containsKey(topicLatencies.getKey())) {
+ topicHistogram = latencyHistograms.get(topicLatencies.getKey());
+ } else {
+ topicHistogram =
+ KafkaSinkMetrics.createRPCLatencyHistogram(
+ KafkaSinkMetrics.RpcMethod.POLL, topicLatencies.getKey());
+ latencyHistograms.put(topicLatencies.getKey(), topicHistogram);
+ }
+ // update all the latencies
+ for (Duration d : topicLatencies.getValue()) {
+ Preconditions.checkArgumentNotNull(topicHistogram);
+ topicHistogram.update(d.toMillis());
+ }
+ }
+ }
+
+ /**
+ * Export all metrics recorded in this instance to the underlying {@code
perWorkerMetrics}
+ * containers. This function will only report metrics once per instance.
Subsequent calls to
+ * this function will no-op.
+ */
+ @Override
+ public void updateKafkaMetrics() {
+ if (!isWritable().compareAndSet(true, false)) {
Review Comment:
Should this "fail" silently? Id assume that if this is called twice,
something has gone wrong
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