kfaraz commented on code in PR #18860:
URL: https://github.com/apache/druid/pull/18860#discussion_r2638884967
##########
indexing-service/src/main/java/org/apache/druid/indexing/seekablestream/supervisor/autoscaler/CostBasedAutoScaler.java:
##########
@@ -204,50 +218,54 @@ public int computeOptimalTaskCount(CostMetrics metrics)
return -1;
}
- // If idle is already in the ideal range [0.2, 0.6], optimal utilization
has been achieved.
- // No scaling is needed - maintain stability by staying at the current
task count.
- final double currentIdleRatio = metrics.getPollIdleRatio();
- if (currentIdleRatio >= 0 &&
WeightedCostFunction.isIdleInIdealRange(currentIdleRatio)) {
- log.debug(
- "Idle ratio [%.3f] is in ideal range for supervisorId [%s], no
scaling needed",
- currentIdleRatio,
- supervisorId
- );
- return -1;
- }
-
int optimalTaskCount = -1;
- double optimalCost = Double.POSITIVE_INFINITY;
+ Tuple3<Double, Double, Double> optimalCost = new
Tuple3<>(Double.POSITIVE_INFINITY,
Review Comment:
Better use a dedicated class than a Tuple or Pair.
##########
indexing-service/src/main/java/org/apache/druid/indexing/seekablestream/supervisor/SeekableStreamSupervisor.java:
##########
@@ -596,7 +601,12 @@ private boolean changeTaskCount(int desiredActiveTaskCount)
AUTOSCALER_SCALING_TIME_METRIC,
scaleActionStopwatch.millisElapsed()
));
- log.info("Changed taskCount to [%s] for supervisor[%s] for
dataSource[%s].", desiredActiveTaskCount, supervisorId, dataSource);
+ log.info(
+ "Changed taskCount to [%s] for supervisor[%s] for dataSource[%s].",
+ desiredActiveTaskCount,
+ supervisorId,
+ dataSource
+ );
Review Comment:
Nit: @Fly-Style , could we please revert all the formatting changes from
this PR, to keep the focus on the actual changes?
I think we can leave out the formatting changes for now.
##########
embedded-tests/src/test/java/org/apache/druid/testing/embedded/indexing/TaskScaleDownRolloverTest.java:
##########
@@ -0,0 +1,232 @@
+/*
+ * 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.druid.testing.embedded.indexing;
+
+import org.apache.druid.data.input.impl.TimestampSpec;
+import org.apache.druid.indexing.kafka.KafkaIndexTaskModule;
+import org.apache.druid.indexing.kafka.simulate.KafkaResource;
+import org.apache.druid.indexing.kafka.supervisor.KafkaSupervisorSpec;
+import
org.apache.druid.indexing.seekablestream.supervisor.autoscaler.CostBasedAutoScalerConfig;
+import org.apache.druid.java.util.common.StringUtils;
+import org.apache.druid.query.DruidMetrics;
+import org.apache.druid.testing.embedded.EmbeddedBroker;
+import org.apache.druid.testing.embedded.EmbeddedClusterApis;
+import org.apache.druid.testing.embedded.EmbeddedCoordinator;
+import org.apache.druid.testing.embedded.EmbeddedDruidCluster;
+import org.apache.druid.testing.embedded.EmbeddedHistorical;
+import org.apache.druid.testing.embedded.EmbeddedIndexer;
+import org.apache.druid.testing.embedded.EmbeddedOverlord;
+import org.apache.druid.testing.embedded.EmbeddedRouter;
+import org.apache.druid.testing.embedded.junit5.EmbeddedClusterTestBase;
+import org.apache.kafka.clients.producer.ProducerRecord;
+import org.hamcrest.Matchers;
+import org.joda.time.DateTime;
+import org.joda.time.DateTimeZone;
+import org.joda.time.Seconds;
+import org.junit.jupiter.api.Assertions;
+import org.junit.jupiter.api.Test;
+import org.junit.jupiter.api.Timeout;
+
+import java.nio.charset.StandardCharsets;
+import java.util.List;
+import java.util.stream.Collectors;
+import java.util.stream.IntStream;
+
+import static
org.apache.druid.indexing.seekablestream.supervisor.autoscaler.CostBasedAutoScaler.OPTIMAL_TASK_COUNT_METRIC;
+
+@SuppressWarnings("SameParameterValue")
+public class TaskScaleDownRolloverTest extends EmbeddedClusterTestBase
+{
+ private static final String TOPIC =
EmbeddedClusterApis.createTestDatasourceName();
+ private static final String EVENT_TEMPLATE =
"{\"timestamp\":\"%s\",\"dimension\":\"value%d\",\"metric\":%d}";
+ private static final int PARTITION_COUNT = 50;
+
+ private final EmbeddedIndexer indexer = new EmbeddedIndexer();
+ private final EmbeddedOverlord overlord = new EmbeddedOverlord();
+ private KafkaResource kafkaServer;
+
+ @Override
+ public EmbeddedDruidCluster createCluster()
+ {
+ final EmbeddedDruidCluster cluster =
EmbeddedDruidCluster.withEmbeddedDerbyAndZookeeper();
+
+ kafkaServer = new KafkaResource()
+ {
+ @Override
+ public void start()
+ {
+ super.start();
+ createTopicWithPartitions(TOPIC, PARTITION_COUNT);
+ produceRecordsToKafka(500, 1);
+ }
+
+ @Override
+ public void stop()
+ {
+ deleteTopic(TOPIC);
+ super.stop();
+ }
+ };
+
+ // Increase worker capacity to handle more tasks
+ indexer.addProperty("druid.segment.handoff.pollDuration", "PT0.1s")
+ .addProperty("druid.worker.capacity", "60");
+
+ overlord.addProperty("druid.indexer.task.default.context",
"{\"useConcurrentLocks\": true}")
+ .addProperty("druid.manager.segments.pollDuration", "PT0.1s");
+
+ cluster.useLatchableEmitter()
+ .useDefaultTimeoutForLatchableEmitter(20)
+ .addServer(new EmbeddedCoordinator())
+ .addServer(overlord)
+ .addServer(indexer)
+ .addServer(new EmbeddedRouter())
+ .addServer(new EmbeddedBroker())
+ .addServer(new EmbeddedHistorical())
+ .addExtension(KafkaIndexTaskModule.class)
+ .addCommonProperty("druid.monitoring.emissionPeriod", "PT1s")
+ .addResource(kafkaServer);
+
+ return cluster;
+ }
+
+ /**
+ * Tests that scale down happen during task rollover via checkTaskDuration().
+ *
+ * <p>Test flow:</p>
+ * <ol>
+ * <li>Start supervisor with 20 tasks and 50 partitions, minimal data (500
records)</li>
+ * <li>Wait for initial tasks to start running</li>
+ * <li>Wait for the first task rollover to complete (task duration is 10
seconds)</li>
+ * <li>Verify that after rollover, fewer tasks are running due to
cost-based autoscaler (no ingestion at all)</li>
+ * </ol>
+ *
+ * <p>Scale down during rollover is triggered in {@code
SeekableStreamSupervisor.checkTaskDuration()}
+ * when all task groups have rolled over and the autoscaler recommends a
lower task count.</p>
+ */
+ @SuppressWarnings("resource")
+ @Test
+ @Timeout(300)
+ void test_scaleDownDuringTaskRollover()
Review Comment:
Can this test not be moved to the `CostBasedAutoScalerIntegrationTest`
itself?
##########
indexing-service/src/main/java/org/apache/druid/indexing/seekablestream/supervisor/SeekableStreamSupervisor.java:
##########
@@ -468,15 +469,19 @@ public void handle()
);
return;
}
- log.debug("PendingCompletionTaskGroups is [%s] for supervisor[%s]
for dataSource[%s]", pendingCompletionTaskGroups,
- supervisorId,
- dataSource
+ log.debug(
+ "PendingCompletionTaskGroups is [%s] for supervisor[%s] for
dataSource[%s]", pendingCompletionTaskGroups,
+ supervisorId,
+ dataSource
);
final Integer desiredTaskCount = computeDesiredTaskCount.call();
ServiceMetricEvent.Builder event = ServiceMetricEvent.builder()
.setDimension(DruidMetrics.SUPERVISOR_ID, supervisorId)
.setDimension(DruidMetrics.DATASOURCE, dataSource)
-
.setDimension(DruidMetrics.STREAM, getIoConfig().getStream());
+ .setDimension(
+
DruidMetrics.STREAM,
+
getIoConfig().getStream()
+ );
Review Comment:
Nit: this change doesn't seem necessary. Did it cross the 120 char limit?
##########
indexing-service/src/main/java/org/apache/druid/indexing/seekablestream/supervisor/autoscaler/CostBasedAutoScaler.java:
##########
@@ -184,7 +198,7 @@ private CostMetrics collectMetrics()
*
* @return optimal task count for scale-up, or -1 if no scaling action needed
*/
- public int computeOptimalTaskCount(CostMetrics metrics)
+ public int computeOptimalTaskCount(CostMetrics metrics, CostComputeMode
costComputeMode)
Review Comment:
Instead of keeping a cost compute mode, please keep two separate methods
that may have some internal common implementation. Methods may be named
something like:
`computeOptimalTaskCount` and `computeOptimalTaskCountOnRollover`.
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