[GitHub] [incubator-gobblin] yukuai518 commented on a change in pull request #2626: [GOBBLIN-762] Add automatic scaling for Gobblin on YARN

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yukuai518 commented on a change in pull request #2626: [GOBBLIN-762] Add automatic scaling for Gobblin on YARN
URL: https://github.com/apache/incubator-gobblin/pull/2626#discussion_r281485690
 
 

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 File path: gobblin-yarn/src/main/java/org/apache/gobblin/yarn/YarnAutoScalingManager.java
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+/*
+ * 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.gobblin.yarn;
+
+import java.util.HashSet;
+import java.util.Map;
+import java.util.Set;
+import java.util.concurrent.Executors;
+import java.util.concurrent.ScheduledExecutorService;
+import java.util.concurrent.TimeUnit;
+import java.util.stream.Collectors;
+
+import org.apache.helix.HelixManager;
+import org.apache.helix.task.JobContext;
+import org.apache.helix.task.JobDag;
+import org.apache.helix.task.TaskDriver;
+import org.apache.helix.task.TaskState;
+import org.apache.helix.task.WorkflowConfig;
+import org.apache.helix.task.WorkflowContext;
+
+import com.google.common.annotations.VisibleForTesting;
+import com.google.common.base.Optional;
+import com.google.common.base.Preconditions;
+import com.google.common.util.concurrent.AbstractIdleService;
+import com.typesafe.config.Config;
+
+import lombok.AllArgsConstructor;
+import lombok.extern.slf4j.Slf4j;
+
+import org.apache.gobblin.util.ConfigUtils;
+import org.apache.gobblin.util.ExecutorsUtils;
+
+
+/**
+ * The autoscaling manager is responsible for figuring out how many containers are required for the workload and
+ * requesting the {@link YarnService} to request that many containers.
+ */
+@Slf4j
+public class YarnAutoScalingManager extends AbstractIdleService {
+  private final String AUTO_SCALING_PREFIX = GobblinYarnConfigurationKeys.GOBBLIN_YARN_PREFIX + "autoScaling.";
+  private final String AUTO_SCALING_POLLING_INTERVAL_SECS =
+      AUTO_SCALING_PREFIX + "pollingIntervalSeconds";
+  private final int DEFAULT_AUTO_SCALING_POLLING_INTERVAL_SECS = 60;
+  // Only one container will be requested for each N partitions of work
+  private final String AUTO_SCALING_PARTITIONS_PER_CONTAINER = AUTO_SCALING_PREFIX + "partitionsPerContainer";
+  private final int DEFAULT_AUTO_SCALING_PARTITIONS_PER_CONTAINER = 1;
+
+  private final Config config;
+  private final HelixManager helixManager;
+  private final ScheduledExecutorService autoScalingExecutor;
+  private final YarnService yarnService;
+  private final int partitionsPerContainer;
+
+  public YarnAutoScalingManager(GobblinApplicationMaster appMaster) {
+    this.config = appMaster.getConfig();
+    this.helixManager = appMaster.getMultiManager().getJobClusterHelixManager();
+    this.yarnService = appMaster.getYarnService();
+    this.partitionsPerContainer = ConfigUtils.getInt(this.config, AUTO_SCALING_PARTITIONS_PER_CONTAINER,
+        DEFAULT_AUTO_SCALING_PARTITIONS_PER_CONTAINER);
+
+    Preconditions.checkArgument(this.partitionsPerContainer > 0,
+        AUTO_SCALING_PARTITIONS_PER_CONTAINER + " needs to be greater than 0");
+
+    this.autoScalingExecutor = Executors.newSingleThreadScheduledExecutor(
+        ExecutorsUtils.newThreadFactory(Optional.of(log), Optional.of("AutoScalingExecutor")));
+  }
+
+  @Override
+  protected void startUp() throws Exception {
+    int scheduleInterval = ConfigUtils.getInt(this.config, AUTO_SCALING_POLLING_INTERVAL_SECS,
+        DEFAULT_AUTO_SCALING_POLLING_INTERVAL_SECS);
+    log.info("Starting the " + YarnAutoScalingManager.class.getSimpleName());
+    log.info("Scheduling the auto scaling task with an interval of {} seconds", scheduleInterval);
+
+    this.autoScalingExecutor.scheduleAtFixedRate(new YarnAutoScalingRunnable(new TaskDriver(this.helixManager),
+            this.yarnService, this.partitionsPerContainer), 0,
+        scheduleInterval, TimeUnit.SECONDS);
+  }
+
+  @Override
+  protected void shutDown() throws Exception {
+    log.info("Stopping the " + YarnAutoScalingManager.class.getSimpleName());
+
+    ExecutorsUtils.shutdownExecutorService(this.autoScalingExecutor, Optional.of(log));
+  }
+
+  /**
+   * A {@link Runnable} that figures out the number of containers required for the workload
+   * and requests those containers.
+   */
+  @VisibleForTesting
+  @AllArgsConstructor
+  static class YarnAutoScalingRunnable implements Runnable {
+    private final TaskDriver taskDriver;
+    private final YarnService yarnService;
+    private final int partitionsPerContainer;
+
+    /**
+     * Iterate through the workflows configured in Helix to figure out the number of required partitions
+     * and request the {@link YarnService} to scale to the desired number of containers.
+     */
+    @Override
+    public void run() {
+      Set<String> inUseInstances = new HashSet<>();
+
+      int numPartitions = 0;
+      for (Map.Entry<String, WorkflowConfig> workFlowEntry : taskDriver.getWorkflows().entrySet()) {
+        WorkflowContext workflowContext = taskDriver.getWorkflowContext(workFlowEntry.getKey());
+
+        // Only allocate for active workflows
 
 Review comment:
   @jhsenjaliya , the reason @htran1 add this async allocation is because the workflow execution was controlled by Helix, but the container allocation was contained by Yarn. These two components currently don't have any interaction.

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