Github user tdas commented on a diff in the pull request:
https://github.com/apache/spark/pull/7276#discussion_r35288489
--- Diff:
streaming/src/main/scala/org/apache/spark/streaming/scheduler/ReceiverSchedulingPolicy.scala
---
@@ -0,0 +1,161 @@
+/*
+ * 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.spark.streaming.scheduler
+
+import scala.collection.Map
+import scala.collection.mutable
+
+import org.apache.spark.streaming.receiver.Receiver
+
+private[streaming] class ReceiverSchedulingPolicy {
+
+ /**
+ * Try our best to schedule receivers with evenly distributed. However,
if the
+ * `preferredLocation`s of receivers are not even, we may not be able to
schedule them evenly
+ * because we have to respect them.
+ *
+ * This method is called when we start to launch receivers at the first
time.
+ */
+ def scheduleReceivers(
+ receivers: Seq[Receiver[_]], executors: Seq[String]): Map[Int,
Seq[String]] = {
+ if (receivers.isEmpty) {
+ return Map.empty
+ }
+
+ if (executors.isEmpty) {
+ return receivers.map(_.streamId -> Seq.empty).toMap
+ }
+
+ val hostToExecutors = executors.groupBy(_.split(":")(0))
+ val locations = new
Array[mutable.ArrayBuffer[String]](receivers.length)
+ val numReceiversOnExecutor = mutable.HashMap[String, Int]()
+ // Set the initial value to 0
+ executors.foreach(numReceiversOnExecutor(_) = 0)
+
+ // Firstly, we need to respect "preferredLocation". So if a receiver
has "preferredLocation",
+ // we need to make sure the "preferredLocation" is in the candidate
location list.
+ for (i <- 0 until receivers.length) {
+ locations(i) = new mutable.ArrayBuffer[String]()
+ // Note: preferredLocation is host but executors are host:port
+ receivers(i).preferredLocation.foreach { host =>
+ hostToExecutors.get(host) match {
+ case Some(executorsOnHost) =>
+ // preferredLocation is a known host. Select an executor that
has the least receivers in
+ // this host
+ val scheduledLocation =
+ executorsOnHost.minBy(executor =>
numReceiversOnExecutor(executor))
+ locations(i) += scheduledLocation
+ numReceiversOnExecutor(scheduledLocation) =
+ numReceiversOnExecutor(scheduledLocation) + 1
+ case None =>
+ // preferredLocation is an unknown host.
+ // Note: There are two cases:
+ // 1. This executor is not up. But it may be up later.
+ // 2. This executor is dead, or it's not a host in the cluster.
+ // Currently, simply add host to the scheduled locations
+ locations(i) += host
+ }
+ }
+ }
+
+ // For those receivers that don't have preferredLocation, make sure we
assign at least one
+ // executor to them.
+ for (scheduledLocations <- locations.filter(_.isEmpty)) {
+ // Select the executor that has the least receivers
+ val (executor, numReceivers) = numReceiversOnExecutor.minBy(_._2)
+ scheduledLocations += executor
+ numReceiversOnExecutor(executor) = numReceivers + 1
+ }
+
+ // Assign idle executors to receivers that have less executors
+ val idleExecutors = numReceiversOnExecutor.filter(_._2 == 0).map(_._1)
+ for (executor <- idleExecutors) {
+ // Assign an idle executor to the receiver that has least locations.
+ val scheduledLocations = locations.minBy(_.size)
+ scheduledLocations += executor
+ }
+
+ receivers.map(_.streamId).zip(locations).toMap
+ }
+
+ /**
+ * Return a list of candidate executors to run the receiver. If the list
is empty, the caller can
+ * run this receiver in arbitrary executor.
+ *
+ * This method tries to balance executors' load. Here is the approach to
schedule executors
+ * for a receiver.
+ * <ol>
+ * <li>
+ * If preferredLocation is set, preferredLocation should be one of
the candidate executors.
+ * </li>
+ * <li>
+ * Every executor will be assigned to a weight according to the
receivers running or
+ * scheduling on it.
+ * <ul>
+ * <li>
+ * If a receiver is running on an executor, it contributes 1.0
to the executor's weight.
+ * </li>
+ * <li>
+ * If a receiver is scheduled to an executor but has not yet
run, it contributes
+ * `1.0 / #candidate_executors_of_this_receiver` to the
executor's weight.</li>
+ * </ul>
+ * At last, if there are more than 3 idle executors (weight = 0),
returns all idle executors.
+ * Otherwise, we only return 3 best options according to the weights.
+ * </li>
+ * </ol>
+ *
+ * This method is called when a receiver is registering with
ReceiverTracker or is restarting.
+ */
+ def rescheduleReceiver(
+ receiverId: Int,
+ preferredLocation: Option[String],
+ receiverTrackingInfoMap: Map[Int, ReceiverTrackingInfo],
+ executors: Seq[String]): Seq[String] = {
--- End diff --
Might be good make the `3` as a parameter, so that we can add logic later
in the ReceiverTracker to increment this number for every failed start.
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