LantaoJin commented on a change in pull request #23951:
[SPARK-13704][CORE][YARN] Re-implement RackResolver to reduce resolving time
URL: https://github.com/apache/spark/pull/23951#discussion_r266334129
##########
File path:
core/src/test/scala/org/apache/spark/scheduler/TaskSetManagerSuite.scala
##########
@@ -69,18 +69,48 @@ class FakeDAGScheduler(sc: SparkContext, taskScheduler:
FakeTaskScheduler)
// Get the rack for a given host
object FakeRackUtil {
private val hostToRack = new mutable.HashMap[String, String]()
+ var loopCount = 0
def cleanUp() {
hostToRack.clear()
+ loopCount = 0
}
def assignHostToRack(host: String, rack: String) {
hostToRack(host) = rack
}
def getRackForHost(host: String): Option[String] = {
+ loopCount = simulateRunResolveCommand(Seq(host))
hostToRack.get(host)
}
+
+ def getRacksForHosts(hosts: List[String]): List[Option[String]] = {
+ loopCount = simulateRunResolveCommand(hosts)
+ hosts.map(hostToRack.get)
+ }
+
+ /**
+ * This is a simulation of building and executing the resolution command.
+ * Simulate function `runResolveCommand()` in
[[org.apache.hadoop.net.ScriptBasedMapping]].
+ * If Seq has 100 elements, it returns 4. If Seq has 1 elements, it returns
1.
+ * @param args a list of arguments
+ * @return script execution times
+ */
+ private def simulateRunResolveCommand(args: Seq[String]): Int = {
+ val maxArgs = 30 // Simulate NET_TOPOLOGY_SCRIPT_NUMBER_ARGS_DEFAULT
+ var numProcessed = 0
+ var loopCount = 0
+ while (numProcessed != args.size) {
+ var start = maxArgs * loopCount
+ numProcessed = start
+ while (numProcessed < (start + maxArgs) && numProcessed < args.size) {
+ numProcessed += 1
+ }
+ loopCount += 1
+ }
+ loopCount
Review comment:
`FakeRackUtil.getRackForHostCount` couldn't equals to 0 here since there are
some other callers.
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