Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/22612#discussion_r232220878
--- Diff:
core/src/main/scala/org/apache/spark/executor/ProcfsBasedSystems.scala ---
@@ -0,0 +1,222 @@
+/*
+ * 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.executor
+
+import java.io._
+import java.nio.charset.Charset
+import java.nio.file.{Files, Paths}
+import java.util.Locale
+
+import scala.collection.mutable
+import scala.collection.mutable.ArrayBuffer
+
+import org.apache.spark.{SparkEnv, SparkException}
+import org.apache.spark.internal.{config, Logging}
+import org.apache.spark.util.Utils
+
+private[spark] case class ProcfsBasedSystemsMetrics(
+ jvmVmemTotal: Long,
+ jvmRSSTotal: Long,
+ pythonVmemTotal: Long,
+ pythonRSSTotal: Long,
+ otherVmemTotal: Long,
+ otherRSSTotal: Long)
+
+// Some of the ideas here are taken from the ProcfsBasedProcessTree class
in hadoop
+// project.
+private[spark] class ProcfsBasedSystems(val procfsDir: String = "/proc/")
extends Logging {
+ val procfsStatFile = "stat"
+ val testing = sys.env.contains("SPARK_TESTING") ||
sys.props.contains("spark.testing")
+ var pageSize = computePageSize()
+ var isAvailable: Boolean = isProcfsAvailable
+ private val pid = computePid()
+ private var ptree = mutable.Map[ Int, Set[Int]]()
+
+ var allMetrics: ProcfsBasedSystemsMetrics = ProcfsBasedSystemsMetrics(0,
0, 0, 0, 0, 0)
+
+ computeProcessTree()
+
+ private def isProcfsAvailable: Boolean = {
+ if (testing) {
+ return true
+ }
+ try {
+ if (!Files.exists(Paths.get(procfsDir))) {
+ return false
+ }
+ }
+ catch {
+ case f: FileNotFoundException => return false
+ }
+ val shouldLogStageExecutorMetrics =
+ SparkEnv.get.conf.get(config.EVENT_LOG_STAGE_EXECUTOR_METRICS)
+ val shouldLogStageExecutorProcessTreeMetrics =
+ SparkEnv.get.conf.get(config.EVENT_LOG_PROCESS_TREE_METRICS)
+ shouldLogStageExecutorProcessTreeMetrics &&
shouldLogStageExecutorMetrics
+ }
+
+ private def computePid(): Int = {
+ if (!isAvailable || testing) {
+ return -1;
+ }
+ try {
+ // This can be simplified in java9:
+ //
https://docs.oracle.com/javase/9/docs/api/java/lang/ProcessHandle.html
+ val cmd = Array("bash", "-c", "echo $PPID")
+ val length = 10
+ val out2 = Utils.executeAndGetOutput(cmd)
+ val pid = Integer.parseInt(out2.split("\n")(0))
+ return pid;
+ }
+ catch {
+ case e: SparkException => logWarning("Exception when trying to
compute process tree." +
+ " As a result reporting of ProcessTree metrics is stopped", e)
+ isAvailable = false
+ return -1
+ }
+ }
+
+ private def computePageSize(): Long = {
+ if (testing) {
+ return 0;
+ }
+ try {
+ val cmd = Array("getconf", "PAGESIZE")
+ val out2 = Utils.executeAndGetOutput(cmd)
+ return Integer.parseInt(out2.split("\n")(0))
+ } catch {
+ case e: Exception => logWarning("Exception when trying to compute
pagesize, as a" +
+ " result reporting of ProcessTree metrics is stopped")
+ isAvailable = false
+ return 0
+ }
+ }
+
+ private def computeProcessTree(): Unit = {
+ if (!isAvailable || testing) {
+ return
+ }
+ ptree = mutable.Map[ Int, Set[Int]]()
+ val queue = mutable.Queue.empty[Int]
+ queue += pid
+ while( !queue.isEmpty ) {
+ val p = queue.dequeue()
+ val c = getChildPids(p)
+ if(!c.isEmpty) {
+ queue ++= c
+ ptree += (p -> c.toSet)
+ }
+ else {
+ ptree += (p -> Set[Int]())
+ }
+ }
+ }
+
+ private def getChildPids(pid: Int): ArrayBuffer[Int] = {
+ try {
+ // val cmd = Array("pgrep", "-P", pid.toString)
+ val builder = new ProcessBuilder("pgrep", "-P", pid.toString)
+ val process = builder.start()
+ // val output = new StringBuilder()
+ val threadName = "read stdout for " + "pgrep"
+ val childPidsInInt = mutable.ArrayBuffer.empty[Int]
+ def appendChildPid(s: String): Unit = {
+ if (s != "") {
+ logDebug("Found a child pid:" + s)
+ childPidsInInt += Integer.parseInt(s)
+ }
+ }
+ val stdoutThread = Utils.processStreamByLine(threadName,
+ process.getInputStream, appendChildPid)
+ val exitCode = process.waitFor()
+ stdoutThread.join()
+ // pgrep will have exit code of 1 if there are more than one child
process
+ // and it will have a exit code of 2 if there is no child process
+ if (exitCode != 0 && exitCode > 2) {
+ val cmd = builder.command().toArray.mkString(" ")
+ logWarning(s"Process $cmd" +
+ s" exited with code $exitCode, with stderr:" +
s"${process.getErrorStream} ")
+ throw new SparkException(s"Process $cmd exited with code
$exitCode")
+ }
+ childPidsInInt
+ } catch {
+ case e: Exception => logWarning("Exception when trying to compute
process tree." +
+ " As a result reporting of ProcessTree metrics is stopped.", e)
+ isAvailable = false
+ return mutable.ArrayBuffer.empty[Int]
+ }
+ }
+
+ def computeProcessInfo(pid: Int): Unit = {
+ /*
+ * Hadoop ProcfsBasedProcessTree class used regex and pattern matching
to retrive the memory
+ * info. I tried that but found it not correct during tests, so I used
normal string analysis
+ * instead. The computation of RSS and Vmem are based on proc(5):
+ * http://man7.org/linux/man-pages/man5/proc.5.html
+ */
+ try {
+ val pidDir = new File(procfsDir, pid.toString)
+ Utils.tryWithResource( new InputStreamReader(
+ new FileInputStream(
+ new File(pidDir, procfsStatFile)), Charset.forName("UTF-8"))) {
fReader =>
+ Utils.tryWithResource( new BufferedReader(fReader)) { in =>
+ val procInfo = in.readLine
+ val procInfoSplit = procInfo.split(" ")
+ if (procInfoSplit != null) {
+ val vmem = procInfoSplit(22).toLong
+ val rssPages = procInfoSplit(23).toLong
+ if (procInfoSplit(1).toLowerCase(Locale.US).contains("java")) {
+ allMetrics = allMetrics.copy(
+ jvmVmemTotal = allMetrics.jvmVmemTotal + vmem,
+ jvmRSSTotal = allMetrics.jvmRSSTotal + (rssPages*pageSize)
+ )
+ }
+ else if
(procInfoSplit(1).toLowerCase(Locale.US).contains("python")) {
+ allMetrics = allMetrics.copy(
+ pythonVmemTotal = allMetrics.pythonVmemTotal + vmem,
+ pythonRSSTotal = allMetrics.pythonRSSTotal +
(rssPages*pageSize)
+ )
+ }
+ else {
+ allMetrics = allMetrics.copy(
+ otherVmemTotal = allMetrics.otherVmemTotal + vmem,
+ otherRSSTotal = allMetrics.otherRSSTotal +
(rssPages*pageSize)
+ )
+ }
+ }
+ }
+ }
+ } catch {
+ case f: FileNotFoundException => logWarning("There was a problem
with reading" +
+ " the stat file of the process. ", f)
+ }
+ }
+
+ private[spark] def computeAllMetrics(): ProcfsBasedSystemsMetrics = {
+ if (!isAvailable) {
+ return ProcfsBasedSystemsMetrics(0, 0, 0, 0, 0, 0)
+ }
+ computeProcessTree
+ val pids = ptree.keySet
+ allMetrics = ProcfsBasedSystemsMetrics(0, 0, 0, 0, 0, 0)
+ for (p <- pids) {
+ computeProcessInfo(p)
--- End diff --
the state used here is a little trickier than it needs to be.
`computeProcessTree` is updating a member variable, even though its only
used locally -- it would be easier to follow if instead it just returned the
process tree, and then you passed it around. Also I dont' think you actually
care about the tree, just the set of pids?
similarly for `allMetrics`. it doesn't really need to be a member
variable, since its use is entirely contained within this function, you could
just pass it around.
```scala
val pids = discoverPids()
val allMetrics = ...
for (p <- pids) {
allMetrics = updateMetricsForProcess(allMetrics, p)
}
```
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