Github user jerryshao commented on a diff in the pull request:
https://github.com/apache/spark/pull/15377#discussion_r83336101
--- Diff: core/src/main/scala/org/apache/spark/util/Utils.scala ---
@@ -2474,25 +2478,42 @@ private[spark] class CallerContext(
val context = "SPARK_" + from + appIdStr + appAttemptIdStr +
jobIdStr + stageIdStr + stageAttemptIdStr + taskIdStr +
taskAttemptNumberStr
+ lazy val conf = new Configuration
+
/**
* Set up the caller context [[context]] by invoking Hadoop
CallerContext API of
* [[org.apache.hadoop.ipc.CallerContext]], which was added in hadoop
2.8.
*/
def setCurrentContext(): Boolean = {
- var succeed = false
- try {
- // scalastyle:off classforname
- val callerContext =
Class.forName("org.apache.hadoop.ipc.CallerContext")
- val Builder =
Class.forName("org.apache.hadoop.ipc.CallerContext$Builder")
- // scalastyle:on classforname
- val builderInst =
Builder.getConstructor(classOf[String]).newInstance(context)
- val hdfsContext = Builder.getMethod("build").invoke(builderInst)
- callerContext.getMethod("setCurrent", callerContext).invoke(null,
hdfsContext)
- succeed = true
- } catch {
- case NonFatal(e) => logInfo("Fail to set Spark caller context", e)
+ if (!CallerContext.callerContextSupported) {
--- End diff --
Alright, so the main purpose to use this flag is to avoid re-executing the
codes below. So AFAIK unless we can guarantee the sequentially calling of this
method, otherwise `callerContextSupported` may introduce concurrent issue,
especially in `Task` running code. Simultaneously started running tasks will
possibly get the flag as `true` and executing below code, which makes this flag
useless.
Also in AM/Client, it will only be called once, so this flag is not used at
those JVMs.
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