Github user pwendell commented on a diff in the pull request:
https://github.com/apache/spark/pull/2087#discussion_r18795734
--- Diff: core/src/main/scala/org/apache/spark/deploy/SparkHadoopUtil.scala
---
@@ -121,6 +125,31 @@ class SparkHadoopUtil extends Logging {
UserGroupInformation.loginUserFromKeytab(principalName, keytabFilename)
}
+ /**
+ * Returns a function that can be called to find the number of Hadoop
FileSystem bytes read by
+ * this thread so far. Reflection is required because thread-level
FileSystem statistics are only
+ * available as of Hadoop 2.5 (see HADOOP-10688). Returns None if the
required method can't be
+ * found.
+ */
+ def getInputBytesReadCallback(path: Path, conf: Configuration):
Option[() => Long] = {
--- End diff --
Hey so there are a couple issues with the current approach:
This a bunch of reflective calls + exception handling every time it is
called. That will have huge performance overhead. Also, this catch-all
exception is sort of scary... what if there is a legitimate exception invoking
this function in versions that support it? The user will never be able to find
it.
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