Github user ash211 commented on a diff in the pull request:
https://github.com/apache/spark/pull/2828#discussion_r19002923
--- Diff: core/src/main/scala/org/apache/spark/deploy/worker/Worker.scala
---
@@ -362,9 +372,19 @@ private[spark] class Worker(
}
}
- def masterDisconnected() {
+ private def masterDisconnected() {
logError("Connection to master failed! Waiting for master to
reconnect...")
connected = false
+ scheduleAttemptsToReconnectToMaster()
+ }
+
+ private def scheduleAttemptsToReconnectToMaster() {
--- End diff --
I dug into Hadoop source and actually found out that the default policy for
Hadoop reconnects is to retry every 10 seconds for 6 attempts, and then every
60 seconds for 10 attempts. Each attempt also has a fuzz factor applied of
[0.5t, 1.5t] to prevent a thundering herd of reconnect attempts across the
cluster.
I don't have a strong opinion on infinite vs ~10min of retries -- I'd vote
for following Hadoop's lead unless presented with compelling arguments to do
something different.
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