Consider the following 2 scenarios:
*Scenario #1*
val pagecounts = sc.textFile("data/pagecounts")
pagecounts.checkpoint
pagecounts.count
*Scenario #2*
val pagecounts = sc.textFile("data/pagecounts")
pagecounts.count
The total time show in the Spark shell Application UI was different for both
scenarios. /Scenario #1 took 0.5 seconds, while scenario #2 took only 0.2
s/.
*Questions:*
1. I understand that scenario #1 is taking more time, because the RDD is
check-pointed (written to disk). Is there a way I can know the time taken
for checkpoint, from the total time?
The Spark shell Application UI shows the following - Scheduler delay, Task
Deserialization time, GC time, Result serialization time, getting result
time. But, doesn't show the breakdown for checkpointing.
2. Is there a way to access the above metrics e.g. scheduler delay, GC time
and save them programmatically? I want to log some of the above metrics for
every action invoked on an RDD.
3. How can I programmatically access the following information:
- Size of an RDD, when persisted to disk on checkpointing?
- How much percentage of an RDD is in memory currently?
- Overall time taken for computing an RDD?
Please let me know if you need more information.
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