Exception ..fyi

[vraman...@gmail.com]

Trying to access from R..while building model..

11:19:13.699 # Session INFO WATER: ],"consensus":true,"locked":true
11:19:13.706 # Session INFO HTTPD: POST /2/Exec2.json str=segmentaa.hex = segmentaa.hex
11:19:17.247 # Session ERRR WATER: env.remove_and_unlock() failed
+ java.lang.IllegalArgumentException: Dataset segmentab.hex is already in use. Unable to use it now. Consider using a different destination name.
+ at water.Lockable$PriorWriteLock.atomic(Lockable.java:85)
+ at water.Lockable$PriorWriteLock.atomic(Lockable.java:74)
+ at water.TAtomic.atomic(TAtomic.java:19)
+ at water.Atomic.compute2(Atomic.java:58)
+ at water.Atomic.fork(Atomic.java:42)
+ at water.Atomic.invoke(Atomic.java:34)
+ at water.Lockable.write_lock(Lockable.java:60)
+ at water.exec.Env.remove_and_unlock(Env.java:349)
+ at water.api.Exec2.serve(Exec2.java:71)
+ at water.api.Request.serveGrid(Request.java:165)
+ at water.Request2.superServeGrid(Request2.java:481)

[Tom Kraljevic]

Please send the logs.

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[Tom Kraljevic]

by chance, did you start a job from the web ui and then try to access it from r before it completed?

this error looks kind of consistent with that.

Sent from my iPhone

> On Aug 27, 2014, at 11:23 AM, vraman...@gmail.com wrote:
>

[vraman...@gmail.com]

I started the training job directly using REST API..
I tried to access the data (essentially, .getFrame(...)) using R, while the job is still going..

Concurrent access is allowed correct?

[Tom Kraljevic]

ah, ok.

the R api is synchronous, so this specific thing is not really tested today.

the locking stuff is intended to prevent concurrent things from damaging each other.

if you give us the high level list of steps (or logs), we can try to repro them and see if there is a bug, but based on the info i think this is the expected behavior. (dataset probably wont matter.)

the stack trace might be a little ugly and misleading though.

thanks
tom

Sent from my iPhone

[vraman...@gmail.com]

Thanks Tom..Regarding logs, I'm running long running job on large data set..I'll see if I can reproduce & resend logs..
In the interim, here are the steps

1) Launch H2o (single instance)

2) Import Files: curl .../ImportFiles2.json

3) Parse fies: curl ../Parse2.json

4) kick off deep learning: curl ../DeepLearning.json
.....while that's running..it runs for long...
5) Start R session

6) connect to h2o

7) h2o.getFrame("train.hex"...)

8) summary(train.hex)
-------------------------------------