Hi Dmitry,

yes, the data set is bigger than the available memory. I am evaluating native 
persistence, specifically SQL queries when pages have to be loaded from disk. 
Thus I need a data set that is significantly bigger than what fits the memory.

I made another attempt, loading smaller batches and leaving some time between 
batches for things to settle down. All went well.

Thus the problem seems to be related to concurrency and/or write workload. The 
fact that the 3 VMs all use the same physical disk (in the host) does not help 
the situation.

No, there are no duplicate keys. The exact same data set loads fine when 
slowing down the load.

As I mentioned, there were no logs indicating any connection, I/O or other 
issues.

Unfortunately I have to move on, and will not be able to rerun the scenario 
with additional logging at this time. Should I get to it later, I will update 
this thread.

Thanks...

Roger

-----Original Message-----
From: dkarachentsev [mailto:dkarachent...@gridgain.com] 
Sent: Tuesday, August 15, 2017 12:04 AM
To: user@ignite.apache.org
Subject: Re: Strange problems with Ignite native Persistence when Data exceeds 
Memory

Hi Roger,

It looks like not all data could fit in memory and pages started to swap into 
disk. This means that too many pages marked as dirty that causes more often and 
longer checkpointing, that with WAL writes may significantly slowdown data 
uploading. Please attach Ignite and GC logs and try to set
PersistenceStoreConfiguration.setWalMode() to LOG_ONLY or BACKGROUND (this will 
reduce disk loading).

Data loss looks strange, is it possible that you have duplicated entry keys?
DataStreamer by default does not override existed entries for performance 
reasons.

Thanks!
-Dmitry.



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