I've had some "complications" (namely, being hospitalized for a medical
issue), but I am running the job right now with OrientDB 2.2.20 and JRE
8u131. It's only a 32GB VM for now, but it's almost 50% complete and the
results are good so far.

On Mon, May 15, 2017 at 10:29 AM, Claudio Massi <[email protected]>
wrote:

> Hi John,
>    if you have 64gb ram, to avoid swapping jvm, try to keep process size
> below 64gb, so use Xmx + MaxDirectMemorySize below the available ram
>
> Try orientdb 2.2.20 with java 8u131-b11 , if using G1GC
>
> Monitor heap usage with: jstat -gc  pid 120s 9999999
>
> Monitor direct memory usage with any jmx tool (see
> http://andreylomakin.blogspot.it/2016/05/how-to-calculate-
> maximum-amount-of.html )
> - use jconsole, section MBeans, choose  
> com.orientechnologies.common.directmemory
> -> OByteBufferPoolMXBean -> Attribute
> - use MonBuffers.java (Source from Alan B. in https://gist.github.com/
> t3rmin4t0r/1a753ccdcfa8d111f07c  then increment Thread.sleep(2000), and
> run adding tools.jar in classpath )
> - use jmxterm (http://wiki.cyclopsgroup.org/jmxterm/)
> ...
>
> Claudio
>
> Il giorno venerdì 5 maggio 2017 18:57:26 UTC+2, John J. Szucs ha scritto:
>>
>> Andrey,
>>
>> THANK YOU! I will give this a try as soon as I can.
>>
>> I will also do some JVM profi
>>
>> — John
>>
>> On May 5, 2017, at 05:05, Andrey Lomakin <[email protected]> wrote:
>>
>> Hi John,
>> If you wish you could use this build till we will do official release
>> https://drive.google.com/file/d/0B2oZq2xVp841T2diVGt
>> TcmZ5OTQ/view?usp=sharing
>>
>> On Fri, May 5, 2017 at 11:58 AM Andrey Lomakin <[email protected]>
>> wrote:
>>
>>> HI John,
>>>
>>> I suppose you encountered issue https://github.com/orien
>>> technologies/orientdb/issues/7390
>>> We will provide release soon.
>>>
>>> Also please do not use such huge heap size we use heap only to keep
>>> temporary data, so I suggest you lower heap size to get ODB the chance to
>>> use more direct memory.
>>>
>>> On Fri, May 5, 2017 at 10:51 AM Luigi Dell'Aquila <[email protected]>
>>> wrote:
>>>
>>>> Hi John,
>>>>
>>>> How are you doing the import? Are you working in transaction? Some code
>>>> will help us understand where the problem is
>>>>
>>>> Thanks
>>>>
>>>> Luigi
>>>>
>>>>
>>>> 2017-05-05 3:53 GMT+02:00 John J. Szucs <[email protected]>:
>>>>
>>>>> Hello, OrientDB community! It's me again with another question.
>>>>>
>>>>> I am still working on my project and have encountered another serious
>>>>> challenge: it seems that writing to indices (especially edge indices?) can
>>>>> cause OrientDB's direct (non-JVM) memory usage to grow without bounds 
>>>>> until
>>>>> the system effectively grinds to a halt due to swap.
>>>>>
>>>>> The specific use case is building a graph based on (English)
>>>>> Wikipedia. There are approximately 17.4M vertices representing pages
>>>>> (including articles, categories, and various meta pages). These vertices
>>>>> are connected by approximately 65M (at last count) edges. There are a few
>>>>> super-nodes. For example, the vertex representing https://en.wikipe
>>>>> dia.org/wiki/United_States has (at last count) 306K incoming edges
>>>>> and 822 outgoing edges. However, the degree of the vertices roughly 
>>>>> follows
>>>>> a Zipf distribution and the vast majority of vertices have only a few 
>>>>> (<10)
>>>>> total (in and out) edges. There are also some other vertex and edge types
>>>>> for lexical data, but I think those are secondary to the issue.
>>>>>
>>>>> Per previous discussion here and on StackOverflow, I have added
>>>>> automatic edge indices on in, out, or the composite of the two to optimize
>>>>> edge queries. When I run the process to extract, transform, and load the
>>>>> data from Wikipedia's XML dumps (using my own ETL code, not OrientDB's),
>>>>> after 24-48 hours, the Linux System Monitor shows that physical memory
>>>>> usage has reached 99.9% and then swap usage begins to grow. At this point,
>>>>> the process is effectively halted by swap thrashing.
>>>>>
>>>>> I am running this on a Fedora 25 Linux VM with 64GB RAM and 16 CPU
>>>>> cores allocated. The JVM settings are as follows:
>>>>>
>>>>> -Xmx32g -Xms32g -server -XX:+PerfDisableSharedMem -XX:+UseG1GC
>>>>> -XX:MaxDirectMemorySize=64413m -Dstorage.wal.syncOnPageFlush=false
>>>>>
>>>>> The MaxDirectMemorySize parameter is recommended by OrientDB itself,
>>>>> during start-up with the "out-of-memory errors" warning. It does seem odd
>>>>> to me that Xmx+MaxDirectMemorySize>available RAM, but I'm more of a
>>>>> deep R&D (not DevOps) guy, so I'm just accepting that unless someone
>>>>> advises me otherwise.
>>>>>
>>>>> If I disable the edge indices, then the process runs fine and
>>>>> completes in a "reasonable" (for it) amount of time: 2-3 days. Of course,
>>>>> if I do this, my run-time performance suffers intolerably.
>>>>>
>>>>> I am running this with OrientDB 2.2.19. I was able to quickly get my
>>>>> code to build with 3.0 M1, but some of the unit tests fail and I am under
>>>>> far too much pressure about this issue from my leadership to try to
>>>>> troubleshoot them right now.
>>>>>
>>>>> What can I do to solve this issue? Thanks in advance for your help!
>>>>>
>>>>> -- John
>>>>>
>>>>> --
>>>>>
>>>>> ---
>>>>> You received this message because you are subscribed to the Google
>>>>> Groups "OrientDB" group.
>>>>> To unsubscribe from this group and stop receiving emails from it, send
>>>>> an email to [email protected].
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>>>>>
>>>>
>>>>
>>>> --
>>>>
>>>> ---
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>>>>
>>> --
>>> Best regards,
>>> Andrey Lomakin, R&D lead.
>>> OrientDB Ltd
>>>
>>> twitter: @Andrey_Lomakin
>>> linkedin: https://ua.linkedin.com/in/andreylomakin
>>> blogger: http://andreylomakin.blogspot.com/
>>>
>> --
>> Best regards,
>> Andrey Lomakin, R&D lead.
>> OrientDB Ltd
>>
>> twitter: @Andrey_Lomakin
>> linkedin: https://ua.linkedin.com/in/andreylomakin
>> blogger: http://andreylomakin.blogspot.com/
>>
>> --
>>
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