Hi Luanne,

It's hard to answer your question, but I will try it..

*When you create relationships, are the nodes on either end already 
persisted?*
Almost never.. It might happen that some of the nodes are already persisted 
and also that all are new.. But how would I save "only the relationship", 
saying I have both of nodes saved with depth 0, how would I implement to 
save only the relationship, as in my entity object I have Sets referring to 
the "connected" nodes?

*Or are you creating both new nodes and relationships to those in one go 
via the save with depth -1?*
Yes often I am creating at same time new nodes and relationships. I feel 
like there is something with respect to this question, should I clearly 
separate the saving of nodes and relationships?
 
*How many relationships approximately are created via a single save?*
I can only give you app. estimate, so let's say 10-15..

Any idea?

On Wednesday, November 18, 2015 at 4:22:47 AM UTC+1, Luanne wrote:
>
> Hi Ivan,
>
> When you create relationships, are the nodes on either end already 
> persisted? Or are you creating both new nodes and relationships to those in 
> one go via the save with depth -1? How many relationships approximately are 
> created via a single save?
>
> -Luanne
>
> On Wed, Nov 18, 2015 at 6:16 AM, Michael Hunger <
> [email protected] <javascript:>> wrote:
>
>> Can you try neo4j-ogm 1.1.4-SNAPSHOT
>>
>> You might need to add m2.neo4j.org as maven repository with snapshots 
>> enabeld.
>>
>> I think it has some fixes in this regard.
>>
>> Michael
>>
>> Am 17.11.2015 um 17:12 schrieb Ivan Senic <[email protected] 
>> <javascript:>>:
>>
>> Hi,
>>
>> I am quite new to neoj4 and I started using it with the neo4j-ogm to map 
>> my java objects into the graph and back. I am experiencing quite a strange 
>> behavior when I start saving entities via OGM into the graph. It seams that 
>> the memory usage rises fast on the neo4j-server (I also experienced few OOM 
>> Exceptions):
>>
>>
>> <https://lh3.googleusercontent.com/-ydCCbXByqXo/VktNm-PHijI/AAAAAAAAAG8/xp9AKbOwiqw/s1600/neo4j.png>
>>
>>
>> <https://lh3.googleusercontent.com/-_wMShgRo8RE/VktNhEFxoPI/AAAAAAAAAG0/YdVArB8EzkU/s1600/neo4jGoesOutOfMemory.png>
>>  
>>
>>
>> As you can see from screens the memory rises up in terms of the seconds. 
>> I started by saving with depth of 1 (behavior described by pic1) and then 
>> also tried with depth -1 (that's pic 2 where I always hit OOM exception)., 
>> It's important to mention that saving is also very slow, making some of my 
>> requests time-out (with 3 seconds time out).. Setting the depth to 0 works 
>> as expected (in terms of memory and speed), but then I get no relationships 
>> in the graph.
>>
>>
>> The interesting thing is that I am not saving too much data at all. In my 
>> use-case I end up with about 6k nodes and 6k relationships when all 
>> requests are processed. Imo that's nothing for the neo4j, thus I am 
>> surprised I am seeing this.
>>
>>
>> With the graph I am trying to represent all the classes (interfaces, 
>> annotations, methods, etc) that are loaded in the JVM by starting a small 
>> example application. So with every new class being loaded I need to update 
>> the graph in order to store information I can read from the byte-code.
>>
>>
>> The only "special" thing might be that I have a lot of bi-directional 
>> relationships (for example class implements interface, interface is 
>> realized by class) .. Here are some screens of my graph:
>>
>>
>>
>> <https://lh3.googleusercontent.com/-_Ew1FYyCCMY/VktQwWRY4GI/AAAAAAAAAHQ/2SoTJZzuIoU/s1600/neo2.png>
>>
>>
>> <https://lh3.googleusercontent.com/-42s8twVJgyI/VktQtfxQIXI/AAAAAAAAAHI/I9D4w5byjaE/s1600/neo1.png>
>>
>>
>> It must be that I am doing something wrong.. And it has to be related to 
>> the OGM.. It can not be that saving such a small number of nodes pushes the 
>> memory so high..
>>
>> Here are some more information about my setup: neo4j 2.3.0, neo44-ogm 
>> 1.1.3, Ubuntu 14.04, JDK 1.7.0_70. I have no special settings than the 
>> default ones.
>>
>> Any help would be great..
>>
>>
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