What is your use-case? What is the large amount of data you're writing to the 
graph?
What OS are you working on?
And what Neo4j version?

Increasing the memory mapping settings also helps with writes, esp. the 
settings for the nodestore and relationship-store, the more of that can be 
memory mapped the more can be written to in parallel.

Neo4j supports concurrent writes, but it 

#1 serializes commits on writing to the transaction log
#2 locks nodes and relationships if you change properties 
#3 locks both nodes if you add a relationship

Common practice is to have a large enough tx size (e.g. 30-50k elements) per 
commit and also aggregate updates that way that they write to different, 
disjunct subgraphs of the data.

HTH,


Michael


otherwise see the blog posts refered to from: http://neo4j.org/develop/import


Am 17.12.2013 um 19:49 schrieb Guan Guan <[email protected]>:

> Hi,
> 
> 
> 
> In our use case, we need to do a lot of data importing/updating everyday ( 
> billions of nodes/relationships ). 
> 
> 
> 
> What's the way to tuning the configuration to boost performance?
> 
> 
> 
> Does the kernel config help data ingestion? Settings like 
> 'neostore.propertystore.db.strings.mapped_memory' is for query cache only, am 
> I correct? Does these parameter help with data import performance?   
> 
> 
> 
> 
> 
> One more question, how does neo4J embedded do with concurrent data importing? 
> I have multiple threads writing to embedded database at the same time, I 
> always get locking exception that multiple threads try to lock the same 
> relationship. What's the recommend way for multiple threads data ingestion?
> 
> 
> 
> 
> 
> Thanks,
> 
> 
> 
> Guan
> 
> 
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