Hi Liu, I'm forwarding your questions to our google groups. The community will assist.
best, Aileen ------ I haven't found the master-slave mode in community version, is it only included in enterprise version? Thanks Best regards LIU > > I want to consult you about the neo4j enterprise version's purchase > problem. What's the purchase way and how much. Thanks in advance. > > Best regards > > > 2014-10-28 7:58 GMT+08:00 Aileen Agricola < > [email protected]>: > >> Hi Liu, >> >> You will receive a response directly from our community. >> >> best, >> Aileen >> >> >> Aileen Agricola >> Web Program Manager | Neo Technology >> [email protected] | 206.437.2524 >> >> *Join us at GraphConnect 2014 SF! graphconnect.com >> <http://graphconnect.com/>* >> *As a friend of Neo4j, use discount code *KOMPIS >> <https://graphconnect2014sf.eventbrite.com/?discount=KOMPIS>* for $100 off >> registration* >> >> >> On Mon, Oct 27, 2014 at 4:57 PM, LIU Xiaobing <[email protected]> wrote: >> >>> Hi Aileen, >>> Thanks, do you mean that you have forwarded my question below to the >>> mail [email protected]? I haven't received any response. If i want >>> to find the response, how can i do? wait an email from >>> [email protected] or search from the neo4j google group? Here is >>> my quesion: >>> >>> Hi experts, >>> Now I encountering one performance problem about neo4j. I try to >>> write some data to neo4j, the data scale is about billions and the >>> relationships between the data is just people-people. When I use py2neo to >>> query and write data to neo4j, i found that it's very slow. >>> The query clause i use: >>> create_rels = 'MERGE(first:{TYPE1} {{id:'{val1}'}}) MERGE >>> (second:{TYPE2} {{id:'{val2}'}}) MERGE (first)-[r:{RTYPE}]->(second) ON >>> CREATE SET r.weight={weight_set} ON MATCH SET {weight_compute} WITH r SET >>> r.half_life={half_life},r.update_time=TIMESTAMP(),r.threshold={threshold} >>> WITH r WHERE r.weight<r.threshold DELETE r' >>> >>> self.query=neo.CypherQuery(self.graph_db,self.create_rels.format(TYPE1=entity1[0],val1=entity1[1],TYPE2=entity2[0],val2=entity2[1],RTYPE=rel_type,weight_set=weight_set,weight_compute=CYPHER_WEIGHT_COMPUTE,half_life=half_life,threshold=threshold)) >>> self.query.execute() >>> >>> the CYPHER_WEIGHT_COMPUTE definition is >>> "r.weight=r.weight+r.weight*EXP((TIMESTAMP()-r.update_time)/(r.half_life*1.0))" >>> >>> The purpose of the clause is that the nodes and relationships will >>> be created when the nodes are not in graph db and the properties of >>> relationships will be update if they are. >>> I have tried such ways to gain the performance, but it didn't work >>> well. >>> 1) configure the configure file of server >>> neo4j-wrapper.conf: >>> wrapper.java.initmemory=4096 >>> wrapper.java.maxmemory=4096 >>> wrapper.java.minmemory=4096 >>> >>> neo4j.properties >>> neostore.nodestore.db.mapped_memory=256M >>> neostore.relationshipstore.db.mapped_memory=256M >>> neostore.propertystore.db.mapped_memory=256M >>> neostore.propertystore.db.strings.mapped_memory=128M >>> neostore.propertystore.db.arrays.mapped_memory=128M >>> >>> node_auto_indexing=true >>> relationship_auto_indexing=true >>> >>> 2) Create constraints of the properties of nodes in order to create >>> indexes >>> Cypher clause: create constraint on (n:UID) assert n.id IS UNIQUE >>> >>> When i check the load of server who's equipped with 16 4-core >>> processors, i found that the cpu's load is very high while the network and >>> io's load is not. Does Cypher clause is cpu-greedy? How can i dig the >>> performance using other ways? Thanks very much. >>> >>> By the way, the version of neo4j is 2.1.5 stable verion, version of >>> client py2neo is 1.1.6, RAM of the server is 8G >>> >>> Best regards >>> >>> 2014-10-27 23:13 GMT+08:00 Aileen Agricola < >>> [email protected]>: >>> >>>> Hi Liu, >>>> >>>> I'm forwarding your question to our google group >>>> [email protected] >>>> Please provide any additional information there. >>>> >>>> best, >>>> >>>> Aileen Agricola >>>> Web Program Manager | Neo Technology >>>> [email protected] | 206.437.2524 >>>> >>>> *Join us at GraphConnect 2014 SF! graphconnect.com >>>> <http://graphconnect.com/>* >>>> *As a friend of Neo4j, use discount code *KOMPIS >>>> <https://graphconnect2014sf.eventbrite.com/?discount=KOMPIS>* for $100 off >>>> registration* >>>> >>>> >>>> On Mon, Oct 27, 2014 at 8:08 AM, LIU Xiaobing <[email protected]> >>>> wrote: >>>> >>>>> Hi experts, >>>>> Now I encountering one performance problem about neo4j. I try to >>>>> write some data to neo4j, the data scale is about billions and the >>>>> relationships between the data is just people-people. When I use py2neo to >>>>> query and write data to neo4j, i found that it's very slow. >>>>> The query clause i use: >>>>> create_rels = 'MERGE(first:{TYPE1} {{id:'{val1}'}}) MERGE >>>>> (second:{TYPE2} {{id:'{val2}'}}) MERGE (first)-[r:{RTYPE}]->(second) ON >>>>> CREATE SET r.weight={weight_set} ON MATCH SET {weight_compute} WITH r SET >>>>> r.half_life={half_life},r.update_time=TIMESTAMP(),r.threshold={threshold} >>>>> WITH r WHERE r.weight<r.threshold DELETE r' >>>>> >>>>> self.query=neo.CypherQuery(self.graph_db,self.create_rels.format(TYPE1=entity1[0],val1=entity1[1],TYPE2=entity2[0],val2=entity2[1],RTYPE=rel_type,weight_set=weight_set,weight_compute=CYPHER_WEIGHT_COMPUTE,half_life=half_life,threshold=threshold)) >>>>> self.query.execute() >>>>> >>>>> the CYPHER_WEIGHT_COMPUTE definition is >>>>> "r.weight=r.weight+r.weight*EXP((TIMESTAMP()-r.update_time)/(r.half_life*1.0))" >>>>> >>>>> The purpose of the clause is that the nodes and relationships will >>>>> be created when the nodes are not in graph db and the properties of >>>>> relationships will be update if they are. >>>>> I have tried such ways to gain the performance, but it didn't work >>>>> well. >>>>> 1) configure the configure file of server >>>>> neo4j-wrapper.conf: >>>>> wrapper.java.initmemory=4096 >>>>> wrapper.java.maxmemory=4096 >>>>> wrapper.java.minmemory=4096 >>>>> >>>>> neo4j.properties >>>>> neostore.nodestore.db.mapped_memory=256M >>>>> neostore.relationshipstore.db.mapped_memory=256M >>>>> neostore.propertystore.db.mapped_memory=256M >>>>> neostore.propertystore.db.strings.mapped_memory=128M >>>>> neostore.propertystore.db.arrays.mapped_memory=128M >>>>> >>>>> node_auto_indexing=true >>>>> relationship_auto_indexing=true >>>>> >>>>> 2) Create constraints of the properties of nodes in order to >>>>> create indexes >>>>> Cypher clause: create constraint on (n:UID) assert n.id IS >>>>> UNIQUE >>>>> >>>>> When i check the load of server who's equipped with 16 4-core >>>>> processors, i found that the cpu's load is very high while the network and >>>>> io's load is not. Does Cypher clause is cpu-greedy? How can i dig the >>>>> performance using other ways? Thanks very much. >>>>> >>>>> By the way, the version of neo4j is 2.1.5 stable verion, version of >>>>> client py2neo is 1.1.6, RAM of the server is 8G >>>>> >>>>> >>>>> -- >>>>> Best Regards >>>>> LIU Xiaobing 刘小兵 >>>>> >>>>> >>>> >>> >>> >>> -- >>> Best Regards >>> LIU Xiaobing 刘小兵 >>> >>> >> > > > -- > Best Regards > LIU Xiaobing 刘小兵 > > -- You received this message because you are subscribed to the Google Groups "Neo4j" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. For more options, visit https://groups.google.com/d/optout.
