Hi, Yes the master/slave mode is only in the enterprise version.
Cheers Mark On 5 November 2014 14:50, Aileen Agricola <[email protected] > wrote: > 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. > -- 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.
