Oh yeah Michael I'm new in traversal api, after I read the doc about traversal api, should I use it with java? I mean is there others way to use traversal api, ex: I can run the syntax traversal api in neo4j shell or http? if there is, please provide me a reference how to use traversal api not through java.
Thank you. On Tuesday, April 1, 2014 8:31:25 PM UTC+7, Michael Hunger wrote: > > For the traversal framework check out: > http://docs.neo4j.org/chunked/milestone/tutorial-traversal.html > > > On Tue, Apr 1, 2014 at 3:09 PM, Rio Eduardo <rioedu...@gmail.com<javascript:> > > wrote: > >> Hi Michael, >> >> you said "In general if you really want to do these deep traversals you >> might be better off (in terms of performance) using the traversal-API with >> an appropriate uniqueness constraint, like node-path". Please give me any >> references so I can learn it. or Does it mean you suggest me to use Gremlin? >> >> Thank you. >> >> >> On Monday, March 31, 2014 8:09:32 PM UTC+7, Michael Hunger wrote: >> >>> Just use a dataset that you can reason about and check if they work >>> correctly. >>> >>> Hard for me to be the consistency checker on your queries :) >>> >>> In general if you really want to do these deep traversals you might be >>> better off (in terms of performance) using the traversal-API with an >>> appropriate uniqueness constraint, like node-path. >>> >>> >>> >>> >>> On Mon, Mar 31, 2014 at 1:09 PM, Rio Eduardo <rioedu...@gmail.com>wrote: >>> >>>> Hello again Michael. >>>> >>>> I just want to make sure that my query is correct to find friends of >>>> friends at depth of four and five. Please help me by checking my query. >>>> >>>> Query at depth of four: >>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User) >>>> WHERE U.user_id=1 >>>> WITH DISTINCT U, FU, FFU >>>> WHERE FFU<>U >>>> WITH DISTINCT U, FU, FFU >>>> MATCH (FFU:User)-[FFF:Friend]->(FFFU:User) >>>> WHERE FFFU<>FU >>>> WITH DISTINCT U, FFU, FFFU >>>> MATCH (FFFU:User)-[FFFF:Friend]->(FFFFU:User) >>>> WHERE FFFFU<>FFU AND FFFFU<>U AND NOT (U)-[:Friend]->(FFFFU) >>>> RETURN DISTINCT FFFFU.username; >>>> >>>> Query at depth of five: >>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User) >>>> WHERE U.user_id=1 >>>> WITH DISTINCT U, FU, FFU >>>> WHERE FFU<>U >>>> WITH DISTINCT U, FU, FFU >>>> MATCH (FFU:User)-[FFF:Friend]->(FFFU:User) >>>> WHERE FFFU<>FU >>>> WITH DISTINCT U, FFU, FFFU >>>> MATCH (FFFU:User)-[FFFF:Friend]->(FFFFU:User) >>>> WHERE FFFFU<>FFU >>>> WITH DISTINCT U, FFFU, FFFFU >>>> MATCH (FFFFU:User)-[FFFFF:Friend]->(FFFFFU:User) >>>> WHERE FFFFFU<>FFFU AND FFFFFU<>U AND NOT (U)-[:Friend]->(FFFFFU) >>>> RETURN DISTINCT FFFFFU.username; >>>> >>>> I need your help so much. >>>> Thank you. >>>> >>>> >>>> On Sunday, March 30, 2014 7:42:27 PM UTC+7, Michael Hunger wrote: >>>> >>>>> Split it up in one more intermediate step, the intermediate steps are >>>>> there to get the cardinality down, so it doesn't have to match billions >>>>> of >>>>> paths, only millions or 100k >>>>> >>>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User)-[FFF: >>>>> Friend]->(FFFU:User) >>>>> WHERE U.user_id=1 >>>>> WITH DISTINCT U, FU, FFU >>>>> WHERE FFU<>U >>>>> WITH DISTINCT U, FFU >>>>> MATCH (FFU:User)-[FFF:Friend]->(FFFU:User) >>>>> WHERE NOT (U)-[:Friend]->(FFFU) >>>>> RETURN distinct FFFU.username; >>>>> >>>>> >>>>> >>>>> >>>>> On Sun, Mar 30, 2014 at 1:29 PM, Rio Eduardo <rioedu...@gmail.com>wrote: >>>>> >>>>>> Please help me again Michael. >>>>>> >>>>>> You ever said: >>>>>> >>>>>> I would also change: >>>>>> >>>>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User) >>>>>> WHERE U.user_id=1 AND FFU.user_id<>U.user_id AND NOT >>>>>> (U)-[:Friend]->(FFU) >>>>>> RETURN FFU.username >>>>>> >>>>>> to >>>>>> >>>>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User) >>>>>> WHERE U.user_id=1 >>>>>> WITH distinct U, FFU >>>>>> WHERE FFU<>U AND NOT (U)-[:Friend]->(FFU) >>>>>> RETURN FFU.username >>>>>> >>>>>> Query above is to find friends of friends at depth of two. And I >>>>>> would like to find friends of friends at depth of three, when I use >>>>>> model >>>>>> of your query, it returns result longer than mine and the result is much >>>>>> more than mine. Ok so here is model of your query at depth of three: >>>>>> >>>>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User)-[FFF: >>>>>> Friend]->(FFFU:User) >>>>>> WHERE U.user_id=1 >>>>>> WITH DISTINCT U, FU, FFU, FFFU >>>>>> WHERE FFU<>U AND FFFU<>FU AND NOT (U)-[:Friend]->(FFFU) >>>>>> RETURN FFFU.username; >>>>>> >>>>>> ... >>>>>> >>>>>> 118858 rows >>>>>> 20090 ms >>>>>> >>>>>> Mine: >>>>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User)-[FFF: >>>>>> Friend]->(FFFU:User) >>>>>> WHERE U.user_id=1 AND FFU<>U AND FFFU<>FU AND NOT >>>>>> (U)-[:Friend]->(FFFU) >>>>>> RETURN DISTINCT FFFU.username; >>>>>> >>>>>> ... >>>>>> >>>>>> 950 rows >>>>>> 18133 ms >>>>>> >>>>>> Please help me, Why is model of your query longer than mine and >>>>>> return much more results than mine? >>>>>> >>>>>> Thank you. >>>>>> >>>>>> >>>>>> >>>>>> On Friday, March 28, 2014 8:30:20 PM UTC+7, Michael Hunger wrote: >>>>>> >>>>>>> Rio, >>>>>>> >>>>>>> was this your first run of both statements? If so, please run them >>>>>>> for a second time. >>>>>>> And did you create an index or constraint for :User(user_id) ? >>>>>>> >>>>>>> MATCH (U:User) RETURN COUNT(U); >>>>>>> >>>>>>> I would also change: >>>>>>> >>>>>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User) >>>>>>> WHERE U.user_id=1 AND FFU.user_id<>U.user_id AND NOT >>>>>>> (U)-[:Friend]->(FFU) >>>>>>> RETURN FFU.username >>>>>>> >>>>>>> to >>>>>>> >>>>>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User) >>>>>>> WHERE U.user_id=1 >>>>>>> WITH distinct U, FFU >>>>>>> WHERE FFU<>U AND NOT (U)-[:Friend]->(FFU) >>>>>>> RETURN FFU.username >>>>>>> >>>>>>> I quickly created a dataset on my machine: >>>>>>> >>>>>>> cypher 2.0 foreach (i in range(1,1000) | create (:User {id:i})); >>>>>>> >>>>>>> create constraint on (u:User) assert u.id is unique; >>>>>>> >>>>>>> match (u1:User),(u2:User) with u1,u2 where rand() < 0.1 create >>>>>>> (u1)-[:Friend]->(u2); >>>>>>> >>>>>>> Relationships created: 99974 >>>>>>> >>>>>>> 778 ms >>>>>>> >>>>>>> match (u:User) return count(*); >>>>>>> >>>>>>> +----------+ >>>>>>> | count(*) | >>>>>>> +----------+ >>>>>>> | 1000 | >>>>>>> +----------+ >>>>>>> 1 row >>>>>>> *4 ms* >>>>>>> >>>>>>> >>>>>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User) >>>>>>> WHERE U.id=1 >>>>>>> WITH distinct U, FFU >>>>>>> WHERE FFU<>U AND NOT (U)-[:Friend]->(FFU) >>>>>>> RETURN FFU.id; >>>>>>> >>>>>>> ... >>>>>>> >>>>>>> 910 rows >>>>>>> >>>>>>> 101 ms >>>>>>> >>>>>>> but even your query takes only >>>>>>> >>>>>>> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User) >>>>>>> WHERE U.id=1 AND FFU.id<>U.id AND NOT (U)-[:Friend]->(FFU) >>>>>>> RETURN FFU.id; >>>>>>> >>>>>>> ... >>>>>>> >>>>>>> 8188 rows >>>>>>> >>>>>>> 578 ms >>>>>>> >>>>>>> >>>>>>> On Fri, Mar 28, 2014 at 2:08 PM, Lundin <lundin....@gmail.com> >>>>>>> wrote: >>>>>>> > >>>>>>> > ms, it is milliseconds. >>>>>>> > >>>>>>> > What is the corresponding result for a SQL db ? >>>>>>> > MATCH (n:User)-[:Friend*3]-(FoFoF) return FoFoF; >>>>>>> > >>>>>>> > Albeit a valid search is it something useful ? I would think >>>>>>> finding a specific persons FoFoF in either end, as a starting point or >>>>>>> end >>>>>>> point, would be a very realistic scenario. Adding an Index on User:name >>>>>>> and >>>>>>> query for a User with name:Rio try to find his FoFoF. >>>>>>> > >>>>>>> > Yes, neo4j has been kind and exposed various function, like >>>>>>> shortestpath in cypher >>>>>>> > http://docs.neo4j.org/refcard/2.0/ >>>>>>> > >>>>>>> > Also look at some gist examples >>>>>>> > https://github.com/neo4j-contrib/graphgist/wiki >>>>>>> > >>>>>>> > Den fredagen den 28:e mars 2014 kl. 05:00:22 UTC+1 skrev Rio >>>>>>> Eduardo: >>>>>>> >> >>>>>>> >> Thank you so much for the reply Lundin. I really apreciate it. >>>>>>> Okay, yesterday I just tested my experiment again. And the result was >>>>>>> not >>>>>>> what I imagined and expected before. Okay, before I tested 1M users, I >>>>>>> reduced the number of users into 1000 users and tested it not in my >>>>>>> social >>>>>>> network but directly in database only(Neo4j Shell) to find out that it >>>>>>> was >>>>>>> not caused by the performance of pc. But the result of returning 1000 >>>>>>> users >>>>>>> was 200ms and 1 row and the result of returning friends at depth of two >>>>>>> was >>>>>>> 85000ms and 2500 rows and are 200ms and 85000ms fast to you? and what >>>>>>> does >>>>>>> ms stand for? is it milliseconds or microseconds? >>>>>>> >> >>>>>>> >> the query I use for returning 1000 users is >>>>>>> >> MATCH (U:User) RETURN COUNT(U); >>>>>>> >> >>>>>>> >> and the query I use for returning friends at depth of two is >>>>>>> >> MATCH (U:User)-[F:Friend]->(FU:User)-[FF:Friend]->(FFU:User) >>>>>>> >> WHERE U.user_id=1 AND FFU.user_id<>U.user_id AND NOT >>>>>>> (U)-[:Friend]->(FFU) >>>>>>> >> RETURN FFU.username >>>>>>> >> >>>>>>> >> Please note that I tested with default configuration of Neo4j and >>>>>>> created users with 1000 random nodes and created friends relationships >>>>>>> with >>>>>>> 50000 random relationships(1 user has 50 friends). Each relationship >>>>>>> has a >>>>>>> label Friend and no properties on it. Each node has a label User, 4 >>>>>>> properties: user_id, username, password and profile_picture. Each >>>>>>> property >>>>>>> has a value of 1-60 characters. average of characters of user_id=1-1000 >>>>>>> characters, all usernames have 10 characters randomly, all passwords >>>>>>> have >>>>>>> 60 characters because I MD5 it, and profile_picture has 1-60 characters. >>>>>>> >> >>>>>>> >> And about your statement "Otherwise if you really need to present >>>>>>> that many "things" just paging the result with SKIP,LIMIT. I has never >>>>>>> made >>>>>>> sense to present 1M of anything at a time for a user.", I already did >>>>>>> according to your statement above but it is still the same, Neo4j >>>>>>> returns >>>>>>> result slower. >>>>>>> >> >>>>>>> >> And I'm wondering if Neo4j already applied one of graph >>>>>>> algorithms(shortest path, djikstra, A*, etc) in its system or not. >>>>>>> >> >>>>>>> >> Thank you. >>>>>>> >> >>>>>>> >> >>>>>>> >> On Friday, March 28, 2014 3:43:49 AM UTC+7, Lundin wrote: >>>>>>> >>> >>>>>>> >>> Rio, any version will do. They can all handle million nodes on >>>>>>> common hardware, no magic at all. When hundred of millions of billions >>>>>>> then >>>>>>> we might need to look into specfication more in detail. But in that >>>>>>> case >>>>>>> with that kind of data there are other bottlencks for a social network >>>>>>> or >>>>>>> any web appp that needs to be taken care of as well. >>>>>>> >>> >>>>>>> >>> you said: >>>>>>> >>>> >>>>>>> >>>> Given any two persons chosen at random, is there a path that >>>>>>> connects them that is at most five relationships long? For a social >>>>>>> network >>>>>>> containing 1,000,000 people, each with approximately 50 friends, the >>>>>>> results strongly suggest that graph databases are the best choice for >>>>>>> connected data. And graph database can still work 150 times faster than >>>>>>> relational database at third degree and 1000 times faster at fourth >>>>>>> degre >>>>>>> >>> >>>>>>> >>> >>>>>>> >>> I fail to see how this is connected to your attempt to list 1M >>>>>>> users in one go at the first page. You would want to seek if there is a >>>>>>> relationship and return that path between users. You need two start >>>>>>> nodes >>>>>>> and seek a path by traveser the relationsip rather than scan tables and >>>>>>> that would be the comparison. >>>>>>> >>> Otherwise if you really need to present that many "things" just >>>>>>> paging the result with SKIP,LIMIT. I has never made sense to present 1M >>>>>>> of >>>>>>> anything at a time for a user. Again, that wouldn't really serve your >>>>>>> experiment much good to prove graph theory. >>>>>>> >>> >>>>>>> >>> What is the result of MATCH(U:User) RETURN count(U); ? >>>>>>> >>> >>>>>>> >>> Also when you do your test make sure to add the warm/cold cache >>>>>>> effect (better/worse performance) >>>>>>> >>> >>>>>>> >>> Den torsdagen den 27:e mars 2014 kl. 17:57:10 UTC+1 skrev Rio >>>>>>> Eduardo: >>>>>>> >>>> >>>>>>> >>>> I just knew about memory allocation and just read Server >>>>>>> Performance Tuning of Neo4j. neo4j.properties: >>>>>>> >>>> # Default values for the low-level graph engine >>>>>>> >>>> >>>>>>> >>>> #neostore.nodestore.db.mapped_memory=25M >>>>>>> >>>> #neostore.relationshipstore.db.mapped_memory=50M >>>>>>> >>>> #neostore.propertystore.db.mapped_memory=90M >>>>>>> >>>> #neostore.propertystore.db.strings.mapped_memory=130M >>>>>>> >>>> #neostore.propertystore.db.arrays.mapped_memory=130M >>>>>>> >>>> >>>>>>> >>>> Should I change this to get high performance? If yes, please >>>>>>> suggest me. >>>>>>> >>>> >>>>>>> >>>> And I just knew about Neo4j Licenses, they are Community, >>>>>>> Personal, Startups, Business and Enterprise. And at Neo4j website all >>>>>>> features are explained. So which Neo4j should I use for my case that >>>>>>> has >>>>>>> millions nodes and relationships? >>>>>>> >>>> >>>>>>> >>>> Please answer. I need your help so much. >>>>>>> >>>> >>>>>>> >>>> Thanks. >>>>>>> >>>> >>>>>>> >>>> On Tuesday, March 25, 2014 12:03:58 AM UTC+7, Rio Eduardo wrote: >>>>>>> >>>>> >>>>>>> >>>>> I'm testing my thesis which is about transforming from >>>>>>> relational database to graph database. After transforming from >>>>>>> relational >>>>>>> database to graph database, I will test their own performance according >>>>>>> to >>>>>>> query response time and throughput. In relational database, I use MySQL >>>>>>> while in graph database I use Neo4j for testing. I will have 3 Million >>>>>>> more >>>>>>> nodes and 6 Million more relationships. But when I just added 60000 >>>>>>> nodes, >>>>>>> my Neo4j is already dead. When I tried to return all 60000 nodes, it >>>>>>> returned unknown. I did the same to MySQL, I added 60000 records but it >>>>>>> could return all 60000 records. It's weird because it's against the >>>>>>> papers >>>>>>> I read that told me graph database is faster than relational database >>>>>>> So >>>>>>> Why is Neo4j slower(totally dead) in lower specification of pc/notebook >>>>>>> while MySQL is not? And What specification of pc/notebook do I should >>>>>>> use >>>>>>> to give the best performance during testing with millions of nodes and >>>>>>> relationships? >>>>>>> >>>>> >>>>>>> >>>>> Thank you. >>>>>>> > >>>>>>> > -- >>>>>>> > 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 neo4j+un...@googlegroups.com. >>>>>>> >>>>>>> > 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 neo4j+un...@googlegroups.com. >>>>>> 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 neo4j+un...@googlegroups.com. >>>> 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 neo4j+un...@googlegroups.com <javascript:>. >> For more options, visit https://groups.google.com/d/optout. >> > > -- You received this message because you are subscribed to the Google Groups "Neo4j" group. 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