Tag: Neo4jClient

Neo4jClient Cypher ResultSet Support

Sometimes when doing Cypher queries the result is only one column and not multiple columns, therefore it makes sense to have a method in the fluent API to let this be known, so we do not have to map the column to an object type.

So fluent support to deserialize common result sets where cypher returns a result with only 1 column with the help of Tatham Oddie is completed.

So in the Neo4jClient you can do this, when the result from Cypher is one column via REST:

var result = agencySource
                        .StartCypher("a1")
                        .AddStartPoint("a2", agency.Reference)
                        .Match("p = allShortestPaths( a1-[*..20]-a2 )")
                        .Return<PathsResult>("p")
                        .ResultSet;

So, if you need cypher results with only one column then use .ResultSet instead of .Results, thus no need for expression tree column matches to assist the deserializer with multiple column names.

Here is a sample rest response with 1 column result that is suited perfectly for ResultSet.

{
  "data" : [ [ {
    "start" : "http://localhost:20001/db/data/node/215",
    "nodes" : [ "http://localhost:20001/db/data/node/215", "http://localhost:20001/db/data/node/0", "http://localhost:20001/db/data/node/219" ],
    "length" : 2,
    "relationships" : [ "http://localhost:20001/db/data/relationship/247", "http://localhost:20001/db/data/relationship/257" ],
    "end" : "http://localhost:20001/db/data/node/219"
  } ], [ {
    "start" : "http://localhost:20001/db/data/node/215",
    "nodes" : [ "http://localhost:20001/db/data/node/215", "http://localhost:20001/db/data/node/1", "http://localhost:20001/db/data/node/219" ],
    "length" : 2,
    "relationships" : [ "http://localhost:20001/db/data/relationship/248", "http://localhost:20001/db/data/relationship/258" ],
    "end" : "http://localhost:20001/db/data/node/219"
  } ] ],
  "columns" : [ "p" ]
}

If you wondering what the hell is agencySource, it is just node references, that I got using gremlin, which can spin off cypher queries, cool is it not?

var agencies = graphClient
                .RootNode
                .Out<Agency>(Hosts.TypeKey)
                .ToList();

This just enumerate through the list of nodes to run your cypher queries off the node directly! Have these imports declarations:

using Neo4jClient.ApiModels.Cypher;
using Neo4jClient.Gremlin;
using Neo4jClient.Cypher;

Summary

Use .ResultSet for single column result sets and use .Results when dealing with multiple column results.

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#Neo4j Gremlin queries with CopySplit/table leveraging Neo4jClient

Hi,

I would like to share gremlin querying using the .Net Neo4jClient.

Consider the following graph

image

The object is to produce a table of results that shows

  • ReferralDate (ReferralDecisionSection Node)
  • ReferralId (Referral Node)
  • FamilyName (User Node)
  • GivenName (User Node)
    The trick is we want to get all referrals but we also what referrals that do not have a who section, so the ReferralDate will be NULL. We also want to get referrals that are indirectly linked to a program (via a decision) but we also want the ones that are not indirectly linked to a program
ReferralDate ReferralId FamilyName GivenName
13 Jan 2012 1 Derbynew Romiko
NULL 2 Derbynew Romiko

So, what we doing is essentially left/right joins on ReferralNode, ReferralDecisionNode and Program.

Lets see how we can do this in .Net Neo4jClient

 return graphClient
                .RootNode
                .CopySplitV<Referral>((
                    new IdentityPipe()
                        .Out(Hosts.TypeKey, a => a.Key == userIdentifier.AgencyKey)
                        .In(UserBelongsTo.TypeKey, u => u.Username == userIdentifier.Username)
                        .Out(UserLinkedToProgram.TypeKey, p => p.Name == "Foundation")
                        .In(HasSuggestedProgram.TypeKey)
                        .In(ReferralHasDecisionsSection.TypeKey, r => r.Completed == false)
                        .AggregateV("ReferralWithProgramFoundation"),
                    new IdentityPipe()
                        .Out(Hosts.TypeKey, a => a.Key == userIdentifier.AgencyKey)
                        .In(ReferralBelongsTo.TypeKey, r => r.Completed == false)
                )
                .FairMerge()
                .ExceptV("ReferralWithProgramFoundation")
                .GremlinDistinct()
                .Out(ReferralHasWhoSection.TypeKey)
                .As("ReferralDate")
                .In(ReferralHasWhoSection.TypeKey)
                .As("ReferralId")
                .Out(CreatedBy.TypeKey, u => u.Username == userIdentifier.Username)
                .As("UserGivenName")
                .As("UserFamilyName")
                .Table(
                    who => who.ReferralDate,
                    referral => referral.UniqueId,
                    user => user.FamilyName,
                    user => user.GivenName
                );

Notice the following

  • CopySplit uses a concept of an identity pipe as a continuation of the previous output
  • CopySplit will execute the two queries in parallel
  • We are getting all the referrals in the system and then we are getting all the referrals in the system that have a program “Foundation”
  • We then store the referrals that have a program (“Foundation”) in a aggregate (variable)
  • We merge the parallel query results together with a FaireMerge
  • We exclude referrals that in a a Program called “Foundation”  with an Except
  • We then deduplicate results with GremlinDistinct
  • We then use AS to mark areas we need for table projections

Note: Using the AS clause within a CopySplit pipe in conjunction with table projections will produce undesired results, I am not sure if Gremlin supports such operations, if you know, please contact me.

Visit Marko Rodriguez for in depth discussions on Gremlin.