Some thoughts for our query language are below. These are taken from a comparison of two Neo4j graph query languages, Cypher and Gremlin, posted at
http://romikoderbynew.com/2012/02/22/gremlin-vs-cypher-initial-thoughts-neo4j/.
Simple graph traversals are much more efficient when using Gremlin
Queries in Gremlin are 30-50% faster for simple traversals
Cypher is ideal for complex traversals where back tracking is required
Cypher is our choice of query language for reporting
Gremlin is our choice of query language for simple traversals where projections are not required
Cypher has intrinsic table projection model, where Gremlins table projection model relies on AS steps which can be cumbersome when backtracking e.g. Back(), As() and
_CopySplit, where cypher is just comma separated matches
Cypher is much better suited for outer joins than Gremlin, to achieve similar results in gremlin requires parallel querying with CopySplit, where as in Cypher using the Match clause with
optional relationships
Gremlin is ideal when you need to retrieve very simple data structures
Table projection in gremlin can be very powerful, however outer joins can be very verbose
An example of Cypher
var resultSet = graphClient.RootNode
.StartCypher("root")
.Match(@"root-[:HOSTS]->(agency)
<-[:USER_BELONGS_TO]-(user)-[:USER_LINKED_TO_PROGRAM]
->(program)
<-[:HAS_PROGRAM]-(centre),
(program)<-[:HAS_SUGGESTED_PROGRAM]-(referralDecisionsSection)
<-[:REFERRAL_HAS_DECISIONS_SECTION]-(referral)-[:CREATED_BY]
->(createdByUser), (referral)-[:REFERRAL_HAS_WHO_SECTION]
->(whoSection)-[:HAS_PARTICIPANT]->(participant)")
.Where<Agency>(agency => agency.Key == userIdentifier.AgencyKey)
.And()
.Where<User>(user => user.Username == userIdentifier.Username)
.And()
.Where<Referral>(referral => referral.Completed == false)
.Return((user, program, centre, createdByUser, referral, whoSection, participant) =>
new ReferralByGroup
{
UserFamilyName = createdByUser.As<User>().FamilyName,
UserGivenName = createdByUser.As<User>().GivenName,
Program = program.As<Program>().Name,
Centre = centre.As<Centre>().Name,
ReferralId = referral.As<Referral>().UniqueId,
ReferralDate = whoSection.As<ReferralWhoSection>().ReferralDate,
ParticipantName = participant.As<ReferralParticipant>().Name,
ParticipantDisplayOrder = participant.As<ReferralParticipant>().DisplayOrder,
})
.Results
.ToArray();
An equivalent in Gremlin:
var resultSet = graphClient
.RootNode
.Out<Agency>(Hosts.TypeKey, a => a.Key == userIdentifier.AgencyKey)
.In<User>(UserBelongsTo.TypeKey, u => u.Username == userIdentifier.Username)
.Out<Program>(UserLinkedToProgram.TypeKey)
.As("Program")
.In<Centre>(HasProgram.TypeKey)
.As("Centre")
.BackV<Program>("Program")
.In<ReferralDecisionsSection>(HasSuggestedProgram.TypeKey)
.In<Referral>(ReferralHasDecisionsSection.TypeKey, r => r.Completed == false)
.As("ReferralId")
.Out<User>(CreatedBy.TypeKey)
.As("UserGivenName")
.As("UserFamilyName")
.BackV<Referral>("ReferralId")
.Out<ReferralWhoSection>(ReferralHasWhoSection.TypeKey)
.As("ReferralDate")
.Out<ReferralParticipant>(HasParticipant.TypeKey)
.As("ParticipantDisplayOrder")
.As("ParticipantName")
.Table
<ReferralByGroup, Program, Centre, Referral, User, User, ReferralWhoSection, ReferralParticipant,
ReferralParticipant>(
program => program.Name,
centre => centre.Name,
referral => referral.UniqueId,
user => user.FamilyName,
user => user.GivenName,
who => who.ReferralDate,
participant => participant.Name,
participant => participant.DisplayOrder
)
.ToArray();
And I will try to post a follow-up email with an equivalent in XGP, XDI Graph Patterns, the query language I’ve been trying to put together as an underpinning
for applying DLP style reasoning to an XDI dataset, similar to what Euler# allows for semantic web queries.
Kind regards,
Bill Barnhill
Booz Allen Hamilton - Belcamp,MD
Cell: 1-443-924-0824
Desk: 1-443-861-9102
