Hi I'm new to gremlin and need to, basically, get everything current to return as a json file. I'm using Syndeia which has a raw query option. I'm having difficulty figuring out how to get both vertices and edges to output. This is what I have thus far:
g.V().has('sLabel','Artifact').has('_isLatest','TRUE').both()
But I also need
g.V().has('sLabel','Artifact').has('_isLatest','TRUE').bothE()
Which gives me all the edges I need, but not the vertices. I realize that g.V() gives vertices and g.E() gives edges, but am unsure how to obtain both/combine them in the one line query. My json comes back as either
"vertices":[] 0 items
"edges":[...] 90 items
Or
"vertices":[...] 90 items
"edges":[] 0 items
My next idea is to do multiple queries into java to parse, combine, and manipulate there. I would really like to avoid doing this, but will if it's the only way. Thank you for being kind and understanding and for your help. I appreciate you all.
You can write a Gremlin query that gives you both the vertices and the edges. There are a few ways to do that. Probably the easiest way is to use path as shown below.
g.V().has('sLabel','Artifact').
has('_isLatest','TRUE').
bothE().
otherV().
path()
as an alternative, you could do:
g.V().has('sLabel','Artifact').
has('_isLatest','TRUE').
bothE().as('e').
otherV().as('v').
select('v','e')
You can do it as follows,
Just see the code below have demonstrated the following,
Vertex query
Edge query
combined query
converted combined query into valueMap
Converted the combined query valueMap into JSON (using version 3)
Converted the combined query valueMap into JSON (using version 1)
Vertex Query
gremlin> g.V(131200).both()
==>v[40992]
==>v[12336]
==>v[20608]
==>v[180376]
gremlin>
Edge query
gremlin> g.V(131200).bothE()
==>e[7rps-2t8g-1fdh-vmo][131200-locatedin->40992]
==>e[3qpy-9io-1bf9-2t8g][12336-containedin->131200]
==>e[7rbk-fwg-1bf9-2t8g][20608-containedin->131200]
==>e[7l03-3v6g-1bf9-2t8g][180376-containedin->131200]
gremlin>
Combined query
gremlin>
gremlin>g.V(131200).project('nodes','edges').by(both().fold()).by(bothE().fold())
==>[nodes:[v[40992],v[12336],v[20608],v[180376]],edges:[e[7rps-2t8g-1fdh-vmo][131200-locatedin->40992],e[3qpy-9io-1bf9-2t8g][12336-containedin->131200],e[7rbk-fwg-1bf9-2t8g][20608-containedin->131200],e[7l03-3v6g-1bf9-2t8g][180376-containedin->131200]]]
gremlin>
converted combined query into valueMap
gremlin>
gremlin> output = g.V(131200).project('nodes','edges').by(both().valueMap().fold()).by(bothE().valueMap().fold()).next()
==>nodes=[{gId=[0b98e8d5-681d-4155-8aaf-5d86babc0cff], isDeleted=[FALSE], isEntity=[TRUE], name=[TotsukaCDC], basetype=[GeoLocation], source=[RCP-Base], type=[DC], geographyL2DisplayName=[KANAGAWA], geographyL2Name=[KANAGAWA], geographyL4Name=[KNG-TOTSUKAKU-NORTH], geographyL4DisplayName=[KNG-TOTSUKAKU-NORTH], displayName=[TotsukaCDC], latitude=[139.525166], locationType=[CDC], geographyL1Name=[KANTO], geographyL3DisplayName=[YOKOHAMA-SHI], geographyL3Name=[YOKOHAMA-SHI], geographyL1DisplayName=[KANTO], locationCode=[tt], longitude=[35.416535]}, {gId=[90e7407c-cd34-44b0-9bf9-1a8866aac429], isDeleted=[FALSE], isEntity=[TRUE], name=[UHN2KNGcdcttRA01_HundredGigE0/0/0/6], basetype=[Entity], source=[RCP-Base], type=[PhysicalPort], portInUse=[TRUE], portNum=[HundredGigE0/0/0/6]}, {gId=[d0fc7284-4cd8-4cba-8d3d-be3c4ca2ba31], isDeleted=[FALSE], isEntity=[TRUE], name=[UHN2KNGcdcttRA01_Hu0/2/0/35], basetype=[Entity], source=[RCP-Base], type=[PhysicalPort], portInUse=[TRUE], portNum=[Hu0/2/0/35]}, {gId=[2f4f5a3a-b88f-4915-acd5-a1d873507f11], isDeleted=[FALSE], isEntity=[TRUE], name=[UHN2KNGcdcttRA01_HundredGigE0/1/0/6], basetype=[Entity], source=[RCP-Base], type=[PhysicalPort], portInUse=[TRUE], portNum=[HundredGigE0/1/0/6]}]
==>edges=[{destName=TotsukaCDC, srcName=UHN2KNGcdcttRA01, gId=1133ff0f-2f4b-4d21-b2d6-fed796ed13f9}, {gId=220d7d2b-8b96-4331-bdc1-50127685946a, destName=UHN2KNGcdcttRA01, srcName=UHN2KNGcdcttRA01_HundredGigE0/0/0/6}, {gId=ebd78fc0-a66c-4033-a776-f80210c02e63, destName=UHN2KNGcdcttRA01, srcName=UHN2KNGcdcttRA01_Hu0/2/0/35}, {srcName=UHN2KNGcdcttRA01_HundredGigE0/1/0/6, gId=0df0f3d0-037a-4caa-9f81-6a6df1c22e25, destName=UHN2KNGcdcttRA01}]
gremlin>
Converted the combined query valueMap into JSON (Using Version 3)
gremlin>
gremlin> mapper = GraphSONMapper.build().version(GraphSONVersion.V3_0).create().createMapper()
==>org.apache.tinkerpop.shaded.jackson.databind.ObjectMapper#10a907ec
gremlin>
gremlin> mapper.writeValueAsString(output) // output is a variable in which data is collected in step 4
==>{"#type":"g:Map","#value":["nodes",{"#type":"g:List","#value":[{"#type":"g:Map","#value":["gId",{"#type":"g:List","#value":["0b98e8d5-681d-4155-8aaf-5d86babc0cff"]},"isDeleted",{"#type":"g:List","#value":["FALSE"]},"isEntity",{"#type":"g:List","#value":["TRUE"]},"name",{"#type":"g:List","#value":["TotsukaCDC"]},"basetype",{"#type":"g:List","#value":["GeoLocation"]},"source",{"#type":"g:List","#value":["RCP-Base"]},"type",{"#type":"g:List","#value":["DC"]},"geographyL2DisplayName",{"#type":"g:List","#value":["KANAGAWA"]},"geographyL2Name",{"#type":"g:List","#value":["KANAGAWA"]},"geographyL4Name",{"#type":"g:List","#value":["KNG-TOTSUKAKU-NORTH"]},"geographyL4DisplayName",{"#type":"g:List","#value":["KNG-TOTSUKAKU-NORTH"]},"displayName",{"#type":"g:List","#value":["TotsukaCDC"]},"latitude",{"#type":"g:List","#value":[{"#type":"g:Double","#value":139.525166}]},"locationType",{"#type":"g:List","#value":["CDC"]},"geographyL1Name",{"#type":"g:List","#value":["KANTO"]},"geographyL3DisplayName",{"#type":"g:List","#value":["YOKOHAMA-SHI"]},"geographyL3Name",{"#type":"g:List","#value":["YOKOHAMA-SHI"]},"geographyL1DisplayName",{"#type":"g:List","#value":["KANTO"]},"locationCode",{"#type":"g:List","#value":["tt"]},"longitude",{"#type":"g:List","#value":[{"#type":"g:Double","#value":35.416535}]}]},{"#type":"g:Map","#value":["gId",{"#type":"g:List","#value":["90e7407c-cd34-44b0-9bf9-1a8866aac429"]},"isDeleted",{"#type":"g:List","#value":["FALSE"]},"isEntity",{"#type":"g:List","#value":["TRUE"]},"name",{"#type":"g:List","#value":["UHN2KNGcdcttRA01_HundredGigE0/0/0/6"]},"basetype",{"#type":"g:List","#value":["Entity"]},"source",{"#type":"g:List","#value":["RCP-Base"]},"type",{"#type":"g:List","#value":["PhysicalPort"]},"portInUse",{"#type":"g:List","#value":["TRUE"]},"portNum",{"#type":"g:List","#value":["HundredGigE0/0/0/6"]}]},{"#type":"g:Map","#value":["gId",{"#type":"g:List","#value":["d0fc7284-4cd8-4cba-8d3d-be3c4ca2ba31"]},"isDeleted",{"#type":"g:List","#value":["FALSE"]},"isEntity",{"#type":"g:List","#value":["TRUE"]},"name",{"#type":"g:List","#value":["UHN2KNGcdcttRA01_Hu0/2/0/35"]},"basetype",{"#type":"g:List","#value":["Entity"]},"source",{"#type":"g:List","#value":["RCP-Base"]},"type",{"#type":"g:List","#value":["PhysicalPort"]},"portInUse",{"#type":"g:List","#value":["TRUE"]},"portNum",{"#type":"g:List","#value":["Hu0/2/0/35"]}]},{"#type":"g:Map","#value":["gId",{"#type":"g:List","#value":["2f4f5a3a-b88f-4915-acd5-a1d873507f11"]},"isDeleted",{"#type":"g:List","#value":["FALSE"]},"isEntity",{"#type":"g:List","#value":["TRUE"]},"name",{"#type":"g:List","#value":["UHN2KNGcdcttRA01_HundredGigE0/1/0/6"]},"basetype",{"#type":"g:List","#value":["Entity"]},"source",{"#type":"g:List","#value":["RCP-Base"]},"type",{"#type":"g:List","#value":["PhysicalPort"]},"portInUse",{"#type":"g:List","#value":["TRUE"]},"portNum",{"#type":"g:List","#value":["HundredGigE0/1/0/6"]}]}]},"edges",{"#type":"g:List","#value":[{"#type":"g:Map","#value":["destName","TotsukaCDC","srcName","UHN2KNGcdcttRA01","gId","1133ff0f-2f4b-4d21-b2d6-fed796ed13f9"]},{"#type":"g:Map","#value":["gId","220d7d2b-8b96-4331-bdc1-50127685946a","destName","UHN2KNGcdcttRA01","srcName","UHN2KNGcdcttRA01_HundredGigE0/0/0/6"]},{"#type":"g:Map","#value":["gId","ebd78fc0-a66c-4033-a776-f80210c02e63","destName","UHN2KNGcdcttRA01","srcName","UHN2KNGcdcttRA01_Hu0/2/0/35"]},{"#type":"g:Map","#value":["srcName","UHN2KNGcdcttRA01_HundredGigE0/1/0/6","gId","0df0f3d0-037a-4caa-9f81-6a6df1c22e25","destName","UHN2KNGcdcttRA01"]}]}]}
gremlin>
Converted the combined query valueMap into JSON (Using Version 1)
gremlin>
gremlin> mapper1 = GraphSONMapper.build().version(GraphSONVersion.V1_0).create().createMapper()
==>org.apache.tinkerpop.shaded.jackson.databind.ObjectMapper#1a7163e3
gremlin>
gremlin> mapper1.writeValueAsString(output)
==>{"nodes":[{"gId":["0b98e8d5-681d-4155-8aaf-5d86babc0cff"],"isDeleted":["FALSE"],"isEntity":["TRUE"],"name":["TotsukaCDC"],"basetype":["GeoLocation"],"source":["RCP-Base"],"type":["DC"],"geographyL2DisplayName":["KANAGAWA"],"geographyL2Name":["KANAGAWA"],"geographyL4Name":["KNG-TOTSUKAKU-NORTH"],"geographyL4DisplayName":["KNG-TOTSUKAKU-NORTH"],"displayName":["TotsukaCDC"],"latitude":[139.525166],"locationType":["CDC"],"geographyL1Name":["KANTO"],"geographyL3DisplayName":["YOKOHAMA-SHI"],"geographyL3Name":["YOKOHAMA-SHI"],"geographyL1DisplayName":["KANTO"],"locationCode":["tt"],"longitude":[35.416535]},{"gId":["90e7407c-cd34-44b0-9bf9-1a8866aac429"],"isDeleted":["FALSE"],"isEntity":["TRUE"],"name":["UHN2KNGcdcttRA01_HundredGigE0/0/0/6"],"basetype":["Entity"],"source":["RCP-Base"],"type":["PhysicalPort"],"portInUse":["TRUE"],"portNum":["HundredGigE0/0/0/6"]},{"gId":["d0fc7284-4cd8-4cba-8d3d-be3c4ca2ba31"],"isDeleted":["FALSE"],"isEntity":["TRUE"],"name":["UHN2KNGcdcttRA01_Hu0/2/0/35"],"basetype":["Entity"],"source":["RCP-Base"],"type":["PhysicalPort"],"portInUse":["TRUE"],"portNum":["Hu0/2/0/35"]},{"gId":["2f4f5a3a-b88f-4915-acd5-a1d873507f11"],"isDeleted":["FALSE"],"isEntity":["TRUE"],"name":["UHN2KNGcdcttRA01_HundredGigE0/1/0/6"],"basetype":["Entity"],"source":["RCP-Base"],"type":["PhysicalPort"],"portInUse":["TRUE"],"portNum":["HundredGigE0/1/0/6"]}],"edges":[{"destName":"TotsukaCDC","srcName":"UHN2KNGcdcttRA01","gId":"1133ff0f-2f4b-4d21-b2d6-fed796ed13f9"},{"gId":"220d7d2b-8b96-4331-bdc1-50127685946a","destName":"UHN2KNGcdcttRA01","srcName":"UHN2KNGcdcttRA01_HundredGigE0/0/0/6"},{"gId":"ebd78fc0-a66c-4033-a776-f80210c02e63","destName":"UHN2KNGcdcttRA01","srcName":"UHN2KNGcdcttRA01_Hu0/2/0/35"},{"srcName":"UHN2KNGcdcttRA01_HundredGigE0/1/0/6","gId":"0df0f3d0-037a-4caa-9f81-6a6df1c22e25","destName":"UHN2KNGcdcttRA01"}]}
I want the details of a vertex along with details of vertices that are joined to it.
I have a group vertex, incoming 'member' edges to user vertices. I want the details of the vertices.
g.V(1).as('a').in('member').valueMap().as('b').select('a','b').unfold().dedup()
==>a=v[1]
==>b={image=[images/profile/friend9.jpg], name=[Thomas Thompson], email=[me#thomasthompson.co.uk]}
==>b={image=[images/profile/friend13.jpg], name=[Laura Tostevin], email=[me#lauratostevin.co.uk]}
==>b={image=[images/profile/friend5.jpg], name=[Alan Thompson], email=[me#alanthompson.co.uk]}
==>b={image=[images/profile/friend10.jpg], name=[Laura Bourne], email=[me#laurabourne.co.uk]}
Ideally what I'd want is:
{label: 'group', id=1, name='A Group', users=[{id=2, label="user",name=".."}, ... }]}
When I tried a project, it didn't like me using 'in'
gremlin> g.V('1').project('name','users').by('name').by(in('member').select())
groovysh_parse: 1: unexpected token: in # line 1, column 83.
'name','users').by('name').by(in('member
To get your preferred output format, you have to join the group's valueMap() with the list of users. On TinkerPop's modern toy graph you would do something like this:
gremlin> g.V(3).union(valueMap(true).
by(unfold()),
project('users').
by(__.in('created').
valueMap(true).
by(unfold()).
fold())).
unfold().
group().
by(keys).
by(select(values))
==>[name:lop,id:3,lang:java,label:software,users:[[id:1,label:person,name:marko,...],...]]
Mapping this to your graph should be pretty straight-forward, it's basically just about changing labels.
Because in is a reserved keyword in Groovy you must use the verbose syntax __.in
try:
g.V('1').project('name','users').by('name').by(__.in('member').valueMap(true).fold())