How to group "match" results - groovy

Question

My question is "how to group the match results" of select-ed items ?
Here is the structure and data I have in my graph :
Structure :
5 kind of vertices : user / experience / school / company / tag
5 kind of edges : studied / worked /school / company / speaks
Data :
user --[worked]--> experience --[company]--> company
user --[worked]--> experience --[company]--> company
user --[stidued]--> experience --[school]--> school
user --[stidued]--> experience --[school]--> school
user --[speaks (level: x)]--> language
user --[speaks (level: x)]--> language
I already wrote something close to what I need with match, dedup and unfold
g.V(16520).match(
__.as('user'),
__.as('user').out('worked').as('workExperiences'),
__.as('user').out('studied').as('schoolExperiences'),
__.as('workExperiences').out('company').as('company'),
__.as('schoolExperiences').out('school').as('school'),
__.as('user').outE('speaks').as('a').values('level').as('level').select('a').inV().values('name').as('language').select('level', 'language').as('languages')
).select('user', 'schoolExperiences', 'school', 'workExperiences', 'company', 'languages')
.unfold().dedup()
Here is what this query gives me :
==>user=v[16520]
==>schoolExperiences=v[4184]
==>school=v[4232]
==>workExperiences=v[12496]
==>company=v[8320]
==>languages={level=6, language=DEU}
==>languages={level=3, language=FRA}
==>schoolExperiences=v[16424]
==>school=v[4136]
==>workExperiences=v[16512]
==>company=v[4176]
I need to find a query that return this kind of result :
==>user=[v[16520]]
==>languages=[{level=6, language=DEU},{level=3, language=FRA}]
==>workExperiences=[v[12496], v[16512]]
==>schoolExperiences=[v[4184], v[16424]]
==>company=[v[4176], v[8320]]
==>school=[v[4136], v[4232]]
I can't manage to find a solution.
Any advice would be appriciated :)
Thanks for reading
F.
PS : I'm running a v3.0.1-incubating Tinkerpop version

Answer 1

Thanks to #DanielKuppitz here is the solution I needed :
g.V(16520).as('user').match(
__.as('user').out('worked').as('experience').out('company').as('companyId').select('experience', 'companyId').fold().as('tmpWorkExperiences'),
__.as('user').out('studied').as('experience').out('school').as('schoolId').select('experience', 'schoolId').fold().as('tmpSchoolExperiences'),
__.as('user').outE('speaks').as('level').inV().as('language').select('level', 'language').by('level').by('name').fold().as('languages')
).select('tmpWorkExperiences').map(unfold().select('experience', 'companyId').by().by(id).fold()).as('workExperiences').
select('tmpWorkExperiences').map(unfold().select('companyId').fold()).as('company').
select('tmpSchoolExperiences').map(unfold().select('experience', 'schoolId').by().by(id).fold()).as('schoolExperiences').
select('tmpSchoolExperiences').map(unfold().select('schoolId').fold()).as('school').
select('workExperiences', 'schoolExperiences', 'company', 'school', 'languages').unfold()
And here is the result :
==>workExperiences=[{experience=v[12496], companyId=8320}, {experience=v[16512], companyId=4176}]
==>schoolExperiences=[{experience=v[4184], schoolId=4232}, {experience=v[16424], schoolId=4136}]
==>company=[v[8320], v[4176]]
==>school=[v[4232], v[4136]]
==>languages=[{level=6, language=DEU}, {level=3, language=FRA}]