我假设您的图表看起来像这样:
g = TinkerGraph.open().traversal()
g.addV('student').property('name', 'A').
addE('scored').to(addV('subject').property('name', 'Math')).
property('mark', 77).
addV('student').property('name', 'B').
addE('scored').to(addV('subject').property('name', 'History')).
property('mark', 70).
addV('student').property('name', 'C').
addE('scored').to(addV('subject').property('name', 'Science')).
property('mark', 97).iterate()
现在收集数据最简单的方法是:
gremlin> g.V().has('student', 'name', within('A', 'B', 'C')).as('student').
outE('scored').as('mark').inV().as('major').
select('student','major','mark').
by('name').
by('name').
by('mark')
==>[student:A,major:Math,mark:77]
==>[student:B,major:History,mark:70]
==>[student:C,major:Science,mark:97]
但如果你真的依赖问题中显示的格式,你可以这样做:
gremlin> g.V().has('student', 'name', within('A', 'B', 'C')).
store('student').by('name').
outE('scored').store('mark').by('mark').
inV().store('major').by('name').
cap('student','major','mark')
==>[major:[Math,History,Science],student:[A,B,C],mark:[77,70,97]]
如果您想获得按标记排序的封顶结果,则需要混合使用 2 个查询:
gremlin> g.V().has('student', 'name', within('A', 'B', 'C')).as('a').
outE('scored').as('b').
order().
by('mark').
inV().as('c').
select('a','c','b').
by('name').
by('name').
by('mark').
aggregate('student').by(select('a')).
aggregate('major').by(select('b')).
aggregate('mark').by(select('c')).
cap('student','major','mark')
==>[major:[History,Math,Science],student:[B,A,C],mark:[70,77,97]]
按输入顺序排序:
gremlin> input = ['C', 'B', 'A']; []
gremlin> g.V().has('student', 'name', within(input)).as('a').
order().
by {input.indexOf(it.value('name'))}.
outE('scored').as('b').
inV().as('c').
select('a','c','b').
by('name').
by('name').
by('mark').
aggregate('student').by(select('a')).
aggregate('major').by(select('b')).
aggregate('mark').by(select('c')).
cap('student','major','mark')
==>[major:[97,70,77],student:[C,B,A],mark:[Science,History,Math]]