优化 gremlin 查询以避免图的多次遍历

Question

I am little new to Gremlin query paradigm. I have following gremlin query to get all the nodes related to node of type foo .

g.V().hasLabel('foo').as('foo')
.coalesce(out('hasBar'), constant('')).as('bar')
.select('foo').coalesce(out('hasDelta'), constant('')).as('Delta')
.select('foo').coalesce(out('hasBar').out('hasGamma'), constant('')).as('Gamma')
.select('foo', 'bar', 'Delta', 'Gamma')

However this is not the optimized one as I have to traverse the graph multiple times and slows down the query execution.

Edit

Sample Data -

g.addV('foo').property('id', '1').property('p1', '1234').property('pk', 1)
g.addV('bar').property('id', '2').property('p2', '12345').property('pk', 1)
g.addV('Gamma').property('id', '3').property('p3', '123').property('pk', 1)
g.addV('Delta').property('id', '4').property('p4', '12').property('pk', 1)
g.V('1').addE("hasBar").to(g.V('2'))
g.V('1').addE("hasGamma").to(g.V('3'))
g.V('2').addE("hasDelta").to(g.V('4'))
g.addV('foo').property('id', '5').property('p1', '12345').property('pk', 1)
g.V('5').addE("hasBar").to(g.V('2'))
g.V('5').addE("hasGamma").to(g.V('3'))
g.addV('foo').property('id', '6').property('p1', '1').property('pk', 1)
g.V('6').addE("hasBar").to(g.V('2'))
g.V('6').addE("hasGamma").to(g.V('3'))
g.addV('foo').property('id', '7').property('p1', '145').property('pk', 1)
g.V('7').addE("hasBar").to(g.V('2'))
g.V('7').addE("hasGamma").to(g.V('3'))
g.addV('foo').property('id', '8').property('p1', '15').property('pk', 1)
g.addV('bar').property('id', '9').property('p2', '78').property('pk', 1)
g.addV('Gamma').property('id', '10').property('p3', '1236').property('pk', 1)
g.addV('Delta').property('id', '11').property('p4', '1258').property('pk', 1)
g.V('8').addE("hasBar").to(g.V('9'))
g.V('8').addE("hasGamma").to(g.V('10'))
g.V('10').addE("hasDelta").to(g.V('11'))

Previously I was fetching all foo and then was querying the corresponding bar, gamma and delta, which is very inefficient, so changed the query to fetch all at once, but now I am doing the same thing, but avoiding network calls.

Above query gives following response -

[
{
    foo: {},
    bar: {},
    Delta: {},
    Gamma: {}
},
{
    foo: {},
    bar: {},
    Delta: {},
    Gamma: {}
}
]

Answer 1

You could just take advantage of labels and use the path step:

g.V().hasLabel('foo').
      outE('hasBar','hasDelta','hasGamma').
      inV().
      path().by(label)

If you want to identify the vertices by a property or their ID adding a second by modulator after the path step will do that.

g.V().hasLabel('foo').
      outE('hasBar','hasDelta','hasGamma').
      inV().
      path().
        by(id).
        by(label)

The paths returned will be of the form (I just assumed numeric IDs):

[1,hasBar,10]
[1,hasDelta,15]
[1,hasGamma,27]