Hi,
*** This is mainly for Kuppitz, but if others care.
Was thinking last night about relational data and Gremlin. The T() step returns
all the tables in the withStructure() RDBMS database. Tables are ‘complex
values’ so they can't leave the VM (only a simple ‘toString’).
Below is a fake Gremlin session. (and these are just ideas…)
tables -> a ListLike of rows
rows -> a MapLike of primitives
gremlin> g.T()
==>t[people]
==>t[addresses]
gremlin> g.T(‘people’)
==>t[people]
gremlin> g.T(‘people’).values()
==>r[people:1]
==>r[people:2]
==>r[people:3]
gremlin> g.T(‘people’).values().asMap()
==>{name:marko,age:29}
==>{name:kuppitz,age:10}
==>{name:josh,age:35}
gremlin> g.T(‘people’).values().has(‘age’,gt(20))
==>r[people:1]
==>r[people:3]
gremlin> g.T(‘people’).values().has(‘age’,gt(20)).values(‘name’)
==>marko
==>josh
Makes sense. Nice that values() and has() generally apply to all ListLike and
MapLike structures. Also, note how asMap() is the valueMap() of TP4, but
generalizes to anything that is MapLike so it can be turned into a primitive
form as a data-rich result from the VM.
gremlin> g.T()
==>t[people]
==>t[addresses]
gremlin> g.T(‘addresses’).values().asMap()
==>{name:marko,city:santafe}
==>{name:kuppitz,city:tucson}
==>{name:josh,city:desertisland}
gremlin> g.join(T(‘people’).as(‘a’),T(‘addresses’).as(‘b’)).
by(select(‘a’).value(’name’).is(eq(select(‘b’).value(’name’))).
values().asMap()
==>{a.name:marko,a.age:29,b.name:marko,b.city:santafe}
==>{a.name:kuppitz,a.age:10,b.name:kuppitz,b.city:tucson}
==>{a.name:josh,a.age:35,b.name:josh,b.city:desertisland}
gremlin> g.join(T(‘people’).as(‘a’),T(‘addresses’).as(‘b’)).
by(’name’). // shorthand for equijoin on name column/key
values().asMap()
==>{a.name:marko,a.age:29,b.name:marko,b.city:santafe}
==>{a.name:kuppitz,a.age:10,b.name:kuppitz,b.city:tucson}
==>{a.name:josh,a.age:35,b.name:josh,b.city:desertisland}
gremlin> g.join(T(‘people’).as(‘a’),T(‘addresses’).as(‘b’)).
by(’name’)
==>t[people<-name->addresses] // without asMap(), just the complex value
‘toString'
gremlin>
And of course, all of this is strategized into a SQL call so its joins aren’t
necessarily computed using TP4-VM resources.
Anywho — what I hope to realize is the relationship between “links” (graph) and
“joins” (tables). How can we make (bytecode-wise at least) RDBMS join
operations and graph traversal operations ‘the same.’?
Singleton: Integer, String, Float, Double, etc.
Collection: List, Map (Vertex, Table, Document)
Linkable: Vertex, Table
Vertices and Tables can be “linked.” Unlike Collections, they don’t maintain a
“parent/child” relationship with the objects they reference. What does this
mean……….?
Take care,
Marko.
http://rredux.com <http://rredux.com/>
