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[[traversal-induced-values]]
== Traversal Induced Values

The parameters of a `Traversal` can be known ahead of time as constants or might otherwise be passed in as dynamic
arguments.

[gremlin-groovy,modern]
----
g.V().has('name','marko').out('knows').has('age', gt(29)).values('name')
----

In plain language, the above Gremlin asks, "What are the names of the people who Marko knows who are over the age of
29?". In this case, "29" is known as a constant to the traversal. Of course, if the question is changed slightly to
instead ask, "What are the names of the people who Marko knows who are older than he is?", the hardcoding of "29" will
no longer suffice. There are multiple ways Gremlin would allow this second question to be answered. The first is
obvious to any programmer - use a variable:

[gremlin-groovy,modern]
----
vMarko = g.V().has('name','marko').next()
g.V(vMarko).out('knows').has('age', gt(marko.value('age'))).values('name')
----

The downside to this approach is that it takes two separate traversals to answer the question. Ideally, there should
be a single traversal, that can query "marko" once, determine his `age` and then use that for the value supplied to
filter the people he knows. In this way the _value_ for the `age` in the `has()`-filter is _induced_ from the `Traversal`
itself.

[gremlin-groovy,modern]
----
g.V().has('name','marko').as('marko').      <1>
  out('knows').as('friend').                <2>
    where('friend', gt('marko')).by('age'). <3>
  values('name')                            <4>
----

<1> Find the "marko" `Vertex` and label it as "marko".
<2> Traverse out on the "knows" edges to the adjacent `Vertex` and label it as "friend".
<3> Continue to traverser only if Marko's current friend is older than him.
<4> Get the name of Marko's older friend.

As another example of how traversal induced values can be used, consider a scenario where there was a graph that
contained people, their friendship relationships, and the movies that they liked.

image:traversal-induced-values-3.png[width=600]

[gremlin-groovy]
----
g.addV("user").property("name", "alice").as("u1").
  addV("user").property("name", "jen").as("u2").
  addV("user").property("name", "dave").as("u3").
  addV("movie").property("name", "the wild bunch").as("m1").
  addV("movie").property("name", "young guns").as("m2").
  addV("movie").property("name", "unforgiven").as("m3").
  addE("friend").from("u1").to("u2").
  addE("friend").from("u1").to("u3").
  addE("like").from("u2").to("m1").
  addE("like").from("u2").to("m2").
  addE("like").from("u3").to("m2").
  addE("like").from("u3").to("m3").iterate()
----

Getting a list of all the movies that Alice's friends like could be done like this:

[gremlin-groovy,existing]
----
g.V().has('name','alice').out("friend").out("like").values("name")
----

but what if there was a need to get a list of movies that *all* her Alice's friends liked. In this case, that would
mean filtering out "the wild bunch" and "unforgiven".

[gremlin-groovy,existing]
----
g.V().has("name","alice").
  out("friend").aggregate("friends").                            <1>
  out("like").dedup().                                           <2>
  filter(__.in("like").where(within("friends")).count().as("a"). <3>
            select("friends").count(local).where(eq("a"))).      <4>
  values("name")
----

<1> Gather Alice's list of friends to a list called "friends".
<2> Traverse to the unique list of movies that Alice's friends like.
<3> Remove movies that weren't liked by all friends. This starts by taking each movie and traversing back in on the
"like" edges to friends who liked the movie (note the use of `where(within("friends"))` to limit those likes to only
Alice's friends as aggregated in step one) and count them up into "a".
<4> Count the aggregated friends and see if the number matches what was stored in "a" which would mean that all friends
like the movie.

Traversal induced values are not just for filtering. They can also be used when writing the values of the properties
of one `Vertex` to another:

[gremlin-groovy,modern]
----
g.V().has('name', 'marko').as('marko').
  out('created').property('creator', select('marko').by('name'))
g.V().has('name', 'marko').out('created').elementMap()
----

In a more complex example of how this might work, consider a situation where the goal is to propagate a value stored on
a particular vertex through one of more additional connected vertices using some value on the connecting edges to
determine the value to assign. For example, the following graph depicts three "tank" vertices where the edges represent
the direction a particular "tank" should drain and the "factor" by which it should do it:

image:traversal-induced-values-1.png[width=700]

If the traversal started at tank "a", then the value of "amount" on that tank would be used to calculate what the value
of tank "b" was by multiplying it by the value of the "factor" property on the edge between vertices "a" and "b". In
this case the amount of tank "b" would then be 50. Following this pattern, when going from tank "b" to tank "c", the
value of the "amount" of tank "c" would be 5.

image:traversal-induced-values-2.png[width=700]

Using Gremlin `sack()`, this kind of operation could be specified as a single traversal:

[gremlin-groovy]
----
g.addV('tank').property('name', 'a').property('amount', 100.0).as('a').
  addV('tank').property('name', 'b').property('amount', 0.0).as('b').
  addV('tank').property('name', 'c').property('amount', 0.0).as('c').
  addE('drain').property('factor', 0.5).from('a').to('b').
  addE('drain').property('factor', 0.1).from('b').to('c').iterate()
vA = g.V().has('name','a').next()
g.withSack(vA.value('amount')).
  V(vA).repeat(outE('drain').sack(mult).by('factor').
              inV().property('amount', sack())).
       until(__.outE('drain').count().is(0)).iterate()
g.V().elementMap()
----

The "sack value" gets initialized to the value of tank "a". The traversal iteratively traverses out on the "drain"
edges and uses `mult` to multiply the sack value by the value of "factor". The sack value at that point is then
written to the "amount" of the current vertex.

As shown in the previous example, `sack()` is a useful way to "carry" and manipulate a value that can be later used
elsewhere in the traversal. Here is another example of its usage where it is utilized to increment all the "age" values
in the modern toy graph by 10:

[gremlin-groovy,modern]
----
g.withSack(0).V().has("age").
  sack(assign).by("age").sack(sum).by(constant(10)).
  property("age", sack()).elementMap()
----

In the above case, the sack is initialized to zero and as each vertex is iterated, the "age" is assigned to the sack
with `sack(assign).by('age')`. That value in the sack is then incremented by the value `constant(10)` and assigned to
the "age" property of the same vertex.

This value the sack is incremented by need not be a constant. It could also be derived from the traversal itself.
Using the same example, the "weight" property on the incident edges will be used as the value to add to the sack:

[gremlin-groovy,modern]
----
g.withSack(0).V().has("age").
  sack(assign).by("age").sack(sum).by(bothE().values("weight").sum()).
  property("age", sack()).elementMap()
----
