anchor.diff:  ...
   ==>ripple
   ==>lop
  +
  +[gremlin-groovy]
  +----
  +graph = GraphFactory.open('conf/hadoop-gryo.properties')
  +g = graph.traversal(computer())
  +g.V().count()
  +g.V().out().out().values('name')
  +----
   
   IMPORTANT: The examples above do not use lambdas (i.e. closures in Gremlin-Groovy). This makes the traversal serializable and thus, able to be distributed to all machines in the Hadoop cluster. If a lambda is required in a traversal, then the traversal must be sent as a `String` and compiled locally at each machine in the cluster. The following example demonstrates the `:remote` command which allows for submitting Gremlin traversals as a `String`.
   
  
positive.code: gremlin> g.V().out().out().values('name')
  ==>lop
  ==>ripple
  
  For using lambdas in Gremlin-Groovy, simply provide `:remote connect` a `TraversalSource` which leverages SparkGraphComputer.
  
  
negative.code: ==>e={peter=1}
  ==>i={ripple=1}
  ==>o={lop=1, josh=1}
  
  [gremlin-groovy]
  ----
  hdfs.copyFromLocal('data/tinkerpop-modern.kryo', 'tinkerpop-modern.kryo')
  hdfs.ls()
  graph = GraphFactory.open('conf/hadoop-gryo.properties')
  g = graph.traversal(standard())
  g.V().count()
  g.V().out().out().values('name')
  g.V().group().by{it.value('name')[1]}.by('name').next()
  ----
  
  OLAP Hadoop-Gremlin
  ~~~~~~~~~~~~~~~~~~~
  