anchor.diff:  gremlin> g.V().out().out().values('name')
   ==>lop
   ==>ripple
  +
  +[gremlin-groovy]
  +----
  +graph = GraphFactory.open('conf/hadoop-gryo.properties')
  +g = graph.traversal(computer(SparkGraphComputer))
  +g.V().count()
  +g.V().out().out().values('name')
  +----
   
   For using lambdas in Gremlin-Groovy, simply provide `:remote connect` a `TraversalSource` which leverages SparkGraphComputer.
   
  
positive.code: gremlin.hadoop.graphInputFormat=org.apache.tinkerpop.gremlin.hadoop.structure.io.gryo.GryoInputFormat
  gremlin.hadoop.graphOutputFormat=org.apache.tinkerpop.gremlin.hadoop.structure.io.gryo.GryoOutputFormat
  gremlin.hadoop.jarsInDistributedCache=true
  gremlin.hadoop.inputLocation=tinkerpop-modern-vertices.kryo
  gremlin.hadoop.outputLocation=output
  #####################################
  # GiraphGraphComputer Configuration #
  
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
  ~~~~~~~~~~~~~~~~~~~
  