anchor.diff:  |giraph.maxWorkers |The maximum number of parallel workers to execute the vertices of the graph (`GiraphGraphComputer`).
   |=========================================================
   
  -IMPORTANT: The maximum number of workers can be no larger than the number of map-slots in the Hadoop cluster minus 1. For example, if the Hadoop cluster has 4 map slots, then `giraph.maxWorkers` can not be larger than 3. One map-slot is reserved for the master compute node and all other slots can be allocated as workers to execute the VertexPrograms on the vertices of the graph.
  -
   Along with the properties above, the numerous link:http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-common/core-default.xml[Hadoop specific properties] can be added as needed to tune and parameterize the executed Hadoop-Gremlin job on the respective Hadoop cluster.
   
   OLTP Hadoop-Gremlin
   ~~~~~~~~~~~~~~~~~~~
   
  -image:hadoop-pipes.png[width=180,float=left] It is possible to execute OLTP operations over Hadoop-Gremlin. However, realize that the underlying HDFS files are typically not random access and thus, to retrieve a vertex, a linear scan is required. It is possible to create input formats that leverage Hadoop Map files.
  -
  -CAUTION: OLTP operations on `HadoopGraph` are not efficient. They require linear scans to execute and are unreasonable for large graphs. In such large graph situations, make use of <<traversalvertexprogram,TraversalVertexProgram>> which is the OLAP implementation of the Gremlin language.
  +image:hadoop-pipes.png[width=180,float=left] It is possible to execute OLTP operations over a `HadoopGraph`. However, realize that the underlying HDFS files are typically not random access and thus, to retrieve a vertex, a linear scan is required. OLTP operations are useful for peeking at the graph prior to executing a long running OLAP job -- e.g. `g.V().valueMap().limit(10)`.
  +
  +CAUTION: OLTP operations on `HadoopGraph` are not efficient. They require linear scans to execute and are unreasonable for large graphs. In such large graph situations, make use of <<traversalvertexprogram,TraversalVertexProgram>> which is the OLAP implementation of the Gremlin language. Hadoop-Gremlin provides various `GraphComputer` implementations to execute OLAP computations over a `HadoopGraph`.
   
   [source,text]
   gremlin> hdfs.copyFromLocal('data/tinkerpop-classic-vertices.gio', 'tinkerpop-classic-vertices.gio')
  
positive.code: |gremlin.hadoop.graphOutputFormat |The format that the output file(s) should be represented in.
  |gremlin.hadoop.memoryOutputFormat |The format of any resultant GraphComputer Memory.
  |gremlin.vertexProgram |The `VertexProgram` to distribute to all vertices in the `HadoopGraph`
  |gremlin.traversalVertexProgram.traversalSupplier.object |For `TraversalVertexProgram`, the location of the Gremlin traversal to use (if not using Gremlin Console).
  |gremlin.traversalVertexProgram.traversalSupplier.type | Whether the traversal supplier is a CLASS, SCRIPT, or OBJECT.
  |gremlin.hadoop.jarsInDistributedCache |Whether to upload the Hadoop-Gremlin jars to Hadoop's distributed cache (necessary if jars are not on machines' classpaths).
  |gremlin.hadoop.deriveMemory |Whether or not `Memory` is yielded (requires an extra MapReduce job if true).
  
negative.code: 
  TIP: image:gremlin-sugar.png[width=50,float=left] For those wanting to use the <<sugar-plugin,SugarPlugin>> with their submitted traversal, do `:remote config useSugar true` as well as `:plugin use tinkerpop.sugar` at the start of the Gremlin Console session if it is not already activated.
  
  The `TraversalSupplier1` class mentioned in the `hadoop-kryo.properties` file is distributed with Hadoop-Gremlin. It declares what Gremlin-Java traversal to execute on the loaded `HadoopGraph`. This is the means by which traversals can be programmatically executed in Hadoop-Gremlin.
  
  [source,java]
  ----
  // gremlin.traversalVertexProgram.traversalSupplier.type=CLASS
  // gremlin.traversalVertexProgram.traversalSupplier.object=com.tinkerpop.gremlin.hadoop.process.computer.example.TraversalSupplier1
  
  public class TraversalSupplier1 implements SSupplier<Traversal> {
      public Traversal get() {
          return HadoopGraph.open().V().out().out().values("name");
      }
  }
  ----
  
  MapReduceGraphComputer
  ^^^^^^^^^^^^^^^^^^^^^^
  
  *COMING SOON*
  
  Interacting with HDFS
  ~~~~~~~~~~~~~~~~~~~~~
  
  The distributed file system of Hadoop is called link:http://en.wikipedia.org/wiki/Apache_Hadoop#Hadoop_distributed_file_system[HDFS]. The results of any OLAP operation are stored in HDFS accessible via `hdfs`.
  
  [source,text]
  gremlin> hdfs.ls()
  