anchor.diff:  export HADOOP_HOME=/usr/local/lib/hadoop-2.7.2
   export HADOOP_CONF_DIR=/usr/local/lib/hadoop-2.7.2/etc/hadoop
   
  -# Have Tinkerpop find the hadoop cluster configs and hadoop native libraries
  +# Have TinkerPop find the hadoop cluster configs and hadoop native libraries
   export CLASSPATH=$HADOOP_CONF_DIR
   export JAVA_OPTIONS="-Djava.library.path=$HADOOP_HOME/lib/native:$HADOOP_HOME/lib/native/Linux-amd64-64"
   
  
positive.code: the Spark History Service, which allows you to access logs of finished jobs via the Yarn resource manager UI.
  
  This recipe uses the gremlin console, but things should not be very different for your own JVM-based application,
  as long as you do not use the `spark-submit` or `spark-shell` commands.
  
  You may not like the idea that the Hadoop and Spark jars from the Tinkerpop distribution differ from the versions in
  your cluster. If so, just build Tinkerpop from source with the corresponding dependencies changed in the various `pom.xml`
  files (e.g. `spark-core_2.11-2.2.0-some-vendor.jar` instead of `spark-core_2.11-2.2.0.jar`). Of course, Tinkerpop will
  only build for exactly matching or slightly differing artifact versions.
negative.code: OLAP traversals with Spark on Yarn
  ----------------------------------
  
  TinkerPop's combination of http://tinkerpop.apache.org/docs/current/reference/#sparkgraphcomputer[SparkGraphComputer]
  and http://tinkerpop.apache.org/docs/current/reference/#_properties_files[HadoopGraph] allows for running
  distributed, analytical graph queries (OLAP) on a computer cluster. The
  http://tinkerpop.apache.org/docs/current/reference/#sparkgraphcomputer[reference documentation] covers the cases
  