## Uses of Class
org.apache.tinkerpop.gremlin.spark.process.computer.SparkGraphComputer

- Packages that use SparkGraphComputer
  Package | Description
  --- | ---
  org.apache.tinkerpop.gremlin.spark.process.computer |

- - ### Uses of SparkGraphComputer in org.apache.tinkerpop.gremlin.spark.process.computer

    Methods in org.apache.tinkerpop.gremlin.spark.process.computer that return SparkGraphComputer
    Modifier and Type | Method and Description
    --- | ---
    `SparkGraphComputer` | SparkGraphComputer.`configure(String key, Object value)`
    `SparkGraphComputer` | SparkGraphComputer.`graphStorageLevel(StorageLevel storageLevel)` Specifies the method by which the `VertexProgram` created graph is persisted.
    `SparkGraphComputer` | SparkGraphComputer.`master(String clusterManager)` Sets the configuration option for `spark.master` which is the cluster manager to connect to which may be one of the allowed master URLs.
    `SparkGraphComputer` | SparkGraphComputer.`persistContext(boolean persist)` Determines if the Spark context should be left open preventing Spark from garbage collecting unreferenced RDDs.
    `SparkGraphComputer` | SparkGraphComputer.`persistStorageLevel(StorageLevel storageLevel)`
    `SparkGraphComputer` | SparkGraphComputer.`serializer(Class<? extends Serializer> serializer)` Specifies the `org.apache.spark.serializer.Serializer` implementation to use.
    `SparkGraphComputer` | SparkGraphComputer.`skipGraphCache(boolean skip)` Determines if the graph RDD should be cached or not.
    `SparkGraphComputer` | SparkGraphComputer.`skipPartitioner(boolean skip)` Determines if the graph RDD should be partitioned or not.
    `SparkGraphComputer` | SparkGraphComputer.`workers(int workers)` Sets the number of workers.

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