anchor.diff:    }
   ----
   
  -=== Working with MaprFS
  -
  -First, build the jar with mapr 5 dependencies.
  -
  -[literal]
  -mvn clean package -Dmaven.test.skip=true -Dhadoop-version=mapr5
  -
  -
  -This will generate the `target/storm-solr-1.0-mapr5-SNAPSHOT.jar` that contains the Storm JAR needed to deploy a topology.
  -
  -In order to execute the `hdfs-to-solr` example, add the spring `fs.hdfs.impl` property to your `Config.groovy` file with the `com.mapr.fs.MapRFileSystem` value. Also, change the `fs.defaultFS` property to use the maprfs schema.
  -
  -[source,groovy]
  -----
  -   spring.fs.defaultFS = "maprfs://cldbhost:port"
  -   spring.fs.hdfs.impl = "com.mapr.fs.MapRFileSystem"
  -
  -----
  +// end::storm-kerberos[]
  +// end::topology[]
  
positive.code: ----
  
  Take a look at the TwitterDataProvider implementation provided in the project as a starting point for implementing a Spring-managed bean for your topology.
  
  
  === Unit Testing
  
  When writing a unit test, you don’t want to have to spin up a Storm cluster to test application-specific logic that doesn’t depend on Storm. Recall that one of the benefits of using this framework is that it separates business logic from Storm boilerplate code. Let’s look at some code from the unit test for our SolrBoltAction implementation.
  
  [source,java]
  ----
  
negative.code: LocalCluster cluster = new LocalCluster();
  cluster.submitTopology(topologyName, stormConf, topologyFactory.build(this));
  try {
     Thread.sleep(localRunSecs * 1000);
  } catch (InterruptedException ie) { ... }
  cluster.killTopology(topologyName);
  cluster.shutdown();
  