Fix the errors that we introduced in the databricks version (seems like maybe a merge issue)

Author: holdenk

src/main/scala/com/oreilly/learningsparkexamples/scala/BasicParseJsonWithJackson.scala

@@ -27,7 +27,7 @@ object BasicParseJsonWithJackson {
     val outputFile = args(2)
     val sc = new SparkContext(master, "BasicParseJsonWithJackson", System.getenv("SPARK_HOME"))
     val input = sc.textFile(inputFile)
-    
+
     // Parse it into a specific case class. We use mapPartitions beacuse:
     // (a) ObjectMapper is not serializable so we either create a singleton object encapsulating ObjectMapper
     //     on the driver and have to send data back to the driver to go through the singleton object.
@@ -44,13 +44,17 @@ object BasicParseJsonWithJackson {
         // list with one element if everything is ok (Some(_)).
         records.flatMap(record => {
           try {
-            Some(mapper.readValue(record, classOf[ioRecord]))
+            Some(mapper.readValue(record, classOf[Person]))
           } catch {
             case e: Exception => None
           }
         })
-      }, true)
-    result.filter(_.lovesPandas).map(mapper.writeValueAsString(_))
+    }, true)
+    result.filter(_.lovesPandas).mapPartitions(records => {
+      val mapper = new ObjectMapper with ScalaObjectMapper
+      mapper.registerModule(DefaultScalaModule)
+      records.map(mapper.writeValueAsString(_))
+    })
       .saveAsTextFile(outputFile)
     }
 }