Creating an Apache Spark RDD of a Class

When loading data as an Apache Spark RDD, if you have a custom class in your application, you can present the data as objects of your class.

You must define the custom class using Jackson semantics for Scala modules. The following example defines a custom User class: 
case class User (@JsonProperty("_id") id:String, 
            @JsonProperty("first_name") firstName:String,
            @JsonProperty("last_name") lastName: String, 
            @JsonProperty("dob") dob: ODate,
            @JsonProperty("interests") interests: List[String])
In the following example, by supplying User as a type parameter to the function while loading the HPE Ezmeral Data Fabric Database table, you can create an RDD of the User class: 
val userprofilesRDD = sc.loadFromMapRDB[User]("/tmp/user_profiles")
                      .where("condition")
When specifying a bean class, the SELECT clause is unnecessary and is ignored.
You must define a custom bean class as follows: 
public static class Person implements Serializable {
            private String _id;
            private String firstName;
            private String lastName;
            private Date dob;
            private Seq<String> interests;
            public String get_id() { return _id; }
            public void set_id(String _id) { this._id = _id; }
            public String getFirstName() { return firstName; }
            public void setFirstName(String firstName) { this.firstName = firstName; }
            public String getLastName() { return lastName; }
            public void setLastName(String lastName) { this.lastName = lastName; }
            public Date getDob() { return dob; }
            public void setDob(Date dob) { this.dob = dob; }
            public Seq<String> getInterests() { return interests; }
            public void setInterests(Seq<String> interests) { this.interests = interests; }
           }
In the following example, by supplying the User bean class as a type parameter while loading the HPE Ezmeral Data Fabric Database table, you can create a MapRDBJavaRDD of the User class: 
import com.mapr.db.spark.api.java.MapRDBJavaSparkContext;
            
MapRDBJavaSparkContext mapRDBSparkContext = new MapRDBJavaSparkContext(spark.sparkContext());
MapRDBJavaRDD userprofilesRDD = mapRDBSparkContext.loadFromMapRDB("/tmp/user_profiles", 
                                User.class).where(<condition>);