Hey,
        
        I´m trying to retrieve a RDD using the GeomesaSpark class.
        Unfortunately a NullPointerException is thrown during execution
        of this method: 
        GeoMesaSpark.rdd(conf, sparkContext,
          ds, query1);
          
         It says SimpleFeatureType.encodeType throws this
        exception. Is something wrong with my datatore or my arguments?
        Here is my code:
        
                Map<String, String> map =
        new HashMap<String, String>();
         
                map.put("instanceId", "accumulo");
                  map.put("zookeepers", "node1-scads02:2181");
                  map.put("user", "user");       
                  map.put("password",
            "password");
                  map.put("tableName", "gdelt");
                  map.put("featureName",
            "event");
        
         
                AccumuloDataStore
            ds = (AccumuloDataStore) DataStoreFinder.getDataStore(map);
         
                SparkConf sc
            = new SparkConf(true);
                sc.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer");
                sc.set("spark.kryo.serializer.buffer.mb", "24");
                 
                Configuration
            conf = new Configuration();
                SparkConf
            sc2 = GeoMesaSpark.init(sc, ds);
                SparkContext
            sparkContext = new
          SparkContext("spark://node1-scads02:7077", "countryWithMostEvent", sc2);
         
                Filter f =
            Filter.INCLUDE;
                Query query1
            = new Query("gdelt", f, new
          String[]{"Actor1CountryCode",
          "Actor2CountryCode"});
                 
                RDD<SimpleFeature>
            actorResultRDD = GeoMesaSpark.rdd(conf, sparkContext, ds,
            query1);
            
          Thanks again.
          
          ps: It would be great when anybody could post a working
          GeomesaSpark example in Java including a RDD transformation.
          
          Best regards
          Marcel Jacob.
        
        
        
        
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