Access hdfs file from spark worker node - hadoop

Question

I am working on a spark application which needs to access and update an object stored as a file in hdfs. I'm unable to figure out how can I do it?
If I'm creating a FileSystem hdfs object and using it:
boolean fileExists = hdfs.exists(new org.apache.hadoop.fs.Path(filePath));
if (fileExists){
JavaRDD<MyObject> modelRDD = sc.objectFile(filePath);
}
I get:
ERROR Executor: Exception in task 110.0 in stage 1.0 (TID 112)
java.lang.NullPointerException
This part of code runs at the worker so I'm assuming it fails because it doesn't have access to the Spark Context. In such a case, how can I access this hdfs file?
this hdfs file resides at the driver node. I can change replace hdfs with hive, storing data as byte array in hive, but even hive context access is not possible from worker node.
Adding full code for better understanding:
public class MyProgram {
private static JavaSparkContext sc;
private static HiveContext hiveContext;
private static String ObjectPersistenceDir = "/metadata/objects";
private static org.apache.hadoop.fs.FileSystem hdfs;
private static String NameNodeURI = "hdfs://<mymachineurl>:9000";
// create and maintain a cache of objects for every run session
//private static HashMap<String, MyObject> cacheObjects;
public static void main(String ... args) {
System.out.println("Inside constructor: creating Spark context and Hive context");
System.out.println("Starting Spark context and SQL context");
sc = new JavaSparkContext(new SparkConf());
hiveContext = new HiveContext(sc);
//cacheObjects= new HashMap<>();
//DataFrame loadedObjects= hiveContext.sql("select id, filepath from saved_objects where name = 'TEST'");
//List<Row> rows = loadedObjects.collectAsList();
//for(Row row : rows){
// String key = (String) row.get(0) ;
// String value = (String) row.get(1);
// JavaRDD<MyObject> objectRDD = sc.objectFile(value);
// cacheObjects.put(key, objectRDD.first());
//}
DataFrame partitionedDF = hiveContext.sql('select * from mydata');
String partitionColumnName = "id";
JavaRDD<Row> partitionedRecs = partitionedDF.repartition(partitionedDF.col(partitionColumnName)).javaRDD();
FlatMapFunction<Iterator<Row>, MyObject> flatMapSetup = new FlatMapFunction<java.util.Iterator<Row>, MyObject>() {
List<MyObject> lm_list = new ArrayList<>();
MyObject object = null;
#Override
public List<MyObject> call(java.util.Iterator<Row> it) throws Exception {
// for every row, create a record and update the object
while (it.hasNext()) {
Row row = it.next();
if (object == null) {
String objectKey = "" + id;
//object = cacheObjects.get(objectKey);
String modelPath = ModelPersistenceDir + "/" +'TEST'+ "/" + id;
JavaRDD<MyObject> objectRDD = sc.objectFile(objectPath);
object = objectRDD.collect().get(0);
// object not in cache means not already created
if(object == null){
if (object == null){
ObjectDef objectDef = new ObjectDef('TEST');
object = new MyObject(objectDef);
}
}
}
/*
/ some update on object
*/
String objectKey = "" + id ;
cacheObjects.put(objectKey, object);
// Algorithm step 2.6 : to save in hive, add to list
lm_list.add(object);
} // while Has Next ends
return lm_list;
} // Call -- Iterator ends
};//); //Map Partition Ends
//todo_nidhi put all objects in collectedObject back to hive
List<MyObject> collectedObject = partitionedRecs.mapPartitions(flatMapSetup).collect();
}