hadoop - Access hdfs file from spark worker node -

i working on spark application needs access , update object stored file in hdfs. i'm unable figure out how can it?

if i'm creating filesystem hdfs object , 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 @ worker i'm assuming fails because doesn't have access spark context. in such case, how can access hdfs file?

this hdfs file resides @ driver node. can change replace hdfs hive, storing data byte array in hive, hive context access not possible worker node.

adding full code 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 , maintain cache of objects every run session     //private static hashmap<string, myobject> cacheobjects;      public static void main(string ... args) {         system.out.println("inside constructor: creating spark context , hive context");         system.out.println("starting spark context , sql context");          sc = new javasparkcontext(new sparkconf());         hivecontext = new hivecontext(sc);          //cacheobjects= new hashmap<>();          //dataframe loadedobjects= hivecontext.sql("select id, filepath saved_objects 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 * 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 {                 // every row, create record , update 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 created                         if(object == null){                             if (object == null){                                 objectdef objectdef = new objectdef('test');                                 object = new myobject(objectdef);                             }                         }                     }                      /*                     / update on object                     */                      string objectkey = "" + id ;                     cacheobjects.put(objectkey, object);                      // algorithm step 2.6 : save in hive, add list                     lm_list.add(object);                 } // while has next ends                 return lm_list;             } // call -- iterator ends         };//); //map partition ends          //todo_nidhi put objects in collectedobject hive         list<myobject> collectedobject =  partitionedrecs.mappartitions(flatmapsetup).collect(); }