Filesystem-based Hashtable

Question

I need to store a lot of data in an associative memory. Does anyone know of some HashMap / HashTable or other associative memory equivalent that uses the file system instead of RAM for storage of the data (the data needs only be stored during one java session but is a few GB large, so only the file system can serve as storage space).
So far I found JDBMHashtable on Sourceforge, however, its implementation is lousy and very slow.
Cheers,
Andreas

Answer 1

depending on your data-access needs, perhaps this would work ?import java.util.HashMap;
class BufferedFileHashMap {
     private int bufferSize;
     private HashMap mymap;
     private volatile int additionCount = 0;
     private int buffered = 0;
     public BufferedFileHashMap(int bufferSize){
          mymap               = new HashMap(bufferSize);
          this.bufferSize     = bufferSize;
     public Object put(Object key, Object obj){
          if(additionCount == bufferSize){
               buffered++;
               // serialize mymap and get a new one
               mymap = new HashMap();
          additionCount++;
          return mymap.put(key, obj);
     public Object get(Object key){
          Object obj;
          // check current map ...
          obj = mymap.get(key);
          if(obj != null)
               return obj;
          // save current map to a temp
          // file and read in previously
          // serialized maps.
          for(int k = 0; k < buffered; k++){
               obj = mymap.get(key);
               if(obj != null)
                    break;
               // read in next
          // read back in the current map
          // from the temp location
          return obj;
public class Test {
     public static void main(String[] args){
          BufferedFileHashMap map = new BufferedFileHashMap(1000); // buffer 1000 objects
} allthought, just a thought (never done this before), will the hashmap serialize
all the objects who are also in the map ... ? hmm, perhaps it won't and potentially the
reason this is a big problem, anyway.