How to Implement a Disk-Based HashMap in Java?

Question

What are the steps to implement a Disk-Based HashMap in Java?

import java.io.*;
import java.util.*;

public class DiskHashMap<K, V> {
    private final File file;
    private final Map<K, V> inMemoryMap;
    private final int maxSize;

    public DiskHashMap(String filePath, int maxSize) throws IOException {
        this.file = new File(filePath);
        this.inMemoryMap = new HashMap<>();
        this.maxSize = maxSize;
        loadFromDisk();
    }

    private void loadFromDisk() throws IOException {
        if (file.exists()) {
            try (ObjectInputStream ois = new ObjectInputStream(new FileInputStream(file))) {
                inMemoryMap.putAll((Map<K, V>) ois.readObject());
            } catch (ClassNotFoundException e) {
                e.printStackTrace();
            }
        }
    }

    private void saveToDisk() throws IOException {
        try (ObjectOutputStream oos = new ObjectOutputStream(new FileOutputStream(file))) {
            oos.writeObject(inMemoryMap);
        }
    }

    public V put(K key, V value) throws IOException {
        if (inMemoryMap.size() >= maxSize) {
            saveToDisk();
            inMemoryMap.clear();
        }
        return inMemoryMap.put(key, value);
    }
    
    public V get(K key) {
        return inMemoryMap.get(key);
    }
}

Answer

A Disk-Based HashMap is a data structure that utilizes disk storage to handle larger datasets beyond memory capacity. This approach allows for efficient data retrieval while minimizing memory usage, making it suitable for applications with substantial data requirements.

// Insert data and save it to disk on exceeding memory threshold
public V put(K key, V value) throws IOException {
    if (inMemoryMap.size() >= maxSize) {
        saveToDisk();  // Save current in-memory state
        inMemoryMap.clear();  // Clear memory to free up space
    }
    return inMemoryMap.put(key, value);
}

Causes

High memory consumption when loading large datasets entirely into memory.
Need for persistent data storage for hashed entries.
Efficiency in data retrieval and storage.

Solutions

Implement lazy loading of data from disk to memory.
Use serialization to save the HashMap state to disk before clearing memory.
Allow for dynamic resizing of the data structure based on usage and performance metrics.

Common Mistakes

Mistake: Not handling IOException during file operations.

Solution: Wrap disk operations in try-catch blocks and handle exceptions gracefully.

Mistake: Overestimating the capacity of the in-memory HashMap.

Solution: Set realistic maximum sizes based on available memory and application needs.

Helpers

disk-based HashMap implementation
Java HashMap to disk
persistent data storage Java
efficient data retrieval Java