What are the ways to handle data in Java?

1. Iteration:

   • for, while, do-while loops.
   • Iterator, ListIterator.
   • Enhanced for loop (foreach).

   List<String> data = new ArrayList<>();
   data.add("item1");
   data.add("item2");
   
   for (String item : data) {
       System.out.println(item); // Processing each element
   }
   

2. Streams:

   • API for declarative collection processing.
   • High-level operations: filter, map, reduce, collect.
   • Support for parallel processing.

   List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5);
   
   List<Integer> evenNumbers = numbers.stream()
                                      .filter(n -> n % 2 == 0) // Filter even
                                      .collect(Collectors.toList()); // Collect into list
   

3. Parallel streams:

   • Extension of streams for automatic parallelization.
   • Simple usage: .parallelStream().

   List<Integer> numbers = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9);
   
   int sum = numbers.parallelStream()
                    .mapToInt(Integer::intValue)
                    .sum(); // Parallel sum
   

4. RxJava / Reactor (Reactive Programming):

   • Reactive programming for asynchronous data stream processing.
   • Uses observables (Observable, Flux) and operators (map, filter, merge).

   // Example with RxJava
   Observable<String> source = Observable.just("Alpha", "Beta", "Gamma");
   
   source.subscribe(s -> System.out.println("Received: " + s)); // Asynchronous processing of each element
   

5. Apache Spark / Hadoop MapReduce:

   • Frameworks for distributed processing of big data.

   • Suitable for ETL, analytics, and data processing at cluster scale.

   • (Code example for Spark/Hadoop is too large for a brief answer, but the essence is distributed computing).

6. Java Data Structures:

   • Use appropriate data structures (Arrays, Lists, Sets, Maps) for efficient data storage and access.
   • For example, HashMap for fast key-based lookup, HashSet for unique elements.

   Map<String, Integer> ages = new HashMap<>();
   ages.put("Alice", 30);
   ages.put("Bob", 25);
   
   System.out.println(ages.get("Alice")); // Fast access by key
   

7. Databases (JDBC / ORM):

   • Handling data stored in external databases.
   • JDBC for direct SQL interaction.
   • ORM (Hibernate, JPA) for object-relational mapping.

   // JDBC example
   try (Connection conn = DriverManager.getConnection(url, user, password);
        Statement stmt = conn.createStatement();
        ResultSet rs = stmt.executeQuery("SELECT name, age FROM users")) {
   
       while (rs.next()) {
           String name = rs.getString("name");
           int age = rs.getInt("age");
           System.out.println("User: " + name + ", Age: " + age); // Processing data from DB
       }
   } catch (SQLException e) {
       e.printStackTrace();
   }
   

The choice of method depends on data volume, performance requirements, parallelism, and complexity of processing.