How do I process a list of objects in parallel in Java?

I have a list of approximately a thousand Java objects and am iterating a List container to process them, the same processing for every object. This sequential approach is taking a lot of time for processing, so I want to attempt to speed it up with parallel processing. I checked Java executor frameworks but got stuck.

I thought of one approach to implement my requirement. I want to specify some minimum fixed number of objects to be processed by each thread so that each does its processing in a quick manner. How can I achieve this? Should I use another approach?

For example:

List<Object> objects = new List<Object>(); 

for (Object object : objects) {
  // Doing some common operation for all Objects 
}

You can use a ThreadPoolExecutor, it will take care of load balance. Tasks will be distributed on different threads.

Here is an example:

import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;

public class Test {

    public static void main(String[] args) {

        // Fixed thread number
        ExecutorService service = Executors.newFixedThreadPool(10);

        // Or un fixed thread number
        // The number of threads will increase with tasks
        // ExecutorService service = Executors.newCachedThreadPool(10);

        List<Object> objects = new ArrayList<>();
        for (Object o : objects) {
            service.execute(new MyTask(o));
        }

        // shutdown
        // this will get blocked until all task finish
        service.shutdown();
        try {
            service.awaitTermination(Long.MAX_VALUE, TimeUnit.MILLISECONDS);
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
    }

    public static class MyTask implements Runnable {
        Object target;

        public MyTask(Object target) {
            this.target = target;
        }

        @Override
        public void run() {
            // business logic at here
        }
    }
}