Go to hazelcast.org/documentation

Distributed Map

Hazelcast will partition your map entries and almost evenly distribute onto all Hazelcast members. Distributed maps have 1 backup by default so that if a member goes down, you do not lose data. Backup operations are synchronous, so when a map.put(key, value) returns, it is guaranteed that the entry is replicated to one other node. For the reads, it is also guaranteed that map.get(key) returns the latest value of the entry. Consistency is strictly enforced.

import com.hazelcast.core.Hazelcast;
import java.util.Map;
import java.util.Collection;
import com.hazelcast.config.Config;

Config cfg = new Config();
HazelcastInstance hz = Hazelcast.newHazelcastInstance(cfg);
Map<String, Customer> mapCustomers = hz.getMap("customers");
mapCustomers.put("1", new Customer("Joe", "Smith"));
mapCustomers.put("2", new Customer("Ali", "Selam"));
mapCustomers.put("3", new Customer("Avi", "Noyan"));

Collection<Customer> colCustomers = mapCustomers.values();
for (Customer customer : colCustomers) {
    // process customer
}

HazelcastInstance.getMap() actually returns com.hazelcast.core.IMap which extends java.util.concurrent.ConcurrentMap interface. So methods like ConcurrentMap.putIfAbsent(key,value) and ConcurrentMap.replace(key,value) can be used on distributed map as shown in the example below.

import com.hazelcast.core.Hazelcast;
import java.util.concurrent.ConcurrentMap;

Customer getCustomer (String id) {
    ConcurrentMap<String, Customer> map = Hazelcast.getMap("customers");
    Customer customer = map.get(id);
    if (customer == null) {
        customer = new Customer (id);
        customer = map.putIfAbsent(id, customer);
    }
    return customer;
}               

public boolean updateCustomer (Customer customer) {
    ConcurrentMap<String, Customer> map = Hazelcast.getMap("customers");
    return (map.replace(customer.getId(), customer) != null);            
}

public boolean removeCustomer (Customer customer) {
    ConcurrentMap<String, Customer> map = Hazelcast.getMap("customers");
    return map.remove(customer.getId(), customer) );           
}

All ConcurrentMap operations such as put and remove might wait if the key is locked by another thread in the local or remote JVM. But, they will eventually return with success. ConcurrentMap operations never throw java.util.ConcurrentModificationException.

Also see: