Working with Hazelcast distributed transactions in Java

21 Sep 2023

Hazelcast is an open-source in-memory data grid that provides distributed data storage and computation capabilities. One of the key features of Hazelcast is its support for distributed transactions. In this blog post, we will explore how to work with distributed transactions in Java using Hazelcast.

What are Distributed Transactions?

Distributed transactions occur when multiple operations need to be executed atomically across multiple nodes in a distributed system. Ensuring the consistency and reliability of these transactions can be challenging in a distributed environment due to the possibility of failures and network delays.

Using Hazelcast’s Transactional API

Hazelcast provides a Transactional API that allows you to perform operations as part of a distributed transaction. The Transactional API ensures that either all the operations within a transaction are committed or none of them are, thus maintaining the consistency of data across the distributed system.

To use the Transactional API in Hazelcast, follow these steps:

Create a HazelcastInstance: Start by creating an instance of Hazelcast, which represents the connection to the Hazelcast cluster.
```
Config config = new Config();
HazelcastInstance hazelcastInstance = Hazelcast.newHazelcastInstance(config);
```
Start a Transaction: To start a transaction, obtain a TransactionContext from the HazelcastInstance and begin the transaction:
```
TransactionContext context = hazelcastInstance.newTransactionContext();
context.beginTransaction();
```
Perform Operations: Within the transaction context, perform the desired operations on Hazelcast data structures, such as IMap, IQueue, IMultiMap, etc.
```
IMap<String, Integer> map = context.getMap("myMap");
map.put("key1", 123);
map.put("key2", 456);
```
Commit or Rollback: Finally, either commit the transaction or rollback the changes:
```
context.commitTransaction();
// or
context.rollbackTransaction();
```

Handling Failures and Retries

In a distributed system, failures can occur at any time. Hazelcast’s Transactional API provides automatic retries on transaction failures, ensuring that the changes made within the transaction are eventually applied consistently.

When a transaction fails due to a temporary issue, such as network failure or node failure, Hazelcast automatically retries the transaction until it succeeds or reaches the configured retry limit. If the transaction fails repeatedly, an exception is thrown, indicating the failure.

Conclusion

Distributed transactions are crucial for maintaining data consistency in a distributed system. Hazelcast’s Transactional API simplifies the management of distributed transactions in Java, ensuring atomicity and reliability across multiple nodes.

By following the steps outlined in this blog post, you’ll be able to work with distributed transactions in Hazelcast and handle failures gracefully. So go ahead and leverage Hazelcast’s powerful capabilities to build robust distributed applications with ease!

#distributedtransactions #Hazelcast #Java