Hazelcast

Fast Stream Processing with Java, Hazelcast and Apache Pulsar Introduction One of the most useful features of real-time stream processing is to combine the strengths and advantages of various technologies to provide a unique developer experience and an efficient way of processing data in real time at scale. Hazelcast is a…

Hazelcast is a distributed in-memory data store and compute platform that enables you to build highly scalable, fast and responsive applications. Spring Boot is a popular Java-based framework for building microservices and standalone applications. …

For some of our services we use the next set of technologies: Spring Boot, MySql, Hibernate and Hibernate 2nd level cache with Hazelcast as a distributed cache provider. And some day we discovered that the updates to one of our entities in 2nd level cache were not propagated to other…

Distributed schedulers are programs capable of running recurring jobs or workloads across multiple servers. While there are many use cases, let’s assume that some action needs to be applied to all users or sets of grouped users. We know that we can simply build a scheduler in Spring Boot using…

I was reading about caching and came to know some less known things. I hope its helpful for you as well. Before implementing caching answer these questions What is Data retrieval cost from database? What is expected Response time? Do I want consistent data? Do I have metrics in place to validate the benefit? How often the data is changing? What…

1-) Introduction In the previous tutorial, I mentioned about how Resilience4j can be used to rate limit requests. In this tutorial, we will take a look at how Bucket4j library can be used with Spring Boot to rate-limit requests based on the client IP address. …

L2 cache invalidation traffic across multiple nodes can be costly, and can reduce the performance of all nodes. In this article, I describe a possible solution to reduce this invalidation traffic. — Introduction As Oracle says: “A second-level cache is a local store of entity data managed by the persistence provider to improve application performance. A second-level cache helps improve performance by avoiding expensive database calls, keeping the entity data local to the application. A second-level cache is typically transparent to the application…

Today I tried caching with Spring Boot and Hazelcast Caching with Spring Boot Using annotations like @EnableCaching (to allow caching annotation features) @Cachable (invokes method when cache does not exist) @CachePut (always invoke method whenever it is called) the function has to return the value to be cached Example: @CachePut( value = [“some-cache-name”], key = “#user” ) fun getUserPermission(user: User): Permission { return getPermission(user) }

To enable caching in your Spring Boot application, you need to: add org.springframework.boot:spring-boot-starter-cache dependency add @EnableCaching annotation to your main class add @Cacheable("myCacheName") annotation to every method you want to cache Using Hazelcast as Cache Manager https://mvnrepository.com/artifact/com.hazelcast/hazelcast-all/4.2.5 <!-- pom.xml --> <dependency> <groupId>com.hazelcast</groupId> <artifactId>hazelcast-all</artifactId> <version>4.2.5</version> </dependency>