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Caching Made Bootiful — Hazelcast Way

Written by  Viktor Gamov -
hazelcast boot 1
TL;DR
Source code from this blog is posted on the Hazelcast Code Examples repository on Github.

The folks at OpenCredo recently published a blog post entitled «Running and Testing Hazelcast in a Spring Boot Application». They introduce some of the basic features of Hazelcast including: Spring dependency injection, how to embed it in a Spring Boot application and write simple integration tests. It is a really good first reading if your using Spring. Make sure you check it out.

In this post, I will demonstrate how to add caching capabilities using Hazelcast in your Spring Boot application. You will see how the Spring Framework caching abstraction plays nicely with Hazelcast without invoking an explicit Hazelcast API.

Let’s get going!

Intro

As many of you know, a cache stores the data so that future requests for that data is faster.

If the requested data is in the cache (cache hit), this request can be served by simply reading the cache, which is faster because it bypasses slow data retrieval or time-consuming computations. If the data is not in the cache (cache miss), the data has to be recomputed or fetched from its original storage location, which is slower.

In this use-case, I will demonstrate techniques you can speed up various parts of your applications that suffer from slow performance.

Slow service

My service returns city names (method getCity()). I know that retrieving a city might take some time, so I will use Spring Caching annotations to delegate cache interactions with Spring.

My service is annotated with Spring Annotations

import org.springframework.cache.annotation.CachePut;
import org.springframework.cache.annotation.Cacheable;

public interface IDummyBean {

    @Cacheable("city") (1)
    String getCity();

    @CachePut(value = "city", key = "#city + 1") (2)
    String setCity(String city);
}
1 @Cachable annotation triggers population of a cache
2 @CachePut annotation updates the cache without interfering with the method execution

Here is an implementation of this service. It returns the city of Ankara (one of the Hazelcast offices locations). Potentially, I could have used Spring Data or another framework to provide an implementation of a service over a range of SQL or NoSQL stores. For simplicity in this example, I will use a naive implementation that simulates typical latency (like network service, slow delay, poorly tuned database, etc).

public class DummyBean implements IDummyBean {
    @Override
    public String getCity() {
        try {
            TimeUnit.SECONDS.sleep(5); (1)
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
        return "Ankara";
    }
    @Override public String setCity(String city) {
        return city;
    }
}
1 Slow O_o method!
This is an emulation of a slow method. Don’t do it in real life!

I simply annotate a slow method with the @Cacheble annotation and let Spring Boot do the heavy lifting. This is all I need to do with my application logic.

Enable Caching

Hazelcast is often an embedded component of an application. Ultimately, the application instance becomes a member of the Hazelcast cluster. Another option is to separate the actual storage - Hazelcast Cluster - and the application logic by applying a client / server (or in our case client / cluster) setup.

For my example, I have two Spring Boot applications.

  • A BootifulMember is a Spring Boot application with a fully auto-configured embedded Hazelcast member. During application startup, Spring Boot scans the classpath for hazelcast.xml and automatically instantiates Spring’s CacheManager bean backed by HazelcastInstance.

    BootifulMember class
    @SpringBootApplication
    @EnableCaching  (1)
    public class BootifulMember {
        public static void main(String[] args) {
            new SpringApplicationBuilder().profiles("member").sources(BootifulMember.class).run(args);
        }
    }
    1 An @EnableCaching annotation activates Spring Boot «magic» for Hazelcastinstance instantiation.
  • BootifulClient is a Spring Boot web application. It also uses Spring Boot auto configuration for Hazelcast. But in this case, it scans Spring Configuration for a CacheManager bean backed by HazelcastClient.newHazelcastClientinstance() and picks hazelcast-client.xml from the classpath.

    Bootiful client application
    @SpringBootApplication
    @EnableCaching
    public class BootifulClient {
        public static void main(String[] args) {
            new SpringApplicationBuilder().sources(BootifulClient.class).profiles("client").run(args);
        }
    
        @Bean
        public IDummyBean dummyBean() {
            return new DummyBean();     (1)
        }
    
        @Bean
        @Profile("client")
        HazelcastInstance hazelcastInstance() {
            return HazelcastClient.newHazelcastClient();    (2)
        }
    
        @Bean
        CacheManager cacheManager() {
            return new HazelcastCacheManager(hazelcastInstance()); (3)
        }
    
        @RestController
        static class CityController {
    
            private final Logger logger = LoggerFactory.getLogger(CityController.class);
    
            @Autowired
            IDummyBean dummy;   (4)
    
            @RequestMapping("/city")
            public String getCity() { (5)
                String logFormat = "%s call took %d millis with result: %s";
                long start1 = nanoTime();
                String city = dummy.getCity();
                long end1 = nanoTime();
                logger.info(format(logFormat, "Rest", TimeUnit.NANOSECONDS.toMillis(end1 - start1), city));
                return city;
            }
    
            @RequestMapping(value = "city/{city}", method = RequestMethod.GET) (6)
            public String setCity(@PathVariable String city) {
                return dummy.setCity(city);
            }
        }
    }
    1 I’m providing the instance of IDummyBean in the application context.
    2 I’m providing HazelcastInstance based on the client configuration from hazelcast-client.xml
    3 Spring Framework generated proxies for annotated methods will interact with caches using a CacheManager class backed by the Hazelcast client instance.
    4 Property injection. Don’t do this in your real life applications.
    5 I’m measuring the time inside a Rest Controller method and reporting it to the console.
    6 By hitting url http://localhost:8081/city/nyc, for example, we’re writing value nyc to the city cache.

By calling the application on http://localhost:8081/city multiple times, you can take a look at logs in the console.

2015-12-31 00:29:16.372  INFO --- c.h.s.c.BootifulClient$CityController: Rest call took 5075 millis with result: Ankara
2015-12-31 00:29:17.986  INFO --- c.h.s.c.BootifulClient$CityController: Rest call took 3 millis with result: Ankara
2015-12-31 00:29:19.008  INFO --- c.h.s.c.BootifulClient$CityController: Rest call took 1 millis with result: Ankara
2015-12-31 00:29:19.936  INFO --- c.h.s.c.BootifulClient$CityController: Rest call took 1 millis with result: Ankara

You notice that the first call took ~5 sec to return the response. But in all subsequent calls to this URL, the return the response almost immediately. We improved our application speed 5000 times!!!

This is a tip for production deployment of your «bootiful» application. By running mvn package spring-boot:repackage, the Spring Boot Maven plugin will generate an executable jar java -jar.. with BootifulMember as the main class.

It’s a wrap!

Congrats! Now you know how you can benefit from Hazelcast caching auto configuration in Spring Boot applications. In the next blog post, I will review techniques using JCache — a vendor independent caching API for Java — to enable caching in your Spring Boot application. Meanwhile, if you have any questions, feel free to post them in the comments section below!

Happy caching and Happy New Year!