Local cache

In distributed systems , Distributed caching is like redis,memcache Use more . actually , Local caching is also necessary in many scenarios .
This paper mainly introduces google The toolkit guava The use of caching tools in .

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Local cache application scenarios ：
(1) Very high performance requirements
(2) Not often change or there are hot words
(3) It can accept the non real-time nature of data

Local caching can be implemented in several ways ：ConcurrentHashMap,Guava cache or Ehcached. Here to talk about Guava cache Use .
Its characteristics are as follows ：

• Use LRU Cache expiration mechanism
• Concurrent processing power ： Be similar to ConcurrentHashMap, It's thread safe , It adopts the segmented lock mechanism .
• Update lock ： stay CacheLoader Of load Control in the method , To the same key, Let only one request read the source and set it in the cache , Other requests block waiting ( Prevent cache breakdown ).
• Integrated data sources ：get Method can read data from the data source and backfill it into the cache when it cannot be read from the cache .
• Monitor cache load / Hit situation

Let's take a look at the code ：

public class LocalCache {
    public static void main(String[] args) throws Exception {
        LoadingCache<ReqArg, String> loadingCache = CacheBuilder.newBuilder()
                .recordStats().maximumSize(1000).expireAfterWrite(1, TimeUnit.MINUTES)
                .build(new CacheLoader<ReqArg, String>() {
                    @Override
                    public String load(ReqArg key) throws Exception {
                        return key.getKey();
                    }
                });

        Thread checkupThread = new Thread(() -> {
            while (true) {
                try {
                    Thread.sleep(1000);
                    System.out.println(loadingCache.stats());
                } catch (InterruptedException e) {
                    break;
                }
            }
        });
        checkupThread.setDaemon(true);
        checkupThread.start();
        
        for (int i = 0; i < 20; i++) {
            String key = String.valueOf(i);
            ReqArg reqArg = new ReqArg(key, key);
            System.out.println(loadingCache.get(reqArg));
        }
        for (int i = 0; i < 10; i++) {
            String key = String.valueOf(i);
            ReqArg reqArg = new ReqArg(key, key);
            System.out.println(loadingCache.get(reqArg));
        }

        Thread.sleep(10 * 60 * 3600);
    }

    static class ReqArg {
        String key;
        String id;

        public ReqArg() {
        }

        public ReqArg(String key, String id) {
            this.key = key;
            this.id = id;
        }

        public String getKey() {
            return key;
        }

        public void setKey(String key) {
            this.key = key;
        }

        public String getId() {
            return id;
        }

        public void setId(String id) {
            this.id = id;
        }

        @Override
        public int hashCode() {
            return new HashCodeBuilder()
                    .append(key)
                    .append(id)
                    .toHashCode();
        }

        @Override
        public boolean equals(Object obj) {
            ReqArg args = (ReqArg) obj;
            return new EqualsBuilder()
                    .append(this.key, args.key)
                    .append(this.id, args.id)
                    .isEquals();
        }
//        public boolean equals(Object o) {
//            return EqualsBuilder.reflectionEquals(this, o);
//
//        }
//
//        public int hashCode() {
//            return HashCodeBuilder.reflectionHashCode(this);
//        }
    }
}

Run the above code , The output is as follows ：

0
1
...
CacheStats{hitCount=10, missCount=20, loadSuccessCount=20, loadExceptionCount=0, totalLoadTime=2012339, evictionCount=0}
CacheStats{hitCount=10, missCount=20, loadSuccessCount=20, loadExceptionCount=0, totalLoadTime=2012339, evictionCount=0}
...

The numbers above are two for The result of the loop output . The following cache hit statistics are threads checkupThread Output . Its meaning is as follows ：
A cache hit 10 Time , Not hit 20 Time , Load data from data source 20 Time .

At the first for In circulation , At this point, the cache is empty , You need to read data from the data source every time (load Method ), And load it into the cache .20 All misses .
In the second for In circulation , All the data has been cached , So read directly from the cache .10 Hit the cache all times .