Shulou(Shulou.com)06/02 Report--

Many novices are not very clear about the example analysis of Redis integrating Spring and using cache. In order to help you solve this problem, the following editor will explain it in detail. People with this need can come and learn. I hope you can get something.

1. Introduction of Redis

What is Redis?

Redis is a key-value storage system. Similar to Memcached, it supports relatively more value types, including string (string), list (linked list), set (collection), zset (sorted set-ordered collection), and hash (hash type). These data types support push/pop, add/remove, and take intersection union and difference sets and richer operations, and these operations are primitive. On this basis, redis supports a variety of different sorting methods. Like memcached, data is cached in memory for efficiency. The difference is that redis will periodically write updated data to disk or modify operations to additional record files, and on this basis to achieve master-slave (master-slave) synchronization.

What are its characteristics?

(1) the Redis database is completely in memory, and the disk is used only for persistence.

(2) compared with many key data stores, Redis has a rich set of data types.

(3) Redis can copy data to any number of slave servers.

Redis advantages?

(1) extraordinarily fast: the speed of Redis is so fast that it can execute about 110000 sets per second and 81000 + records per second.

(2) support rich data types: Redis supports * most developers already know such data types as lists, collections, ordered collections, and hashes. This makes it very easy to solve a variety of problems, because we know which problems can be handled better through its data types.

(3) the operations are atomic: all Redis operations are atomic, which ensures that the Redis server accessed by two clients at the same time will get the updated value.

(4) Multi-functional utility: Redis is a multi-utility tool that can be used in multiple uses such as caching, message, queue use (Redis native support publish / subscribe), any short-lived data, applications, such as Web application sessions, web page * count, etc.

Shortcomings of Redis?

(1) single thread

(2) memory consumption

Second, use examples

This article uses maven+eclipse+sping

1. Introduce jar package

Org.springframework.data spring-data-redis 1.6.1.RELEASE redis.clients jedis 2.7.3

2. Configure bean

Add the following configuration to application.xml

Some configuration data redis.properties of the configuration file redis is as follows:

# redis Center redis.host=10.75.202.11 redis.port=6379 redis.password=123456 redis.maxIdle=100 redis.maxActive=300 redis.maxWait=1000 redis.testOnBorrow=true redis.timeout=100000 # A class that does not need to be cached targetNames=xxxRecordManager,xxxSetRecordManager,xxxStatisticsIdentificationManager # a method that does not require caching methodNames= # set cache expiration time com.service.impl.xxxRecordManager= 60 com.service.impl.xxxSetRecordManager= 60 defaultCacheExpireTime=3600 fep.local.cache.capacity = 10000

To scan these properties files, add the following configuration to application.xml

Classpath:properties/*.properties

3. Some tool classes

(1) RedisUtil

In the bean above, RedisUtil is an instance used to cache and remove data

Package com.mucfc.msm.common; import java.io.Serializable; import java.util.Set; import java.util.concurrent.TimeUnit; import org.apache.log4j.Logger; import org.springframework.data.redis.core.RedisTemplate; import org.springframework.data.redis.core.ValueOperations; / * redis cache utility class * * / public final class RedisUtil {private Logger logger = Logger.getLogger (RedisUtil.class); private RedisTemplate redisTemplate / * batch delete the corresponding value * * @ param keys * / public void remove (final String... Keys) {for (String key: keys) {remove (key);}} / * * bulk delete key * * @ param pattern * / public void removePattern (final String pattern) {Set keys = redisTemplate.keys (pattern); if (keys.size () > 0) redisTemplate.delete (keys) } / * Delete the corresponding value * * @ param key * / public void remove (final String key) {if (exists (key)) {redisTemplate.delete (key);}} / * determine whether there is a corresponding value * * @ param key * @ return * / public boolean exists (final String key) {return redisTemplate.hasKey (key) } / * read cache * * @ return * / public Object get (final String key) {Object result = null; ValueOperations operations = redisTemplate .opsForValue (); result = operations.get (key); return result;} / * write cache * * @ param key * @ return * / public boolean set (final String key, Object value) {boolean result = false Try {ValueOperations operations = redisTemplate .opsForValue (); operations.set (key, value); result = true;} catch (Exception e) {e.printStackTrace ();} return result;} / * write cache * * @ param key * @ return * / public boolean set (final String key, Object value, Long expireTime) {boolean result = false Try {ValueOperations operations = redisTemplate .opsForValue (); operations.set (key, value); redisTemplate.expire (key, expireTime, TimeUnit.SECONDS); result = true;} catch (Exception e) {e.printStackTrace ();} return result;} public void setRedisTemplate (RedisTemplate redisTemplate) {this.redisTemplate = redisTemplate;}}

(2) MethodCacheInterceptor

Section MethodCacheInterceptor, which is used to add judgment to different methods if there is data in the cache, from caching data. Otherwise, it is fetched from the database * times and the result is saved to the cache.

Package com.mucfc.msm.common; import java.io.File; import java.io.FileInputStream; import java.io.InputStream; import java.util.ArrayList; import java.util.List; import java.util.Properties; import org.aopalliance.intercept.MethodInterceptor; import org.aopalliance.intercept.MethodInvocation; import org.apache.log4j.Logger; public class MethodCacheInterceptor implements MethodInterceptor {private Logger logger = Logger.getLogger (MethodCacheInterceptor.class); private RedisUtil redisUtil; private List targetNamesList; / / No cached service name private List methodNamesList / / the name of the method that is not cached private Long defaultCacheExpireTime; / / cache default expiration time private Long xxxRecordManagerTime; / / private Long xxxSetRecordManagerTime / * initialize read class names and method names that do not need to be cached * / public MethodCacheInterceptor () {try {File f = new File ("D:\\ lunaJee-workspace\\ msm\\ msm_core\\ src\\ main\\ java\\ mucfc\\ msm\\ common\\ cacheConf.properties") / / the location of the configuration file is written directly, so you need to modify InputStream in = new FileInputStream (f); / / InputStream in = getClass (). GetClassLoader (). GetResourceAsStream (/ / "D:\\ lunaJee-workspace\\ msm\\ msm_core\ src\ main\ java\ com\ mucfc\ msm\ common\\ cacheConf.properties"); Properties p = new Properties (); p.load (in) / / split the string String [] targetNames = p.getProperty ("targetNames") .split (","); String [] methodNames = p.getProperty ("methodNames") .split (","); / / load the expiration time setting defaultCacheExpireTime = Long.valueOf (p.getProperty ("defaultCacheExpireTime")); xxxRecordManagerTime = Long.valueOf (p.getProperty ("com.service.impl.xxxRecordManager")) XxxSetRecordManagerTime = Long.valueOf (p.getProperty ("com.service.impl.xxxSetRecordManager")); / / create list targetNamesList = new ArrayList (targetNames.length); methodNamesList = new ArrayList (methodNames.length); Integer maxLen = targetNames.length > methodNames.length? TargetNames.length: methodNames.length; / / add class names and method names that do not need caching to list for (int I = 0; I < maxLen; iSuppli +) {if (I < targetNames.length) {targetNamesList.add (targetNams [I]);} if (I < methodNames.length) {methodNamesList.add (methodNams [I]);}} catch (Exception e) {e.printStackTrace () } @ Override public Object invoke (MethodInvocation invocation) throws Throwable {Object value = null; String targetName = invocation.getThis (). GetClass (). GetName (); String methodName = invocation.getMethod (). GetName (); / / content that does not need to be cached / / if (! isAddCache (StringUtil.subStrForLastDot (targetName), methodName)) {if (! isAddCache (targetName, methodName)) {/ / the result returned by the execution method return invocation.proceed () } Object [] arguments = invocation.getArguments (); String key = getCacheKey (targetName, methodName, arguments); System.out.println (key); try {/ / determine whether there is a cache if (redisUtil.exists (key)) {return redisUtil.get (key);} / / write cache value = invocation.proceed (); if (value! = null) {final String tkey = key; final Object tvalue = value New Thread (new Runnable () {@ Override public void run () {if (tkey.startsWith ("com.service.impl.xxxRecordManager")) {redisUtil.set (tkey, tvalue, xxxRecordManagerTime);} else if (tkey.startsWith ("com.service.impl.xxxSetRecordManager")) {redisUtil.set (tkey, tvalue, xxxSetRecordManagerTime);} else {redisUtil.set (tkey, tvalue, defaultCacheExpireTime) }) .start ();}} catch (Exception e) {e.printStackTrace (); if (value = = null) {return invocation.proceed ();}} return value;} / * * whether to join the cache * * @ return * / private boolean isAddCache (String targetName, String methodName) {boolean flag = true If (targetNamesList.contains (targetName) | | methodNamesList.contains (methodName)) {flag = false;} return flag;} / * create cache key * * @ param targetName * @ param methodName * @ param arguments * / private String getCacheKey (String targetName, String methodName, Object [] arguments) {StringBuffer sbu = new StringBuffer (); sbu.append (targetName) .append ("_") .append (methodName) If ((arguments! = null) & & (arguments.length! = 0) {for (int I = 0; I < arguments.length; iTunes +) {sbu.append ("_") .append (arguments [I]);}} return sbu.toString ();} public void setRedisUtil (RedisUtil redisUtil) {this.redisUtil = redisUtil;}

4. Configure classes or methods that need to be cached

Add the following configuration to application.xml. Multiple classes or methods can be configured.

Com\ .mucfc\ .msm\ .service\ .impl\... * ServiceImpl.*

5. Implementation result:

Write a simple unit test as follows:

@ Test public void getSettUnitBySettUnitIdTest () {String systemId = "CES"; String merchantId = "133"; SettUnit configSettUnit = settUnitService.getSettUnitBySettUnitId (systemId, merchantId," ESP "); SettUnit configSettUnit1 = settUnitService.getSettUnitBySettUnitId (systemId, merchantId," ESP "); boolean flag= (configSettUnit = = configSettUnit1); System.out.println (configSettUnit); logger.info (" find results "+ configSettUnit.getBusinessType ()) / / localSecondFIFOCache.put ("configSettUnit", configSettUnit.getBusinessType ()); / / String string = localSecondFIFOCache.get ("configSettUnit"); logger.info ("find results" + string);}

This is the process of performing unit tests * times:

A breakpoint is made in the class MethodCacheInterceptor, and then this method is entered before each query.

Run in turn, and find that there is no cache, so you will check the database directly.

The printed SQL statement:

Second execution:

Because the cache has already been written when the * is executed. So the second time to fetch data directly from the cache

3. Take the results of two times to compare the addresses:

It turns out that the two are not the same object, yes, it is right. If you are using Ehcache, the memory addresses of the two will be the same. That's because redis and ehcache use different caching mechanisms. Ehcache is based on the memory usage cache of the local computer, so that when caching data is used, it is fetched directly on the local computer. If you convert it to a java object, it will be the same memory address, while redis is on a computer with redis service (usually another computer), so when the data is transferred locally, it will correspond to a different memory address, so using = = to compare will return false. But it does take it from the cache, as we can see from the breakpoint above.

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