#590 add explanation for caching pattern

caching/README.md

@@ -10,20 +10,326 @@ tags:
 ---
 
 ## Intent
-To avoid expensive re-acquisition of resources by not releasing
-the resources immediately after their use. The resources retain their identity, are kept in some
-fast-access storage, and are re-used to avoid having to acquire them again.
+
+The caching pattern avoids expensive re-acquisition of resources by not releasing them immediately 
+after use. The resources retain their identity, are kept in some fast-access storage, and are 
+re-used to avoid having to acquire them again.
+
+## Explanation
+
+Real world example
+
+> A team is working on a website that provides new homes for abandoned cats. People can post their
+> cats on the website after registering, but all the new posts require approval from one of the
+> site moderators. The user accounts of the site moderators contain a specific flag and the data
+> is stored in a MongoDB database. Checking for the moderator flag each time a post is viewed 
+> becomes expensive and it's a good idea to utilize caching here.
+
+In plain words
+
+> Caching pattern keeps frequently needed data in fast-access storage to improve performance.
+
+Wikipedia says:
+
+> In computing, a cache is a hardware or software component that stores data so that future 
+> requests for that data can be served faster; the data stored in a cache might be the result of 
+> an earlier computation or a copy of data stored elsewhere. A cache hit occurs when the requested 
+> data can be found in a cache, while a cache miss occurs when it cannot. Cache hits are served by 
+> reading data from the cache, which is faster than recomputing a result or reading from a slower 
+> data store; thus, the more requests that can be served from the cache, the faster the system 
+> performs.
+
+**Programmatic Example**
+
+Let's first look at the data layer of our application. The interesting classes are `UserAccount`
+which is a simple Java object containing the user account details, and `DbManager` which handles
+reading and writing of these objects to/from MongoDB database.
+
+```java
+@Setter
+@Getter
+@AllArgsConstructor
+@ToString
+public class UserAccount {
+  private String userId;
+  private String userName;
+  private String additionalInfo;
+}
+
+@Slf4j
+public final class DbManager {
+
+  private static MongoClient mongoClient;
+  private static MongoDatabase db;
+
+  private DbManager() { /*...*/ }
+
+  public static void createVirtualDb() { /*...*/ }
+
+  public static void connect() throws ParseException { /*...*/ }
+
+  public static UserAccount readFromDb(String userId) { /*...*/ }
+
+  public static void writeToDb(UserAccount userAccount) { /*...*/ }
+
+  public static void updateDb(UserAccount userAccount) { /*...*/ }
+
+  public static void upsertDb(UserAccount userAccount) { /*...*/ }
+}
+```
+
+In the example, we are demonstrating various different caching policies
+
+* Write-through writes data to the cache and DB in a single transaction
+* Write-around writes data immediately into the DB instead of the cache
+* Write-behind writes data into the cache initially whilst the data is only written into the DB 
+  when the cache is full
+* Cache-aside pushes the responsibility of keeping the data synchronized in both data sources to 
+  the application itself
+* Read-through strategy is also included in the aforementioned strategies and it returns data from 
+  the cache to the caller if it exists, otherwise queries from DB and stores it into the cache for 
+  future use.
+  
+The cache implementation in `LruCache` is a hash table accompanied by a doubly 
+linked-list. The linked-list helps in capturing and maintaining the LRU data in the cache. When 
+data is queried (from the cache), added (to the cache), or updated, the data is moved to the front 
+of the list to depict itself as the most-recently-used data. The LRU data is always at the end of 
+the list.
+
+```java
+@Slf4j
+public class LruCache {
+
+  static class Node {
+    String userId;
+    UserAccount userAccount;
+    Node previous;
+    Node next;
+
+    public Node(String userId, UserAccount userAccount) {
+      this.userId = userId;
+      this.userAccount = userAccount;
+    }
+  }
+  
+  /* ... omitted details ... */
+
+  public LruCache(int capacity) {
+    this.capacity = capacity;
+  }
+
+  public UserAccount get(String userId) {
+    if (cache.containsKey(userId)) {
+      var node = cache.get(userId);
+      remove(node);
+      setHead(node);
+      return node.userAccount;
+    }
+    return null;
+  }
+
+  public void set(String userId, UserAccount userAccount) {
+    if (cache.containsKey(userId)) {
+      var old = cache.get(userId);
+      old.userAccount = userAccount;
+      remove(old);
+      setHead(old);
+    } else {
+      var newNode = new Node(userId, userAccount);
+      if (cache.size() >= capacity) {
+        LOGGER.info("# Cache is FULL! Removing {} from cache...", end.userId);
+        cache.remove(end.userId); // remove LRU data from cache.
+        remove(end);
+        setHead(newNode);
+      } else {
+        setHead(newNode);
+      }
+      cache.put(userId, newNode);
+    }
+  }
+
+  public boolean contains(String userId) {
+    return cache.containsKey(userId);
+  }
+  
+  public void remove(Node node) { /* ... */ }
+  public void setHead(Node node) { /* ... */ }
+  public void invalidate(String userId) { /* ... */ }
+  public boolean isFull() { /* ... */ }
+  public UserAccount getLruData() { /* ... */ }
+  public void clear() { /* ... */ }
+  public List<UserAccount> getCacheDataInListForm() { /* ... */ }
+  public void setCapacity(int newCapacity) { /* ... */ }
+}
+```
+
+The next layer we are going to look at is `CacheStore` which implements the different caching
+strategies.
+
+```java
+@Slf4j
+public class CacheStore {
+
+  private static LruCache cache;
+
+  /* ... details omitted ... */
+
+  public static UserAccount readThrough(String userId) {
+    if (cache.contains(userId)) {
+      LOGGER.info("# Cache Hit!");
+      return cache.get(userId);
+    }
+    LOGGER.info("# Cache Miss!");
+    UserAccount userAccount = DbManager.readFromDb(userId);
+    cache.set(userId, userAccount);
+    return userAccount;
+  }
+
+  public static void writeThrough(UserAccount userAccount) {
+    if (cache.contains(userAccount.getUserId())) {
+      DbManager.updateDb(userAccount);
+    } else {
+      DbManager.writeToDb(userAccount);
+    }
+    cache.set(userAccount.getUserId(), userAccount);
+  }
+
+  public static void clearCache() {
+    if (cache != null) {
+      cache.clear();
+    }
+  }
+
+  public static void flushCache() {
+    LOGGER.info("# flushCache...");
+    Optional.ofNullable(cache)
+        .map(LruCache::getCacheDataInListForm)
+        .orElse(List.of())
+        .forEach(DbManager::updateDb);
+  }
+
+  /* ... omitted the implementation of other caching strategies ... */
+
+}
+```
+
+`AppManager` helps to bridge the gap in communication between the main class and the application's
+back-end. DB connection is initialized through this class. The chosen caching strategy/policy is
+also initialized here. Before the cache can be used, the size of the cache has to be set. Depending 
+on the chosen caching policy, `AppManager` will call the appropriate function in the `CacheStore` 
+class.
+
+```java
+@Slf4j
+public final class AppManager {
+
+  private static CachingPolicy cachingPolicy;
+
+  private AppManager() {
+  }
+
+  public static void initDb(boolean useMongoDb) { /* ... */ }
+
+  public static void initCachingPolicy(CachingPolicy policy) { /* ... */ }
+
+  public static void initCacheCapacity(int capacity) { /* ... */ }
+
+  public static UserAccount find(String userId) {
+    if (cachingPolicy == CachingPolicy.THROUGH || cachingPolicy == CachingPolicy.AROUND) {
+      return CacheStore.readThrough(userId);
+    } else if (cachingPolicy == CachingPolicy.BEHIND) {
+      return CacheStore.readThroughWithWriteBackPolicy(userId);
+    } else if (cachingPolicy == CachingPolicy.ASIDE) {
+      return findAside(userId);
+    }
+    return null;
+  }
+
+  public static void save(UserAccount userAccount) {
+    if (cachingPolicy == CachingPolicy.THROUGH) {
+      CacheStore.writeThrough(userAccount);
+    } else if (cachingPolicy == CachingPolicy.AROUND) {
+      CacheStore.writeAround(userAccount);
+    } else if (cachingPolicy == CachingPolicy.BEHIND) {
+      CacheStore.writeBehind(userAccount);
+    } else if (cachingPolicy == CachingPolicy.ASIDE) {
+      saveAside(userAccount);
+    }
+  }
+
+  public static String printCacheContent() {
+    return CacheStore.print();
+  }
+
+  /* ... details omitted ... */
+}
+```
+
+Here is what we do in the main class of the application.
+
+```java
+@Slf4j
+public class App {
+
+  public static void main(String[] args) {
+    AppManager.initDb(false);
+    AppManager.initCacheCapacity(3);
+    var app = new App();
+    app.useReadAndWriteThroughStrategy();
+    app.useReadThroughAndWriteAroundStrategy();
+    app.useReadThroughAndWriteBehindStrategy();
+    app.useCacheAsideStategy();
+  }
+
+  public void useReadAndWriteThroughStrategy() {
+    LOGGER.info("# CachingPolicy.THROUGH");
+    AppManager.initCachingPolicy(CachingPolicy.THROUGH);
+    var userAccount1 = new UserAccount("001", "John", "He is a boy.");
+    AppManager.save(userAccount1);
+    LOGGER.info(AppManager.printCacheContent());
+    AppManager.find("001");
+    AppManager.find("001");
+  }
+
+  public void useReadThroughAndWriteAroundStrategy() { /* ... */ }
+
+  public void useReadThroughAndWriteBehindStrategy() { /* ... */ }
+
+  public void useCacheAsideStategy() { /* ... */ }
+}
+```
+
+Finally, here is some of the console output from the program.
+
+```
+12:32:53.845 [main] INFO com.iluwatar.caching.App - # CachingPolicy.THROUGH
+12:32:53.900 [main] INFO com.iluwatar.caching.App - 
+--CACHE CONTENT--
+UserAccount(userId=001, userName=John, additionalInfo=He is a boy.)
+----
+```
 
 ## Class diagram
+
 ![alt text](./etc/caching.png "Caching")
 
 ## Applicability
+
 Use the Caching pattern(s) when
 
-* Repetitious acquisition, initialization, and release of the same resource causes unnecessary performance overhead.
+* Repetitious acquisition, initialization, and release of the same resource cause unnecessary 
+  performance overhead.
+
+## Related patterns
+
+* [Proxy](https://java-design-patterns.com/patterns/proxy/)
 
 ## Credits
 
 * [Write-through, write-around, write-back: Cache explained](http://www.computerweekly.com/feature/Write-through-write-around-write-back-Cache-explained)
 * [Read-Through, Write-Through, Write-Behind, and Refresh-Ahead Caching](https://docs.oracle.com/cd/E15357_01/coh.360/e15723/cache_rtwtwbra.htm#COHDG5177)
 * [Cache-Aside pattern](https://docs.microsoft.com/en-us/azure/architecture/patterns/cache-aside)
+* [Java EE 8 High Performance: Master techniques such as memory optimization, caching, concurrency, and multithreading to achieve maximum performance from your enterprise applications](https://www.amazon.com/gp/product/178847306X/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=javadesignpat-20&creative=9325&linkCode=as2&creativeASIN=178847306X&linkId=e948720055599f248cdac47da9125ff4)
+* [Java Performance: In-Depth Advice for Tuning and Programming Java 8, 11, and Beyond](https://www.amazon.com/gp/product/1492056111/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=javadesignpat-20&creative=9325&linkCode=as2&creativeASIN=1492056111&linkId=7e553581559b9ec04221259e52004b08)
+* [Effective Java](https://www.amazon.com/gp/product/B078H61SCH/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=javadesignpat-20&creative=9325&linkCode=as2&creativeASIN=B078H61SCH&linkId=f06607a0b48c76541ef19c5b8b9e7882)
+* [Java Performance: The Definitive Guide: Getting the Most Out of Your Code](https://www.amazon.com/gp/product/1449358454/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=javadesignpat-20&creative=9325&linkCode=as2&creativeASIN=1449358454&linkId=475c18363e350630cc0b39ab681b2687)

caching/src/main/java/com/iluwatar/caching/AppManager.java

@@ -25,6 +25,7 @@ package com.iluwatar.caching;
 
 import java.text.ParseException;
 import java.util.Optional;
+import lombok.extern.slf4j.Slf4j;
 
 /**
  * AppManager helps to bridge the gap in communication between the main class and the application's
@@ -33,6 +34,7 @@ import java.util.Optional;
  * Depending on the chosen caching policy, AppManager will call the appropriate function in the
  * CacheStore class.
  */
+@Slf4j
 public final class AppManager {
 
   private static CachingPolicy cachingPolicy;
@@ -50,7 +52,7 @@ public final class AppManager {
       try {
         DbManager.connect();
       } catch (ParseException e) {
-        e.printStackTrace();
+        LOGGER.error("Error connecting to MongoDB", e);
       }
     } else {
       DbManager.createVirtualDb();

caching/src/main/java/com/iluwatar/caching/DbManager.java

@@ -30,6 +30,7 @@ import com.mongodb.client.model.UpdateOptions;
 import java.text.ParseException;
 import java.util.HashMap;
 import java.util.Map;
+import lombok.extern.slf4j.Slf4j;
 import org.bson.Document;
 
 /**
@@ -41,6 +42,7 @@ import org.bson.Document;
  * underlying data storage (connect()) or a simple Java data structure to (temporarily) store the
  * data/objects during runtime (createVirtualDB()).</p>
  */
+@Slf4j
 public final class DbManager {
 
   private static MongoClient mongoClient;
@@ -83,7 +85,7 @@ public final class DbManager {
       try {
         connect();
       } catch (ParseException e) {
-        e.printStackTrace();
+        LOGGER.error("Error connecting to MongoDB", e);
       }
     }
     var iterable = db
@@ -110,7 +112,7 @@ public final class DbManager {
       try {
         connect();
       } catch (ParseException e) {
-        e.printStackTrace();
+        LOGGER.error("Error connecting to MongoDB", e);
       }
     }
     db.getCollection(CachingConstants.USER_ACCOUNT).insertOne(
@@ -132,7 +134,7 @@ public final class DbManager {
       try {
         connect();
       } catch (ParseException e) {
-        e.printStackTrace();
+        LOGGER.error("Error connecting to MongoDB", e);
       }
     }
     db.getCollection(CachingConstants.USER_ACCOUNT).updateOne(
@@ -153,7 +155,7 @@ public final class DbManager {
       try {
         connect();
       } catch (ParseException e) {
-        e.printStackTrace();
+        LOGGER.error("Error connecting to MongoDB", e);
       }
     }
     db.getCollection(CachingConstants.USER_ACCOUNT).updateOne(