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Android DiskLruCache磁盘缓存机制原理 关于Android的 DiskLruCache磁盘缓存机制原理

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一、为什么用DiskLruCache

1、LruCache和DiskLruCache

LruCacheDiskLruCache两者都是利用到LRU算法,通过LRU算法对缓存进行管理,以最近最少使用作为管理的依据,删除最近最少使用的数据,保留最近最常用的数据;

LruCache运用于内存缓存,而DiskLruCache是存储设备缓存;

2、为何使用DiskLruCache

离线数据存在的意义,当无网络或者是网络状况不好时,APP依然具备部分功能是一种很好的用户体验;

假设网易新闻这类新闻客户端,数据完全存储在缓存中而不使用DiskLruCache技术存储,那么当客户端被销毁,缓存被释放,意味着再次打开APP将是一片空白;

另外DiskLruCache技术也可为app“离线阅读”这一功能做技术支持;

DiskLruCache的存储路径是可以自定义的,不过也可以是默认的存储路径,而默认的存储路径一般是这样的:/sdcard/Android/data/包名/cache,包名是指APP的包名。我们可以在手机上打开,浏览这一路径;

二、DiskLruCache使用

1、添加依赖

// add dependence 
implementation 'com.jakewharton:disklrucache:2.0.2' 


2、创建DiskLruCache对象

/* 
 * directory – 缓存目录 
 * appVersion - 缓存版本 
 * valueCount – 每个key对应value的个数 
 * maxSize – 缓存大小的上限 
 */ 
DiskLruCache diskLruCache = DiskLruCache.open(directory, 1, 1, 1024 * 1024 * 10); 

3、添加 / 获取 缓存(一对一)

/** 
 * 添加一条缓存,一个key对应一个value 
 */ 
public void addDiskCache(String key, String value) throws IOException { 
    File cacheDir = context.getCacheDir(); 
    DiskLruCache diskLruCache = DiskLruCache.open(cacheDir, 1, 1, 1024 * 1024 * 10); 
    DiskLruCache.Editor editor = diskLruCache.edit(key); 
    // index与valueCount对应,分别为0,1,2...valueCount-1 
    editor.newOutputStream(0).write(value.getBytes());  
    editor.commit(); 
    diskLruCache.close(); 
} 
/** 
 * 获取一条缓存,一个key对应一个value 
 */ 
public void getDiskCache(String key) throws IOException { 
    File directory = context.getCacheDir(); 
    DiskLruCache diskLruCache = DiskLruCache.open(directory, 1, 1, 1024 * 1024 * 10); 
    String value = diskLruCache.get(key).getString(0); 
    diskLruCache.close(); 
} 

4、添加 / 获取 缓存(一对多)

/** 
 * 添加一条缓存,1个key对应2个value 
 */ 
public void addDiskCache(String key, String value1, String value2) throws IOException { 
    File directory = context.getCacheDir(); 
    DiskLruCache diskLruCache = DiskLruCache.open(directory, 1, 2, 1024 * 1024 * 10); 
    DiskLruCache.Editor editor = diskLruCache.edit(key); 
    editor.newOutputStream(0).write(value1.getBytes()); 
    editor.newOutputStream(1).write(value2.getBytes()); 
    editor.commit(); 
    diskLruCache.close(); 
} 
/** 
 * 添加一条缓存,1个key对应2个value 
 */ 
public void getDiskCache(String key) throws IOException { 
    File directory = context.getCacheDir(); 
    DiskLruCache diskLruCache = DiskLruCache.open(directory, 1, 2, 1024); 
    DiskLruCache.Snapshot snapshot = diskLruCache.get(key); 
    String value1 = snapshot.getString(0); 
    String value2 = snapshot.getString(1); 
    diskLruCache.close(); 
} 

三、源码分析

1、open()

DiskLruCache的构造方法是private修饰,这也就是告诉我们,不能通过new DiskLruCache来获取实例,构造方法如下:

private DiskLruCache(File directory, int appVersion, int valueCount, long maxSize) { 
    this.directory = directory; 
    this.appVersion = appVersion; 
    this.journalFile = new File(directory, JOURNAL_FILE); 
    this.journalFileTmp = new File(directory, JOURNAL_FILE_TEMP); 
    this.journalFileBackup = new File(directory, JOURNAL_FILE_BACKUP); 
    this.valueCount = valueCount; 
    this.maxSize = maxSize; 
} 


但是提供了open()方法,供我们获取DiskLruCache的实例,open方法如下:

/** 
   * Opens the cache in {@code directory}, creating a cache if none exists 
   * there. 
   * 
   * @param directory a writable directory 
   * @param valueCount the number of values per cache entry. Must be positive. 
   * @param maxSize the maximum number of bytes this cache should use to store 
   * @throws IOException if reading or writing the cache directory fails 
   */ 
  public static DiskLruCache open(File directory, int appVersion, int valueCount, long maxSize) 
      throws IOException { 
    if (maxSize <= 0) { 
      throw new IllegalArgumentException("maxSize <= 0"); 
    } 
    if (valueCount <= 0) { 
      throw new IllegalArgumentException("valueCount <= 0"); 
    } 
    // If a bkp file exists, use it instead. 
    //看备份文件是否存在 
    File backupFile = new File(directory, JOURNAL_FILE_BACKUP); 
   //如果备份文件存在,并且日志文件也存在,就把备份文件删除 
    //如果备份文件存在,日志文件不存在,就把备份文件重命名为日志文件 
     if (backupFile.exists()) { 
      File journalFile = new File(directory, JOURNAL_FILE); 
      // If journal file also exists just delete backup file. 
        // 
      if (journalFile.exists()) { 
        backupFile.delete(); 
      } else { 
        renameTo(backupFile, journalFile, false); 
      } 
    } 
    // Prefer to pick up where we left off. 
    //初始化DiskLruCache,包括,大小,版本,路径,key对应多少value 
    DiskLruCache cache = new DiskLruCache(directory, appVersion, valueCount, maxSize); 
    //如果日志文件存在,就开始赌文件信息,并返回 
    //主要就是构建entry列表 
    if (cache.journalFile.exists()) { 
      try { 
        cache.readJournal(); 
        cache.processJournal(); 
        return cache; 
      } catch (IOException journalIsCorrupt) { 
        System.out 
            .println("DiskLruCache " 
                + directory 
                + " is corrupt: " 
                + journalIsCorrupt.getMessage() 
                + ", removing"); 
        cache.delete(); 
      } 
    } 
    //不存在就新建一个 
    // Create a new empty cache. 
    directory.mkdirs(); 
    cache = new DiskLruCache(directory, appVersion, valueCount, maxSize); 
    cache.rebuildJournal(); 
    return cache; 
  } 
open函数:如果日志文件存在,直接去构建entry列表;如果不存在,就构建日志文件;

2、rebuildJournal()

构建文件: 
  //这个就是我们可以直接在disk里面看到的journal文件 主要就是对他的操作 
 private final File journalFile; 
 //journal文件的temp 缓存文件,一般都是先构建这个缓存文件,等待构建完成以后将这个缓存文件重新命名为journal 
 private final File journalFileTmp; 
/** 
   * Creates a new journal that omits redundant information. This replaces the 
   * current journal if it exists. 
   */ 
  private synchronized void rebuildJournal() throws IOException { 
    if (journalWriter != null) { 
      journalWriter.close(); 
    } 
    //指向journalFileTmp这个日志文件的缓存 
    Writer writer = new BufferedWriter( 
        new OutputStreamWriter(new FileOutputStream(journalFileTmp), Util.US_ASCII)); 
    try { 
      writer.write(MAGIC); 
      writer.write("\n"); 
      writer.write(VERSION_1); 
      writer.write("\n"); 
      writer.write(Integer.toString(appVersion)); 
      writer.write("\n"); 
      writer.write(Integer.toString(valueCount)); 
      writer.write("\n"); 
      writer.write("\n"); 
      for (Entry entry : lruEntries.values()) { 
        if (entry.currentEditor != null) { 
          writer.write(DIRTY + ' ' + entry.key + '\n'); 
        } else { 
          writer.write(CLEAN + ' ' + entry.key + entry.getLengths() + '\n'); 
        } 
      } 
    } finally { 
      writer.close(); 
    } 
    if (journalFile.exists()) { 
      renameTo(journalFile, journalFileBackup, true); 
    } 
     //所以这个地方 构建日志文件的流程主要就是先构建出日志文件的缓存文件,如果缓存构建成功 那就直接重命名这个缓存文件,这样做好处在哪里? 
    renameTo(journalFileTmp, journalFile, false); 
    journalFileBackup.delete(); 
    //这里也是把写入日志文件的writer初始化 
    journalWriter = new BufferedWriter( 
        new OutputStreamWriter(new FileOutputStream(journalFile, true), Util.US_ASCII)); 
  } 


来看当日志文件存在的时候,做了什么

3、readJournal()

private void readJournal() throws IOException { 
StrictLineReader reader = new StrictLineReader(new FileInputStream(journalFile), Util.US_ASCII); 
try { 
//读日志文件的头信息 
  String magic = reader.readLine(); 
  String version = reader.readLine(); 
  String appVersionString = reader.readLine(); 
  String valueCountString = reader.readLine(); 
  String blank = reader.readLine(); 
  if (!MAGIC.equals(magic) 
      || !VERSION_1.equals(version) 
      || !Integer.toString(appVersion).equals(appVersionString) 
      || !Integer.toString(valueCount).equals(valueCountString) 
      || !"".equals(blank)) { 
    throw new IOException("unexpected journal header: [" + magic + ", " + version + ", " 
        + valueCountString + ", " + blank + "]"); 
  } 
//这里开始,就开始读取日志信息 
  int lineCount = 0; 
  while (true) { 
    try { 
    //构建LruEntries entry列表 
      readJournalLine(reader.readLine()); 
      lineCount++; 
    } catch (EOFException endOfJournal) { 
      break; 
    } 
  } 
  redundantOpCount = lineCount - lruEntries.size(); 
  // If we ended on a truncated line, rebuild the journal before appending to it. 
  if (reader.hasUnterminatedLine()) { 
    rebuildJournal(); 
  } else { 
    //初始化写入文件的writer 
    journalWriter = new BufferedWriter(new OutputStreamWriter( 
        new FileOutputStream(journalFile, true), Util.US_ASCII)); 
  } 
} finally { 
  Util.closeQuietly(reader); 
} 
} 


然后看下这个函数里面的几个主要变量:

//每个entry对应的缓存文件的格式 一般为1,也就是一个key,对应几个缓存,一般设为1,key-value一一对应的关系 
private final int valueCount; 
private long size = 0; 
//这个是专门用于写入日志文件的writer 
private Writer journalWriter; 
//这个集合应该不陌生了, 
private final LinkedHashMap<String, Entry> lruEntries = 
        new LinkedHashMap<String, Entry>(0, 0.75f, true); 
//这个值大于一定数目时 就会触发对journal文件的清理了 
private int redundantOpCount; 


下面就看下entry这个实体类的内部结构

private final class Entry { 
        private final String key; 
        /** 
         * Lengths of this entry's files. 
         * 这个entry中 每个文件的长度,这个数组的长度为valueCount 一般都是1 
         */ 
        private final long[] lengths; 
        /** 
         * True if this entry has ever been published. 
         * 曾经被发布过 那他的值就是true 
         */ 
        private boolean readable; 
        /** 
         * The ongoing edit or null if this entry is not being edited. 
         * 这个entry对应的editor 
         */ 
        private Editor currentEditor; 
        @Override 
        public String toString() { 
            return "Entry{" + 
                    "key='" + key + '\'' + 
                    ", lengths=" + Arrays.toString(lengths) + 
                    ", readable=" + readable + 
                    ", currentEditor=" + currentEditor + 
                    ", sequenceNumber=" + sequenceNumber + 
                    '}'; 
        } 
        /** 
         * The sequence number of the most recently committed edit to this entry. 
         * 最近编辑他的序列号 
         */ 
        private long sequenceNumber; 
        private Entry(String key) { 
            this.key = key; 
            this.lengths = new long[valueCount]; 
        } 
        public String getLengths() throws IOException { 
            StringBuilder result = new StringBuilder(); 
            for (long size : lengths) { 
                result.append(' ').append(size); 
            } 
            return result.toString(); 
        } 
        /** 
         * Set lengths using decimal numbers like "10123". 
         */ 
        private void setLengths(String[] strings) throws IOException { 
            if (strings.length != valueCount) { 
                throw invalidLengths(strings); 
            } 
            try { 
                for (int i = 0; i < strings.length; i++) { 
                    lengths[i] = Long.parseLong(strings[i]); 
                } 
            } catch (NumberFormatException e) { 
                throw invalidLengths(strings); 
            } 
        } 
        private IOException invalidLengths(String[] strings) throws IOException { 
            throw new IOException("unexpected journal line: " + java.util.Arrays.toString(strings)); 
        } 
        //臨時文件創建成功了以後 就會重命名為正式文件了 
        public File getCleanFile(int i) { 
            Log.v("getCleanFile","getCleanFile path=="+new File(directory, key + "." + i).getAbsolutePath()); 
            return new File(directory, key + "." + i); 
        } 
        //tmp开头的都是临时文件 
        public File getDirtyFile(int i) { 
            Log.v("getDirtyFile","getDirtyFile path=="+new File(directory, key + "." + i + ".tmp").getAbsolutePath()); 
            return new File(directory, key + "." + i + ".tmp"); 
        } 
} 


DiskLruCacheopen函数的主要流程就基本走完了;

4、get()

/** 
   * Returns a snapshot of the entry named {@code key}, or null if it doesn't 
   * exist is not currently readable. If a value is returned, it is moved to 
   * the head of the LRU queue. 
   * 通过key获取对应的snapshot 
   */ 
  public synchronized Snapshot get(String key) throws IOException { 
    checkNotClosed(); 
    validateKey(key); 
    Entry entry = lruEntries.get(key); 
    if (entry == null) { 
      return null; 
    } 
    if (!entry.readable) { 
      return null; 
    } 
    // Open all streams eagerly to guarantee that we see a single published 
    // snapshot. If we opened streams lazily then the streams could come 
    // from different edits. 
    InputStream[] ins = new InputStream[valueCount]; 
    try { 
      for (int i = 0; i < valueCount; i++) { 
        ins[i] = new FileInputStream(entry.getCleanFile(i)); 
      } 
    } catch (FileNotFoundException e) { 
      // A file must have been deleted manually! 
      for (int i = 0; i < valueCount; i++) { 
        if (ins[i] != null) { 
          Util.closeQuietly(ins[i]); 
        } else { 
          break; 
        } 
      } 
      return null; 
    } 
    redundantOpCount++; 
    //在取得需要的文件以后 记得在日志文件里增加一条记录 并检查是否需要重新构建日志文件 
    journalWriter.append(READ + ' ' + key + '\n'); 
    if (journalRebuildRequired()) { 
      executorService.submit(cleanupCallable); 
    } 
    return new Snapshot(key, entry.sequenceNumber, ins, entry.lengths); 
  } 


5、validateKey

private void validateKey(String key) { 
        Matcher matcher = LEGAL_KEY_PATTERN.matcher(key); 
        if (!matcher.matches()) { 
          throw new IllegalArgumentException("keys must match regex " 
                  + STRING_KEY_PATTERN + ": \"" + key + "\""); 
        } 
  } 


这里是对存储entrymap的key做了正则验证,所以key一定要用md5加密,因为有些特殊字符验证不能通过;

然后看这句代码对应的:

if (journalRebuildRequired()) { 
      executorService.submit(cleanupCallable); 
    } 


对应的回调函数是:

/** This cache uses a single background thread to evict entries. */ 
  final ThreadPoolExecutor executorService = 
      new ThreadPoolExecutor(0, 1, 60L, TimeUnit.SECONDS, new LinkedBlockingQueue<Runnable>()); 
  private final Callable<Void> cleanupCallable = new Callable<Void>() { 
    public Void call() throws Exception { 
      synchronized (DiskLruCache.this) { 
        if (journalWriter == null) { 
          return null; // Closed. 
        } 
        trimToSize(); 
        if (journalRebuildRequired()) { 
          rebuildJournal(); 
          redundantOpCount = 0; 
        } 
      } 
      return null; 
    } 
  }; 


其中再来看看trimTOSize()的状态

6、trimTOSize()

private void trimToSize() throws IOException { 
    while (size > maxSize) { 
      Map.Entry<String, Entry> toEvict = lruEntries.entrySet().iterator().next(); 
      remove(toEvict.getKey()); 
    } 
  } 


就是检测总缓存是否超过了限制数量,

再来看journalRebuildRequired函数

7、journalRebuildRequired()

/** 
   * We only rebuild the journal when it will halve the size of the journal 
   * and eliminate at least 2000 ops. 
   */ 
  private boolean journalRebuildRequired() { 
    final int redundantOpCompactThreshold = 2000; 
    return redundantOpCount >= redundantOpCompactThreshold // 
        && redundantOpCount >= lruEntries.size(); 
  } 


就是校验redundantOpCount是否超出了范围,如果是,就重构日志文件;

最后看get函数的返回值 new Snapshot()

/** A snapshot of the values for an entry. */ 
//这个类持有该entry中每个文件的inputStream 通过这个inputStream 可以读取他的内容 
  public final class Snapshot implements Closeable { 
    private final String key; 
    private final long sequenceNumber; 
    private final InputStream[] ins; 
    private final long[] lengths; 
    private Snapshot(String key, long sequenceNumber, InputStream[] ins, long[] lengths) { 
      this.key = key; 
      this.sequenceNumber = sequenceNumber; 
      this.ins = ins; 
      this.lengths = lengths; 
    } 
    /** 
     * Returns an editor for this snapshot's entry, or null if either the 
     * entry has changed since this snapshot was created or if another edit 
     * is in progress. 
     */ 
    public Editor edit() throws IOException { 
      return DiskLruCache.this.edit(key, sequenceNumber); 
    } 
    /** Returns the unbuffered stream with the value for {@code index}. */ 
    public InputStream getInputStream(int index) { 
      return ins[index]; 
    } 
    /** Returns the string value for {@code index}. */ 
    public String getString(int index) throws IOException { 
      return inputStreamToString(getInputStream(index)); 
    } 
    /** Returns the byte length of the value for {@code index}. */ 
    public long getLength(int index) { 
      return lengths[index]; 
    } 
    public void close() { 
      for (InputStream in : ins) { 
        Util.closeQuietly(in); 
      } 
    } 
  } 


到这里就明白了get最终返回的其实就是entry根据key 来取的snapshot对象,这个对象直接把inputStream暴露给外面;

8、save的过程

public Editor edit(String key) throws IOException { 
    return edit(key, ANY_SEQUENCE_NUMBER); 
} 
//根据传进去的key 创建一个entry 并且将这个key加入到entry的那个map里 然后创建一个对应的editor 
//同时在日志文件里加入一条对该key的dirty记录 
private synchronized Editor edit(String key, long expectedSequenceNumber) throws IOException { 
    //因为这里涉及到写文件 所以要先校验一下写日志文件的writer 是否被正确的初始化 
    checkNotClosed(); 
    //这个地方是校验 我们的key的,通常来说 假设我们要用这个缓存来存一张图片的话,我们的key 通常是用这个图片的 
    //网络地址 进行md5加密,而对这个key的格式在这里是有要求的 所以这一步就是验证key是否符合规范 
    validateKey(key); 
    Entry entry = lruEntries.get(key); 
    if (expectedSequenceNumber != ANY_SEQUENCE_NUMBER && (entry == null 
            || entry.sequenceNumber != expectedSequenceNumber)) { 
        return null; // Snapshot is stale. 
    } 
    if (entry == null) { 
        entry = new Entry(key); 
        lruEntries.put(key, entry); 
    } else if (entry.currentEditor != null) { 
        return null; // Another edit is in progress. 
    } 
    Editor editor = new Editor(entry); 
    entry.currentEditor = editor; 
    // Flush the journal before creating files to prevent file leaks. 
    journalWriter.write(DIRTY + ' ' + key + '\n'); 
    journalWriter.flush(); 
    return editor; 
} 


然后取得输出流

public OutputStream newOutputStream(int index) throws IOException { 
        if (index < 0 || index >= valueCount) { 
            throw new IllegalArgumentException("Expected index " + index + " to " 
                    + "be greater than 0 and less than the maximum value count " 
                    + "of " + valueCount); 
        } 
        synchronized (DiskLruCache.this) { 
            if (entry.currentEditor != this) { 
                throw new IllegalStateException(); 
            } 
            if (!entry.readable) { 
                written[index] = true; 
            } 
            File dirtyFile = entry.getDirtyFile(index); 
            FileOutputStream outputStream; 
            try { 
                outputStream = new FileOutputStream(dirtyFile); 
            } catch (FileNotFoundException e) { 
                // Attempt to recreate the cache directory. 
                directory.mkdirs(); 
                try { 
                    outputStream = new FileOutputStream(dirtyFile); 
                } catch (FileNotFoundException e2) { 
                    // We are unable to recover. Silently eat the writes. 
                    return NULL_OUTPUT_STREAM; 
                } 
            } 
            return new FaultHidingOutputStream(outputStream); 
        } 
    } 


注意这个index 其实一般传0 就可以了,DiskLruCache 认为 一个key 下面可以对应多个文件,这些文件 用一个数组来存储,所以正常情况下,我们都是

一个key 对应一个缓存文件 所以传0

//tmp开头的都是临时文件 
     public File getDirtyFile(int i) { 
         return new File(directory, key + "." + i + ".tmp"); 
     } 


然后你这边就能看到,这个输出流,实际上是tmp 也就是缓存文件的 .tmp 也就是缓存文件的 缓存文件 输出流;

这个流 我们写完毕以后 就要commit;

public void commit() throws IOException { 
        if (hasErrors) { 
            completeEdit(this, false); 
            remove(entry.key); // The previous entry is stale. 
        } else { 
            completeEdit(this, true); 
        } 
        committed = true; 
    } 


这个就是根据缓存文件的大小 更新disklrucache的总大小 然后再日志文件里对该key加入cleanlog

//最后判断是否超过最大的maxSize 以便对缓存进行清理 
private synchronized void completeEdit(Editor editor, boolean success) throws IOException { 
    Entry entry = editor.entry; 
    if (entry.currentEditor != editor) { 
        throw new IllegalStateException(); 
    } 
    // If this edit is creating the entry for the first time, every index must have a value. 
    if (success && !entry.readable) { 
        for (int i = 0; i < valueCount; i++) { 
            if (!editor.written[i]) { 
                editor.abort(); 
                throw new IllegalStateException("Newly created entry didn't create value for index " + i); 
            } 
            if (!entry.getDirtyFile(i).exists()) { 
                editor.abort(); 
                return; 
            } 
        } 
    } 
    for (int i = 0; i < valueCount; i++) { 
        File dirty = entry.getDirtyFile(i); 
        if (success) { 
            if (dirty.exists()) { 
                File clean = entry.getCleanFile(i); 
                dirty.renameTo(clean); 
                long oldLength = entry.lengths[i]; 
                long newLength = clean.length(); 
                entry.lengths[i] = newLength; 
                size = size - oldLength + newLength; 
            } 
        } else { 
            deleteIfExists(dirty); 
        } 
    } 
    redundantOpCount++; 
    entry.currentEditor = null; 
    if (entry.readable | success) { 
        entry.readable = true; 
        journalWriter.write(CLEAN + ' ' + entry.key + entry.getLengths() + '\n'); 
        if (success) { 
            entry.sequenceNumber = nextSequenceNumber++; 
        } 
    } else { 
        lruEntries.remove(entry.key); 
        journalWriter.write(REMOVE + ' ' + entry.key + '\n'); 
    } 
    journalWriter.flush(); 
    if (size > maxSize || journalRebuildRequired()) { 
        executorService.submit(cleanupCallable); 
    } 
} 


commit以后 就会把tmp文件转正 ,重命名为 真正的缓存文件了;

这个里面的流程和日志文件的rebuild 是差不多的,都是为了防止写文件的出问题。所以做了这样的冗余处理;

总结:

DiskLruCache,利用一个journal文件,保证了保证了cache实体的可用性(只有CLEAN的可用),且获取文件的长度的时候可以通过在该文件的记录中读取。

利用FaultHidingOutputStreamFileOutPutStream很好的对写入文件过程中是否发生错误进行捕获,而不是让用户手动去调用出错后的处理方法;

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