這次做一個圖片加載器，裡面涉及到線程池，bitmap的高效加載，LruCache，DiskLruCache。接下來我先介紹這四個知識點
一.線程池
優點：
（1）重用線程池中的線程，避免因為線程的創建和銷毀帶來性能上的開銷
（2）有效控制線程池的最大並發數，避免大量線程之間因互相搶占系統資源而阻塞
（3）對線程進行簡單管理，並提供定時執行和指定間隔循環執行等功能
1.ThreadPoolExecutor介紹
是線程池的真正實現，構造方法
public ThreadPoolExecutor(int corePoolSize,
int maximumPoolSize,
long keepAliveTime,
TimeUnit unit,
BlockingQueue workQueue,
ThreadFactory threadFactory)
corePoolSize：核心線程數
maximumPoolSize：最大線程數。超過將阻塞
keepAliveTime：非核心線程超時時長，超過將會被回收
unit：指定keepAliveTime的時間單位。常用TimeUnit.SECONDS（秒），TimeUnit.MINUTES（分鐘）等
workQueue：存儲線程的隊列。通過ThreadPoolExecutor.execute方法提交的Runnable對象會存儲在這個線程中
threadFactory:是一個接口，提供創建新線程的功能。只有一個方法：public Thread newThread(Runnable r)
2.ThreadPoolExecutor典型配置
/**
* 線程池，用來管理線程
*/
private static final ThreadFactory sThreadFactory = new ThreadFactory() {
// AtomicInteger，一個提供原子操作的Integer的類。
private final AtomicInteger mCount = new AtomicInteger(1);
@Override
public Thread newThread(Runnable r) {
return new Thread(r, "ImageLoader#" + mCount.getAndIncrement());
}
};
private static final int CPU_COUNT = Runtime.getRuntime().availableProcessors();
private static final int CORE_POOL_SIZE = CPU_COUNT + 1;
private static final int MAX_POOL_SIZE = CPU_COUNT * 2 + 1;
private static final long KEEP_ALIVE = 10L;
public static final Executor THREAD_POOL_EXECUTOR = new ThreadPoolExecutor(
CORE_POOL_SIZE, MAX_POOL_SIZE, KEEP_ALIVE, TimeUnit.SECONDS,
new LinkedBlockingDeque(), sThreadFactory);
二.bitmap高效加載
通過BitmapFactory.Options來加載所需尺寸的圖片，主要是用到了inSampleSize參數，即采樣率
流程如下：
public Bitmap decodeSampleBitmapFromResource(Resources resources,
int resId, int reqWidth, int reqHeight) {
BitmapFactory.Options options = new BitmapFactory.Options();
options.inJustDecodeBounds = true;
// 獲取options
BitmapFactory.decodeResource(resources, resId, options);
// 結合目標view所需大小計算采樣率
options.inSampleSize = calculateInSampleSize(options, reqWidth,
reqHeight);
options.inJustDecodeBounds = false;
return BitmapFactory.decodeResource(resources, resId, options);
}
/**
* 指定輸出圖片的縮放比例
*
* @param options
* @param reqWidth
* @param reqHeight
* @return
*/
public static int calculateInSampleSize(BitmapFactory.Options options,
int reqWidth, int reqHeight) {
// 獲得原始圖片的寬高
int imageHeight = options.outHeight;
int imageWidth = options.outWidth;
int inSimpleSize = 1;
if (imageHeight > reqHeight || imageWidth > reqWidth) {
int halfHeight = imageHeight / 2;
int halfWidth = imageWidth / 2;
while ((halfHeight / inSimpleSize) >= reqHeight
&& (halfWidth / inSimpleSize) >= reqWidth) {
inSimpleSize *= 2;
Log.e("SimpleSize", inSimpleSize + "");
}
}
Log.e("inSimpleSize", inSimpleSize + "");
return inSimpleSize;
}
三.LruCache（內存緩存）
Lru就是Least Recently Used近期最少使用算法。核心思想：當緩存滿時，優先淘汰近期最少使用的緩存對象
先看源碼：（推薦使用supprt-v4包中的LruCache，地址在E:\adt\sdk\sources\android-19\android\support\v4\util）
public class LruCache {
//map用來存儲外界的緩存對象
private final LinkedHashMap map;
/**
* @param maxSize for caches that do not override {@link #sizeOf}, this is
* the maximum number of entries in the cache. For all other caches,
* this is the maximum sum of the sizes of the entries in this cache.
*/
public LruCache(int maxSize) {
if (maxSize <= 0) {
throw new IllegalArgumentException("maxSize <= 0");
}
this.maxSize = maxSize;
this.map = new LinkedHashMap(0, 0.75f, true);
}
//獲取一個緩存對象
public final V get(K key) {
if (key == null) {
throw new NullPointerException("key == null");
}
V mapValue;
synchronized (this) {
mapValue = map.get(key);
if (mapValue != null) {
hitCount++;
return mapValue;
}
missCount++;
}
/*
* Attempt to create a value. This may take a long time, and the map
* may be different when create() returns. If a conflicting value was
* added to the map while create() was working, we leave that value in
* the map and release the created value.
*/
V createdValue = create(key);
if (createdValue == null) {
return null;
}
synchronized (this) {
createCount++;
mapValue = map.put(key, createdValue);
if (mapValue != null) {
// There was a conflict so undo that last put
map.put(key, mapValue);
} else {
size += safeSizeOf(key, createdValue);
}
}
if (mapValue != null) {
entryRemoved(false, key, createdValue, mapValue);
return mapValue;
} else {
trimToSize(maxSize);
return createdValue;
}
}
//添加一個緩存對象
public final V put(K key, V value) {
if (key == null || value == null) {
throw new NullPointerException("key == null || value == null");
}
V previous;
synchronized (this) {
putCount++;
size += safeSizeOf(key, value);
previous = map.put(key, value);
if (previous != null) {
size -= safeSizeOf(key, previous);
}
}
if (previous != null) {
entryRemoved(false, key, previous, value);
}
trimToSize(maxSize);
return previous;
}
/**
* Remove the eldest entries until the total of remaining entries is at or
* below the requested size.
*
* @param maxSize the maximum size of the cache before returning. May be -1
* to evict even 0-sized elements.
*/
public void trimToSize(int maxSize) {
while (true) {
K key;
V value;
synchronized (this) {
if (size < 0 || (map.isEmpty() && size != 0)) {
throw new IllegalStateException(getClass().getName()
+ ".sizeOf() is reporting inconsistent results!");
}
if (size <= maxSize || map.isEmpty()) {
break;
}
Map.Entry toEvict = map.entrySet().iterator().next();
key = toEvict.getKey();
value = toEvict.getValue();
map.remove(key);
size -= safeSizeOf(key, value);
evictionCount++;
}
entryRemoved(true, key, value, null);
}
}
//移除一個緩存對象，並且減少該對象對應的size
public final V remove(K key) {
if (key == null) {
throw new NullPointerException("key == null");
}
V previous;
synchronized (this) {
previous = map.remove(key);
if (previous != null) {
size -= safeSizeOf(key, previous);
}
}
if (previous != null) {
entryRemoved(false, key, previous, null);
}
return previous;
}
//生成一個null對象
protected V create(K key) {
return null;
}
//返回一個緩存對象的副本
public synchronized final Map snapshot() {
return new LinkedHashMap(map);
}
}
研究完了源碼，使用起來就方便了
初始化：
final int maxMemory = (int) (Runtime.getRuntime().maxMemory() / 1024);
int cacheSize = maxMemory / 8;
mMemoryCache = new LruCache(cacheSize) {
@Override
protected int sizeOf(String key, Bitmap value) {
return value.getByteCount() / 1024;
}
};
獲取緩存:mMemoryCache.get(key)
添加緩存:mMemoryCache.put(key, bitmap)
四.DiskLruCache（磁盤緩存）
書上說地址在：https://android.googlesource.com/platform/libcore/+/android-4.1.1_r1/luni/src/main/java/libcore/io/DiskLruCache.java
但是下載下來好像要改好多東西，所以我就在Universal-ImageLoader裡面找了相同的文件
1.DiskLruCache的創建
public static DiskLruCache open(File directory, int appVersion, int valueCount, long maxSize)
directory：存儲路徑
appVersion：通常為1
valueCount：單個節點對應數據個數，通常為1
maxSize：緩存總大小，比如50MB
// 初始化DiskLruCache
File diskCacheDir = getDiskCacheDir(mContext, "bitmap");
if (!diskCacheDir.exists()) {
diskCacheDir.mkdirs();
}
if (getUsableSpace(diskCacheDir) > DISK_CACHE_SIZE) {
try {
mDiskLruCache = DiskLruCache.open(diskCacheDir, 1, 1,
DISK_CACHE_SIZE);
} catch (IOException e) {
e.printStackTrace();
}
}
getDiskCacheDir：獲取磁盤緩存目錄
getUsableSpace：獲取sd卡的大小和剩余空間
這兩個函數的實現方法在代碼包裡面有，就不細說
2.DiskLruCache緩存的添加
緩存的添加是通過Editor來完成的。Editor表示緩存對象的編輯對象
//將uri轉化為key
String key = hashKeyForURI(uri);
try {
DiskLruCache.Editor editor = mDiskLruCache.edit(key);
if (editor != null) {
OutputStream outputStream = editor
.newOutputStream(DISK_CACHE_INDEX);
if (downloadURIToStream(uri, outputStream)) {
editor.commit();
} else {
editor.abort();
}
mDiskLruCache.flush();
}
} catch (IOException e) {
return null;
}
上面的代碼就是將圖片寫入文件系統，接下來就可以從文件系統中獲取圖片
解釋幾點
1.為什麼要將uri轉化為hashKey？如果uri中含有特殊字符會影響uri的使用
2.downloadURIToStream實現了“把圖片寫入到文件系統”的功能，確切的來說，還要配合editor.commit
3.DiskLruCache緩存的查找
String key = hashKeyForURI(uri);
try {
DiskLruCache.Snapshot snapshot = mDiskLruCache.get(key);
if (snapshot != null) {
FileInputStream fileInputStream = (FileInputStream) snapshot
.getInputStream(DISK_CACHE_INDEX);
FileDescriptor fileDescriptor = fileInputStream.getFD();
bitmap = mImageResizer.decodeSampleBitmapFromFileDescriptor(
fileDescriptor, width, height);
if (bitmap != null) {
addBitmapToMemoryCache(key, bitmap);
}
}
} catch (IOException e) {
e.printStackTrace();
}
注意，這裡的Snapshot和LruCache的Snapshot不一樣。LruCache的Snapshot表示內存緩存的副本，這裡的Snapshot僅僅指保存了三個參數的一個對象
至此，ImageLoader已經大體實現。
代碼包裡面SquareImageView.java是為了得到一個寬高相同的ImageView。
同時，為了優化列表的卡頓現象，我們采用了“僅當列表靜止時才加載圖片”的策略
public void onScrollStateChanged(AbsListView view, int scrollState) {
if (scrollState == OnScrollListener.SCROLL_STATE_IDLE) {
mIsGridViewIdle = true;
adapter.notifyDataSetChanged();
} else {
mIsGridViewIdle = false;
}
}
在getView裡面添加如下代碼
if (mIsGridViewIdle) {
imageLoader.bindBitmap(uri, imageView);
}
運行截圖
loadBitmapFromHttp和downloadBitmapFromURI都可以實現網絡加載。前者是先放到disk中，然後獲取，後者是先獲取，然後放到memorycache中
我先把downloadBitmapFromURI注釋掉
![這裡寫圖片描述](https://www.android5.online/Android/UploadFiles_5356/201702/2017022217134748.png "\")
然後把loadBitmapFromHttp注釋掉
