SparseArray和ArrayMap是Android中特有的数据结构，他们都是根据key有序排列的数据结构，主要思想是二分查找，采取时间换空间的策略，适用效率要求不高但对内存有优化的场景，也是Android推荐代替Map的数据结构。
首先分析SparseArray
- SparseArray内部有一个保存key的int数组和一个保存值的Object数组，还有一个DELETED的静态常量对象，用于删除时标记替换，和数组大小，默认构造器初始化其大小为10：
private static final Object DELETED = new Object();
private boolean mGarbage = false;
private int[] mKeys;
private Object[] mValues;
private int mSize;
- 在put和get及delete方法中都会用二分查找（里面采用了位运算）去查找目标对象的index，可以说是这个数据结构的重点：
//查找目标位置
int i = ContainerHelpers.binarySearch(mKeys, mSize, key)
//ContainerHelpers里面的实现
static int binarySearch(int[] array, int size, int value) {
int lo = 0;
int hi = size - 1;
while (lo <= hi) {
final int mid = (lo + hi) >>> 1;
final int midVal = array[mid];
if (midVal < value) {
lo = mid + 1;
} else if (midVal > value) {
hi = mid - 1;
} else {
return mid; // value found
}
}
return ~lo; // value not present
}
- get方法通过key查找，找到了且目标对象不是DELETED，就返回对象，否则返回默认的对象：
public E get(int key) {
return get(key, null);
}
//重载方法
public E get(int key, E valueIfKeyNotFound) {
int i = ContainerHelpers.binarySearch(mKeys, mSize, key);
if (i < 0 || mValues[i] == DELETED) {
return valueIfKeyNotFound;
} else {
return (E) mValues[i];
}
}
- delete方法，查找到目标对象就把它标记成DELETED，remove方法直接调用了delete：
public void delete(int key) {
int i = ContainerHelpers.binarySearch(mKeys, mSize, key);
if (i >= 0) {
if (mValues[i] != DELETED) {
mValues[i] = DELETED;
mGarbage = true;
}
}
}
- put方法，会判断是否查找到这个key，找到了就直接替换，找不到的话，如果目标index的对象标记了DELETED，直接替换，否则，如果有过删除会先进行gc（整合数组），然后重新获取目标index（因为整合后组数大小内容会变），最后在这个位置插入数据：
public void put(int key, E value) {
int i = ContainerHelpers.binarySearch(mKeys, mSize, key);
if (i >= 0) {
mValues[i] = value;
} else {
i = ~i;
if (i < mSize && mValues[i] == DELETED) {
mKeys[i] = key;
mValues[i] = value;
return;
}
if (mGarbage && mSize >= mKeys.length) {
gc();
// Search again because indices may have changed.
i = ~ContainerHelpers.binarySearch(mKeys, mSize, key);
}
mKeys = GrowingArrayUtils.insert(mKeys, mSize, i, key);
mValues = GrowingArrayUtils.insert(mValues, mSize, i, value);
mSize++;
}
}
- SparseIntArray、SparseLongArray、SparseBooleanArray和SparseArray类似，只不过保存值的数组是对应的基本类型数组，取消了装箱这步操作，对比SparseArray<Integer>等在内存上肯定有优势。
接下来分析ArrayMap
- ArrayMap实现了map接口，内部有一个保存key的hash值的int数组，和一个保存key、value的object数组（成对保存，key后紧接value）：
int[] mHashes;
Object[] mArray;
int mSize;
- 同SparseArray类似，也采用二分查找找到目标index，只不过get方法是取values[index*2+1]，且没有重载方法：
public V get(Object key) {
final int index = indexOfKey(key);
return index >= 0 ? (V)mArray[(index<<1)+1] : null;
}
//获取目标位置
public int indexOfKey(Object key) {
return key == null ? indexOfNull()
: indexOf(key, mIdentityHashCode ? System.identityHashCode(key) : key.hashCode());
}
int indexOf(Object key, int hash) {
//...
int index = binarySearchHashes(mHashes, N, hash);
if (index < 0) {
return index;
}
if (key.equals(mArray[index<<1])) {
return index;
}
int end;
for (end = index + 1; end < N && mHashes[end] == hash; end++) {
if (key.equals(mArray[end << 1])) return end;
}
for (int i = index - 1; i >= 0 && mHashes[i] == hash; i--) {
if (key.equals(mArray[i << 1])) return i;
}
return ~end;
}
- remove方法会把目标的key和value值都删除，并把数组整合（has数组的大小超过8时，会分段复制来删除这条数据，否则只会复制后面一段数据来覆盖）：
public V remove(Object key) {
final int index = indexOfKey(key);
if (index >= 0) {
return removeAt(index);
}
return null;
}
//删除数据
public V removeAt(int index) {
final Object old = mArray[(index << 1) + 1];
final int osize = mSize;
final int nsize;
if (osize <= 1) {
final int[] ohashes = mHashes;
final Object[] oarray = mArray;
mHashes = EmptyArray.INT;
mArray = EmptyArray.OBJECT;
freeArrays(ohashes, oarray, osize);
nsize = 0;
} else {
nsize = osize - 1;
if (mHashes.length > (BASE_SIZE*2) && mSize < mHashes.length/3) {
final int n = osize > (BASE_SIZE*2) ? (osize + (osize>>1)) : (BASE_SIZE*2);
final int[] ohashes = mHashes;
final Object[] oarray = mArray;
allocArrays(n);
if (CONCURRENT_MODIFICATION_EXCEPTIONS && osize != mSize) {
throw new ConcurrentModificationException();
}
if (index > 0) {
System.arraycopy(ohashes, 0, mHashes, 0, index);
System.arraycopy(oarray, 0, mArray, 0, index << 1);
}
if (index < nsize) {
System.arraycopy(ohashes, index + 1, mHashes, index, nsize - index);
System.arraycopy(oarray, (index + 1) << 1, mArray, index << 1,
(nsize - index) << 1);
}
} else {
if (index < nsize) {
System.arraycopy(mHashes, index + 1, mHashes, index, nsize - index);
System.arraycopy(mArray, (index + 1) << 1, mArray, index << 1,
(nsize - index) << 1);
}
mArray[nsize << 1] = null;
mArray[(nsize << 1) + 1] = null;
}
}
if (CONCURRENT_MODIFICATION_EXCEPTIONS && osize != mSize) {
throw new ConcurrentModificationException();
}
mSize = nsize;
return (V)old;
}
- put如果找到了直接替换，没找到也会复制数组，并在对应位置插入：
public V put(K key, V value) {
final int osize = mSize;
final int hash;
int index;
if (key == null) {
hash = 0;
index = indexOfNull();
} else {
hash = mIdentityHashCode ? System.identityHashCode(key) : key.hashCode();
index = indexOf(key, hash);
}
if (index >= 0) {
index = (index<<1) + 1;
final V old = (V)mArray[index];
mArray[index] = value;
return old;
}
index = ~index;
if (osize >= mHashes.length) {
final int n = osize >= (BASE_SIZE*2) ? (osize+(osize>>1))
: (osize >= BASE_SIZE ? (BASE_SIZE*2) : BASE_SIZE);
final int[] ohashes = mHashes;
final Object[] oarray = mArray;
allocArrays(n);
if (CONCURRENT_MODIFICATION_EXCEPTIONS && osize != mSize) {
throw new ConcurrentModificationException();
}
if (mHashes.length > 0) {
System.arraycopy(ohashes, 0, mHashes, 0, ohashes.length);
System.arraycopy(oarray, 0, mArray, 0, oarray.length);
}
freeArrays(ohashes, oarray, osize);
}
if (index < osize) {
System.arraycopy(mHashes, index, mHashes, index + 1, osize - index);
System.arraycopy(mArray, index << 1, mArray, (index + 1) << 1, (mSize - index) << 1);
}
if (CONCURRENT_MODIFICATION_EXCEPTIONS) {
if (osize != mSize || index >= mHashes.length) {
throw new ConcurrentModificationException();
}
}
mHashes[index] = hash;
mArray[index<<1] = key;
mArray[(index<<1)+1] = value;
mSize++;
return null;
}
网友评论