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Android SparseArray源码翻阅

热度:56   发布时间:2016-04-28 01:32:35.0
Android SparseArray源码阅读
/* * Copyright (C) 2006 The Android Open Source Project * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * *      http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */package android.util;import com.android.internal.util.ArrayUtils;import com.android.internal.util.GrowingArrayUtils;import libcore.util.EmptyArray;/** * SparseArrays map integers to Objects.  Unlike a normal array of Objects, * there can be gaps in the indices.  It is intended to be more memory efficient * than using a HashMap to map Integers to Objects, both because it avoids * auto-boxing keys and its data structure doesn't rely on an extra entry object * for each mapping. *  * SparseArray用于映射integers到object。但不像普通数组那样,sparseArray的元素间没有无用元素。 * 在映射integers到object的过程中,SparseArray由于采用避免自动装箱的keys和它的数据结构不依赖额外 * 的对象来存储映射关系的实现,因此它比hashMap的内存使用更高效一些。 *  *  * <p>Note that this container keeps its mappings in an array data structure, * using a binary search to find keys.  The implementation is not intended to be appropriate for * data structures * that may contain large numbers of items.  It is generally slower than a traditional * HashMap, since lookups require a binary search and adds and removes require inserting * and deleting entries in the array.  For containers holding up to hundreds of items, * the performance difference is not significant, less than 50%.</p> *  * 注意:SparseArray在查找keys的过程中采用了二分查找, 这种实现不适合数据量大的情况。由于查找时要用到二分查找, * 添加删除时涉及到数组其他元素的挪动,因此通常SparseArray会比hashMap慢。当处理上百的数据量,这种性能差异不是特别 * 明显,性能差异不超过50%。 *  * * <p>To help with performance, the container includes an optimization when removing * keys: instead of compacting its array immediately, it leaves the removed entry marked * as deleted.  The entry can then be re-used for the same key, or compacted later in * a single garbage collection step of all removed entries.  This garbage collection will * need to be performed at any time the array needs to be grown or the the map size or * entry values are retrieved.</p> *  * 为了优化性能,SparseArray针对remove case作了优化,remove时它不是立即挤压数组空间,而是标记为delete。 * 这个被标记的元素要么被重复利用,要么在多次remove之后通过一次gc操作中被挤压出去。 * gc需要在下列情况之前被执行:数组要扩容;get map size;get values; *  * * <p>It is possible to iterate over the items in this container using * [email protected] #keyAt(int)} and [email protected] #valueAt(int)}. Iterating over the keys using * <code>keyAt(int)</code> with ascending values of the index will return the * keys in ascending order, or the values corresponding to the keys in ascending * order in the case of <code>valueAt(int)</code>.</p> *  * 可以用keyAt valueAt实现遍历 */public class SparseArray<E> implements Cloneable {    //巧妙的flag    //当有元素被remove delete时,先暂时设置该对象为DELETED,并置mGarbage=true    //用以提升性能,体现在哪里?问题1    private static final Object DELETED = new Object();    private boolean mGarbage = false;    //存储的数据结构,两个数组加一个size    //特殊在哪里?或者怎么用的呢?问题2    private int[] mKeys;    private Object[] mValues;    private int mSize;    /**     * Creates a new SparseArray containing no mappings.     */    public SparseArray() {        this(10);//默认容量是10个元素    }    /**     * Creates a new SparseArray containing no mappings that will not     * require any additional memory allocation to store the specified     * number of mappings.  If you supply an initial capacity of 0, the     * sparse array will be initialized with a light-weight representation     * not requiring any additional array allocations.     */    public SparseArray(int initialCapacity) {        if (initialCapacity == 0) {            //看EmptyArray的实现便知,mKeys的初值等于new int[0], 其他同理            mKeys = EmptyArray.INT;            mValues = EmptyArray.OBJECT;        } else {            //newUnpaddedObjectArray有啥特性?问题3            mValues = ArrayUtils.newUnpaddedObjectArray(initialCapacity);            mKeys = new int[mValues.length];        }        mSize = 0;    }    @Override    @SuppressWarnings("unchecked")    public SparseArray<E> clone() {        SparseArray<E> clone = null;        try {            //java深拷贝            clone = (SparseArray<E>) super.clone();            clone.mKeys = mKeys.clone();            clone.mValues = mValues.clone();        } catch (CloneNotSupportedException cnse) {            /* ignore */        }        return clone;    }    /**     * Gets the Object mapped from the specified key, or <code>null</code>     * if no such mapping has been made.     */    public E get(int key) {        return get(key, null);    }    /**     * Gets the Object mapped from the specified key, or the specified Object     * if no such mapping has been made.     */    @SuppressWarnings("unchecked")    public E get(int key, E valueIfKeyNotFound) {        //二分查找, 返回值含义是什么?问题4        int i = ContainerHelpers.binarySearch(mKeys, mSize, key);        if (i < 0 || mValues[i] == DELETED) {            // 没找到对应的key,或者找到了Key,但该元素被标记为delete            // 则返回默认值            return valueIfKeyNotFound;        } else {            // i>0 且该位置的元素未被标记为待删除,返回该值            return (E) mValues[i];        }    }    /**     * Removes the mapping from the specified key, if there was any.     */    public void delete(int key) {        //二分查找        int i = ContainerHelpers.binarySearch(mKeys, mSize, key);        //若找到了        if (i >= 0) {            //若之前未被标记delete            if (mValues[i] != DELETED) {                //标记为delete,garbage=true                mValues[i] = DELETED;                mGarbage = true;            }        }    }    /**     * Alias for [email protected] #delete(int)}.     */    public void remove(int key) {        delete(key);    }    /**     * Removes the mapping at the specified index.     */    public void removeAt(int index) {        //移除特定位置的元素,注意传入的是mValues的index不是Key        if (mValues[index] != DELETED) {            mValues[index] = DELETED;            mGarbage = true;        }    }    /**     * Remove a range of mappings as a batch.     *     * @param index Index to begin at     * @param size Number of mappings to remove     */    public void removeAtRange(int index, int size) {        //确定结束位置        final int end = Math.min(mSize, index + size);        //从起点开始循环 remove        for (int i = index; i < end; i++) {            removeAt(i);        }    }    private void gc() {        // Log.e("SparseArray", "gc start with " + mSize);        //'挤'空间了, 提供空间利用率        int n = mSize;        int o = 0;        int[] keys = mKeys;        Object[] values = mValues;        //循环整个元素区间        /*         * 模拟一遍就明白了         *i    = 0 1 2 3 4 5  6          *key  = 1 2 6 8 9 10 11         *value= x y z D u D  w         *value D代表delete的对象         *         *i=0时,val==x, val != DELETED,i==o, o++, o == 1         *i=1时,val==y, val != DELETED,i==o, o++, o == 2         *i=2时,val==z, val != DELETED,i==o, o++, o == 3         *i=3时,val==D, val == DELETED,o == 3         *i=4时,val==u, val != DELETED,i!=o, keys[3] = keys[4], values[3] = values[4], values[4] = null, o++, o == 4         *   (i=4之后,key= 1 2 6 9 9 10 11, value= x y z u null D w)         *i=5时,val==D, val == DELETED,o == 4         *   (i=5之后,key= 1 2 6 9 9 10 11, value= x y z u null D w)较上一步没变化         *i=6时,val==w, val != DELETED,i!=o, keys[4] = keys[6], values[4] = values[6], values[6] = null, o++, o == 5         *   (i=6之后,key= 1 2 6 9 11 10 11, value= x y z u w D null)         *循环结束            *mSize = 5         */        for (int i = 0; i < n; i++) {            Object val = values[i];            if (val != DELETED) {                if (i != o) {                    keys[o] = keys[i];                    values[o] = val;                    values[i] = null;                }                o++;            }        }        mGarbage = false;        mSize = o;        // Log.e("SparseArray", "gc end with " + mSize);    }    /**     * Adds a mapping from the specified key to the specified value,     * replacing the previous mapping from the specified key if there     * was one.     */    public void put(int key, E value) {        //先二分查找,确定插入位置,保证了key数组的有序性        int i = ContainerHelpers.binarySearch(mKeys, mSize, key);        if (i >= 0) {            //找到了,直接替换            mValues[i] = value;        } else {            //一点小技巧,跟二分查找的返回值有关            //没找到的情况下i的意义是 i = -insertPoint -1,比如i=-2,则insertPoint=1            //而-2在内存中存的是补码,对他取反刚好得insertPoint,跟上面计算结果一样,但位操作更高效            i = ~i;            //若i在size范围内,且刚好对应位置标记为delete了,直接放入            if (i < mSize && mValues[i] == DELETED) {                mKeys[i] = key;                mValues[i] = value;                return;            }            //若前面if不成立,即i超出了size范围,或者对应的位置的元素是有效的            if (mGarbage && mSize >= mKeys.length) {                //压缩空间                gc();                //重新查找插入点                // Search again because indices may have changed.                i = ~ContainerHelpers.binarySearch(mKeys, mSize, key);            }            //插入,若空间不够则会重新分配数组            mKeys = GrowingArrayUtils.insert(mKeys, mSize, i, key);            mValues = GrowingArrayUtils.insert(mValues, mSize, i, value);            mSize++;        }    }    /**     * Returns the number of key-value mappings that this SparseArray     * currently stores.     */    public int size() {        if (mGarbage) {            gc();        }        return mSize;    }    /**     * Given an index in the range <code>0...size()-1</code>, returns     * the key from the <code>index</code>th key-value mapping that this     * SparseArray stores.     *     * <p>The keys corresponding to indices in ascending order are guaranteed to     * be in ascending order, e.g., <code>keyAt(0)</code> will return the     * smallest key and <code>keyAt(size()-1)</code> will return the largest     * key.</p>     */    public int keyAt(int index) {        if (mGarbage) {            gc();        }        return mKeys[index];    }    /**     * Given an index in the range <code>0...size()-1</code>, returns     * the value from the <code>index</code>th key-value mapping that this     * SparseArray stores.     *     * <p>The values corresponding to indices in ascending order are guaranteed     * to be associated with keys in ascending order, e.g.,     * <code>valueAt(0)</code> will return the value associated with the     * smallest key and <code>valueAt(size()-1)</code> will return the value     * associated with the largest key.</p>     */    @SuppressWarnings("unchecked")    public E valueAt(int index) {        if (mGarbage) {            gc();        }        return (E) mValues[index];    }    /**     * Given an index in the range <code>0...size()-1</code>, sets a new     * value for the <code>index</code>th key-value mapping that this     * SparseArray stores.     */    public void setValueAt(int index, E value) {        if (mGarbage) {            gc();        }        mValues[index] = value;    }    /**     * Returns the index for which [email protected] #keyAt} would return the     * specified key, or a negative number if the specified     * key is not mapped.     */    public int indexOfKey(int key) {        if (mGarbage) {            gc();        }        return ContainerHelpers.binarySearch(mKeys, mSize, key);    }    /**     * Returns an index for which [email protected] #valueAt} would return the     * specified key, or a negative number if no keys map to the     * specified value.     * <p>Beware that this is a linear search, unlike lookups by key,     * and that multiple keys can map to the same value and this will     * find only one of them.     * <p>Note also that unlike most collections' [email protected] indexOf} methods,     * this method compares values using [email protected] ==} rather than [email protected] equals}.     */    public int indexOfValue(E value) {        if (mGarbage) {            gc();        }        for (int i = 0; i < mSize; i++)            if (mValues[i] == value)                return i;        return -1;    }    /**     * Removes all key-value mappings from this SparseArray.     */    public void clear() {        int n = mSize;        Object[] values = mValues;        for (int i = 0; i < n; i++) {            //值空,利于jvm gc            values[i] = null;        }        mSize = 0;        mGarbage = false;    }    /**     * Puts a key/value pair into the array, optimizing for the case where     * the key is greater than all existing keys in the array.     */    public void append(int key, E value) {        //若key小于等于已有的最大key,直接Put        if (mSize != 0 && key <= mKeys[mSize - 1]) {            put(key, value);            return;        }        if (mGarbage && mSize >= mKeys.length) {            gc();        }        //若key大于了现有的所有key,就不用走put的二分查找过程了,直接append        //即comments说的优化        mKeys = GrowingArrayUtils.append(mKeys, mSize, key);        mValues = GrowingArrayUtils.append(mValues, mSize, value);        mSize++;    }    /**     * [email protected]}     *     * <p>This implementation composes a string by iterating over its mappings. If     * this map contains itself as a value, the string "(this Map)"     * will appear in its place.     */    @Override    public String toString() {        if (size() <= 0) {            return "{}";        }        StringBuilder buffer = new StringBuilder(mSize * 28);        buffer.append('{');        for (int i=0; i<mSize; i++) {            if (i > 0) {                buffer.append(", ");            }            int key = keyAt(i);            buffer.append(key);            buffer.append('=');            Object value = valueAt(i);            if (value != this) {                buffer.append(value);            } else {                buffer.append("(this Map)");            }        }        buffer.append('}');        return buffer.toString();    }}

问题1,mGarbage标记结合DELETED,用以提升性能,体现在哪里?
    将可能的多次gc操作变为一次完成。比如用户调用了多次removeAt操作,若不用这种策略,则会每次remove都对应一次gc即用一次循环来'挤压'空间。
    采用这种flag优化后,多次remove仅多次设置了标志,在gc触发时,仅需要一次循环就可以将空间'挤压'好。

问题2,sparseArray的存储结构,两个数组加一个size有的特性?
    特性一,key数组是有序的,key在数组的index和vale在数组的index一样
    特性二,sparseArray每次gc过程,保证了他的有效值(size)区间内没有无效值,或者说'无缝隙',有效值是连续的
    特性三,如文档所说,当map Integers to Objects时,相对hashMap,sparseArray被设计成更加的内存高效,
           sparseArray避免了自动装箱机制和用额外的对象来存储每个映射。

问题3,ArrayUtils.newUnpaddedObjectArray(initialCapacity);有什么特性?
    最终调用的是VMRuntime.getRuntime().newUnpaddedArray(Object.class, minLen);
    参考 http://androidxref.com/5.0.0_r2/xref/libcore/libart/src/main/java/dalvik/system/VMRuntime.java#260

问题4, 二分查找的返回值含义,若值存在则返回该值的Index,否则返回和该值的插入点相关的一个值(-(insertion point) - 1)
   (the index of the search key, if it is contained in the list; otherwise, (-(insertion point) - 1).)

原文地址:https://github.com/cheyiliu/All-in-One/wiki/SparseArray
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