public class BloomFilter<E> implements Serializable {
    
    private static final long serialVersionUID = 3507830443935243576L;
    private long timestamp;//用于时间戳更新机制
    private HashMap<E, Boolean> deleteMap ; //储存已删除元素
    private BitSet bitset;//位图存储
    private int bitSetSize;
     // expected (maximum) number of elements to be added
    private int expectedNumberOfFilterElements; 
     // number of elements actually added to the Bloom filter
    private int numberOfAddedElements; 
    private int k;     //每一个元素对应k个位
     // encoding used for storing hash values as strings
    static Charset charset = Charset.forName("UTF-8"); 
     // MD5 gives good enough accuracy in most circumstances. 
     // Change to SHA1 if it's needed
    static String hashName = "MD5"; 
    static final MessageDigest digestFunction;

    static { // The digest method is reused between instances to provide higher entropy.
        MessageDigest tmp;
        try {
            tmp = java.security.MessageDigest.getInstance(hashName);
        } catch (NoSuchAlgorithmException e) {
            tmp = null;
        }
        digestFunction = tmp;
    }

    /**
     * Constructs an empty Bloom filter.
     *
     * @param bitSetSize defines how many bits should be used for the filter.
     * @param expectedNumberOfFilterElements defines the maximum 
     *           number of elements the filter is  expected to contain.
     */
    public BloomFilter(int bitSetSize, int expectedNumberOfFilterElements) {
        this.expectedNumberOfFilterElements = expectedNumberOfFilterElements;
        this.k = (int) Math.round(
               (bitSetSize / expectedNumberOfFilterElements) * Math.log(2.0));
        bitset = new BitSet(bitSetSize);
        deleteMap = new HashMap<E, Boolean>();
        this.bitSetSize = bitSetSize;
        numberOfAddedElements = 0;
    }

    /**
     * Generates a digest based on the contents of a String.
     *
     * @param val specifies the input data.
     * @param charset specifies the encoding of the input data.
     * @return digest as long.
     */
    public static long createHash(String val, Charset charset) {
        try {
            return createHash(val.getBytes(charset.name()));
        }
        catch (UnsupportedEncodingException e) {
            e.printStackTrace();
            // Ingore
        }
        return -1;
    }

    /**
     * Generates a digest based on the contents of a String.
     *
     * @param val specifies the input data. The encoding is expected to be UTF-8.
     * @return digest as long.
     */
    public static long createHash(String val) {
        return createHash(val, charset);
    }

    /**
     * Generates a digest based on the contents of an array of bytes.
     *
     * @param data specifies input data.
     * @return digest as long.
     */
    public static long createHash(byte[] data) {
        long h = 0;
        byte[] res;

        synchronized (digestFunction) {
            res = digestFunction.digest(data);
        }

        for (int i = 0; i < 4; i++) {
            h <<= 8;
            h |= ((int) res[i]) & 0xFF;
        }
        return h;
    }

    /**
     * Compares the contents of two instances to see if they are equal.
     *
     * @param obj is the object to compare to.
     * @return True if the contents of the objects are equal.
     */
    @SuppressWarnings("unchecked")
    @Override
    public boolean equals(Object obj) {
        if (obj == null) {
            return false;
        }
        if (getClass() != obj.getClass()) {
            return false;
        }
        final BloomFilter<E> other = (BloomFilter<E>) obj;        
        if (this.expectedNumberOfFilterElements != 
               other.expectedNumberOfFilterElements) {
            return false;
        }
        if (this.k != other.k) {
            return false;
        }
        if (this.bitSetSize != other.bitSetSize) {
            return false;
        }
        if (this.bitset != other.bitset && 
               (this.bitset == null || !this.bitset.equals(other.bitset))) {
            return false;
        }
        return true;
    }

    /**
     * Calculates a hash code for this class.
     * @return hash code representing the contents of an instance of this class.
     */
    @Override
    public int hashCode() {
        int hash = 7;
        hash = 61 * hash + (this.bitset != null ? this.bitset.hashCode() : 0);
        hash = 61 * hash + this.expectedNumberOfFilterElements;
        hash = 61 * hash + this.bitSetSize;
        hash = 61 * hash + this.k;
        return hash;
    }


    /**
     * Calculates the expected probability of false positives based on
     * the number of expected filter elements and the size of the Bloom filter.
     * <br /><br />
     * The value returned by this method is the <i>expected</i> rate of false
     * positives, assuming the number of inserted elements equals the number of
     * expected elements. If the number of elements in the Bloom filter is less
     * than the expected value, the true probability of false positives will be lower.
     *
     * @return expected probability of false positives.
     */
    public double expectedFalsePositiveProbability() {
        return getFalsePositiveProbability(expectedNumberOfFilterElements);
    }

    /**
     * Calculate the probability of a false positive given the specified
     * number of inserted elements.
     *
     * @param numberOfElements number of inserted elements.
     * @return probability of a false positive.
     */
    public double getFalsePositiveProbability(double numberOfElements) {
        // (1 - e^(-k * n / m)) ^ k
        return Math.pow((1 - Math.exp(-k * (double) numberOfElements
                        / (double) bitSetSize)), k);

    }

    /**
     * Get the current probability of a false positive. The probability is calculated from
     * the size of the Bloom filter and the current number of elements added to it.
     *
     * @return probability of false positives.
     */
    public double getFalsePositiveProbability() {
        return getFalsePositiveProbability(numberOfAddedElements);
    }


    /**
     * Returns the value chosen for K.<br />
     * <br />
     * K is the optimal number of hash functions based on the size
     * of the Bloom filter and the expected number of inserted elements.
     *
     * @return optimal k.
     */
    public int getK() {
        return k;
    }

    /**
     * Sets all bits to false in the Bloom filter.
     */
    public void clear() {
        bitset.clear();
        numberOfAddedElements = 0;
    }

    /**
     * Adds an object to the Bloom filter. The output from the object's
     * toString() method is used as input to the hash functions.
     *
     * @param element is an element to register in the Bloom filter.
     */
    public void add(E element) {
        deleteMap.remove(element);
       long hash;
       String valString = element.toString();
       for (int x = 0; x < k; x++) {
           hash = createHash(valString + Integer.toString(x));
           hash = hash % (long)bitSetSize;
           bitset.set(Math.abs((int)hash), true);
       }
       numberOfAddedElements ++;
    }

    /**
     * Remove all elements from a Collection to the Bloom filter.
     * @param c Collection of elements.
     */
    public void removeAll(Collection<? extends E> c) {
        for (E element : c)
            remove(element);
    }
    
    
    public void remove(E element) {
        deleteMap.put(element, Boolean.TRUE);
    }
    
    
    public int getDeleteMapSize(){
        return deleteMap.size();
    }

    /**
     * Adds all elements from a Collection to the Bloom filter.
     * @param c Collection of elements.
     */
    public void addAll(Collection<? extends E> c) {
        for (E element : c) {
            if (element != null)
                add(element);
        }
    }

    /**
     * Returns true if the element could have been inserted into the Bloom filter.
     * Use getFalsePositiveProbability() to calculate the probability of this
     * being correct.
     *
     * @param element element to check.
     * @return true if the element could have been inserted into the Bloom filter.
     */
    public boolean contains(E element) {
        Boolean contains = deleteMap.get(element);
        if (contains != null && contains)
            return false;
        long hash;
        String valString = element.toString();
        for (int x = 0; x < k; x++) {
            hash = createHash(valString + Integer.toString(x));
            hash = hash % (long) bitSetSize;
            if (!bitset.get(Math.abs((int) hash)))
                return false;
        }
        return true;
    }

    /**
     * Returns true if all the elements of a Collection could have been inserted
     * into the Bloom filter. Use getFalsePositiveProbability() to calculate the
     * probability of this being correct.
     * @param c elements to check.
     * @return true if all the elements in c could have been inserted into the Bloom filter.
     */
    public boolean containsAll(Collection<? extends E> c) {
        for (E element : c)
            if (!contains(element))
                return false;
        return true;
    }

    /**
     * Read a single bit from the Bloom filter.
     * @param bit the bit to read.
     * @return true if the bit is set, false if it is not.
     */
    public boolean getBit(int bit) {
        return bitset.get(bit);
    }

    /**
     * Set a single bit in the Bloom filter.
     * @param bit is the bit to set.
     * @param value If true, the bit is set. If false, the bit is cleared.
     */
    public void setBit(int bit, boolean value) {
        bitset.set(bit, value);
    }

    /**
     * Return the bit set used to store the Bloom filter.
     * @return bit set representing the Bloom filter.
     */
    public BitSet getBitSet() {
        return bitset;
    }

    /**
     * Returns the number of bits in the Bloom filter. Use count() to retrieve
     * the number of inserted elements.
     *
     * @return the size of the bitset used by the Bloom filter.
     */
    public int size() {
        return this.bitSetSize;
    }

    /**
     * Returns the number of elements added to the Bloom filter after it
     * was constructed or after clear() was called.
     *
     * @return number of elements added to the Bloom filter.
     */
    public int count() {
        return this.numberOfAddedElements;
    }

    /**
     * Returns the expected number of elements to be inserted into the filter.
     * This value is the same value as the one passed to the constructor.
     *
     * @return expected number of elements.
     */
    public int getExpectedNumberOfElements() {
        return expectedNumberOfFilterElements;
    }

    /**
     * 返回更新的时间戳机制
     * @return
     */
    public long getTimestamp() {
        return timestamp;
    }

    /**
     * 设置跟新的时间戳
     * @param timestamp
     */
    public void setTimestamp(long timestamp) {
        this.timestamp = timestamp;
    }

    @Override
    public String toString() {
        return "BloomFilter [timestamp=" + timestamp + ", bitSetSize=" + bitSetSize
                + ", expectedNumberOfFilterElements=" 
                + expectedNumberOfFilterElements + ", numberOfAddedElements="
                + numberOfAddedElements + ", k=" 
                + k +",deleteMapSize=" +getDeleteMapSize()+"]";
    }
}