来电归属地数据查询Java实现

项目需要实现来电归属地查询，所以就找到了下面这个文章

Android 号码, 来电归属地 Jni 使用C++对二进制文件查询(一) 理论篇

Android 号码, 来电归属地 Jni 使用C++对二进制文件查询(二) C++实现篇

Android 号码, 来电归属地 Jni 使用C++对二进制文件查询(三) APK 实现篇

原理主要在（一）和（二）中，作者的数据压缩思路很给力，将6M的原始文本数据压缩到400kb左右，原作者已经将分析讲的很清楚了，这里提炼一下要点，并将c++实现转化成java实现。

1、压缩主要通过减小数据冗余完成；

2、原始数据格式：手机号码前7位,城市名

3、数据冗余点，手机号码有递增规律、城市重复排列

4、将手机号码的排列转换为号码区间，城市名建索引

5、号码区间用2个short，城市索引用1个short

6、为了查询的效率，原始数据按号码递增排列，这样查询的时候能够用二分快速查找

下面是原文中的一张图，可以更好的理解数据的存储结构

转换实现

private static void convertTXTtoDAT() {File readFile = new File(CONVERT_TXT_NAME);if (!readFile.exists()) {System.out.println(CONVERT_TXT_NAME + " not exist");return;}File writeFile = new File(OUTPUT_FILE_NAME);try {writeFile.createNewFile();} catch (IOException e) {e.printStackTrace();}if (!writeFile.exists()) {System.out.println(OUTPUT_FILE_NAME + " not create!");return;}CityCollector cityCollector = new CityCollector();BufferedReader reader = null;RandomAccessFile writer = null;try {reader = new BufferedReader(new FileReader(readFile));writer = new RandomAccessFile(writeFile, "rw");int count = 0;writer.writeInt(count);String data = reader.readLine();String[] content = data.split(",");int number = Integer.parseInt(content[0]);String cityName = content[1];int cityIndex = cityCollector.putCity(cityName);NumberCompressor compressor = new NumberCompressor(number,cityIndex);while ((data = reader.readLine()) != null) {content = data.split(",");if (content.length != 2) {continue;}number = Integer.parseInt(content[0]);cityName = content[1];cityIndex = cityCollector.putCity(cityName);if (cityIndex == compressor.getCityIndex()&& number - compressor.getCurrentNumber() == 1) {compressor.increaseSkipNum();} else {writer.writeShort(compressor.getStartNum());writer.writeShort(compressor.getAfterNum());writer.writeShort(compressor.getCityIndex());++count;compressor = new NumberCompressor(number, cityIndex);}}writer.writeShort(compressor.getStartNum());writer.writeShort(compressor.getAfterNum());writer.writeShort(cityIndex);++count;writer.seek(0);writer.writeInt(count);writer.seek(writer.length());writer.write(cityCollector.getFormatCityByte());} catch (IOException e) {} finally {if (reader != null) {try {reader.close();} catch (IOException e) {e.printStackTrace();}}if (writer != null) {try {writer.close();} catch (IOException e) {e.printStackTrace();}}}}

其中CityCollector是存储城市信息的工具类，按顺序存储城市名，并返回其索引，最后和号码数据一起存入文件

public class CityCollector {/** * 将城市存储长度固定，便于查找时的快速定位，可以按需要修改 */public static final int MAXCITYLENGTH = 34;private ArrayList<String> mCityList = new ArrayList<String>();public CityCollector() {}public byte[] getFormatCityByte() {ByteBuffer buffer = ByteBuffer.allocate(mCityList.size() * MAXCITYLENGTH);int size = mCityList.size();for (int i = 0; i < size; ++i) {buffer.position(MAXCITYLENGTH * i);buffer.put(mCityList.get(i).getBytes());}return buffer.array();}public int putCity(String city) {int cityIndex = mCityList.indexOf(city);if (cityIndex != -1) {return cityIndex;} else {mCityList.add(city);return mCityList.size() - 1;}}}

NumberCompressor是为实现号码压缩存储的一个结构，包括一个号码区间的起始号，该区间的号码数量，和区间的城市索引（一个区间内的号码在同一个城市）

public class NumberCompressor {private int mBeginNum;private int mSkipNum = 0;private int mCityIndex;public NumberCompressor(int number, int cityIndex) {mBeginNum = number;mCityIndex = cityIndex;}public void increaseSkipNum() {++mSkipNum;}public int getCurrentNumber() {return mBeginNum + mSkipNum;}public int getCityIndex() {return mCityIndex;}public int getStartNum() {return mBeginNum / 100;}public int getAfterNum() {return mBeginNum % 100 + mSkipNum * 100;}}

查找就是存储的逆向过程，由于数据是有序存储的，所以这里查找用二分实现，如下

private static String searchNumberLocation(int number) {File file = new File(OUTPUT_FILE_NAME);RandomAccessFile readFile = null;String result = null;try {readFile = new RandomAccessFile(file, "r");int count = readFile.readInt();int left = 0;int right = count - 1;int blockSize = 3 * 2; // 3 * shortwhile (left <= right) {int middle = (left + right) / 2;readFile.seek(4 + middle * blockSize); // 4 is the count(int)// sizeint firstNum = readFile.readShort();int secondNum = readFile.readShort();int beginNum = firstNum * 100 + secondNum % 100;int endNum = beginNum + secondNum / 100;if (number < beginNum) {right = middle - 1;} else if (number > endNum) {left = middle + 1;} else {int cityIndex = readFile.readShort();readFile.seek(4 + count * blockSize + cityIndex* CityCollector.MAXCITYLENGTH);byte[] b = new byte[CityCollector.MAXCITYLENGTH];readFile.read(b);result = new String(b).trim();break;}}} catch (FileNotFoundException e) {e.printStackTrace();} catch (IOException e) {e.printStackTrace();}if (readFile != null) {try {readFile.close();} catch (IOException e) {e.printStackTrace();}}return result;}