理解MongoDB默认的ObjectID

BSON ObjectID Specification

A BSON ObjectID is a 12-byte value consisting of a 4-byte timestamp (seconds since epoch), a 3-byte machine id, a 2-byte process id, and a 3-byte counter. Note that the timestamp and counter fields must be stored big endian unlike the rest of BSON. This is because they are compared byte-by-byte and we want to ensure a mostly increasing order. The format:

• TimeStamp. This is a unix style timestamp. It is a signed int representing the number of seconds before or after January 1st 1970 (UTC).

• Machine. This is the first three bytes of the (md5) hash of the machine host name, or of the mac/network address, or the virtual machine id.

• Pid. This is 2 bytes of the process id (or thread id) of the process generating the object id.

• Increment. This is an ever incrementing value, or a random number if a counter can't be used in the language/runtime.

BSON ObjectIds can be any 12 byte binary string that is unique; however, the server itself and almost all drivers use the format above.

分段查看ObjectId的指令及结果如下：

1. > db.test.findOne()._id.toString()
2. ObjectId("50c6b336ba95d7738d1042e3")
3. > db.test.findOne()._id.toString().substring(10,18)
4. 50c6b336
5. > db.test.findOne()._id.toString().substring(18,24)
6. ba95d7
7. > db.test.findOne()._id.toString().substring(24,28)
8. 738d
9. > db.test.findOne()._id.toString().substring(28,34)
10. 1042e3

ObjectId占用12字节的存储空间，由"时间戳" 、"机器名"、"PID号"和"计数器"组成。使用机器名的好处是在分布式环境中能够避免单点计数的性能瓶颈。使用PID号的好处是支持同一机器内运行多个mongod实例。最终采用时间戳和计数器的组合来保证唯一性。

时间戳

确保ObjectId唯一性依赖的是时间的顺序，不依赖时间的取值，因此集群节点的时间不必完全同步。既然ObjectId已经有了时间戳，那么在文档中就可以省掉一个时间戳了。在使用ObjectID提取时间时，应注意到MongoDB允许各节点时间不一致这一细节。

下面是查看时间戳的两种写法：

1. > db.test1.findOne()._id.getTimestamp()
2. ISODate("2012-12-12T03:52:45Z")
3. > Date(parseInt(db.test1.findOne()._id.toString().substring(10,18),16))
4. Wed Dec 12 2012 12:11:02 GMT+0800

机器名

机器名通过Md5加密后取前三个字节，应该还是有重复概率的，配置生产集群时检查一下总不会错。另外，我也注意到重启MongoDB后MD5加密结果会发生变化，在利用ObjectID提取机器名信息时需格外注意。

PID号

注意到每次重启mongod进程后PID号通常会发生变化就可以了。

计数器

计数器占3个字节，表示的取值范围就是256*256*256-1=16777215。不妨认为MongDB性能的极限是单台设备一秒钟插入一千万条记录。以目前的水平看，单台设备一秒钟插入一万条就很不错了，因此ObjectID计数器的设计是够用的。

循环插入了一些记录，下面的查询中b是循环计数器，可以看出我机器上的ObjectId计数器是按顺序增加的：

1. > parseInt(db.test.findOne({b:1000})._id.toString().substring(28,34),16)
2. 1947382
3. > parseInt(db.test.findOne({b:1001})._id.toString().substring(28,34),16)
4. 1947383
5. > parseInt(db.test.findOne({b:1002})._id.toString().substring(28,34),16)
6. 1947384
7. > parseInt(db.test.findOne({b:1003})._id.toString().substring(28,34),16)
8. 1947385

以下代码源自：http://www.cnblogs.com/xjk15082/archive/2011/09/18/2180792.html

1. 构建objectId
2. public class ObjectId implements Comparable , java.io.Serializable {
3. final int _time;
4. final int _machine;
5. final int _inc;
6. boolean _new;
7. public ObjectId(){
8. _time = (int) (System.currentTimeMillis() / 1000);
9. _machine = _genmachine;
10. _inc = _nextInc.getAndIncrement();
11. _new = true;
12. }
13. ……
14. }

1. 机器码和进程码的生成
2. private static final int _genmachine;
3. static {
4. try {
5. final int machinePiece;
6. {
7. StringBuilder sb = new StringBuilder();
8. Enumeration e = NetworkInterface.getNetworkInterfaces();
9. while ( e.hasMoreElements() ){
10. NetworkInterface ni = e.nextElement();
11. sb.append( ni.toString() );
12. }
13. machinePiece = sb.toString().hashCode() << 16;
14. LOGGER.fine( "machine piece post: " + Integer.toHexString( machinePiece ) );
15. }
16. final int processPiece;
17. {
18. int processId = new java.util.Random().nextInt();
19. try {
20. processId = java.lang.management.ManagementFactory.getRuntimeMXBean().getName().hashCode();
21. }catch ( Throwable t ){
22. }
23. ClassLoader loader = ObjectId.class.getClassLoader();
24. int loaderId = loader != null ? System.identityHashCode(loader) : 0;
25. StringBuilder sb = new StringBuilder();
26. sb.append(Integer.toHexString(processId));
27. sb.append(Integer.toHexString(loaderId));
28. processPiece = sb.toString().hashCode() & 0xFFFF;
29. LOGGER.fine( "process piece: " + Integer.toHexString( processPiece ) );
30. }
31. _genmachine = machinePiece | processPiece;
32. LOGGER.fine( "machine : " + Integer.toHexString( _genmachine ) );
33. }catch ( java.io.IOException ioe ){
34. throw new RuntimeException( ioe );
35. }
36. }