MongoDB本身不支持增量備份，所以這里介紹幾種我找到的，或者是自己使用代碼實現的方法：
我的環境：集群環境，
如果是分片集群，只好各【分片集群】和【配置服務器集群】分開備份處理，因為使用了Oplog
所以不適合單機環境

一、 Delay server + Oplog replay(延遲節點+Oplog 重現)

【MongoDB The.Definitive.Guide 2nd.pdf】P363中介紹的使用mongooplog 工具來做增量備份的方法

應該 也屬于此類方法。

二、使用mongosync 同步工具，?? ?它的功能有：

?? ?1.?? ?全量同步
?? ?2.?? ?增量同步
?? ?3.?? ?全量和增量同步，實時同步
?? ?4.?? ?可批量同步某個庫/表
?? ?優點：
?? ??? ?切換快，（如果使用了增量備份，那備份機必須是集群，因為用到oplog ）
?? ?（url: http://www.tuicool.com/articles/iei6n2）
?? ?下載鏈接：http://pan.baidu.com/s/1qXrpbDa 密碼：yybn

三、使用開源代碼: Wordnik MongoDB Admin Tools 進行增量備份。

?? ?具體操作可以看git:? https://github.com/reverb/wordnik-oss/blob/master/modules/mongo-admin-utils/README.md
?? ?下面有打包好的文件：
?? ??? ?鏈接：http://pan.baidu.com/s/1bogjYVH 密碼：i82e
?? ?我測試下來，增量備份速度不太理想，也有可能是和測試環境有關系。


這里我把我使用python 代碼實現 oplog 增量備份及恢復的羅列如下：

1. Delay server + Oplog replay(延遲節點+Oplog 重現)
使用Oplog replay 的優點是：可以在恢復時，具體恢復到某一個時間點

步驟如下：
?? ?1、在集群中添加一個延遲節點，比如延遲設置成10小時；
?? ?2、另外找一臺MongoDB 實例（可以是集群，也可以是單機）使用代碼同步local.oplog.rs 表數據到
?? ?備份庫中（不要選擇local庫，因為local 庫中的表你無法修改表結構，表索引，比如我新建立的表庫名：oplog_bak）
?? ?代碼如下（python）：

'''Author: tangDate: 2016/03/07MongoDB Incremental Backup oplog.rs to other serverDB'''import timeimport jsonimport pymongoimport datetimeimport osimport sysimport bsondef init_back_database(p_db_name):'''init back desc db'''dest_conn.get_database(p_db_name).create_collection('oplog.rs',autoIndexId=False)dest_conn.get_database(p_db_name).get_collection('oplog.rs').create_index([("ts",pymongo.ASCENDING)],unique=True)dest_conn.get_database(p_db_name).get_collection('oplog.rs').create_index([('ns',pymongo.ASCENDING)])dest_conn.get_database(p_db_name).get_collection('oplog.rs').insert({"ts":bson.timestamp.Timestamp(0,1)})def inc_oplog(p_db_name):"""copy source server oplog to backup db""" #get last_timestamprow_count = dest_conn.get_database(p_db_name).get_collection('oplog.rs').count()if row_count==0:init_back_database(p_db_name)last_timestamp = bson.timestamp.Timestamp(int(time.time())-24*3600,1) else: cur_oplog_rs = dest_conn.get_database(p_db_name).get_collection('oplog.rs').find({},{"ts":1}).sort([("ts",-1)]).limit(1)for row in cur_oplog_rs:last_timestamp = row["ts"]#copy oplogcur_oplog = source_conn.get_database('local').get_collection('oplog.rs').find({"ts":{"$gt":last_timestamp},"op":{"$in":['i','d','u']}}).limit(100000)for row in cur_oplog:#insertrow_data = row#change dist2str save, bypass: field name not start $if row_data.has_key('o'):row_data['o'] = str(row_data['o'])if row_data.has_key('o2'):row_data['o2'] = str(row_data['o2']) #print row_data dest_conn.get_database(p_db_name).get_collection('oplog.rs').insert(row_data)#end copy oplog #end inc_oplog def replay_oplog(p_db_name,p_tb_name,p_start_ts,p_end_ts):'''use oplog log row,replay data to every collections'''#copy oplogcur_oplog = source_conn.get_database(p_db_name).get_collection('oplog.rs').find({"ts":{"$gt":p_last_ts}}) for row in cur_oplog:db_name = row["ns"].split('.')[0]tbl_name = row["ns"].split('.')[1]#insert if row['op']=='i':document_dist = eval(row['o'])dest_conn.get_database(db_name).get_collection(tbl_name).insert(document_dist)#updateif row.has_key('b'):muli_flg = row['b']else:muli_flg = False if row['op']=='u':document_dist = eval(row['o'])if row.has_key('o2'):document2_dist = eval(row['o2'])dest_conn.get_database(db_name).get_collection(tbl_name).update(document2_dist,document_dist,multi=muli_flg)else:dest_conn.get_database(db_name).get_collection(tbl_name).update({},document_dist,multi=muli_flg)#deleteif row['op']=='d':document_dist = eval(row['o'])dest_conn.get_database(db_name).get_collection(tbl_name).remove(document_dist,multi=muli_flg)#end def replay_oplog if __name__=='__main__':btype = sys.argv[1]source_host = sys.argv[2]desc_host = sys.argv[3]desc_dbname = sys.argv[4]last_ts = sys.argv[5] source_conn = pymongo.MongoClient(['mongodb://%s'%source_host])dest_conn = pymongo.MongoClient(['mongodb://%s'%desc_host])if btype in ['b','back','bak']:inc_oplog(desc_dbname)if btype in ['r','rest','restore']:replay_oplog(desc_dbname, last_ts)

【MongoDB The.Definitive.Guide 2nd.pdf】P363：

Creating Incremental Backups with mongooplog

All of the backup methods outlined must make a full copy of the data, even if very little
of it has changed since the last backup. If you have data that is very large relative to the
amount that is being written, you may want to look into incremental backups.
Instead of making full copies of the data every day or week, you take one backup and
then use the oplog to back up all operations that have happened since the backup. This
technique is much more complex than the ones described above, so prefer them unless
incremental backups are absolutely necessary.
This technique requires two machines, A and B, running mongod. A is your main
machine (probably a secondary) and B is your backup machine:
1. Make a note of the latest optime in A’s oplog:
> op = db.oplog.rs.find().sort({$natural: -1}).limit(1).next();
> start = op['ts']['t']/1000
Keep this somewhere safe—you’ll need it for a later step.
2. Take a backup of your data, using one of the techniques above to get a point-intime backup. Restore this backup to the data directory on B.
3. Periodically add any operations that have happened on A to B’s copy of the data.
There is a special tool that comes with MongoDB distributions that makes this easy:
mongooplog (pronounced mon-goop-log) which copies data from the oplog of one
server and applies it to the data set on another. On B, run:
$ mongooplog --from A --seconds 1234567
--seconds should be passed the number of seconds between the start variable
calculated in step 1 and the current time, then add a bit (better to replay operations
a second time than miss them).
This keeps your backup relatively up-to-date with your data. This technique is sort of
like keeping a secondary up-to-date manually, so you may just want to use a slavedelayed secondary instead

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