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MongoDB误操作恢复测试

MongoDB误操作恢复测试

作者: 丶Daniel | 来源:发表于2019-12-06 03:12 被阅读0次

    前序:

    由于无论在什么架构下,都会不可避免的出现人为误操作的事故出现,本文就对可能出现的误操作问题的解决办法进行测试,这些都是本人想到的解决办法并加以测试实验

    架构:Replica set(1Primary+1Secondary+1slaveDelay)

    延时时间:600秒

    Primary:192.168.1.100:27017

    Secondary:192.168.1.100:27018

    SlaveDelay:192.168.1.100:27019 #延时节点

    步骤:

    一、误删除collection的部分数据记录时:

    我认为的两种情况:删除的数据存在于延时节点中、删除的数据未存在于延时节点中

    删除的数据存在于延时节点中

    这个时候直接从延时节点将误删除的数据导出来,再导入Primary节点即可

    1、Primary库中目前数据情况:

    trs1:PRIMARY>use tt

    trs1:PRIMARY>db.t1.find()

    {"_id" : ObjectId("583667ab6268d1913b424a9a"), "a": 1 }

    {"_id" : ObjectId("583667ab6268d1913b424a9b"), "a": 2 }

    {"_id" : ObjectId("583667ab6268d1913b424a9c"), "a": 3 }

    {"_id" : ObjectId("583667ab6268d1913b424a9d"), "a": 4 }

    {"_id" : ObjectId("583667ab6268d1913b424a9e"), "a": 5 }

    {"_id" : ObjectId("583667ab6268d1913b424a9f"), "a": 6 }

    {"_id" : ObjectId("583667ab6268d1913b424aa0"), "a": 7 }

    {"_id" : ObjectId("583667ab6268d1913b424aa1"), "a": 8 }

    {"_id" : ObjectId("583667ab6268d1913b424aa2"), "a": 9 }

    {"_id" : ObjectId("583667ab6268d1913b424aa3"), "a": 10 }

    延时节点中也是此数据

    2、删除部分数据:

    trs1:PRIMARY>db.t1.remove({a:{gte:4,lte:7}})

    WriteResult({"nRemoved" : 4 })

    trs1:PRIMARY>db.t1.find()

    {"_id" : ObjectId("583667ab6268d1913b424a9a"), "a": 1 }

    {"_id" : ObjectId("583667ab6268d1913b424a9b"), "a": 2 }

    {"_id" : ObjectId("583667ab6268d1913b424a9c"), "a": 3 }

    {"_id" : ObjectId("583667ab6268d1913b424aa1"), "a": 8 }

    {"_id" : ObjectId("583667ab6268d1913b424aa2"), "a": 9 }

    {"_id" : ObjectId("583667ab6268d1913b424aa3"), "a": 10 }

    3、在延时节点中将被删除数据导出:

    [mongo@localhost~]mongoexport --host 10.25.161.15:27019 -d tt -c t1 -q '{a:{gte:4,$lte:7}}'--out ~/backups/myRecords.json

    2016-11-24T12:24:17.643+0800 connected to: 10.25.161.15:27019

    2016-11-24T12:24:17.644+0800 exported 4 records

    4、将数据导入到Primary库集合中:

    [mongo@localhost~]$ mongoimport --host 10.25.161.15:27017 -d tt -c t1 --file ~/backups/myRecords.json

    2016-11-24T12:25:09.962+0800 connected to: 10.25.161.15:27017

    2016-11-24T12:25:09.972+0800 imported 4 documents

    5、查询数据恢复结果:

    trs1:PRIMARY>db.t1.find().sort({a:1})

    {"_id" : ObjectId("583667ab6268d1913b424a9a"), "a": 1 }

    {"_id" : ObjectId("583667ab6268d1913b424a9b"), "a": 2 }

    {"_id" : ObjectId("583667ab6268d1913b424a9c"), "a": 3 }

    {"_id" : ObjectId("583667ab6268d1913b424a9d"), "a": 4 }

    {"_id" : ObjectId("583667ab6268d1913b424a9e"), "a": 5 }

    {"_id" : ObjectId("583667ab6268d1913b424a9f"), "a": 6 }

    {"_id" : ObjectId("583667ab6268d1913b424aa0"), "a": 7 }

    {"_id" : ObjectId("583667ab6268d1913b424aa1"), "a": 8 }

    {"_id" : ObjectId("583667ab6268d1913b424aa2"), "a": 9 }

    {"_id" : ObjectId("583667ab6268d1913b424aa3"), "a": 10 }

    查看已经恢复回来了,但是这算是在理想状态下:未有业务继续写入,导入导出数据量小,所以不知道在生产环境下还能否顺利实现,还需要待后续实验

    删除的数据未存在于延时节点中

    这个时候就需要使用oplog日志恢复了,将误删除的数据用oplog恢复回来

    1、查看Primary库数据信息

    trs1:PRIMARY>db.t1.find().sort({a:1})

    {"_id" : ObjectId("583667ab6268d1913b424a9a"), "a": 1 }

    {"_id" : ObjectId("583667ab6268d1913b424a9b"), "a": 2 }

    {"_id" : ObjectId("583667ab6268d1913b424a9c"), "a": 3 }

    {"_id" : ObjectId("583667ab6268d1913b424a9d"), "a": 4 }

    {"_id" : ObjectId("583667ab6268d1913b424a9e"), "a": 5 }

    {"_id" : ObjectId("583667ab6268d1913b424a9f"), "a": 6 }

    {"_id" : ObjectId("583667ab6268d1913b424aa0"), "a": 7 }

    {"_id" : ObjectId("583667ab6268d1913b424aa1"), "a": 8 }

    {"_id" : ObjectId("583667ab6268d1913b424aa2"), "a": 9 }

    {"_id" : ObjectId("583667ab6268d1913b424aa3"), "a": 10 }

    2、查看时间戳s1

    trs1:PRIMARY>rs.status().members[0].optime.ts

    Timestamp(1479961509,4)

    3、插入10条数据

    trs1:PRIMARY>for(var i=1;i<11;i++){

    ...db.t1.insert({b:i})

    ...}

    WriteResult({"nInserted" : 1 })

    3、查看时间戳s2

    trs1:PRIMARY>rs.status().members[0].optime.ts

    Timestamp(1479972707,10)

    4、删除5条数据(模拟误删除)

    trs1:PRIMARY>db.t1.remove({b:{$gte:6}})

    WriteResult({"nRemoved" : 5 })

    5、再插入1条数据(模拟误操作之后又有业务进行了insert动作)

    trs1:PRIMARY>db.t1.insert({c:1})

    WriteResult({"nInserted" : 1 })

    6、mongobackup备份导出时间戳s1之后的oplog

    mongobackup-h 10.25.161.15 -port 27017 --backup -s 1479961509,4

    7、使用mongobackup进行oplog恢复s1与s2时间段内的数据

    mongobackup-h 10.25.161.15 -port 27017 --recovery -s 1479961509,4 -t 1479972707,10

    connectedto: 10.25.161.15:27017

    ThuNov 24 15:36:34.005 Replaying file oplog.bson

    ThuNov 24 15:36:34.006 Only applying oplog entries matching this criteria: {"ts" : { "gte" : { "timestamp" : {"t" : 1479961509, "i" : 4 } }, "lte" : {"timestamp" : { "t" : 1479972707, "i" : 10 } } }}

    16objects found

    ThuNov 24 15:36:34.006 Successfully Recovered.

    8、查询恢复后的数据

    trs1:PRIMARY>db.t1.find({b:10})

    {"_id" : ObjectId("58369763c95ee8a72cfab654"), "b": 10 }

    trs1:PRIMARY>db.t1.find({b:{gte:1,lte:10}})

    {"_id" : ObjectId("58369763c95ee8a72cfab64b"), "b": 1 }

    {"_id" : ObjectId("58369763c95ee8a72cfab64c"), "b": 2 }

    {"_id" : ObjectId("58369763c95ee8a72cfab64d"), "b": 3 }

    {"_id" : ObjectId("58369763c95ee8a72cfab64e"), "b": 4 }

    {"_id" : ObjectId("58369763c95ee8a72cfab64f"), "b": 5 }

    {"_id" : ObjectId("58369763c95ee8a72cfab650"), "b": 6 }

    {"_id" : ObjectId("58369763c95ee8a72cfab651"), "b": 7 }

    {"_id" : ObjectId("58369763c95ee8a72cfab652"), "b": 8 }

    {"_id" : ObjectId("58369763c95ee8a72cfab653"), "b": 9 }

    {"_id" : ObjectId("58369763c95ee8a72cfab654"), "b": 10 }

    trs1:PRIMARY>db.t1.find({c:1})

    {"_id" : ObjectId("583697d1c95ee8a72cfab655"), "c": 1 }

    查询之后我们发现原来删除的{b:6}~{b:10}的数据都恢复了,并且{c:1}的这笔数据也没有被清除,达到了我们预计的结果,其实实际中整个操作的难点在于时间戳的确认,我先在理想情况下把实验做完,后续再进行补充说明实际情况下的时间戳确认。

    二、误删除collection

    有时候误删除整个collection的话,就没办法仅通过延迟节点恢复了,因为延迟节点不存在最近一次同步之后Primary更新的数据,这就需要oplog闪亮登场了

    在我目前的认知看来,可以有两种恢复方法:延时节点collection+oplog恢复、mongodump备份+oplog恢复

    延时节点collection+oplog恢复:

    1、查看表数据量

    trs1:PRIMARY>db.t1.find()

    {"_id" : ObjectId("5836a4c7c95ee8a72cfab656"), "a": 1 }

    {"_id" : ObjectId("5836a4c7c95ee8a72cfab657"), "a": 2 }

    {"_id" : ObjectId("5836a4c7c95ee8a72cfab658"), "a": 3 }

    {"_id" : ObjectId("5836a4c7c95ee8a72cfab659"), "a": 4 }

    {"_id" : ObjectId("5836a4c7c95ee8a72cfab65a"), "a": 5 }

    2、插入一条新记录(模拟延迟节点没有的数据)

    trs1:PRIMARY>db.t1.insert({a:6})

    WriteResult({"nInserted" : 1 })

    3、Drop collection

    trs1:PRIMARY>db.t1.drop()

    true

    4、查看延时节点最近一次同步的时间戳s1

    trs1:SECONDARY>rs.status().members[2].optime.ts

    Timestamp(1479976135, 6)

    5、mongoexport导出延时节点中collection的所有数据

    [mongo@localhostbackups]$ mongoexport --host 10.25.161.15:27019 -d tt -c t1

    2016-11-24T17:31:24.970+0800 connected to: 10.25.161.15:27019

    {"_id":{"$oid":"5836a4c7c95ee8a72cfab656"},"a":1.0}

    {"_id":{"$oid":"5836a4c7c95ee8a72cfab657"},"a":2.0}

    {"_id":{"$oid":"5836a4c7c95ee8a72cfab658"},"a":3.0}

    {"_id":{"$oid":"5836a4c7c95ee8a72cfab659"},"a":4.0}

    {"_id":{"$oid":"5836a4c7c95ee8a72cfab65a"},"a":5.0}

    2016-11-24T17:31:24.971+0800 exported 5 records

    6、mongobackup导出时间戳s1之后的oplog

    [mongo@localhostbackups]$ mongobackup -h 10.25.161.15 -port 27017 --backup -s 1479976135,6

    connectedto: 10.25.161.15:27017

    ThuNov 24 17:32:14.457 local.oplog.rs to backup/oplog.bson

    ThuNov 24 17:32:14.458 2objects

    7、mongoimport第④步中的json数据

    [mongo@localhostbackups]$ mongoimport --host 10.25.161.15:27017 -d tt -c t1 --file ./myRecords.json

    2016-11-24T17:34:55.200+0800 connected to: 10.25.161.15:27017

    2016-11-24T17:34:55.229+0800 imported 5 documents

    8、查询drop前的最后一个时间戳s2

    因为如果选择drop的时间戳的话,mongobackup恢复时仍然是会重放drop动作的(我已实验过,注意第⑨步中的红色字体就明白了)

    [mongo@localhostbackups]$ bsondump backup/oplog.bson | grep -B 1'"drop":"t1"'

    。。。。。。。

    {"ts":{"timestamp":{"t":1479979785,"i":1}},"t":{"numberLong":"4"},"h":{"numberLong":"-1488414770385429463"},"v":2,"op":"i","ns":"tt.t1","o":{"_id":{"oid":"5836b309c95ee8a72cfab65b"},"a":6.0}}

    {"ts":{"timestamp":{"t":1479979814,"i":1}},"t":{"numberLong":"4"},"h":{"numberLong":"-1645421116110840065"},"v":2,"op":"c","ns":"tt.cmd","o":{"drop":"t1"}}

    9、mongobackup恢复collection到drop之前状态

    mongobackup-h 10.25.161.15 -port 27017 --recovery -s 1479976135,6 -t 1479979785,1

    connectedto: 10.25.161.15:27017

    ThuNov 24 17:39:49.289 Replaying file oplog.bson

    ThuNov 24 17:39:49.289 Only applying oplog entries matching this criteria: {"ts" : { "gte" : {"timestamp" : { "t" : 1479976135, "i" : 6 } },"lte" : { "timestamp" : {"t" : 1479979785, "i" : 1 } } } }

    2objects found

    ThuNov 24 17:39:49.290 Successfully Recovered.

    10、验证结果

    trs1:PRIMARY>db.t1.find()

    {"_id" : ObjectId("5836a4c7c95ee8a72cfab658"), "a": 3 }

    {"_id" : ObjectId("5836a4c7c95ee8a72cfab656"), "a": 1 }

    {"_id" : ObjectId("5836a4c7c95ee8a72cfab657"), "a": 2 }

    {"_id" : ObjectId("5836a4c7c95ee8a72cfab65a"), "a": 5 }

    {"_id" : ObjectId("5836a4c7c95ee8a72cfab659"), "a": 4 }

    {"_id" : ObjectId("5836b309c95ee8a72cfab65b"), "a": 6 }

    mongodump备份+oplog恢复:

    开启实时oplog备份
    [mongo@localhostbackups]$ pwd

    /home/mongo/backups

    [mongo@localhostbackups]mongobackup -h 10.25.161.15 --port 27017 --backup --stream

    插入10万笔数据(模拟dump备份时有新数据生成)
    trs1:PRIMARY>for(var i=0;i<100000;i++){

    ...db.t1.insert({a:i})}

    WriteResult({"nInserted" : 1 })

    mongodump执行全量备份
    [mongo@localhostbackups]$ pwd

    /home/mongo/backups

    [mongo@localhostbackups]$mongodump --host 10.25.161.15:27017 --oplog

    2016-11-25T11:24:56.731+0800 writing tt.t1 to

    2016-11-25T11:24:56.762+0800 done dumping tt.t1 (4239 documents)

    2016-11-25T11:24:56.763+0800 writing captured oplog to

    2016-11-25T11:24:56.769+0800 dumped 36 oplog entries

    待insert完成后,drop掉此collection(模拟误删除collection动作)
    trs1:PRIMARY>db.t1.count()

    100000

    trs1:PRIMARY>db.t1.drop()

    true

    停止mongobackup的实时oplog备份
    使用Ctrl+C就可以停止

    查看第③步备份中最后一笔oplog的时间戳s1
    [mongo@localhostbackups]$ pwd

    /home/mongo/backups

    [mongo@localhostbackups]$ ll dump/

    total4

    -rw-rw-r--.1 mongo mongo 3816 Nov 25 11:24oplog.bson

    drwxrwxr-x.2 mongo mongo 43 Nov 25 11:24 tt

    [mongo@localhostbackups]$ bsondump dump/oplog.bson | tail -1

    2016-11-25T11:35:26.735+0800 36 objects found

    {"ts":{"timestamp":{"t":1480044296,"i":776}},"t":{"numberLong":"4"},"h":{"numberLong":"4007452313334291247"},"v":2,"op":"i","ns":"tt.t1","o":{"_id":{"oid":"5837af0823358cbda370c7b0"},"a":4267.0}}

    注:因为mongodump在备份时,数据一直在变化,所以为了备份数据一致性使用了--oplog参数,用于备份在mongodump过程中新生成的数据,所以oplog.bson最后一笔数据的时间戳就是mongodump结束时的时间戳

    首先使用全量备份进行恢复
    [mongo@localhostbackups]$ mongorestore --host10.25.161.15:27017 --oplogReplay ./dump

    2016-11-25T16:15:15.149+0800 building a list of dbs and collections torestore from dump dir

    2016-11-25T16:15:15.151+0800 reading metadata for tt.t1 fromdump/tt/t1.metadata.json

    2016-11-25T16:15:15.167+0800 restoring tt.t1 from dump/tt/t1.bson

    2016-11-25T16:15:15.368+0800 restoring indexes for collection tt.t1 frommetadata

    2016-11-25T16:15:15.369+0800 finished restoring tt.t1 (4239 documents)

    2016-11-25T16:15:15.369+0800 replaying oplog

    2016-11-25T16:15:15.387+0800 done

    trs1:PRIMARY>db.t1.count()

    4268

    通过bsondump查看drop collection之前的最后一个时间戳s2
    $bsondump backup/oplog000000.bson | grep -B 1'"drop":"t1"' | sort

    {"ts":{"timestamp":{"t":1480044395,"i":807}},"t":{"numberLong":"4"},"h":{"numberLong":"-7281969221530393253"},"v":2,"op":"i","ns":"tt.t1","o":{"_id":{"oid":"5837af6b23358cbda3723da4"},"a":99999.0}}

    {"ts":{"timestamp":{"t":1480044421,"i":1}},"t":{"numberLong":"4"},"h":{"numberLong":"8681873880357004177"},"v":2,"op":"c","ns":"tt.cmd","o":{"drop":"t1"}}

    注:如果有多行drop记录,则使用sort选取最后一个drop动作的前一个时间戳(即上述红色数字)

    mongobackup恢复时间戳s1~s2之间的数据
    [mongo@localhostbackups]$ mongobackup -h 10.25.161.15 --port 27017 --recovery -s 1480044296,776 -t 1480044395,807 ./backup/

    connectedto: 10.25.161.15:27017

    FriNov 25 16:17:35.343 Replaying file oplog.bson

    FriNov 25 16:17:35.343 Only applying oplog entries matching this criteria: {"ts" : { "gte" : { "timestamp" : {"t" : 1480044296, "i" : 776 } }, "lte" : {"timestamp" : { "t" : 1480044395, "i" : 807 } }} }

    100103objects found

    FriNov 25 16:17:35.962 Successfully Recovered.

    验证恢复情况
    trs1:PRIMARY>db.t1.count()

    100000
    ————————————————
    版权声明:本文为CSDN博主「逃跑的肉丸」的原创文章,遵循 CC 4.0 BY-SA 版权协议,转载请附上原文出处链接及本声明。
    原文链接:https://blog.csdn.net/jianlong727/article/details/53485507

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