前面介紹了如何搭建mongodb sharding 叢集，本文對shard進行大量資料拆分測試，並談了對於片鍵的選擇注意事項，（可能不全，希望指教）

1 啟用test資料庫的分片功能。

mongos> db.runCommand({"enablesharding": "test"})

{ "ok" : 1 }

2 檢視整個sharding 的架構

mongos> db.runCommand({listshards:1});

{

"shards" : [

{

"_id" : "shard0000",

"host" : "10.250.7.225:27018"

},

{

"_id" : "shard0001",

"host" : "10.250.7.249:27019"

},

{

"_id" : "shard0002",

"host" : "10.250.7.241:27020"

}

],

"ok" : 1

}

mongos> printShardingStatus();

--- Sharding Status ---

sharding version: { "_id" : 1, "version" : 3 }

shards:

{ "_id" : "shard0000", "host" : "10.250.7.225:27018" }

{ "_id" : "shard0001", "host" : "10.250.7.249:27019" }

{ "_id" : "shard0002", "host" : "10.250.7.241:27020" }

databases:

{ "_id" : "admin", "partitioned" : false, "primary" : "config" }

{ "_id" : "test", "partitioned" : true, "primary" : "shard0000" }

Note：test 資料庫的 partitioned 為true 意味開啟了sharding 功能。

3 啟用test資料庫中的集合sharding功能，並指定片鍵為"_id"，索引唯一。

mongos> db.runCommand({shardcollection:'test.yql',key:{_id:1}, unique : true});

{ "collectionsharded" : "test.yql", "ok" : 1 }

插入17條資料，並檢視yql的狀況

mongos> db.yql.stats();

{

"sharded" : true,

"flags" : 1,

"ns" : "test.yql",

"count" : 17,

"numExtents" : 1,

"size" : 1616,

"storageSize" : 8192,

"totalIndexSize" : 8176,

"indexSizes" : {

"_id_" : 8176

},

"avgObjSize" : 95.05882352941177,

"nindexes" : 1,

"nchunks" : 1,

"shards" : {

"shard0000" : { --表示yql被拆分到了10.250.7.225這臺機器上了

"ns" : "test.yql",

"count" : 17,

"size" : 1616,

"avgObjSize" : 95.05882352941177,

"storageSize" : 8192,

"numExtents" : 1,

"nindexes" : 1,

"lastExtentSize" : 8192,

"paddingFactor" : 1,

"flags" : 1,

"totalIndexSize" : 8176,

"indexSizes" : {

"_id_" : 8176

},

"ok" : 1

}

},

"ok" : 1

}

mongos>

4 使用 pymongodb 向test.yql插入200w的資料

[mongodb@rac4 pymongo]$ python

Python 2.4.3 (#1, Jan 21 2009, 01:11:33)

[GCC 4.1.2 20071124 (Red Hat 4.1.2-42)] on linux2

Type "help", "copyright", "credits" or "license" for more information.

>>>

>>> import pymongo

>>>conn = pymongo.Connection(host="127.0.0.1")

>>> db=conn.test

>>> for i in xrange(2000000):

... val=dict(val="yangql"+str(i))

... db.yql.insert(val)

ObjectId('4eb2aa5940643e5bb61e847b')

ObjectId('4eb2aa5940643e5bb61e847c')

ObjectId('4eb2aa5940643e5bb61e847d')

ObjectId('4eb2aa5940643e5bb61e847e')

ObjectId('4eb2aa5940643e5bb61e847f')

....省略....

5 再次檢視,collection yql在整個sharding的分佈狀況：這次collection yql 被拆分到了三個不同的shard上面。

mongos> db.yql.stats();

{

"sharded" : true,

"flags" : 1,

"ns" : "test.yql",

"count" : 2000017,

"numExtents" : 23,

"size" : 92001336,

"storageSize" : 146833408,

"totalIndexSize" : 64917440,

"indexSizes" : {

"_id_" : 64917440

},

"avgObjSize" : 46.00027699764552,

"nindexes" : 1,

"nchunks" : 4,

"shards" : {

"shard0000" : {

"ns" : "test.yql",

"count" : 29448,

"size" : 1296204,

"avgObjSize" : 44.016707416462914,

"storageSize" : 2793472,

"numExtents" : 5,

"nindexes" : 1,

"lastExtentSize" : 2097152,

"paddingFactor" : 1,

"flags" : 1,

"totalIndexSize" : 964768,

"indexSizes" : {

"_id_" : 964768

},

"ok" : 1

},

"shard0001" : {

"ns" : "test.yql",

"count" : 1942524,

"size" : 89471128,

"avgObjSize" : 46.05921368281679,

"storageSize" : 141246464, --這裡shard0001上面的資料比較多，和片鍵的選擇有關。

"numExtents" : 13,

"nindexes" : 1,

"lastExtentSize" : 30072832,

"paddingFactor" : 1,

"flags" : 1,

"totalIndexSize" : 63036960,

"indexSizes" : {

"_id_" : 63036960

},

"ok" : 1

},

"shard0002" : {

"ns" : "test.yql",

"count" : 28045,

"size" : 1234004,

"avgObjSize" : 44.00085576751649,

"storageSize" : 2793472,

"numExtents" : 5,

"nindexes" : 1,

"lastExtentSize" : 2097152,

"paddingFactor" : 1,

"flags" : 1,

"totalIndexSize" : 915712,

"indexSizes" : {

"_id_" : 915712

},

"ok" : 1

}

},

"ok" : 1

}

從下面的查詢結果可以看出，集合yql 根據片鍵的分佈：

shard0000 _id:{$minKey:1} --&gt>"4eb298b3adbd9673afee95e3"

shard0000 _id:4eb298b3adbd9673afee95e3"--&gt>"4eb2a64640643e5bb60072f7"

shard0002 _id: "4eb2a64640643e5bb60072f7--&gt>"4eb2a65340643e5bb600e084"

shard0001 _id:4eb2a65340643e5bb600e084"--&gt>{ $maxKey:1}

mongos> printShardingStatus();

--- Sharding Status ---

sharding version: { "_id" : 1, "version" : 3 }

shards:

{ "_id" : "shard0000", "host" : "10.250.7.225:27018" }

{ "_id" : "shard0001", "host" : "10.250.7.249:27019" }

{ "_id" : "shard0002", "host" : "10.250.7.241:27020" }

databases:

{ "_id" : "admin", "partitioned" : false, "primary" : "config" }

{ "_id" : "test", "partitioned" : true, "primary" : "shard0000" }

test.yql chunks:

shard0000 2

shard0002 1

shard0001 1

{ "_id" : { $minKey : 1 } } --&gt> { "_id" : ObjectId("4eb298b3adbd9673afee95e3") } on : shard0000 { "t" : 2000, "i" : 1 }

{ "_id" : ObjectId("4eb298b3adbd9673afee95e3") } --&gt> { "_id" : ObjectId("4eb2a64640643e5bb60072f7") } on : shard0000 { "t" : 1000, "i" : 3 }

{ "_id" : ObjectId("4eb2a64640643e5bb60072f7") } --&gt> { "_id" : ObjectId("4eb2a65340643e5bb600e084") } on : shard0002 { "t" : 3000, "i" : 1 }

{ "_id" : ObjectId("4eb2a65340643e5bb600e084") } --&gt> { "_id" : { $maxKey : 1 } } on : shard0001 { "t" : 3000, "i" : 0 }

mongos>

在配置的時候，我們只是指定了片鍵，對集合的拆分則是由mongos來進行的，即叢集自動進行資料拆分，並進行負載均衡！對於片鍵的選擇會影響到集合在shard的分佈，對於本文中的例子：

選擇_id 為片鍵，分了四個區間：

[{$minKey:1},"4eb298b3adbd9673afee95e3" ]

["4eb298b3adbd9673afee95e3","4eb2a64640643e5bb60072f7"]

["4eb2a64640643e5bb60072f7","4eb2a65340643e5bb600e084"]

["4eb2a65340643e5bb600e084",{$maxKey:1}]

隨著資料的繼續插入，再進行拆分資料插入的資料依然會插入到shard0001伺服器上的，對於上面的例子再次插入200w的資料：

檢視yql的分片分佈：shard0000 和shard0002上面儲存的資料沒有變化，所有插入的資料全部落入到shard0001上面。

mongos> db.yql.stats();

{

"sharded" : true,

"flags" : 1,

"ns" : "test.yql",

"count" : 4000017,

"numExtents" : 26,

"size" : 184000936,

"storageSize" : 278208512,

"totalIndexSize" : 129802176,

"indexSizes" : {

"_id_" : 129802176

},

"avgObjSize" : 46.00003849983638,

"nindexes" : 1,

"nchunks" : 4,

"shards" : {

"shard0000" : {

"ns" : "test.yql",

"count" : 29448,

"size" : 1296204,

"avgObjSize" : 44.016707416462914,

"storageSize" : 2793472,

"numExtents" : 5,

"nindexes" : 1,

"lastExtentSize" : 2097152,

"paddingFactor" : 1,

"flags" : 1,

"totalIndexSize" : 964768,

"indexSizes" : {

"_id_" : 964768

},

"ok" : 1

},

"shard0001" : {

"ns" : "test.yql",

"count" : 3942524,

"size" : 181470728,

"avgObjSize" : 46.02907376086994,

"storageSize" : 272621568,

"numExtents" : 16,

"nindexes" : 1,

"lastExtentSize" : 51974144,

"paddingFactor" : 1,

"flags" : 1,

"totalIndexSize" : 127921696,

"indexSizes" : {

"_id_" : 127921696

},

"ok" : 1

},

"shard0002" : {

"ns" : "test.yql",

"count" : 28045,

"size" : 1234004,

"avgObjSize" : 44.00085576751649,

"storageSize" : 2793472,

"numExtents" : 5,

"nindexes" : 1,

"lastExtentSize" : 2097152,

"paddingFactor" : 1,

"flags" : 1,

"totalIndexSize" : 915712,

"indexSizes" : {

"_id_" : 915712

},

"ok" : 1

}

},

"ok" : 1

}

mongos>

這樣不符合sharding的初衷：負載均衡，最終也會導致shard0001 上面的磁碟空間和記憶體不足。

Note：如果寫入負載比較高，要分散負載，此時必須考慮選擇均勻分佈的片鍵。不能在只有幾個值的片鍵，比如對於status 有四個值，A,B,C,D.mongos 不會建立多於4個塊。選擇片鍵時，除了均勻分佈也要有個增長上線即最大值，否則就會出現上面的情況，違背了sharding的初衷。

【Mongodb】對 shard 進行大量資料拆分測試

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