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Mongo db
- 2. 2 JSON JSON – JavaScript Object Notation All you need to know first is Object and Array. Use Unicode to replace special symbols.
- 3. 3 MongoDB MongoDB (from humongous) is a cross-platform document-oriented database • Document-oriented • Ad hoc queries • Indexing • Replication • Load balancing • File storage • Aggregation • Server-side JavaScript execution • Capped collections
- 4. 4 MongoDB • SQL v.s. MongoDB naming SQL MongoDB database database table collection row document column field index index primary key primary key table joins N/A view N/A
- 5. 5 MongoDB • Create your MongoDB – Register MongoLab (Free 500 MB storage) and create DB / Account • https://mongolab.com/ – Install MongoDB GUI tool • 3T MongoChef • Robomongo (0.8.x not full support MongoDB 3.0)
- 6. 6 Replication Set • Replication provides redundancy and increases data availability. With multiple copies of data on different database servers, replication protects a database from the loss of a single server. • When to Voite? – Initiation – Primary disconnect with other Secondary B A ….Heartbeat Voting B Replication A …. Primary Secondary Secondary
- 7. 7 Replication Set Bully Algorithm (欺凌演算法) 1. 一開始有五個節點，5號為主節點。 2. 當5號失聯後，2 、3號發現，並同時跟4號說我要當 主節點。 3. 4號說，我ID比你們都還大，不讓2、3號當主節點 3號說，我ID比2號大(4號2票，3號1票) 4. 此時1號才知道5號已經失聯，傳送給2、3、4號要 求當主節點。 5. 1號太小咖，所以沒有任何一票。 6. 4號再次試著通知5號，但是沒反應，所以就宣布他 成為主節點。
- 8. 8 Shard • Shard, or horizontal scaling, by contrast, divides the data set and distributes the data over multiple servers, or shards. Each shard is an independent database, and collectively, the shards make up a single logical database.
- 9. 9 Shard • Deploy a Shard Cluster • Increase a Shard • Remove a Shard Router (mongos) Shard1 (mongod) Shard2 (mongod) Config Server (mongod) Shard3 (mongod)
- 10. 10 Reference • No SQL list – http://nosql-database.org/ • MongoDB – http://www.cnblogs.com/zhy4606/category/322458.html – http://blog.csdn.net/Crazy__Programmer/article/category/1711961 • MongoDB的寫入安全機制 – http://blog.chinaunix.net/uid-15795819-id-3373361.html • No SQL 演算法 – https://goo.gl/FDG7fT – http://my.oschina.net/juliashine/blog/88173 • 使用WEP API 與 Mongodb連結 – http://goo.gl/WCz6sc
Editor's Notes
- 文件導向 使用BJSON格式儲存資料，每個collection沒有固定欄位 即席查询(大陸翻譯) 可根據使用者自己定義出要產生的查詢結果，MongoDB可以搭配 Javascript產生所需的查詢結果 索引 可加快資料的查詢速度 副本 機器間自動備份與容錯轉移 負載均衡 透過分片，將資料平均的分散到各資料庫內 文件儲存 透過分片與副本集，將文件自動分配置多個機器中，進而形成網格文件系統，並且支援多種語言 聚合 透過mapreduce進而對文件進行批次操作，類似SQL中的GROUP功能 Javascript可在Server端執行 封頂集合 指定固定大小，將文件依照指定的順序插入，所占用的磁碟空間是固定的，無法刪除單一資料但是可以drop所有的資料內容，會使用在Log, cache 參考連結http://blog.csdn.net/zhangzhebjut/article/details/15504279
- http://www.arthurtoday.com/2011/06/mongodb-gridfs.html
- 副本集的成員最多可以有50台 參與投票的機器最多只有7台 http://blog.nosqlfan.com/html/4139.html
- Mongos 負責溝通介面 Config Server負責儲存調配分片
- http://showmeurdeadline.tumblr.com/post/132139743018/shard-%E8%A8%AD%E5%AE%9A How to create a sharded cluster in one machine Create Services (2 shard, 1 config, 1 mongos, chunk size is 10 MB) D:MongoDB\bin\mongod.exe --port 10001 --dbpath D:\MongoDB\shard1\data --logpath D:\MongoDB\shard1\log\log.txt D:MongoDB\bin\mongod.exe --port 10002 --dbpath D:\MongoDB\shard2\data --logpath D:\MongoDB\shard2\log\log.txt D:MongoDB\bin\mongod.exe --port 10003 --dbpath D:\MongoDB\shard3\data --logpath D:\MongoDB\shard3\log\log.txt D:MongoDB\bin\mongod.exe --port 20001 --configsvr --dbpath D:\MongoDB\config\date --logpath D:\MongoDB\config\log\log.txt D:MongoDB\bin\mongos.exe --port 30001 --configdb 127.0.0.1:20001 --logpath D:\MongoDB\mongos\log\log.txt --chunksize 10 Create sharding mongos> sh.status() --- Sharding Status --- sharding version: { "_id" : 1, "minCompatibleVersion" : 5, "currentVersion" : 6, "clusterId" : ObjectId("5632f589e3d2976287ef05af") } shards: balancer: Currently enabled: yes Currently running: no Failed balancer rounds in last 5 attempts: 0 Migration Results for the last 24 hours: No recent migrations databases: { "_id" : "admin", "partitioned" : false, "primary" : "config" } Create Shard mongos> sh.addShard('127.0.0.1:10001') { "shardAdded" : "shard0000", "ok" : 1 } mongos> sh.addShard('127.0.0.1:10002') { "shardAdded" : "shard0001", "ok" : 1 } mongos> sh.status() --- Sharding Status --- sharding version: { "_id" : 1, "minCompatibleVersion" : 5, "currentVersion" : 6, "clusterId" : ObjectId("5632f589e3d2976287ef05af") } shards: { "_id" : "shard0000", "host" : "127.0.0.1:10001" } { "_id" : "shard0001", "host" : "127.0.0.1:10002" } balancer: Currently enabled: yes Currently running: no Failed balancer rounds in last 5 attempts: 0 Migration Results for the last 24 hours: No recent migrations databases: { "_id" : "admin", "partitioned" : false, "primary" : "config" } 執行要切割的 sh.enableSharding('EagleVision') sh.enableSharding('ydb') 設定你要切割的條件 db.ycollection.ensureIndex( { _id : "hashed" } ) sh.shardCollection("ydb.ycollection", { "_id": "hashed" } ) 將資料擷取出來 D:MongoDB\bin\mongodump.exe --port 10003 -d ydb -cycollection 確認裡面的資料 bsondump dump/ydb/ycollection.bson 將現有的shard移除 db.adminCommand({"removeShard":"127.0.0.1:10003"}) 將shard加回去 use config db.shards.update( {'_id':'shard0002'}, {$unset:{draining:true}},false,true )
- 取得資料→資料蒐集→分析管理