db sharding

----------------------------------------------------------------------------------- // A. Configure the database mydb and enable the shard use admindb. runcommand ({enablesharding: "mydb "})In this case, the database mydb is based on the shard replset3 (primary shard)After mydb is configured to enable sharding, the configuration information is stored in the databases set of the config database of the configuration server!// B. Set the set to be shard

distributed MongoDB cluster.I. Role description three roles are required to build a MongoDB sharding cluster: The shard server stores the actual data score slices. Each shard can be a Mongod instance, or a group of mongod instances constitute a Replica Set (the Replica Set described in previous blogs ). To implement auto-failover in each shard, MongoDB officially recommends that each shard be a set of Replica sets. Config Server to store a specific c

/192.168.10.103:20001,192.168.10.219:20001",name:"shard1", maxsize:20480} )mongos> db.runCommand({addshard:"shard2/192.168.10.103:20002,192.168.10.219:20002",name:"shard2", maxsize:20480} );mongos> db.runCommand( {listshards : 1 } ){ "shards" : [ { "_id" : "shard1", "host" : "shard1/192.168.10.103:20001,192.168.10.219:20001" }, { "_id" : "shard2", "host" : "shard2/192.168.10.103:20002,192.168.10.219:20002" } ], "ok"

unit capacity of the shard. Here, 1 m is set, for ease of viewing the results, run the following command in the background:/apps/Mongo/bin/mongos -- Port 50000 -- configdb 127.0.0.1: 40000 -- chunksize 50 -- logpath =/data/shard/log/route. log -- fork --------------------------------------------------------------------------------: At this time, no slices are added to the sharding cluster. You can see that the admin database of the

hotspots and new data evenly in each library, while ensuring easy horizontal expansion, consider such a pattern:"Horizontal Scaling Scale-out Scenario mode one"Phase one: A library of DB0 within 4 tables, id%4:Phase II: Increased DB1 library, T2 and T3 entire table relocated to DB1Phase III: Increase the DB2 and DB3 libraries, T1 the entire table relocated to db2,t3 the entire table relocation DB3:For the sake of regular expression, through internal name mapping or otherwise, we interchange the

/shard2 -- shardsvrMongod -- port 27217 -- fork -- logpath ar/log/mongo_config.log -- dbpath/data0/mongo/config -- configsvrConfigure routesMongos -- port 27417 -- fork -- logpath ar/log/mongos. log -- configdb 127.0.0.1: 27217 -- chunkSize 1Configure shard on the clientMongo -- port 27417MongoDB shell version: 1.6.5Connecting to: 127.0.0.1: 27417/test> Use admin;Switched to db admin> Db. runCommand ({addsh

Singlekeyshardingalgorithm, which is a single-row policy, you can also use multi-column strategy, such as user_id and order_id at the same time meet a certain condition, which table.New Tableshardingstrategy (Arrays.aslist ("order_id", "Order_type", "order_date"), New Multikeyshardingalgorithm ())) All of these are based on one or more columns to determine the sub-database of the policy, the official also provides a routing policy is not based on the column, refer to forced routing. http://dang

migrate./manage.py migrate --database=logsharding0./manage.py migrate --database=logsharding1 At this time, we found thatreport_logThe table is no longerlog_statLibrary, but only appears inlogshardingx. HoweverlogshardingxThere will still beauth_group,auth_group_permissions... Tables of these Django components. By now, we have achieved database sharding. We don't have to worry about these extra tables, but we always feel that they are not elegant. Th

Tags: mongodb sharding shardMongodb shardingIntroductionsharding in MongoDBShard Build:Shards (recommended with replica), Query routers, Config Servers.Shards Store the data. To provide high availability and dataconsistency, in a production sharded cluster, each shard is a replica set [1]. For more information on replica sets, see replicasets.Query Routers , or MONGOs instances, interface with clientapplications and direct operations to the appropr

1, Sharding application scenarios are generally those? When the amount of data in the database becomes larger and bigger, the pressure becomes larger, both read and write. Imagine, if the data in a table reached tens of millions of millions of levels, whether the index, optimize caching, etc., will face tremendous performance pressure. Sharding to reduce the pressure on a single machine by spreading the da

127.0.0.1:2222/admindb.runCommand({"addshard":"127.0.0.1:3333",allowlocal:true})db.runCommand({"addshard":"127.0.0.1:4444",allowlocal:true})Enable the sharding function of the test Database mongos> use admin switched to db admin mongos> db.runCommand({"enablesharding":"test"}) { "ok" : 1 } mongos> db.runCommand({"shardcollection":"test.user","key":{"_id":1}}) { "collectionsharded" : "test.user

without database/table sharding 'db' => array ('My _ site' => $ default ,), // database/table sharding 'shared '=> array ('user' => array ('host' => array (/*** link configuration used by libraries numbered 0 to 10 */'0-10' => $ default, /*** link configuration used by libraries numbered 11 to 28 */'11-28' => $ default, /*** link configuration used by libraries

Ideas: 1. Read the database sharding and table sharding policies completely. Note the differences between database sharding and table sharding and write Reading Notes. 2. Test the source code of the ibatis + spring2.0-based sub-database. Pay attention to routing rules. 3. Source Code Implementation of the test table sh

If MongoDB is just a document-type database, there is no bright spot, however MongoDB's greatest advantage is read-extended, hot-backup, failback, and Auto-sharding (write extension). This section of the series to the end of the introduction of these features.Backup copy realizes the database backup simultaneously, realizes the reading and writing separation, and realizes the load balance of the read operation, namely one main write server, multiple s

effective:Mongos> db. printShardingStatus () # mongodb command--- Sharding Status ---Sharding version :{"_ Id": 1,"Version": 4,"MinCompatibleVersion": 4,"CurrentVersion": 5,"ClusterId": ObjectId ("53c76f7a9adee90a8b860eea ")}Shards:{"_ Id": "s1", "host": "shard_1905_01/192.168.3.201: 27017,192.168 .3.206: 27017,192.168 .3.210: 27017 "}{"_ Id": "s2", "host": "sha

　　 1, Sharding application scenarios are generally those? When the amount of data in the database becomes larger and bigger, the pressure becomes larger, both read and write. Imagine, if the data in a table reached tens of millions of millions of levels, whether the index, optimize caching, etc., will face tremendous performance pressure. Sharding to reduce the pressure on a single machine by spreading th

The MongoDB version used in this article is 2.4.6, which uses the following deployment architecture for testing and not for the online environment. The following tests are all done on this machine, and the on-line environment requires separate deployment for each component.650) this.width=650; "Src=" Http://docs.mongodb.org/manual/_images/sharded-cluster-production-architecture.png " alt= "Diagram of a sample sharded cluster for production purposes. Contains exactly 3 config servers, 2 or more "

Detailed mysql table sharding design and application bitsCN.com Detailed design and application of mysql table sharding Generally, when the data in our database exceeds million records, we should consider table sharding or partition. this time I will discuss in detail some methods of table sharding. Currently, all th

/mongos.log--logappend--fork(5) Configuring Shard ClusterConnect to the MONGOs process on port 30000 of one of the machines, and switch to the admin database to do the following configuration[Email protected] bin]#./mongo--port 300001.8.1127.0.0.1:30000/Test> Use adminswitched to DB admin>db.runcommand ({addshard: "shard1/ 192.168.3.231:27017,192.168.3.232:27017,192.168.3.233:27017 "}); {"shardadded": "Shard1", "OK": 1 }>db.runcommand ({addshard: "sha

distribution in each Shard, and collection configuration information for all DB and sharding in the cluster.Route ProcessThis is a front-end route that the client accesses, then asks Config Servers which shard to query or save the record, and then connect the corresponding shard to operate, and finally return the results to the client. The client simply sends the query or update request that was originally