MongoDB Replica,Shard Cluster

中央大學電算中心 楊素秋2014-05-05

OUTLINE

• 1. MongoDB Replica• 2. Deploy a Replica Set• 3. Sharing Cluster• 4. Deploy a Sharded Cluster• 5. Conclusion

1. MongoDB Replica

• Provides redundancy– protects a database from• loss of a single server

• Increases data availability– recover from• hardware failure• service interruptions

2. Deploy a Replica Set

• 安裝 / 啟動 mongoDB on each hosts – http://docs.mongodb.org/manual/tutorial/install-mongodb-on-red-hat-centos-or-

fedora-linux/

• 設定 /etc/mongod.conf• service mongod restart

• 在 primary host (140.115.2.32)– rs.initiate()– rs.add(“140.115.2.32:27017”)– rs.add(“140.115.2.31:27017”)– rs.addArb(“140.115.2.34:27017”)

• Priority – cfg = rs.conf()– cfg.members[0].priority = 2.0 – cfg.members[1].priority = 0.5– rs.reconfig(cfg)

2. Deploy a Replica Set (cont.)

• Slave Node – MongoDBManager.java

2. Deploy a Replica Set (cont.)

public static synchronized DB getDB() throws Exception { if(mongo == null) { mongo = new Mongo(); mongo.slaveOk(); } return mongo.getDB("fdns"); } public static synchronized Mongo getMongo() throws Exception { if(mongo == null) { mongo = new Mongo(); mongo.slaveOk(); } return mongo; }

• Slave Node – mongo shell

• use fdns

• rs.slaveOk()• show collections

– mongo shell• db.collectionName.remove() // FAIL• db.collectionName.drop()

2. Deploy a Replica Set (cont.)

3. Sharing Cluster

• Single machine challenges– High query rates• exhaust CPU capacity

– Larger data sets• exceed the storage capacity

• Referances– http://docs.mongodb.org/manual/core/sharding-introduc

tion/– http://docs.mongodb.org/manual/core/sharded-cluster-c

omponents/

3. Sharing Cluster(cont.)

• Sharded Cluster Components– Shards • holds a subset of a collection’s data• a single mongod instance, or a replica set

– Config Servers• a mongod instance

– holds metadata about the cluster– metadata maps chunks to shards

3. Sharing Cluster (cont.)

– Routing Instances • a mongos instance

– routes the reads and writes from applications to the shards

• Applications do not access the shards directly

3. Sharing Cluster (cont.)

• Vertical scaling– adds more CPU and storage resources to increase capacity

• horizontal scaling (Sharding)• divides the data set• distributes data over multiple servers(shards)– Each shard is an independent database– shards make up a single logical database

• Range based partitioning– MongoDB divides the data set into ranges• determined by the shard key values to provide

• Hash Based Sharding• MongoDB computes a hash of a field’s value– uses these hashes to create chunks.

4. Deploy a Shard Cluster

– http://docs.mongodb.org/manual/tutorial/deploy-shard-cluster/

5. Conclusion

• Replica Set **– Primary : service– Secondary : Data Mining

• Apache Mahout: cluster, classification• Mining flooding, attacks traffic

– Arbiter

• Sharing Cluster– Load balance– Scalability