Distributed storage system
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The document discusses distributed storage systems, including defining distributed computing, how distributed databases work, advantages like scalability and fault tolerance, and challenges around transactions and transparency. It also introduces UniversalDistributedStorage, which uses hashing, leader election, and multi-master replication to provide a distributed, fault-tolerant storage solution. Performance testing showed throughput of thousands of requests per second.
Distributed storage system
- 1. DISTRIBUTED STORAGE SYSTEM Mr. Dương Công Lợi Company: VNG-Corp Tel: +84989510016 Email:[email protected]
- 2. CONTENTS 1. What is distributed-computing system? 2. Principle of distributed database/storage system 3. Distributed storage system paradigm 4. UniversalDistributedStorage
- 3. 1. WHAT IS DISTRIBUTED-COMPUTING SYSTEM? Distributed-Computing is the process of solving a computational problem using a distributed system. A distributed system is a computing system in which a number of components on multiple computers cooperate by communicating over a network to achieve a common goal.
- 4. DISTRIBUTED DATABASE/STORAGE SYSTEM A distributed database system, the database is stored on several computers . A distributed database is a collection of multiple , Logic computer network .
- 5. DISTRIBUTED SYSTEM ADVANCE Advance Avoid bottleneck & single-point-of-failure More Scalability More Availability Routing model Client routing: client request to appropriate server to read/write data Server routing: server forward request of client to appropriate server and send result to this client * can combine the two model above into a system
- 6. DISTRIBUTED STORAGE SYSTEM Store some data {1,2,3,4,6,7,8} into 1 server And store them into 3 distributed server 1,2,3,4, 6,7,8 1,2,3 4,6 7,8
- 7. 2. PRINCIPLE OF DISTRIBUTED DATABASE/STORAGE SYSTEM Shard data key and store it to appropriate server use Distributed Hash Table (DHT) DHT must be consistent hashing: Uniform distribution of generation Consistent Jenkins, Murmur are the good choice; MD5, SHA slower
- 8. CANONICAL PROBLEMS IN DISTRIBUTED SYSTEMS Distributed data independence Distributed transactions: ACID (Atomicity, Consistency, Isolation, Durability) requirement Fault tolerance Transparency
- 9. 3. DISTRIBUTED STORAGE SYSTEM PARADIGM Data Hashing/Addressing Determine server for data store in Data Replication Store data into multi server node for more available, fault-tolerance
- 10. DISTRIBUTED STORAGE SYSTEM ARCHITECT Data Hashing/Addressing Use DHT to addressing server (use server-name) to a number, performing it on one circle called the keys space Use DHT to addressing data and find server store it by successor(k)=ceiling(addressing(k)) successor(k): server store k 0 server3 server1 server2
- 11. DISTRIBUTED STORAGE SYSTEM ARCHITECT Addressing – Virtual node Each server node is generated to more node-id for evenly distributed, load balance Server1: n1, n4, n6 Server2: n2, n7 Server3: n3, n5 0 server3 server1 server2 n7 n1 n5 n2 n4 n6 n3 n6
- 12. DISTRIBUTED STORAGE SYSTEM ARCHITECT Data Replication Data k1 store in server1 as master and store in server2 as slave 0 server3 server1 server2 k1
- 14. 4. UNIVERSALDISTRIBUTEDSTORAGE UniversalDistributedStorage is a distributed storage system develop for: Distributed data independence Distributed transactions (ACID) Fault tolerance Leader election (decision for join or leave server node) Replicate with multiple master replication Transparency
- 17. UNIVERSALDISTRIBUTEDSTORAGE FEATURE Data hashing/addressing Use Murmur hashing function
- 18. UNIVERSALDISTRIBUTEDSTORAGE FEATURE Leader election Use Bully Leader Election algorithm
- 20. UNIVERSALDISTRIBUTEDSTORAGE FEATURE Multi-master replication Problem of multi-master replication
- 21. UNIVERSALDISTRIBUTEDSTORAGE FEATURE Multi-master replication Data store to main master (called sub-leader), then this data post to queue to sync to other master.
- 22. UNIVERSALDISTRIBUTEDSTORAGE STATISTIC System information: 3 machine 8GB Ram, core i5 3,220GHz LAN/WAN network 7 physical servers on 3 above mechine Concurrence write 16500000 items in 3680s, rate~ 4480req/sec (at client computing) Concurrence read 16500000 items in 1458s, rate~ 11320req/sec (at client computing) * It doesn’t limit of this system, it limit at clients (this test using 3 client thread)
- 23. Q & A Contact: Duong Cong Loi [email protected] https://www.facebook.com/duongcong.loi