Alireza Angabini Advanced DB class Dr. M.Rahgozar Fall 88

Introduction PNUTS Overview Functionality Architecture Applications Experimental Results Conclusion 2 A.Angabini - PNUTS

 Main requirements of Web Apps  Scalability  Response Time and Geographic Scope  High Availability & Fault Tolerance  Relaxed Consistency Guarantees 3 A.Angabini - PNUTS

 PNUTS is  Massively parallel  Geographically distributed database system  Designed Yahoo!  Used by their web application  Shared between several applications 4 A.Angabini - PNUTS

 Data Model & Features  Fault Tolerance  Pub-Sub Message System  Hosting 5 A.Angabini - PNUTS

 Data & Query Model  Consistency Model 6 A.Angabini - PNUTS

Simplified relational data model Organizes data into tables of records with attributes Allows arbitrary structure inside a record – “blob” Schema are flexible New attribute is added without halting query or update activity Allow to have empty attribute in the record Query language Supports selection and projection in single table Updates & deletes with primary key only 7 A.Angabini - PNUTS

Hide the complexity of replication Considered between general serializability & eventual consistency Per-record timeline consistency “All replica of given record apply all updates to the record in the same order” 8 A.Angabini - PNUTS

 Support range of API calls with different levels of consistency  Read-any  Read-critical(required_version)  Read-latest  Write  Test-and-set-write(required_version) 9 A.Angabini - PNUTS

 Data tables are horizontally partitioned into groups of records called tablets 10 A.Angabini - PNUTS

 Ordered table  Primary-key space of a table is divided into intervals  Each interval corresponds to one tablet  The router stores interval mapping  For a given PMK, binary search is used to find the tablet 11 A.Angabini - PNUTS

 Hash-organized table  n-bit hash function H(), 0 ≤ H() < 2 n  [ n ) is divided into intervals  Each interval corresponds to single tablet  To map a key to a tablet, 1. Hash the key 2. Search set of interval using binary search 12 A.Angabini - PNUTS

 The system uses asynchronous replication  To ensure low-latency updates  Yahoo! Message Broker (YMB)  Used for replication & logging because: 1.Multiple steps are applied before committed to DB 2.YMB is designed for wide-area replication 13 A.Angabini - PNUTS

 Recovery from failure (3 Steps) 1. the tablet controller requests a copy from the source tablet3. the source tablet is copied to the destination region2. “checkpoint message” is published to YMB 14 A.Angabini - PNUTS

 User Database  Social Applications  Content Meta-Data  Listings Management  Session Data 15 A.Angabini - PNUTS

Three PNUTS regions 2 west coast, 1 east coast 5 storage units, 2 message brokers, 1 router West: Dual 2.8 GHz Xeon, 4GB RAM, 6 disk RAID 5 array East: Quad 2.13 GHz Xeon, 4GB RAM, 1 SATA disk Workload requests/second 0-50% writes 80% locality Storage engine for hash table “Yahoo! propriety disk-based hashtable” Storage engine for ordered tables MySQL using InnoDB 16 A.Angabini - PNUTS

The coming experiments show The impact of several factors on the average latency for request 17 A.Angabini - PNUTS

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Rich database functionality and low latency at massive scale. Tradeoffs between functionality, performance and scalability. Choose asynchronous replication to ensure low write latency. Delivers the data management as hosted service 23 A.Angabini - PNUTS

B. Cooper, R. Ramakrishnan, U. Srivastava, A. Silberstein, P. Bohannon, H. Jacobsen, N. Puz, D. Weaver, and R. Yerneni, "PNUTS: Yahoo!'s hosted data serving platform," Proceedings of the VLDB Endowment archive, vol. 1, 2008, p. 1277–1288. Technical report, Raghu Ramakrishnan, Yahoo! Research and Platform Engineering Team 24 A.Angabini - PNUTS

Thanks For Your Attention ? 25 A.Angabini - PNUTS