Cassandra tw presentation
- 1. CASSANDRA Looking at the bottom
- 2. What are we learning today? > Why NoSQL like CASSANDRA > Internal organ of CASSANDRA > Basics of Distributed System Theory > Basics of Scalable system design
- 3. > Consistency via ACID transactions > Strict constraint checks > Maturity > Huge toolkits Strength of SQL
- 4. CAP Theorem
- 6. > Guess how long it might take for aurora for handling network partition or master failure?? Challenges with RDMS
- 7. > Challenge with Single Master(Tough Heavy writing) Challenges with RDMS
- 8. SHARDING Solution for Heavy writing
- 9. > Making high availability > Remove split brain syndrome > Faster Write Tackle these topics
- 10. Cassandra uses a synthesis of well known techniques to achieve scalability and availability. Cassandra was designed to fulfill the storage needs of the Inbox Search problem. In-box Search is a feature that enables users to search through their Facebook Inbox. At Facebook this meant the system was required to handle a very high write throughput, billions of writes per day, and also scale with the number of users. Since users are served from data centers that are geographically distributed, being able to replicate data across data centers was key to keep search latencies down. Inbox Search was launched in June of 2008 for around 100 million users and today we are at over 250 million users and Cassandra has kept up the promise so far. Cassandra is now deployed as the backend storage system for multiple services within Facebook. History of CASSANDRA
- 12. In Cassandra, cluster nodes communicates between each other by using a protocol called “Gossip” How node know other node?
- 14. > Fault tolerance gained by duplication > Scale out or scale down can be handled by consistent hashing very easily Fault Tolerance
- 15. Internal data structure to achieve massive write faster Achieving faster write
- 17. commit_log(disc) -> write to slave -> response to client What happened at the time to read like below query after inserting billions of row? select * from activities where activity_id=875858858 and timestamp>x and timestamp<y How writes work?
- 18. INDEXING (add more details and challenges) Answer
- 19. What is log structured merge tree? LSM tree
- 20. Answer
- 21. Steps: * Log the record(for recovery in case of crash) * Add to C0 component(in memory writes) * Merge merge.. into C1, compaction compaction and add to SSTable in the disc. How it works?
- 22. How does it look like?
- 23. How read work?
- 24. Thanks The Omar Future Principle Software Engineer