Cassandra tech talk
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The document outlines a tech talk on Apache Cassandra, covering its definition as a free, distributed database with a unique architecture, data partitioning, and replication strategies. It highlights key benefits such as high write/read volumes, horizontal scalability, and flexibility, as well as notable users and limitations to consider when transitioning from relational databases. The agenda includes an overview of Cassandra's architecture, data handling, and a demo session.
Cassandra tech talk
- 1. UDA SE Tech Talk Sep 20 2012 CASSANDRA
- 2. Agenda •What is Cassandra? •Architecture •Why use Cassandra? •Current Consumers/use cases? •Limitations •Demo 2
- 3. CASSANDRA 3
- 4. What is Cassandra? -Free, Open Source, Distributed database -Written by 2 Facebook Engineers -Hybrid of -BigTable from Google -DynamoDB from Amazon -For Structured, Semi-structured, Unstructured Data -Designed to scale across commodity servers -Assures AP out of CAP -(Consistency, Availability, Partition Tolerance) 4
- 5. Architectural Overview •Independent nodes form cluster •All nodes peers •Gossip protocol to discover/connect nodes •Gossip process runs every second •Nodes exchanges state mesgs with max 3 nodes •Nodes exchange info about themselves/Others •Seed Nodes have cluster info in cassandra.yaml file •All nodes have same seed nodes in their config file •Nodes remember all gossip info since last restart 5
- 6. Data Partitioning •Should be decided when setting up •Total Data managed by Cassandra like a Ring •Ring is divided into Ranges •Each node responsible for one or more •Before a node joins it is given a token •Token depends on •Node’s position •Range of data it is responsible for •Column Family partitioned based on row key •For given row key value, ring is walked clockwise until token is within range •2 High Level Partitioning Schemes: - Random Partitioner - Ordered Partitioner •Random Partitioner uses consistent hashing •Ordered Partitioner ensures sorted order. 6
- 7. Data Partitioning (Contd) Partitioning in Multi-Data Center Clusters 7
- 8. Replication •Replication – process of storing copies of data •Replication Strategy •Number of Replicas •Distro of replicas over the nodes •Relies on cluster configured Snitch •SimpleStrategy - default •NetworkTopologyStrategy •Takes rack, data center into consideration 8
- 9. Snitches… •The snitch is a configurable component of cluster •Defines how the nodes are grouped together •Types of snitches: •SimpleSnitch •BriskSimpleSnitch •RackInferringSnitch •PropertyFileSnitch •EC2Snitch •Dynamic Snitching 9
- 10. Snitches…(contd) 10
- 11. Why Use Cassandra? •Very High Volume writes/reads •All writes HAVE to succeed •Horizontal scalability •Commodity HW •Integration with Hadoop/Hbase/HIVE •SQL Like usage •No Single point of failure •Powerful dynamic Schema data model •Maximum flexibility •Performance at scale 11
- 12. Some Well known Current Customers WebEx Ooyala Clearspring Openwave Cloudkick OpenX Cloudtalk Plaxo connex.io Rackspace Constant Contact Reddit Digg SimpleGeo Facebook SoundCloud IBM Twitter Netflix Walmart Labs Formspring Yakaz Mahalo.com 12
- 13. Limitations Be aware of these differences when you move from a relational database to Cassandra. • No transactions, • No JOINs • No foreign keys and keys are immutable • Keys have to be unique • Failed operations may leave changes • Searching is complicated • Super columns and order preserving partitioners are discouraged • Healing from failure is manual • It remembers deletes (until v0.8, at least) 13
- 14. DEMO
- 15. Questions?