Acunu Analytics and Cassandra at Hailo All Your Base 2013
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Hailo, the taxi app, has served more than 5 million passengers in 15 cities and has taken fares of $100 million this year. I'm going to talk about how that rapid growth has been powered by a platform based on Cassandra and operational analytics and insights powered by Acunu Analytics. I'll cover some challenges and lessons learned from scaling fast!
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Acunu Analytics and Cassandra at Hailo All Your Base 2013
- 1. Acunu Analytics and Cassandra at Hailo Tim Moreton, CTO at Acunu David Gardner, Architect at Hailo ALL YOUR BASE 2013
- 2. Dave ALL YOUR BASE 2013
- 3. What is Hailo? Hailo is The Taxi Magnet. Use Hailo to get a cab wherever you are, whenever you want. ALL YOUR BASE 2013
- 4. ALL YOUR BASE 2013
- 5. What is Hailo? • The world’s highest-rated taxi app – over 11,000 five-star reviews • Over 500,000 registered passengers • A Hailo hail is accepted around the world every 4 seconds • Hailo operates in 15 cities on 3 continents from Tokyo to Toronto in nearly 2 years of operation ALL YOUR BASE 2013
- 6. The history The story behind Cassandra and Acunu adoption at Hailo ALL YOUR BASE 2013
- 7. Hailo launched in London in November 2011 • Launched on AWS • Two PHP/MySQL web apps plus a Java backend • Mostly built by a team of 3 or 4 backend engineers • MySQL multi-master for single AZ resilience • Get/create/update entity • • Analytics Text search ALL YOUR BASE 2013
- 8. Why Cassandra? • A desire for greater resilience – “become a utility” Cassandra is designed for high availability • Plans for international expansion around a single consumer app Cassandra is good at global replication • Expected growth Cassandra scales linearly for both reads and writes • Prior experience I had experience with Cassandra and could recommend it ALL YOUR BASE 2013
- 9. The path to adoption • Largely unilateral decision by developers – a result of a startup culture • Replacement of key consumer app functionality, splitting up the PHP/MySQL web app into a mixture of global PHP/Java services backed by a Cassandra data store • Launched into production in September 2012 – originally just powering North American expansion, before gradually switching over Dublin and London ALL YOUR BASE 2013
- 10. One year on... • Further decompose functionality into Go/Java SOA • Migrating: Entity databases to Cassandra Analytics to Acunu Search into Elastic Search ALL YOUR BASE 2013
- 11. Cassandra ALL YOUR BASE 2013
- 12. We like Cassandra • Solid design • HA characteristics • Easy multi-DC setup • Simplicity of operation ALL YOUR BASE 2013
- 13. “Cassandra just works” Dom W, Senior Engineer ALL YOUR BASE 2013
- 14. CF = customers 126007613634425612: createdTimestamp: 1370465412 email: dave@cruft.co givenName: Dave familyName: Gardner locale: en_GB phone: +447911111111 ALL YOUR BASE 2013
- 15. Considerations for entity storage • Do not read the entire entity, update one property and then write back a mutation containing every column • Only mutate columns that have been set • This avoids read-before-write race conditions ALL YOUR BASE 2013
- 16. ALL YOUR BASE 2013
- 19. ALL YOUR BASE 2013
- 20. Considerations for time series storage • Choose row key carefully, since this partitions the records • Think about how many records you want in a single row • Denormalise on write into many indexes/views ALL YOUR BASE 2013
- 21. ALL YOUR BASE 2013
- 22. 10 Average years experience per team member MySQL ALL YOUR BASE 2013 Cassandra
- 23. ALL YOUR BASE 2013
- 24. People who can attempt to query MySQL People who can attempt to query Cassandra #CASSANDRAEU 2013 ALL YOUR BASE CASSANDRASUMMITEU
- 25. ALL YOUR BASE 2013
- 26. Acunu Analytics ALL YOUR BASE 2013
- 27. Analytics • With Cassandra we lost the ability to carry out analytics eg: COUNT, SUM, AVG, GROUP BY • We use Acunu Analytics to give us this ability in real time, for preplanned query templates • It is backed by Cassandra and therefore highly available, resilient and globally distributed • Integration is straightforward ALL YOUR BASE 2013
- 28. Events NSQ ALL YOUR BASE 2013
- 29. Events NSQ ALL YOUR BASE 2013
- 30. Events NSQ Analytics turns events and SQL-like queries into C* operations ALL YOUR BASE 2013
- 31. Events NSQ Analytics turns events and SQL-like queries into C* operations Cassandra stores raw events and intermediate results ALL YOUR BASE 2013
- 32. Acunu Dashboards provides real-time visualization Events Alerts NSQ Analytics turns events and SQL-like queries into C* operations Cassandra stores raw events and intermediate results ALL YOUR BASE 2013
- 33. ALL YOUR BASE 2013
- 34. 1 Define aggregate cubes CREATE CUBE APPROX TOP(keyword) WHERE browser, time GROUP BY time count by day ALL YOUR BASE 2013 count by hour of day uniques by hashtag
- 35. 1 Define aggregate cubes CREATE CUBE APPROX TOP(keyword) WHERE browser, time GROUP BY time 2 New events update cubes count by day ALL YOUR BASE 2013 count by hour of day uniques by hashtag
- 36. 1 Define aggregate cubes CREATE CUBE APPROX TOP(keyword) WHERE browser, time GROUP BY time 2 New events update cubes count by day ALL YOUR BASE 2013 count by hour of day uniques by hashtag
- 37. 1 Define aggregate cubes CREATE CUBE APPROX TOP(keyword) WHERE browser, time GROUP BY time 2 New events update cubes raw events ALL YOUR BASE 2013 count by day count by hour of day uniques by hashtag
- 38. 1 Define aggregate cubes 3 Rich instant queries over cubes CREATE CUBE APPROX TOP(keyword) WHERE browser, time GROUP BY time SELECT TOP(keyword) FROM table WHERE browser = ‘chrome’ AND time BETWEEN.. GROUP BY d1, d2, ... JOIN ... HAVING.. ORDER BY .. 2 New events update cubes + raw events ALL YOUR BASE 2013 count by day count by hour of day uniques by hashtag
- 39. 1 Define aggregate cubes 3 Rich instant queries over cubes CREATE CUBE APPROX TOP(keyword) WHERE browser, time GROUP BY time SELECT TOP(keyword) FROM table WHERE browser = ‘chrome’ AND time BETWEEN.. GROUP BY d1, d2, ... JOIN ... HAVING.. ORDER BY .. 2 New events update cubes + raw events count by day 4 Drilldown to raw events ALL YOUR BASE 2013 count by hour of day uniques by hashtag
- 40. 1 Define aggregate cubes 3 Rich instant queries over cubes CREATE CUBE APPROX TOP(keyword) WHERE browser, time GROUP BY time SELECT TOP(keyword) FROM table WHERE browser = ‘chrome’ AND time BETWEEN.. GROUP BY d1, d2, ... JOIN ... HAVING.. ORDER BY .. 2 New events update cubes + raw events count by day count by hour of day 5 Backfill new cubes using historic data ALL YOUR BASE 2013 uniques by hashtag
- 41. AQL SELECT SUM(accepted), SUM(ignored), SUM(declined), SUM(withdrawn) FROM Allocations WHERE timestamp BETWEEN '1 week ago' AND 'now’ AND driver='LON123456789’ GROUP BY timestamp(day) ALL YOUR BASE 2013
- 42. ALL YOUR BASE 2013
- 43. Use Cases • Infrastructure and Application monitoring • Real-time A/B testing of app layout and incentives • Real time geo-view of supply/demand for drivers • Several more in the pipeline! ALL YOUR BASE 2013
- 45. We like Cassandra and Acunu • Solid design • HA characteristics • Easy multi-DC setup • Simplicity of operation • With Acunu, rich queries again, easier denormalization ALL YOUR BASE 2013
- 46. Lessons for successful adoption • Have an advocate, sell the dream • Learn the fundamentals, get the best out of Cassandra • Invest in tools to make life easier • Keep management in the loop, explain the trade offs ALL YOUR BASE 2013
- 47. Questions? ALL YOUR BASE 2013