Darshan Rawal is leading the development of hybrid cloud based messaging products for global Tier 1 Telcos. Darshan has been working in Silicon valley since 2000, building nimble, cost effective products/services, handling millions of users and billions of transactions per day. Previous to Openwave Messaging, Darshan held engineering positions @ SS8 networks, Yahoo, DE Shaw, yp.com and has a M.S in Software Engineering from Carnegie Mellon University.

1. Pushing Cassandra’s
Boundaries
Darshan Rawal
VP Engineering, Openwave Messaging Inc.

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Agenda
! Introduction
! Our Cassandra Journey
! Spectrum of BIG Data challenges
! Cassandra Pivots
! Typical Cassandra Instance YoY change
! Cassandra Insights
! Conclusion

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Openwave Messaging Customers

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Universal Messaging Suite

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Our Cassandra Journey – 3.5 years

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Cassandra Under Fire - A Story
! Customer Emergency
• Where: Major North American OWM customer
• When: Q4 2012
• What: File System corruption in legacy platform
• Impact: All (~800K) accounts without mail access
! Resolution: A lab system goes live
! Metrics:
• 20 minutes to upgrade RAM per Cassandra Node
• Run wild maintainence/compaction; solved via SSDs
• 100% Uptime

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Spectrum of BIG Data Challenges

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Cassandra Pivots

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Atomic Batches – Client Side Impact
getConnection()
batch_mutate(…)
freeConnection()
getConnection()
batch_mutate(…)
freeConnection()
getConnection()
batch_mutate(…)
freeConnection()
getConnection()
batch_mutate( …)
batch_mutate( …)
batch_mutate( …)
freeConnection()
prepare_batch()
getConnection()
atomic_batch_mutate(…)
freeConnection()
Cassandra
1.1x
Cassandra 1.2.x
Application
Optimization

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Typical Cassandra Instance - YoY Change

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Cassandra Journey Insights
! It’s a new paradigm, will take time / investment
! There is no free lunch; cool features have a price
! Sizing is all about IOPS, not all IOPS are equal
! Eventual Consistency is dual edged sword
! Adapt paradigms that don’t fit upfront

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Cassandra Insights
Aspect Insight
Replication Factor Ratio of RF / Ring size plays a crucial role in
throughput. Linear growth as the ratio shrinks
Tombstones Needs effective tuning for delete heavy applications
Refactor application level soft deletes
Sizing Plan for the perfect storm: Compaction + N Failures
+ Recovery (especially for dense deployments)
Reliable Counters Utilize Client side affinity
Super Cols Best Avoided
Client Interaction Thundering herd issues due to backend GC

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In retrospection

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Current challenges @ Openwave Messaging

15. Darshan.Rawal@owmessaging.com