1. Adaptive Hybrid Quorums in Practical Settings Aaron Davidson, Aviad Rubinstein, Anirudh Todi, Peter Bailis and Shivaram Venkataraman Introduction Implementation in Cassandra Evaluation What are Quorums? Adaptive Hybrid Quorums Experimental Consistency • Use PBSPredictor() and WARS Model [1] to track latencies and predict consistency • Track workload properties, • e.g. is it read- or write- oriented? • Optimization algorithm → adaptively find the best quorum for current workload and system performance • Replication → consistency + durability + availability. • quorum – subset of the replicas • Write and read from a quorum → efficiency • Traditionally: full quorums – • every 2 quorums intersect → consistency • In practice: partial quorums → • sacrificing consistency for efficiency Phase 2 Phase 2 recovery recovery node fails node fails Failure Modeling Experimental Latency • Node failure model: • Incorporate model into adaptive hybrid consistency • Ongoing work: model message drops… t-visibility Phase 1 – node crashes but we don’t know it… • Dynamo: send to N replicas (full quorum), wait for R/W (partial quorum). • Eventually all replicas receive request • → eventual consistency • Bailis et al. [1]: bound the time for consistency node fails detection (1,2) Phase 2 – Writes go to hinted node N-1 replicas remain (1,1) recovery node restarts Phase 3 – Hinted-handoff Recovering node is partially available Key Observation References Quorums are temporary → change them adaptively! [1] Peter Bailis, Shivaram Venkataraman, Michael J. Franklin, Joseph M. Hellerstein, and Ion Stoica. Probabilistically bounded staleness for practical partial quorums. PVLDB, 5(8):776787, 2012.