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Optimized Transactional Data Structure Approach to Concurrency Control for In-Memory Databases

The optimistic concurrency control (OCC) utilized by in-memory databases performs writes on thread-local copies and makes the writes visible upon passing validation. However, high contention workloads suffer from failure of the validation step due to non-semantic memory access conflicts, leading to frequent transaction aborts. In this work, we improve the commit rate of in-memory databases by replacing OCC and the underlying indexing of key-value entries in the Silo database with a lock-free transactional dictionary. To further optimize the transactional commit rate, we present transactional merging, a technique that relaxes the semantic conflict resolution of transactional data structures by merging conflicting operations to reduce aborts. Transactional merging guarantees strict serializability through a strategy that recovers the correct abstract state given that a transaction attempting to merge operations aborts. The experimental evaluation demonstrates that the lock-free transactional dictionary with transactional merging achieves an average speedup of 175% over OCC and the Masstree indexing used in the Silo database for write-dominated workloads on a non-uniform memory access system.