Scaling Optimistic Concurrency Control by Approximately Partitioning the Certifier and Log.

In optimistic concurrency control, a certifier algorithm processes a log of transaction operations to determine whether each transaction satisfies a given isolation level and therefore should commit or abort. This logging and certification of transactions is often sequential and can become a bottleneck. To improve transaction throughput, it is beneficial to parallelize or scale out the certifier and the log. One common technique for such parallelization is to partition the database. If the database is perfectly partitioned such that transactions only access data from a single partition, then both the log and the certifier can be parallelized such that each partition has its own independent log and certifier. However, for many applications, partitioning is only approximate, i.e., a transaction can access multiple partitions. Parallelization using such approximate partitioning requires synchronization between the certifiers and logs to ensure correctness. In this paper, we present the design of a parallel certifier and a partitioned log that uses minimal synchronization to obtain the benefits of parallelization using approximate partitioning. Our parallel certifier algorithm dynamically assigns constraints to each certifier. Certifiers enforce constraints using only atomic writes and reads on shared variables, thus avoiding expensive synchronization primitives such as locks. Our partitioned log uses a lightweight causal messaging protocol to ensure that transactions accessing the same partition appear in the same relative order in all logs where they both appear. We describe the techniques applied to an abstract certifier algorithm and log protocol, making them applicable to a variety of systems. We also show how both techniques can be used in Hyder, a scale-out log-structured indexed record manager.