Adaptive optimistic concurrency control for heterogeneous workloads

Abstract

Optimistic concurrency control (OCC) protocols validate whether a transaction has conflicts with other concurrent transactions after this transaction completes its execution. In this work, we demonstrate that the validation phase has a great influence on the performance of modern in-memory database systems, especially under heterogeneous workloads. The cost of validating operations in a transaction is determined by two main factors. The first factor is the operation type. An OCC protocol would take much less cost on validating a single-record read operation than validating a key-range scan operation. The second factor is the workload type. Existing schemes in OCC variants for validating key-range scan perform differently under various workloads. Although various validation schemes share the same goal of guaranteeing a transaction schedule to be serializable, there are remarkable differences between the costs they introduced. These observations motivate us to design an optimistic concurrency control which can choose a low-cost validation scheme at runtime, referred to as adaptive optimistic concurrency control (AOCC). First, at transactionlevel granularity, AOCC can assign a validation method to a transaction according to the features of its operations. Furthermore, for each operation in a transaction, the validation method is selected according to not only the number of accessed records but also the instant characteristics of workloads. Experimental results show that AOCC has good performance and scalability under heterogeneous workloads mixed with point accesses and predicate queries.

Growth of relational model: Interdependence and complementary to big data

“…The optimistic approach to concurrency control came from Kung and Robinson, but only one-version databases were considered [67]. The optimistic techniques [68] are used in applications where transaction conflicts are very rare. In this approach, the transactions are allowed to perform as desired until a write phase is encountered.…”

A Transactional Perspective on Execute-order-validate Blockchains

“…Various works have attempted to either make data access more cache-friendly [35,28] or extract more execution parallelism [34,32]. Others strove to streamline the transaction ordering based on workload characteristics and application requirements [17,12,29].…”

An Analysis of Concurrency Control Protocols for In-Memory Databases with CCBench (Extended Version)

“…This suggests the importance of adaptive behavior. Although adaptive concurrency controls have been studied [37,55,59,69], their importance has not been discussed in depth regarding optimizations except for backoff [46]. Studies on adaptive optimization methods remain on the frontier.…”

“…Whereas previous studies mostly evaluated scalability and did not explore the behavior of protocols when thread parallelism was set to a high degree [30,32,33,35,37,39,43,44,46,56,63,65,69,70,73,74,76,77], we fixed the thread parallelism at 224 and analyzed protocols for various settings. We classified a variety of methods on the basis of three performance factors: cache, delay, and version lifetime.…”

“…These modern protocols use a variety of optimization methods, and their behaviors depend on the workload characteristics (e.g., thread count, skew, read ratio, cardinality, payload size, transaction size, and read-modify-write or not). Recent new proposal studies have compared these protocols with conventional ones [30,32,33,35,37,39,43,44,46,56,63,65,69,70,73,74,76,77], and recent analytical studies have compared the performance of conventional protocols on a common platform [23,24,72,75]. These studies mostly evaluated protocol scalability.…”