Checking Causal Consistency of Distributed Databases

Abstract

The CAP Theorem shows that (strong) Consistency, Availability, and Partition tolerance are impossible to be ensured together. Causal consistency is one of the weak consistency models that can be implemented to ensure availability and partition tolerance in distributed systems. In this work, we propose a tool to check automatically the conformance of distributed/concurrent systems executions to causal consistency models. Our approach consists in reducing the problem of checking if an execution is causally consistent to solving Datalog queries. The reduction is based on complete characterizations of the executions violating causal consistency in terms of the existence of cycles in suitably defined relations between the operations occurring in these executions. We have implemented the reduction in a testing tool for distributed databases, and carried out several experiments on real case studies, showing the efficiency of the suggested approach.

Efficient Black-Box Checking of Snapshot Isolation in Databases

“…Database Schema. In our testing of production databases, we used a simple, yet effective, database schema adopted by most of blackbox checkers [6,38,47,48]: a two-column table storing key-value pairs. Extending it to multi-columns or even the column-family data model could be done by: (i) representing each cell in a table as a compound key, i.e., "TableName:PrimaryKey:ColumnName", and a single value, i.e., the content of the cell [7,29]; and (ii) utilizing the compiler in [7] to rewrite (more complex) SQL queries to key-value read/write operations.…”