The performance of transactional database systems is typically evaluated by measuring the amount of transactions they can commit to the database per second. However, fairly measuring this for the same workload on different systems is not trivial. It is therefore relevant to formalize schedule efficiency, investigate the space of all possible efficient schedules, and identify whether there is any room for improvement. Prior transaction theory largely centers on decision problems relating to safety, such as the serializability, robustness, and allocation problems. Most pertinently, these problems take already scheduled transactions as input, and do not directly consider the efficiency of those schedules. In this work, we define schedules as assignments of operations on objects to discrete points in time. This allows us to quantify efficiency as the elapsed duration between the schedule’s beginning and end, more commonly known as the makespan in the scheduling literature. We establish that, given some set of transactions and a desired makespan, it is NP-complete to decide if there exists a conflict serializable schedule which is bounded by that makespan. We additionally provide an instance optimal algorithm for scheduling transaction sets with a single contention point, that is, exactly one object may appear in conflicting operations. Lastly, we give worst-case optimal bounds on the makespan, meaning that schedules can never exceed this bound, and for the worst transaction sets, the bound is optimal.

We propose a theory that can determine the lowest isolation level that can be allocated to each transaction program in an application in a mixed-isolation-level setting, to guarantee that all executions will be serializable and thus preserve all integrity constraints, even those that are not explicitly declared. This extends prior work applied to completely known transactions, to deal with the realistic situation where transactions are generated by running programs with parameters that are not known in advance. Using our theory, we propose an optimization method that allows for high throughput while ensuring that all executions are serializable. Our method is based on searching for application code modifications that are semantics-preserving while improving the isolation level allocation. We illustrate our approach to the SmallBank benchmark.

A serializable concurrency control mechanism ensures consistency for OLTP systems at the expense of a reduced transaction throughput. A DBMS, therefore usually offers the possibility to allocate lower isolation levels for some transactions when it is safe to do so. However, such trading of consistency for efficiency does not come with any safety guarantees. In this article, we study the mixed robustness problem which asks whether, for a given set of transactions and a given allocation of isolation levels, every possible interleaved execution of those transactions that is allowed under the provided allocation is always serializable. That is, whether the given allocation is indeed safe. While robustness has already been studied in the literature for the homogeneous setting where all transactions are allocated the same isolation level, the heterogeneous setting that we consider in this article, despite its practical relevance, has largely been ignored. We focus on multiversion concurrency control and consider the isolation levels that are available in PostgreSQL and Oracle: read committed (RC), snapshot isolation (SI), and serializable snapshot isolation (SSI). We show that the mixed robustness problem can be decided in polynomial time. In addition, we provide a polynomial time algorithm for computing the optimal robust allocation for a given set of transactions, prioritizing lower over higher isolation levels. The present results therefore establish the groundwork to automate isolation level allocation within existing databases supporting multiversion concurrency control.

A DBMS allows trading consistency for efficiency through the allocation of isolation levels that are strictly weaker than serializability. The robustness problem asks whether, for a given set of transactions and a given allocation of isolation levels, every possible interleaved execution of those transactions that is allowed under the provided allocation, is always safe. In the literature, safe is interpreted as conflict-serializable (to which we refer here as conflict-robustness). In this paper, we study the view-robustness problem, interpreting safe as view-serializable. View-serializability is a more permissive notion that allows for a greater number of schedules to be serializable and aligns more closely with the intuitive understanding of what it means for a database to be consistent. However, view-serializability is more complex to analyze (e.g., conflict-serializability can be decided in polynomial time whereas deciding view-serializability is NP-complete). While conflict-robustness implies view-robustness, the converse does not hold in general. In this paper, we provide a sufficient condition for isolation levels guaranteeing that conflict- and view-robustness coincide and show that this condition is satisfied by the isolation levels occurring in Postgres and Oracle: read committed (RC), snapshot isolation (SI) and serializable snapshot isolation (SSI). It hence follows that for these systems, widening from conflict- to view-serializability does not allow for more sets of transactions to become robust. Interestingly, the complexity of deciding serializability within these isolation levels is still quite different. Indeed, deciding conflict-serializability for schedules allowed under RC and SI remains in polynomial time, while we show that deciding view-serializability within these isolation levels remains NP-complete.

A serializable concurrency control mechanism ensures consistency for OLTP systems at the expense of a reduced transaction throughput. A DBMS therefore usually offers the possibility to allocate lower isolation levels for some transactions when it is safe to do so. However, such trading of consistency for efficiency does not come with any safety guarantees. In this paper, we study the mixed robustness problem which asks whether, for a given set of transactions and a given allocation of isolation levels, every possible interleaved execution of those transactions that is allowed under the provided allocation is always serializable. That is, whether the given allocation is indeed safe. While robustness has already been studied in the literature for the homogeneous setting where all transactions are allocated the same isolation level, the heterogeneous setting that we consider in this paper, despite its practical relevance, has largely been ignored. We focus on multiversion concurrency control and consider the isolation levels that are available in Postgres and Oracle: read committed (RC), snapshot isolation (SI) and serializable snapshot isolation (SSI). We show that the mixed robustness problem can be decided in polynomial time. In addition, we provide a polynomial time algorithm for computing the optimal robust allocation for a given set of transactions, prioritizing lower over higher isolation levels. The present results therefore establish the groundwork to automate isolation level allocation within existing databases supporting multiversion concurrency control.

The popular isolation level Multiversion Read Committed (RC) trades some of the strong guarantees of serializability for increased transaction throughput. Sometimes, transaction workloads can be safely executed under RC obtaining serializability at the lower cost of RC. Such workloads are said to be robust against RC. Previous work has yielded a tractable procedure for deciding robustness against RC for workloads generated by transaction programs modeled as transaction templates. An important insight of that work is that, by more accurately modeling transaction programs, we are able to recognize larger sets of workloads as robust. In this work, we increase the modeling power of transaction templates by extending them with functional constraints, which are useful for capturing data dependencies like foreign keys. We show that the incorporation of functional constraints can identify more workloads as robust that otherwise would not be. Even though we establish that the robustness problem becomes undecidable in its most general form, we show that various restrictions on functional constraints lead to decidable and even tractable fragments that can be used to model and test for robustness against RC for realistic scenarios.

Transaction processing is a central part of most database applications. While serializability remains the gold standard for desirable transactional semantics, many database systems offer improved transaction throughput at the expense of introducing potential anomalies through the choice of a lower isolation level. Transactions are often not arbitrary but are constrained by a set of transaction programs defined at the application level (as is the case for TPC-C for instance), implying that not every potential anomaly can effectively be realized. The question central to this paper is the following: when - within the context of specific transaction programs - do isolation levels weaker than serializability, provide the same guarantees as serializability? We refer to the latter as the robustness problem. This paper surveys recent results on robustness testing against (multiversion) read committed focusing on complete rather than sufficient conditions. We show how to lift robustness testing to transaction templates as well as to programs to increase practical applicability. We discuss open questions and highlight promising directions for future research.

While serializability always guarantees application correctness, lower isolation levels can be chosen to improve transaction throughput at the risk of introducing certain anomalies. A set of transactions is robust against a given isolation level if every possible interleaving of the transactions under the specified isolation level is serializable. Robustness therefore always guarantees application correctness with the performance benefit of the lower isolation level. While the robustness problem has received considerable attention in the literature, only sufficient conditions have been obtained. The most notable exception is the seminal work by Fekete where he obtained a characterization for deciding robustness against SNAPSHOT ISOLATION. In this article, we address the robustness problem for the lower SQL isolation levels READ UNCOMMITTED and READ COMMITTED, which are defined in terms of the forbidden dirty write and dirty read patterns. The first main contribution of this article is that we characterize robustness against both isolation levels in terms of the absence of counter-example schedules of a specific form (split and multi-split schedules) and by the absence of cycles in interference graphs that satisfy various properties. A critical difference with Fekete’s work, is that the properties of cycles obtained in this article have to take the relative ordering of operations within transactions into account as READ UNCOMMITTED and READ COMMITTED do not satisfy the atomic visibility requirement. A particular consequence is that the latter renders the robustness problem against READ COMMITTED coNP-complete. The second main contribution of this article is the coNP-hardness proof. For READ UNCOMMITTED, we obtain LOGSPACE-completeness.

The isolation level Multiversion Read Committed (RC), offered by many database systems, is known to trade consistency for increased transaction throughput. Sometimes, transaction workloads can be safely executed under RC obtaining the perfect isolation of serializability at the lower cost of RC. To identify such cases, we introduce an expressive model of transaction programs to better reason about the serializability of transactional workloads. We develop tractable algorithms to decide whether any possible schedule of a workload executed under RC is serializable (referred to as the robustness problem). Our approach yields robust subsets that are larger than those identified by previous methods. We provide experimental evidence that workloads that are robust against RC can be evaluated faster under RC compared to stronger isolation levels. We discuss techniques for making workloads robust against RC by promoting selective read operations to updates. Depending on the scenario, the performance improvements can be considerable. Robustness testing and safely executing transactions under the lower isolation level RC can therefore provide a direct way to increase transaction throughput without changing DBMS internals.

While serializability always guarantees application correctness, lower isolation levels can be chosen to improve transaction throughput at the risk of introducing certain anomalies. A set of transactions is robust against a given isolation level if every possible interleaving of the transactions under the specified isolation level is serializable. Robustness therefore always guarantees application correctness with the performance benefit of the lower isolation level. While the robustness problem has received considerable attention in the literature, only sufficient conditions have been obtained. The most notable exception is the seminal work by Fekete where he obtained a characterization for deciding robustness against SNAPSHOT ISOLATION. In this paper, we address the robustness problem for the lower SQL isolation levels READ UNCOMMITTED and READ COMMITTED which are defined in terms of the forbidden dirty write and dirty read patterns. The first main contribution of this paper is that we characterize robustness against both isolation levels in terms of the absence of counter example schedules of a specific form (split and multi-split schedules) and by the absence of cycles in interference graphs that satisfy various properties. A critical difference with Fekete's work, is that the properties of cycles obtained in this paper have to take the relative ordering of operations within transactions into account as READ UNCOMMITTED and READ COMMITTED do not satisfy the atomic visibility requirement. A particular consequence is that the latter renders the robustness problem against READ COMMITTED coNP-complete. The second main contribution of this paper is the coNP-hardness proof. For READ UNCOMMITTED, we obtain LOGSPACE-completeness.

Recently, Ketsman et al. started the investigation of the parallel evaluation of recursive queries in the Massively Parallel Communication (MPC) model. Among other things, it was shown that parallel-correctness and parallel-boundedness for general Datalog programs is undecidable, by a reduction from the undecidable containment problem for Datalog. Furthermore, economic policies were introduced as a means to specify data distribution in a recursive setting. In this paper, we extend the latter framework to account for more general distributed evaluation strategies in terms of communication policies. We then show that the undecidability of parallel-correctness runs deeper: it already holds for fragments of Datalog, e.g., monadic and frontier-guarded Datalog, with a decidable containment problem, under relatively simple evaluation strategies. These simple evaluation strategies are defined w.r.t. data-moving distribution constraints. We then investigate restrictions of economic policies that yield decidability. In particular, we show that parallel-correctness is 2EXPTIME-complete for monadic and frontier-guarded Datalog under hash-based economic policies. Next, we consider restrictions of data-moving constraints and show that parallel-correctness and parallel-boundedness are 2EXPTIME-complete for frontier-guarded Datalog. Interestingly, distributed evaluation no longer preserves the usual containment relationships between fragments of Datalog. Indeed, not every monadic Datalog program is equivalent to a frontier-guarded one in the distributed setting. We illustrate the latter by considering two alternative settings where in one of these parallel-correctness is decidable for frontier-guarded Datalog but undecidable for monadic Datalog.

Single-round multiway join algorithms first reshuffle data over many servers and then evaluate the query at hand in a parallel and communication-free way. A key question is whether a given distribution policy for the reshuffle is adequate for computing a given query. This property is referred to as parallel-correctness. Another key problem is to detect whether the data reshuffle step can be avoided when evaluating subsequent queries. The latter problem is referred to as transfer of parallel-correctness. This paper extends the study of parallel-correctness and transfer of parallel-correctness of conjunctive queries to incorporate bag semantics. We provide semantical characterizations for both problems, obtain complexity bounds and discuss the relationship with their set semantics counterparts. Finally, we revisit both problems under a modified distribution model that takes advantage of a linear order on compute nodes and obtain tight complexity bounds.