The article studies query evaluation in parallel constant time in the CRCW PRAM model. While it is well-known that all relational algebra queries can be evaluated in constant time on an appropriate CRCW PRAM model, this article is interested in the efficiency of evaluation algorithms, that is, in the number of processors or, asymptotically equivalent, in the work. Naive evaluation in the parallel setting results in huge (polynomial) bounds on the work of such algorithms and in presentations of the result sets that can be extremely scattered in memory. The article discusses some obstacles for constant-time PRAM query evaluation. It presents algorithms for relational operators and explores three settings, in which efficient sequential query evaluation algorithms exist: acyclic queries, semijoin algebra queries, and join queries the latter in the worst-case optimal framework. Under mild assumptions that data values are numbers of polynomial size in the size of the database or that the relations of the database are suitably sorted constant-time algorithms are presented that are weakly work-efficient in the sense that work O(T1+epsilon) can be achieved, for every epsilon > 0, compared to the time T of an optimal sequential algorithm. Important tools are the algorithms for approximate prefix sums and compaction from Goldberg and Zwick (1995).

Previous work on Dynamic Complexity has established that there exist dynamic constant-time parallel algorithms for regular tree languages and context-free languages under label or symbol changes. However, these algorithms were not developed with the goal to minimise work (or, equivalently, the number of processors). In fact, their inspection yields the work bounds $O(n^2)$ and $O(n^7)$ per change operation, respectively. In this paper, dynamic algorithms for regular tree languages are proposed that generalise the previous algorithms in that they allow unbounded node rank and leaf insertions, while improving the work bound from $O(n^2)$ to $O(n^{\epsilon})$, for arbitrary $\epsilon > 0$. For context-free languages, algorithms with better work bounds (compared with $O(n^7)$) for restricted classes are proposed: for every $\epsilon > 0$ there are such algorithms for deterministic context-free languages with work bound $O(n^{3+\epsilon})$ and for visibly pushdown languages with work bound $O(n^{2+\epsilon})$.

The paper studies query evaluation in parallel constant time in the PRAM model. While it is well-known that all relational algebra queries can be evaluated in constant time on an appropriate CRCW-PRAM, this paper is interested in the efficiency of evaluation algorithms, that is, in the number of processors or, asymptotically equivalent, in the work. Naive evaluation in the parallel setting results in huge (polynomial) bounds on the work of such algorithms and in presentations of the result sets that can be extremely scattered in memory. The paper first discusses some obstacles for constant time PRAM query evaluation. It presents algorithms for relational operators that are considerably more efficient than the naive approaches. Further it explores three settings, in which efficient sequential query evaluation algorithms exist: acyclic queries, semi-join algebra queries, and join queries -- the latter in the worst-case optimal framework. Under natural assumptions on the representation of the database, the work of the given algorithms matches the best sequential algorithms in the case of semi-join queries, and it comes close in the other two settings. An important tool is the compaction technique from Hagerup (1992).

The paper studies the rewriting problem, that is, the decision problem whether, for a given conjunctive query $Q$ and a set $\mathcal{V}$ of views, there is a conjunctive query $Q'$ over $\mathcal{V}$ that is equivalent to $Q$, for cases where the query, the views, and/or the desired rewriting are acyclic or even more restricted. It shows that, if $Q$ itself is acyclic, an acyclic rewriting exists if there is any rewriting. An analogous statement also holds for free-connex acyclic, hierarchical, and q-hierarchical queries. Regarding the complexity of the rewriting problem, the paper identifies a border between tractable and (presumably) intractable variants of the rewriting problem: for schemas of bounded arity, the acyclic rewriting problem is NP-hard, even if both $Q$ and the views in $\mathcal{V}$ are acyclic or hierarchical. However, it becomes tractable if the views are free-connex acyclic (i.e., in a nutshell, their body is (i) acyclic and (ii) remains acyclic if their head is added as an additional atom).

The paper proposes dynamic parallel algorithms for connectivity and bipartiteness of undirected graphs that require constant time and $O(n^{1/2+\epsilon})$ work on the CRCW PRAM model. The work of these algorithms almost matches the work of the $O(\log n)$ time algorithm for connectivity by Kopelowitz et al. (2018) on the EREW PRAM model and the time of the sequential algorithm for bipartiteness by Eppstein et al. (1997). In particular, we show that the sparsification technique, which has been used in both mentioned papers, can in principle also be used for constant time algorithms in the CRCW PRAM model, despite the logarithmic depth of sparsification trees.

Low-latency sliding window algorithms for regular and context-free languages are studied, where latency refers to the worst-case time spent for a single window update or query. For every regular language $L$ it is shown that there exists a constant-latency solution that supports adding and removing symbols independently on both ends of the window (the so-called two-way variable-size model). We prove that this result extends to all visibly pushdown languages. For deterministic 1-counter languages we present a $\mathcal{O}(\log n)$ latency sliding window algorithm for the two-way variable-size model where $n$ refers to the window size. We complement these results with a conditional lower bound: there exists a fixed real-time deterministic context-free language $L$ such that, assuming the OMV (online matrix vector multiplication) conjecture, there is no sliding window algorithm for $L$ with latency $n^{1/2-\epsilon}$ for any $\epsilon>0$, even in the most restricted sliding window model (one-way fixed-size model). The above mentioned results all refer to the unit-cost RAM model with logarithmic word size. For regular languages we also present a refined picture using word sizes $\mathcal{O}(1)$, $\mathcal{O}(\log\log n)$, and $\mathcal{O}(\log n)$.

Which amount of parallel resources is needed for updating a query result after changing an input? In this work we study the amount of work required for dynamically answering membership and range queries for formal languages in parallel constant time with polynomially many processors. As a prerequisite, we propose a framework for specifying dynamic, parallel, constant-time programs that require small amounts of work. This framework is based on the dynamic descriptive complexity framework by Patnaik and Immerman.

The ACM PODS Alberto O. Mendelzon Test-of-Time Award is awarded every year to a paper or a small number of papers published in the PODS proceedings ten years prior that had the most impact in terms of research, methodology, or transfer to practice over the intervening decade. The PODS Executive Committee has appointed us to serve as the Award Committee for 2021. After careful consideration and having solicited external nominations and advice, we have selected the following paper as the award winner for 2021: Tight bounds for L_p samplers, finding duplicates in streams, and related problems by Hossein Jowhari, Mert Sağlam and Gábor Tardos Citation. This paper addresses a question posed by Cormode et al. in VLDB 2005, namely whether a uniform (or nearly uniform) sample can be maintained in a dynamically changing database, where data items may be inserted and deleted, while using space much smaller than the size of the database. More generally, it considers maintaining an L_p sample, where an element must be sampled with probability proportional to w^p (possibly up to some small relative error), where w is a weight that may change dynamically. In SODA 2010, Monemizadeh and Woodruff showed that it is possible to perform L_p sampling in a stream using polylogarithmic space. The PODS 2011 paper by Jowhari, Sağlam and Tardos essentially closes the problem by presenting algorithms with improved space usage, as well as a matching lower bound showing that it is not possible to asymptotically improve the upper bounds. The paper has had a considerable impact on the design of algorithms in streaming and distributed models of computation, where L_p sampling has become an essential part of the toolbox. The survey "L_p Samplers and Their Applications" in ACM Computing Surveys (2019) presents a number of surprising applications, for example in graph algorithms and in randomized numerical linear algebra.

This paper introduces a declarative framework to specify and reason about distributions of data over computing nodes in a distributed setting. More specifically, it proposes distribution constraints which are tuple and equality generating dependencies (tgds and egds) extended with node variables ranging over computing nodes. In particular, they can express co-partitioning constraints and constraints about range-based data distributions by using comparison atoms. The main technical contribution is the study of the implication problem of distribution constraints. While implication is undecidable in general, relevant fragments of so-called data-full constraints are exhibited for which the corresponding implication problems are complete for EXPTIME, PSPACE and NP. These results yield bounds on deciding parallel-correctness for conjunctive queries in the presence of distribution constraints.

How can the result of a query be updated after changing a database? This is a fundamental task for database management systems which ideally takes previously computed information into account. In dynamic complexity theory, it is studied from a theoretical perspective where updates are specified by rules written in first-order logic. In this article we sketch recent techniques and results from dynamic complexity theory with a focus on the reachability query.

In the setting of DynFO, dynamic programs update the stored result of a query whenever the underlying data changes. This update is expressed in terms of first-order logic. We introduce a strategy for constructing dynamic programs that utilises periodic computation of auxiliary data from scratch and the ability to maintain a query for a limited number of change steps. We show that if some program can maintain a query for log n change steps after an AC^1-computable initialisation, it can be maintained by a first-order dynamic program as well, i.e., in DynFO. As an application, it is shown that decision and optimisation problems defined by monadic second-order (MSO) formulas are in DynFO, if only change sequences that produce graphs of bounded treewidth are allowed. To establish this result, a Feferman-Vaught-type composition theorem for MSO is established that might be useful in its own right.

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, also referred to as parallel-correctness. This article extends the study of the complexity of parallel-correctness and its constituents, parallel-soundness and parallel-completeness, to unions of conjunctive queries with negation. As a by-product, it is shown that the containment problem for conjunctive queries with negation is coNEXPTIME-complete.

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 parallelcorrectness 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. 2012 ACM Subject Classification Theory of computation → Database theory

In April 2016, a community of researchers working in the area of Principles of Data Management (PDM) joined in the Dagstuhl Castle in Germany for a workshop organized jointly by the Executive Committee of the ACM Symposium on Principles of Database Systems (PODS) and the Council of the International Conference on Database Theory (ICDT). The mission of this workshop was to identify and explore some of the most important research directions that have high relevance to society and to Computer Science today, and where the PDM community has the potential to make significant contributions. This report describes the family of research directions that the workshop focused on from three perspectives: potential practical relevance, results already obtained, and research questions that appear surmountable in the short and medium term. This report organizes the identified research challenges for PDM around seven core themes, namely Query Processing at Scale, Multi-model

Dynamic Complexity studies the maintainability of queries with logical formulas in a setting where the underlying structure or database changes over time. Most often, these formulas are from first-order logic, giving rise to the dynamic complexity class DynFO. This paper investigates extensions of DynFO in the spirit of parameterised algorithms. In this setting structures come with a parameter k and the extensions allow additional space of size f(k) (in the form of an additional structure of this size) or additional time f(k) (in the form of iterations of formulas) or both. The resulting classes are compared with their non-dynamic counterparts and other classes. The main part of the paper explores the applicability of methods for parameterised algorithms to this setting through case studies for various well-known parameterised problems.

Context-free games on strings are two-player rewriting games based on a set of production rules and a regular target language. In each round, the first player selects a position of the current string; then the second player replaces the symbol at that position according to one of the production rules. The first player wins as soon as the current string belongs to the target language. In this paper the one-pass setting for context-free games is studied, where the knowledge of the first player is incomplete: She selects positions in a left-to-right fashion and only sees the current symbol and the symbols from previous rounds. The paper studies conditions under which dominant and undominated strategies exist for the first player, and when they can be chosen from restricted types of strategies that can be computed efficiently.