Seminars

Speaker: Nofar Carmeli (nofar.carme.li/)

Zoom link: univ-lille-fr.zoom.us/j/95419000064

Title: The Complexity of Answering Unions of Conjunctive Queries.

Abstract:
We discuss the fine-grained complexity of enumerating the answers to a query over a relational database. With the ideal guarantees, linear time is required before the first answer to read the input and determine its existence, and then we need to print the answers one by one. Consequently, we wish to identify the queries that can be solved with linear preprocessing time and constant or logarithmic delay between answers. A known dichotomy classifies CQs into those that admit such enumeration and those that do not. The computationally expensive component of query answering is joining tables, which can be done efficiently if and only if the join query is acyclic. However, the join query usually does not appear in a vacuum; for example, it may be part of a larger query, or it may be applied to a database with dependencies. We inspect how the complexity changes in these settings and chart the borders of tractability within. In addition, we consider the task of enumerating query answers with a uniformly random order, and we propose to do so using an efficient random-access structure for representing the set of answers. We also prove conditional lower bounds showing that our algorithms capture all tractable queries in some cases. Among our results, we show that a union of tractable conjunctive queries may be intractable w.r.t. random access; on the other hand, a union of intractable conjunctive queries may be tractable w.r.t. enumeration.

Title: Extracting nested relational queries from implicit definitions

Abstract:
arxiv.org/pdf/2005.06503.pdf

In this talk, I will present results obtained jointly with Michael
Benedikt establishing a connection between the Nested Relational
Calculus (NRC) and sets implicitly definable using Δ₀ formulas.

Call a formula φ(I,O) an implicit definition of the relation O(x,...) in
terms of I(y,...) if O is functionally determined by I: for every I, O,
O', if both φ(I,O) and φ(I,O') hold, then we have O ≡ O'. When φ is
first-order and I and O are relations over base sorts, then Beth's
definability theorem states that there is a first-order formula
ψ(I,x,...) corresponding to O whenever φ(I,O) holds. Further, this
explicit definition ψ can be effectively be computed from a sequent
calculus proof witnessing that φ is functional. This allows for
practical use of implicit definitions in the context of database
programming, as there is a well-established link between fragments of
explicitly FO definable relations and relational calculi.

NRC is a conservative extension of relational calculi from database
theory with limited powerset types in addition to tupling and anonymous
base types. NRC expressions thus not only encompass flat relations over
primitive datatypes like SQL but also nested collections, while
remaining useful in practice.

We extend the above correspondence between first-order logic and flat
relational queries to NRC and implicit definitions using set-theoretical
Δ₀ formulas over (typed) nested collection. Our proof of the equivalence
goes through a notion of Δ₀-interpretation and a generalization of Beth
definability for multi-sorted structures. This proof is non-constructive
and thus does not yield any useful algorithm for converting implicit
definitions into NRC terms. Using an approach more closely related to
proof-theoretic interpolation, we give a constructive proof of the
result restricted to intuitionistic provability, i.e, when the input
functionality proof π of φ(I,O) is carried out in intuitionistic logic.
Further, if π is cut-free, this can be done efficiently. Whether or not
there exists a polynomial-time procedure working with classical proofs
of functionality is still an open problem.

I will focus on the effective result for the talk, and if time allows,
discuss the difficulties with extending it to classical logic. I will
not assume any background in either database or model theory.

Title: The Complexity of Counting Problems over Incomplete Databases

Abstract: In this presentation, I will talk about various counting problems that naturally
arise in the context of query evaluation over incomplete databases. Incomplete
databases are relational databases that can contain unknown values in the form
of labeled nulls. We will assume that the domains of these unknown values are
finite and, for a Boolean query $q$, we will consider the following two
problems: given as input an incomplete database $D$, (a) return the number of
completions of $D$ that satisfy $q$; or (b) return or the number of valuations
of the nulls of $D$ yielding a completion that satisfies $q$.


We will study the computational complexity of these problems when $q$ is a
self-join--free conjunctive query, and study the impact on the complexity of
the following two restrictions: (1) every null occurs at most once in $D$ (what
is called *Codd tables*); and (2) the domain of each null is the same. Roughly
speaking, we will see that counting completions is much harder than counting
valuations, and that both (1) and (2) can reduce the complexity of our
problems.

I will also talk about the approximability of these problems and prove that,
while counting valuations can efficiently be approximated, in most cases
counting completions cannot.

On our way, we will encounter the counting complexity classes #P, Span-P and
Span-L.

The presentation will be based on joint work with Marcelo Arenas and Pablo
Barcelo; see arxiv.org/abs/1912.11064

Title: Finding paths in large graphs

Abstract:
When dealing with large graphs, classical algorithms for finding paths such as Dijkstra's Algorithm are unsuitable, because they require to perform too many disk accesses. To avoid this while keeping a data structure of size quasi-linear in the size of the graph, we propose to guide the path search with a distance oracle, obtained from a topological embedding of the graph.
I will present fresh experimental research on this topic, in which we obtain graph embeddings using learning algorithms from natural language processing. On some graphs, such as the graph of publications from DBLP, our topologically-guided path search allows us to visit a small portion of the graph only, in average.
This is joint work with Charles Paperman.

Title: Containment for Probabilistic automata.

Abstract: This is an ICALP 2018 paper. We analyze when the model of probabilistic
automata has decidable properties, when restricting the ambiguity. The
notion of ambiguity is usually used in weighted automata or transducers,
but we follow a recent paper by Fijalkow, Riveros and Worrell, which
introduced this approach. We do not solve everything but our decidability
results rely unexpectedly on Schanuel's conjecture and we provide some
geometric intuition behind the hardness of the problem.

Abstract: The time complexity of 1-limited automata is investigated from a
descriptional complexity view point. Though the model recognizes
regular languages only, it may use quadratic time in the input length.
We show that, with a polynomial increase in size and preserving
determinism, each 1-limited automaton can be transformed into a
linear-time equivalent one. We also obtain polynomial transformations
into related models, including weight-reducing Hennie machines (i.e.,
one-tape Turing machines syntactically forced to operate in
linear-time), and we show exponential gaps for converse
transformations in the deterministic case.

Title: Combined Complexity of Probabilistic Query Evaluation

Abstract:
Query evaluation over probabilistic databases (probabilistic query evaluation, or PQE) is known to be intractable in many cases, even in data complexity, i.e., when the query is fixed. Although some restrictions of the queries and instances have been proposed to lower the complexity, these known tractable cases usually do not apply to combined complexity, i.e., when the query is not fixed. This talk gives an overview of my PhD research, which investigates which queries and instances ensure the tractability of PQE in combined complexity.

I will first present our work on PQE of conjunctive queries on binary signatures, which can be rephrased as a probabilistic graph homomorphism problem. We restrict the query and instance graphs to be trees and show the impact on the combined complexity of diverse features such as edge labels, branching, or connectedness. This is joint work with Antoine Amarilli and Pierre Senellart and was presented at PODS'2017.

Second, we will explore the combined complexity of evaluating queries on treelike databases, i.e., databases whose treewidth is bounded by a constant. We introduce a class of queries (named 'CFG-Datalog') which generalizes many known query languages that are tractable in this context. Specifically, we show that the (non-probabilistic) evaluation of CFG-Datalog on treelike databases can be solved with complexity linear in the product of the instance size and of the query size. In the process, we introduce a new representation of the provenance of a query on a database, based on cyclic Boolean circuits. This is joint work with Antoine Amarilli, Pierre Bourhis, and Pierre Senellart, and was presented at ICDT'2017.

Last, we will move to the field of knowledge compilation and present our work that connects various notions of width for Boolean circuits. We show that circuits of bounded treewidth can be efficiently compiled into structured deterministic decomposable normal forms (d-SDNNFs), which in particular allows efficient probability computation. We show the implications of this result for PQE of CFG-Datalog on treelike databases. We also prove general lower bounds on knowledge compilation formalisms, which imply lower bounds for provenance computation. This is joint work with Antoine Amarilli and Pierre Senellart and was presented at ICDT'2018.

This talk connects two classical areas of theoretical computer science: descriptive complexity and distributed computing. The former is a branch of computational complexity theory that characterizes complexity classes in terms of equivalent logical formalisms. The latter studies algorithms that run in networks of interconnected processors.

Although an active field of research since the late 1970s, distributed computing is still lacking the analogue of a complexity theory. One reason for this may be the large number of distinct models of distributed computation, which make it rather difficult to develop a unified formal framework. In my talk, I will outline how the descriptive approach, i.e., connections to logic, could be helpful in this regard.