405 research outputs found
A Dichotomy on the Complexity of Consistent Query Answering for Atoms with Simple Keys
We study the problem of consistent query answering under primary key
violations. In this setting, the relations in a database violate the key
constraints and we are interested in maximal subsets of the database that
satisfy the constraints, which we call repairs. For a boolean query Q, the
problem CERTAINTY(Q) asks whether every such repair satisfies the query or not;
the problem is known to be always in coNP for conjunctive queries. However,
there are queries for which it can be solved in polynomial time. It has been
conjectured that there exists a dichotomy on the complexity of CERTAINTY(Q) for
conjunctive queries: it is either in PTIME or coNP-complete. In this paper, we
prove that the conjecture is indeed true for the case of conjunctive queries
without self-joins, where each atom has as a key either a single attribute
(simple key) or all attributes of the atom
The Design of Arbitrage-Free Data Pricing Schemes
Motivated by a growing market that involves buying and selling data over the
web, we study pricing schemes that assign value to queries issued over a
database. Previous work studied pricing mechanisms that compute the price of a
query by extending a data seller's explicit prices on certain queries, or
investigated the properties that a pricing function should exhibit without
detailing a generic construction. In this work, we present a formal framework
for pricing queries over data that allows the construction of general families
of pricing functions, with the main goal of avoiding arbitrage. We consider two
types of pricing schemes: instance-independent schemes, where the price depends
only on the structure of the query, and answer-dependent schemes, where the
price also depends on the query output. Our main result is a complete
characterization of the structure of pricing functions in both settings, by
relating it to properties of a function over a lattice. We use our
characterization, together with information-theoretic methods, to construct a
variety of arbitrage-free pricing functions. Finally, we discuss various
tradeoffs in the design space and present techniques for efficient computation
of the proposed pricing functions.Comment: full pape
Communication Steps for Parallel Query Processing
We consider the problem of computing a relational query on a large input
database of size , using a large number of servers. The computation is
performed in rounds, and each server can receive only
bits of data, where is a parameter that controls
replication. We examine how many global communication steps are needed to
compute . We establish both lower and upper bounds, in two settings. For a
single round of communication, we give lower bounds in the strongest possible
model, where arbitrary bits may be exchanged; we show that any algorithm
requires , where is the fractional vertex
cover of the hypergraph of . We also give an algorithm that matches the
lower bound for a specific class of databases. For multiple rounds of
communication, we present lower bounds in a model where routing decisions for a
tuple are tuple-based. We show that for the class of tree-like queries there
exists a tradeoff between the number of rounds and the space exponent
. The lower bounds for multiple rounds are the first of their
kind. Our results also imply that transitive closure cannot be computed in O(1)
rounds of communication
Worst-Case Optimal Algorithms for Parallel Query Processing
In this paper, we study the communication complexity for the problem of
computing a conjunctive query on a large database in a parallel setting with
servers. In contrast to previous work, where upper and lower bounds on the
communication were specified for particular structures of data (either data
without skew, or data with specific types of skew), in this work we focus on
worst-case analysis of the communication cost. The goal is to find worst-case
optimal parallel algorithms, similar to the work of [18] for sequential
algorithms.
We first show that for a single round we can obtain an optimal worst-case
algorithm. The optimal load for a conjunctive query when all relations have
size equal to is , where is a new query-related
quantity called the edge quasi-packing number, which is different from both the
edge packing number and edge cover number of the query hypergraph. For multiple
rounds, we present algorithms that are optimal for several classes of queries.
Finally, we show a surprising connection to the external memory model, which
allows us to translate parallel algorithms to external memory algorithms. This
technique allows us to recover (within a polylogarithmic factor) several recent
results on the I/O complexity for computing join queries, and also obtain
optimal algorithms for other classes of queries
Speculative Bubbles: Conditions Of Creation And Explosion
This study is an attempt to illustrate the compatibility of financial bubbles, even under conditions of market efficiency and rational anticipations. The classical models of rational anticipations fail to describe a unique course of the price evolution of a financial due to the multiplicity of solutions to which they arrive. The approach of the bubble as a martingale can offer principles of approaching the bubbles, the possibility of creation and their eventual explosion, even under conditions of strong market efficiency and rational anticipations
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