SearcharxivSearch

arXiv · 1104.3084

I/O-Efficient Data Structures for Colored Range and Prefix Reporting

Abstract

Motivated by information retrieval applications, we consider the one-dimensional colored range reporting problem in rank space. The goal is to build a static data structure for sets C_1,...,C_m \subseteq {1,...,sigma} that supports queries of the kind: Given indices a,b, report the set Union_{a <= i <= b} C_i. We study the problem in the I/O model, and show that there exists an optimal linear-space data structure that answers queries in O(1+k/B) I/Os, where k denotes the output size and B the disk block size in words. In fact, we obtain the same bound for the harder problem of three-sided orthogonal range reporting. In this problem, we are to preprocess a set of n two-dimensional points in rank space, such that all points inside a query rectangle of the form [x_1,x_2] x (-infinity,y] can be reported. The best previous bounds for this problem is either O(n lg^2_B n) space and O(1+k/B) query I/Os, or O(n) space and O(lg^(h)_B n +k/B) query I/Os, where lg^(h)_B n is the base B logarithm iterated h times, for any constant integer h. The previous bounds are both achieved under the indivisibility assumption, while our solution exploits the full capabilities of the underlying machine. Breaking the indivisibility assumption thus provides us with cleaner and optimal bounds. Our results also imply an optimal solution to the following colored prefix reporting problem. Given a set S of strings, each O(1) disk blocks in length, and a function c: S -> 2^{1,...,sigma}, support queries of the kind: Given a string p, report the set Union_{x in S intersection p*} c(x), where p* denotes the set of strings with prefix p. Finally, we consider the possibility of top-k extensions of this result, and present a simple solution in a model that allows non-blocked I/O.

Explore related subjects

Keep this discovery

BibTeXRIS

Kasper Green Larsen, Rasmus Pagh. 2011-04-15. I/O-Efficient Data Structures for Colored Range and Prefix Reporting. https://arxiv.org/abs/1104.3084

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Quasi-Monte Carlo Beyond Hardy-Krause II: $(1 + \varepsilon)n$ Samples Suffice

Numerical integration studies how well one can estimate the integral of a function $f$ over $[0,1)^d$ using $n$ sample points. The two classical methods, Monte Carlo (MC) and quasi-Monte Carlo (QMC), have complementary strengths and weaknesses, and a fundamental question is to design an approach that combines the benefits of both. Recently, building on the transference principle in discrepancy theory, Bansal and Jiang~\cite{BJ25a} gave a randomized QMC method that bridges MC and QMC guarantees using only i.i.d.\ samples. Their method also goes beyond the classical Koksma--Hlawka inequality: it achieves integration error $\widetilde{O}_d(\sigma_{\mathsf{SO}}(f)/n)$, where the smoothed-out variation $\sigma_{\mathsf{SO}}(f)$ can be substantially smaller than the Hardy--Krause variation that governs the classical bound. However, their algorithm requires $n^2$ i.i.d.\ samples as input, and this quadratic blowup is inherent to any method based on the transference principle. In this work, we bypass the quadratic blowup: for any constant $\varepsilon > 0$, we show that $(1+\varepsilon)n$ i.i.d.\ samples suffice to both obtain the beyond-Hardy--Krause guarantee of~\cite{BJ25a}, resolving an open problem posed there, and to produce low-discrepancy point sequences. Our algorithms are variants of the online Haar-thinning method of Dwivedi, Feldheim, Gurel-Gurevich, and Ramdas~\cite{DFG+19}.

cs.DS

Single-Exponential Algorithms and a Polynomial Kernel for Strong Connectivity Augmentation

Strong Connectivity Augmentation (SCA) asks whether a directed acyclic graph can be made strongly connected by adding at most $k$ prescribed links whose total weight is within a given budget. Klinkby, Misra, and Saurabh (SODA 2021) gave an $O^*(2^{O(k\log k)})$-time algorithm and asked whether the problem admits a single-exponential parameterized algorithm and a polynomial kernel. We answer both questions affirmatively: SCA can be solved in $O^*(9^k)$ time and admits a polynomial kernel with $O(k^4)$ vertices and $O(k^{16})$ bits. For unweighted SCA, we obtain $O^*(4^k)$ time and a kernel with $O(k^3)$ vertices. Our algorithms are based on a particularly simple reduction to Strongly Connected Spanning Subgraph with two edge costs.

cs.DS