MapReduce is a programming system for distributed processing of large-scale data in an
efficient and fault tolerant manner on a private, public, or hybrid cloud. MapReduce is …

The term “big data” will always be remembered as the big buzzword of 2013. According to
the Wikipedia, big data “is a collection of data sets so large and complex that it becomes …

We study the problem of computing conjunctive queries over large databases on parallel
architectures without shared storage. Using the structure of such a query q and the skew in …

We study the problem of finding and monitoring fixed-size subgraphs in a continually
changing large-scale graph. We present the first approach that (i) performs worst-case …

Subgraph enumeration, which aims to find all the subgraphs of a large data graph that are
isomorphic to a given pattern graph, is a fundamental graph problem with a wide range of …

The past few years have seen a major change in computing systems, as growing data
volumes and stalling processor speeds require more and more applications to scale out to …

A new technique of trilinear operations of aggregating, uniting and canceling is introduced
and applied to constructing fast linear non-commutative algorithms for matrix multiplication …

We study the problem of computing a conjunctive query q in parallel, using p of servers, on a
large database. We consider algorithms with one round of communication, and study the …

We study the problem of implementing graph algorithms efficiently on Pregel-like systems,
which can be surprisingly challenging. Standard graph algorithms in this setting can incur …

Subgraph matching finds a set I of all occurrences of a pattern graph in a target graph. It has
a wide range of applications while suffers an expensive computation. This efficiency issue …