MapReduce is a framework for processing and managing large-scale datasets in a
distributed cluster, which has been used for applications such as generating search indexes …

Context: In recent years, the valuable knowledge that can be retrieved from petabyte scale
datasets–known as Big Data–led to the development of solutions to process information …

There has been much research devoted to improving the performance of data analytics
frameworks, but comparatively little effort has been spent systematically identifying the …

Sprocket is a highly configurable, stage-based, scalable, serverless video processing
framework that exploits intra-video parallelism to achieve low latency. Sprocket enables …

Entity matching (EM) identifies data instances that refer to the same real-world entity, such
as (David Smith, UWMadison) and (DM Smith, UWM). This problem has been a long …

This paper describes a learning-based approach to the acceleration of approximate
programs. We describe the Parrot transformation, a program transformation that selects and …

Shark is a new data analysis system that marries query processing with complex analytics
on large clusters. It leverages a novel distributed memory abstraction to provide a unified …

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 present LocationSpark, a spatial data processing system built on top of Apache Spark, a
widely used distributed data processing system. LocationSpark offers a rich set of spatial …

Streaming computations are by nature long-running, and their workloads can change in
unpredictable ways. This in turn means that maintaining performance may require …