Small commodities, big infrastructure

Benchmarking Infrastructure for Big Data

This paper discusses the applicability of 20 years of experience benchmarking transactional systems (TPC) and storage system benchmarking (SPC) to the design of systems suitable for use in comparing different analytic systems. One of the most challenging problems is finding tools to make meaningful comparisons between substantially different architectures working on solving similar problems. Fo...

Redoop Infrastructure for Recurring Big Data Queries

This demonstration presents the Redoop infrastructure, the first fullfledged MapReduce framework with native support for recurring big data queries. Recurring queries, repeatedly being executed for long periods of time over evolving high-volume data, have become a bedrock component in most large-scale data analytic applications. Redoop is a comprehensive extension to Hadoop that pushes the supp...

Big Data Challenges for e-Science Infrastructure

This paper discusses the challenges that are imposed by the Big Data Science on the modern and future Scientific Data Infrastructure (SDI). The paper refers to different scientific communities to define requirements on data management, access control and security. The paper introduces the Scientific Data Lifecycle Management (SDLM) model that includes all the major stages and reflects specifics...

Tupleware: "Big" Data, Big Analytics, Small Clusters

There is a fundamental discrepancy between the targeted and actual users of current analytics frameworks. Most systems are designed for the challenges of the Googles and Facebooks of the world— processing petabytes of data distributed across large cloud deployments consisting of thousands of cheap commodity machines. Yet, the vast majority of users analyze relatively small datasets of up to sev...

Big heart, small ring.