English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Cloud computing has demonstrated that processing very large datasets overcommodity clusters can be done simply given the right programming model andinfrastructure. In this paper, we describe the design and implementation of theSector storage cloud and the Sphere compute cloud. In contrast to existingstorage and compute clouds, Sector can manage data not only within a datacenter, but also across geographically distributed data centers. Similarly, theSphere compute cloud supports User Defined Functions (UDF) over data bothwithin a data center and across data centers. As a special case, MapReducestyle programming can be implemented in Sphere by using a Map UDF followed by aReduce UDF. We describe some experimental studies comparing Sector/Sphere andHadoop using the Terasort Benchmark. In these studies, Sector is about twice asfast as Hadoop. Sector/Sphere is open source.

Sector and Sphere: Towards Simplified Storage and Processing of Large Scale Distributed Data