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 Tools annual

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 Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Big data processing is a hot topic in today's computer science world. Thereis a significant demand for analysing big data to satisfy many requirements ofmany industries. Emergence of the Kappa architecture created a strongrequirement for a highly capable and efficient data processing engine.Therefore data processing engines such as Apache Flink and Apache Spark emergedin open source world to fulfil that efficient and high performing dataprocessing requirement. There are many available benchmarks to evaluate thosetwo data processing engines. But complex deployment patterns and dependenciesmake those benchmarks very difficult to reproduce by our own. This project hastwo main goals. They are making few of community accepted benchmarks easilyreproducible on cloud and validate the performance claimed by those studies.

Reproducible Experiments for Comparing Apache Flink and Apache Spark on Public Clouds