Abstract: The performance of big data workflows depends on both the workflow mapping scheme, which determines task assignment and container allocation in Hadoop, and the on-node scheduling policy, ...

Cloud computing allows scalability at a lower cost for data analytics in a big data environment. This paradigm considers the dimensioning of resources to process different volumes of data, minimizing ...

Driven by artificial intelligence (AI), cloud computing, and the digital transformation, U.S. data centers consumed an estimated 150 TWh of electricity in 2023—equivalent to around 3% of the nation’s ...

The latest trends and issues around the use of open source software in the enterprise. The best run DevOps teams in the world choose Perforce, that’s the claim from Perforce. The company makes this ...

Big Data analytics requirements have forced a huge shift in data storage paradigms, from traditional block- and file-based storage networks to more scalable models like object storage, scale-out NAS ...

Abstract: The materializing high-throughput technologies in 21st Century have contributed to the aggregate of data produced by mankind to increase each year. The consequent "Big-Data" in biology, ...

Big data became popular about a decade ago. The falling cost of storage led many enterprises to retain much of the data they ingested or generated so they could mine it for key business insights.

Big on Data bro Andrew Brust's recent post on the spring cleaning of Hadoop projects evidently touched a nerve, given the readership numbers that went off the charts. By now, the Apache Hadoop family ...