Talk:Programming with Big Data in R

This article was nominated for deletion on 27 June 2013 (UTC). The result of the discussion was no consensus.

	This article is within the scope of WikiProject Computing, a collaborative effort to improve the coverage of computers, computing, and information technology on Wikipedia. If you would like to participate, please visit the project page, where you can join the discussion and see a list of open tasks.ComputingWikipedia:WikiProject ComputingTemplate:WikiProject ComputingComputing articles
???	This article has not yet received a rating on the project's importance scale.

Statistics Low‑importance

	This article is within the scope of WikiProject Statistics, a collaborative effort to improve the coverage of statistics on Wikipedia. If you would like to participate, please visit the project page, where you can join the discussion and see a list of open tasks.StatisticsWikipedia:WikiProject StatisticsTemplate:WikiProject StatisticsStatistics articles
Low	This article has been rated as Low-importance on the importance scale.

Trimmed from lead

These afterthoughts at the bottom of the lead are not adding clarity IMO, so I've trimmed them off, until someone figures out a way to sort this out enough to make it a value add.

It is clear that pbdR is not only suitable for small clusters, but is also more stable for analyzing big data and more scalable for supercomputers.[third-party source needed] In short, pbdR

does not like Rmpi, snow, snowfall, do-like,[clarification needed] nor parallel packages in R,

does not focus on interactive computing nor master/workers,

but is able to use both SPMD and task parallelisms.

— MaxEnt 04:44, 22 May 2020 (UTC)[reply]

The actual markup:

It is clear that pbdR is not only suitable for small [[Computer cluster|clusters]], but is also more stable for analyzing [[big data]] and more scalable for [[supercomputer]]s.<ref>{{cite book|author=Schmidt, D., Ostrouchov, G., Chen, W.-C., and Patel, P.|title=Tight Coupling of R and Distributed Linear Algebra for High-Level Programming with Big Data|year=2012|pages=811–815|journal=High Performance Computing, Networking, Storage and Analysis (SCC), 2012 SC Companion|url=http://dl.acm.org/citation.cfm?id=2477156|doi=10.1109/SC.Companion.2012.113|isbn=978-0-7695-4956-9}}</ref>{{third-party-inline|date=October 2014}} In short, pbdR
* does ''not'' like Rmpi, {{clarify|text=snow, snowfall, do-like,|date=October 2014}} nor parallel packages in R,
* does ''not'' focus on interactive computing nor master/workers,
* but is able to use ''both'' SPMD and task parallelisms.

Probably the restored version needs to begin "According to D. Schmidt, et al, R is suitable for $purpose.

Then the three verbs 'like', 'focus', and 'able' need to revised into encyclopedia tone. — MaxEnt 04:48, 22 May 2020 (UTC)[reply]