Timeline for Is the R language suitable for Big Data
Current License: CC BY-SA 3.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Dec 5, 2015 at 6:03 | comment | added | wacax | Two new alternatives that are worth mentioning are: SparkR databricks.com/blog/2015/06/09/… and h2o.ai h2o.ai/product both well suited for big data. | |
| S Jan 31, 2015 at 11:34 | history | suggested | chenrui333 | CC BY-SA 3.0 |
Update RHadoop project information.
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| Jan 30, 2015 at 20:06 | review | Suggested edits | |||
| S Jan 31, 2015 at 11:34 | |||||
| Jun 11, 2014 at 6:34 | comment | added | Steve Kallestad | RHadoop does overcome this limitation. The tutorial here: github.com/RevolutionAnalytics/rmr2/blob/master/docs/… spells it out clearly. You need to shift into a mapreduce mindset, but it does provide the power of R to the hadoop environment. | |
| Jun 9, 2014 at 23:07 | comment | added | Felipe | But does using R with Hadoop overcome this limitation (having to do computations in memory)? | |
| May 17, 2014 at 11:03 | vote | accept | akellyirl | ||
| May 14, 2014 at 11:24 | history | answered | MCP_infiltrator | CC BY-SA 3.0 |