SparkR

Shivaram Venkataraman, Ion Stoica, Matei Zaharia, Zongheng Yang, Davies Liu, Eric Liang, Hossein Falaki, Xiangrui Meng, Reynold Xin, Ali Ghodsi, Michael Franklin
<span title="">2016</span> <i title="ACM Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vxrc3vebzzachiwy3nopwi3h5u" style="color: black;">Proceedings of the 2016 International Conference on Management of Data - SIGMOD &#39;16</a> </i> &nbsp;
R is a popular statistical programming language with a number of extensions that support data processing and machine learning tasks. However, interactive data analysis in R is usually limited as the R runtime is single threaded and can only process data sets that fit in a single machine's memory. We present SparkR, an R package that provides a frontend to Apache Spark and uses Spark's distributed computation engine to enable large scale data analysis from the R shell. We describe the main
more &raquo; ... goals of SparkR, discuss how the high-level DataFrame API enables scalable computation and present some of the key details of our implementation.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1145/2882903.2903740">doi:10.1145/2882903.2903740</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/sigmod/VenkataramanYLL16.html">dblp:conf/sigmod/VenkataramanYLL16</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/inpgt6bmmne43bgtkzzhjv7vxu">fatcat:inpgt6bmmne43bgtkzzhjv7vxu</a> </span>
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