ℹ️ Informasi Berkas Arsip: Metadata koleksi ini tersedia di database, namun berkas fisik --javierlura-1689-1-2020mas-i.pdf belum disalin ke direktori penyimpanan server (./files/disk1/ atau ./files/uploads/). Anda tetap dapat membaca/mencetak lembar katalog ini atau mengunggah berkas PDF melalui menu Edit Koleksi.
Mastering Spark with R The Complete Guide to Large-Scale Analysis and Modeling
Penulis: Javier Luraschi, Kevin Kuo, and Edgar Ruiz •
Identifier: --javierlura-1689
Apache Spark is a distributed computing platform built on extensibility: Spark’s APIs make it easy to combine input from many data sources and process it using diverse programming languages and algorithms to build a data application. R is one of the most powerful languages for data science and statistics, so it makes a lot of sense to connect R to Spark. Fortunately, R’s rich language features enable simple APIs for calling Spark from R that look similar to running R on local data sources. With a bit of background about both systems, you will be able to invoke massive computations in Spark or run your R code in parallel from the comfort of your favorite R programming environment.