![]() ![]() R-release (arm64): sparklyr_1.7.8.tgz, r-oldrel (arm64): sparklyr_1.7.8.tgz, r-release (x86_64): sparklyr_1.7.8.tgz, r-oldrel (x86_64): sparklyr_1.7.8.tgzĪdona, catalog, geospark, graphframes, rsparkling, shinyML, spark.sas7bdat, sparkavro, sparkbq, sparkhail, sparklyr.flint, sparklyr. ![]() Version:Īssertthat, base64enc, config (≥ 0.2), DBI (≥ 1.0.0), dbplyr (≥ 2.2.1), digest, dplyr (≥ 1.0.9), ellipsis (≥ 0.1.0), forge, generics, globals, glue, httr (≥ 1.2.1), jsonlite (≥ġ.4), methods, openssl (≥ 0.8), purrr, r2d3, rappdirs, rlang (≥ 0.1.4), rprojroot, rstudioapi (≥ 0.10), tibble, tidyr (≥ġ.2.0), tidyselect, uuid, vctrs, withr, xml2Īrrow (≥ 0.17.0), broom, diffobj, foreach, ggplot2, iterators, janeaustenr, Lahman, mlbench, nnet, nycflights13, R6, RCurl, reshape2, shiny (≥ 1.0.1), parsnip, testthat By default the above script uses the system wide installation of R. This can be done by running the script SPARKHOME/R/install-dev.sh. Installing sparkR Libraries of sparkR need to be created in SPARKHOME/R/lib. Spark's built-in machine learning algorithms. SparkR is an R package that provides a light-weight frontend to use Spark from R. Provides a 'dplyr' compatible back-end, and provides an interface to ![]() Package supports connecting to local and remote Apache Spark clusters, I’m currently working on a project where I’ll be interacting with data in Spark, so wanted to get a sense. This post grew out of some notes I was making on the differences between SparkR and sparklyr, two packages that provide an R interface to Spark. R interface to Apache Spark, a fast and generalĮngine for big data processing, see. SparkR vs sparklyr for interacting with Spark from R. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |